@article{pmid31940523,

title = {Biomarker Localization From Deep Learning Regression Networks},

author = {Carlos Cano-Espinosa and German Gonzalez and George R Washko and Miguel Cazorla and Raul San Jose Estepar},

doi = {10.1109/TMI.2020.2965486},

issn = {1558-254X},

year  = {2020},

date = {2020-06-01},

journal = {IEEE Trans Med Imaging},

volume = {39},

number = {6},

pages = {2121--2132},

abstract = {Biomarker estimation methods from medical images have traditionally followed a segment-and-measure strategy. Deep-learning regression networks have changed such a paradigm, enabling the direct estimation of biomarkers in databases where segmentation masks are not present. While such methods achieve high performance, they operate as a black-box. In this work, we present a novel deep learning network structure that, when trained with only the value of the biomarker, can perform biomarker regression and the generation of an accurate localization mask simultaneously, thus enabling a qualitative assessment of the image locus that relates to the quantitative result. We showcase the proposed method with three different network structures and compare their performance against direct regression networks in four different problems: pectoralis muscle area (PMA), subcutaneous fat area (SFA), liver mass area in single slice computed tomography (CT), and Agatston score estimated from non-contrast thoracic CT images (CAC). Our results show that the proposed method improves the performance with respect to direct biomarker regression methods (correlation coefficient of 0.978, 0.998, and 0.950 for the proposed method in comparison to 0.971, 0.982, and 0.936 for the reference regression methods on PMA, SFA and CAC respectively) while achieving good localization (DICE coefficients of 0.875, 0.914 for PMA and SFA respectively, p < 0.05 for all pairs). We observe the same improvement in regression results comparing the proposed method with those obtained by quantify the outputs using an U-Net segmentation network (0.989 and 0.951 respectively). We, therefore, conclude that it is possible to obtain simultaneously good biomarker regression and localization when training biomarker regression networks using only the biomarker value.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32239319,

title = {Quantitative CT Evidence of Airway Inflammation in WTC Workers and Volunteers with Low FVC Spirometric Pattern},

author = {Jonathan Weber and Anthony P Reeves and John T Doucette and Yunho Jeon and Akshay Sood and Raúl San José Estépar and Juan C Celedón and Rafael E de la Hoz},

doi = {10.1007/s00408-020-00350-5},

issn = {1432-1750},

year  = {2020},

date = {2020-06-01},

journal = {Lung},

volume = {198},

number = {3},

pages = {555--563},

abstract = {BACKGROUND: The most common abnormal spirometric pattern reported in WTC worker and volunteer cohorts has consistently been that of a nonobstructive reduced forced vital capacity (low FVC). Low FVC is associated with obesity, which is highly prevalent in these cohorts. We used quantitative CT (QCT) to investigate proximal and distal airway inflammation and emphysema in participants with stable low FVC pattern.nnMETHODS: We selected study participants with at least two available longitudinal surveillance spirometries, and a chest CT with QCT measurements of proximal airway inflammation (wall area percent, WAP), end-expiratory air trapping, suggestive of distal airway obstruction (expiratory to inspiratory mean lung attenuation ratio, MLA), and emphysema (percentage of lung volume with attenuation below - 950 HU, LAV%). The comparison groups in multinomial logistic regression models were participants with consistently normal spirometries, and participants with stable fixed obstruction (COPD).nnRESULTS: Compared to normal spirometry participants, and after adjusting for age, sex, race/ethnicity, BMI, smoking, and early arrival at the WTC disaster site, low FVC participants had higher WAP (OR 1.24, 95% CI 1.06, 1.45, per 5% unit), suggestive of proximal airway inflammation, but did not differ in MLA, or LAV%. COPD participants did not differ in WAP with the low FVC ones and were more likely to have higher MLA or LAV% than the other two subgroups.nnDISCUSSION: WTC workers with spirometric low FVC have higher QCT-measured WAP compared to those with normal spirometries, but did not differ in distal airway and emphysema measurements, independently of obesity, smoking, and other covariates.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32048167,

title = {Cost-effectiveness microsimulation of catheter-directed thrombolysis in submassive pulmonary embolism using a right ventricular function model},

author = {Stefanie E Mason and Jinyi Zhu and Farbod N Rahaghi and George R Washko and Ankur Pandya},

doi = {10.1007/s11239-020-02058-y},

issn = {1573-742X},

year  = {2020},

date = {2020-05-01},

journal = {J Thromb Thrombolysis},

volume = {49},

number = {4},

pages = {673--680},

abstract = {Approximately 30-50% of hemodynamically stable patients presenting with acute pulmonary embolism (PE) have evidence of right ventricular (RV) dysfunction. These patients are classified as submassive PE and the role of reperfusion therapy remains unclear. We sought to identify the circumstances under which catheter-directed thrombolysis (CDT) would represent high-value care for submassive PE. We used a computer-based, individual-level, state-transition model with one million simulated patients to perform a cost-effectiveness analysis comparing the treatment of submassive PE with CDT followed by anticoagulation to treatment with anticoagulation alone. Because RV function impacts prognosis and is commonly used in PE outcomes research, our model used RV dysfunction to differentiate health states. One-way, two-way, and probabilistic sensitivity analyses were used to quantify model uncertainty. Our base case analysis generated an incremental cost-effectiveness ratio (ICER) of $119,326 per quality adjusted life year. Sensitivity analyses resulted in ICERs consistent with high-value care when CDT conferred a reduction in the absolute probability of RV dysfunction of 3.5% or more. CDT yielded low-value ICERs if the absolute reduction was less than 1.56%. Our model suggests that catheter-directed thrombolytics represents high-value care compared to anticoagulation alone when CDT offers an absolute improvement in RV dysfunction of 3.5% or more, but there is substantial uncertainly around these results. We estimated the monetary value of clarifying the costs and consequences surrounding RV dysfunction after submassive PE to be approximately $268 million annually, suggesting further research in this area could be highly valuable.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32283960,

title = {Pharmacologic Management of Chronic Obstructive Pulmonary Disease. An Official American Thoracic Society Clinical Practice Guideline},

author = {Linda Nici and Manoj J Mammen and Edward Charbek and Paul E Alexander and David H Au and Cynthia M Boyd and Gerard J Criner and Gavin C Donaldson and Michael Dreher and Vincent S Fan and Andrea S Gershon and MeiLan K Han and Jerry A Krishnan and Fernando J Martinez and Paula M Meek and Michael Morgan and Michael I Polkey and Milo A Puhan and Mohsen Sadatsafavi and Don D Sin and George R Washko and Jadwiga A Wedzicha and Shawn D Aaron},

doi = {10.1164/rccm.202003-0625ST},

issn = {1535-4970},

year  = {2020},

date = {2020-05-01},

journal = {Am J Respir Crit Care Med},

volume = {201},

number = {9},

pages = {e56--e69},

abstract = {: This document provides clinical recommendations for the pharmacologic treatment of chronic obstructive pulmonary disease (COPD). It represents a collaborative effort on the part of a panel of expert COPD clinicians and researchers along with a team of methodologists under the guidance of the American Thoracic Society.: Comprehensive evidence syntheses were performed on all relevant studies that addressed the clinical questions and critical patient-centered outcomes agreed upon by the panel of experts. The evidence was appraised, rated, and graded, and recommendations were formulated using the Grading of Recommendations, Assessment, Development, and Evaluation approach.: After weighing the quality of evidence and balancing the desirable and undesirable effects, the guideline panel made the following recommendations: ) a strong recommendation for the use of long-acting β-agonist (LABA)/long-acting muscarinic antagonist (LAMA) combination therapy over LABA or LAMA monotherapy in patients with COPD and dyspnea or exercise intolerance; ) a conditional recommendation for the use of triple therapy with inhaled corticosteroids (ICS)/LABA/LAMA over dual therapy with LABA/LAMA in patients with COPD and dyspnea or exercise intolerance who have experienced one or more exacerbations in the past year; ) a conditional recommendation for ICS withdrawal for patients with COPD receiving triple therapy (ICS/LABA/LAMA) if the patient has had no exacerbations in the past year; ) no recommendation for or against ICS as an additive therapy to long-acting bronchodilators in patients with COPD and blood eosinophilia, except for those patients with a history of one or more exacerbations in the past year requiring antibiotics or oral steroids or hospitalization, for whom ICS is conditionally recommended as an additive therapy; ) a conditional recommendation against the use of maintenance oral corticosteroids in patients with COPD and a history of severe and frequent exacerbations; and ) a conditional recommendation for opioid-based therapy in patients with COPD who experience advanced refractory dyspnea despite otherwise optimal therapy.: The task force made recommendations regarding the pharmacologic treatment of COPD based on currently available evidence. Additional research in populations that are underrepresented in clinical trials is needed, including studies in patients with COPD 80 years of age and older, those with multiple chronic health conditions, and those with a codiagnosis of COPD and asthma.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31887283,

title = {Machine Learning Characterization of COPD Subtypes: Insights From the COPDGene Study},

author = {Peter J Castaldi and Adel Boueiz and Jeong Yun and Raul San Jose Estepar and James C Ross and George Washko and Michael H Cho and Craig P Hersh and Gregory L Kinney and Kendra A Young and Elizabeth A Regan and David A Lynch and Gerald J Criner and Jennifer G Dy and Stephen I Rennard and Richard Casaburi and Barry J Make and James Crapo and Edwin K Silverman and John E Hokanson and },

doi = {10.1016/j.chest.2019.11.039},

issn = {1931-3543},

year  = {2020},

date = {2020-05-01},

journal = {Chest},

volume = {157},

number = {5},

pages = {1147--1157},

abstract = {COPD is a heterogeneous syndrome. Many COPD subtypes have been proposed, but there is not yet consensus on how many COPD subtypes there are and how they should be defined. The COPD Genetic Epidemiology Study (COPDGene), which has generated 10-year longitudinal chest imaging, spirometry, and molecular data, is a rich resource for relating COPD phenotypes to underlying genetic and molecular mechanisms. In this article, we place COPDGene clustering studies in context with other highly cited COPD clustering studies, and summarize the main COPD subtype findings from COPDGene. First, most manifestations of COPD occur along a continuum, which explains why continuous aspects of COPD or disease axes may be more accurate and reproducible than subtypes identified through clustering methods. Second, continuous COPD-related measures can be used to create subgroups through the use of predictive models to define cut-points, and we review COPDGene research on blood eosinophil count thresholds as a specific example. Third, COPD phenotypes identified or prioritized through machine learning methods have led to novel biological discoveries, including novel emphysema genetic risk variants and systemic inflammatory subtypes of COPD. Fourth, trajectory-based COPD subtyping captures differences in the longitudinal evolution of COPD, addressing a major limitation of clustering analyses that are confounded by disease severity. Ongoing longitudinal characterization of subjects in COPDGene will provide useful insights about the relationship between lung imaging parameters, molecular markers, and COPD progression that will enable the identification of subtypes based on underlying disease processes and distinct patterns of disease progression, with the potential to improve the clinical relevance and reproducibility of COPD subtypes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31471206,

title = {Ventilation Heterogeneity and Its Association with Nodule Formation Among Participants in the National Lung Screening Trial-A Preliminary Investigation},

author = {David A Kaminsky and Nirav Daphtary and Raul S J Estepar and Taka Ashikaga and Lukas Mikulic and Jeffrey Klein and C Matthew Kinsey},

doi = {10.1016/j.acra.2019.07.024},

issn = {1878-4046},

year  = {2020},

date = {2020-05-01},

journal = {Acad Radiol},

volume = {27},

number = {5},

pages = {630--635},

abstract = {RATIONALE AND OBJECTIVES: We have developed a technique to measure ventilation heterogeneity (VH) on low dose chest CT scan that we hypothesize may be associated with the development of lung nodules, and perhaps cancer. If true, such an analysis may improve screening by identifying regional areas of higher risk.nnMATERIALS AND METHODS: Using the National Lung Screening Trial database, we identified a small subset of those participants who were labeled as having a positive screening test at 1 year (T1) but not at baseline (T0). We isolated the region in which the nodule would form on the T0 scan ("target region") and measured VH as the standard deviation of the linear dimension of a virtual cubic airspace based on measurement of lung attenuation within the region.nnRESULTS: We analyzed 24 cases, 9 with lung cancer and 15 with a benign nodule. We found that the VH of the target region was nearly statistically greater than that of the corresponding contralateral control region (0.168 [0.110-0.226] vs. 0.112 [0.083-0.203], p = 0.051). The % emphysema within the target region was greater than that of the corresponding contralateral control region (1.339 [0.264-4.367] vs. 1.092 [0.375-4.748], p = 0.037). There was a significant correlation between the % emphysema and the VH of the target region (rho = +0.437, p = 0.026).nnCONCLUSION: Our study provides the first data in support of increased local VH being associated with subsequent lung nodule formation. Further work is necessary to determine whether this technique can enhance screening for lung cancer by low dose chest CT scan.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32216636,

title = {SlicerDMRI: Diffusion MRI and Tractography Research Software for Brain Cancer Surgery Planning and Visualization},

author = {Fan Zhang and Thomas Noh and Parikshit Juvekar and Sarah F Frisken and Laura Rigolo and Isaiah Norton and Tina Kapur and Sonia Pujol and William Wells and Alex Yarmarkovich and Gordon Kindlmann and Demian Wassermann and Raul San Jose Estepar and Yogesh Rathi and Ron Kikinis and Hans J Johnson and Carl-Fredrik Westin and Steve Pieper and Alexandra J Golby and Lauren J O'Donnell},

doi = {10.1200/CCI.19.00141},

issn = {2473-4276},

year  = {2020},

date = {2020-03-01},

journal = {JCO Clin Cancer Inform},

volume = {4},

pages = {299--309},

abstract = {PURPOSE: We present SlicerDMRI, an open-source software suite that enables research using diffusion magnetic resonance imaging (dMRI), the only modality that can map the white matter connections of the living human brain. SlicerDMRI enables analysis and visualization of dMRI data and is aimed at the needs of clinical research users. SlicerDMRI is built upon and deeply integrated with 3D Slicer, a National Institutes of Health-supported open-source platform for medical image informatics, image processing, and three-dimensional visualization. Integration with 3D Slicer provides many features of interest to cancer researchers, such as real-time integration with neuronavigation equipment, intraoperative imaging modalities, and multimodal data fusion. One key application of SlicerDMRI is in neurosurgery research, where brain mapping using dMRI can provide patient-specific maps of critical brain connections as well as insight into the tissue microstructure that surrounds brain tumors.nnPATIENTS AND METHODS: In this article, we focus on a demonstration of SlicerDMRI as an informatics tool to enable end-to-end dMRI analyses in two retrospective imaging data sets from patients with high-grade glioma. Analyses demonstrated here include conventional diffusion tensor analysis, advanced multifiber tractography, automated identification of critical fiber tracts, and integration of multimodal imagery with dMRI.nnRESULTS: We illustrate the ability of SlicerDMRI to perform both conventional and advanced dMRI analyses as well as to enable multimodal image analysis and visualization. We provide an overview of the clinical rationale for each analysis along with pointers to the SlicerDMRI tools used in each.nnCONCLUSION: SlicerDMRI provides open-source and clinician-accessible research software tools for dMRI analysis. SlicerDMRI is available for easy automated installation through the 3D Slicer Extension Manager.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31369720,

title = {Adult Life-Course Trajectories of Lung Function and the Development of Emphysema: The CARDIA Lung Study},

author = {George R Washko and Laura A Colangelo and Raul San José Estépar and Samuel Y Ash and Surya P Bhatt and Yuka Okajima and Kiang Liu and David R Jacobs and Carlos Iribarren and Bharat Thyagarajan and Cora E Lewis and Rajesh Kumar and MeiLan K Han and Mark T Dransfield and Mercedes R Carnethon and Ravi Kalhan},

doi = {10.1016/j.amjmed.2019.06.049},

issn = {1555-7162},

year  = {2020},

date = {2020-02-01},

journal = {Am J Med},

volume = {133},

number = {2},

pages = {222--230.e11},

abstract = {BACKGROUND: Peak lung function and rate of decline predict future airflow obstruction and nonrespiratory comorbid conditions. Associations between lung function trajectories and emphysema have not been explored.nnMETHODS: Using data from the population-based CARDIA Study, we sought to describe the prevalence of visually ascertained emphysema at multiple time points and contextualize its development based upon participant's adult life course measures of lung function. There were 3171 men and women enrolled at a mean age of 25 years, who underwent serial spirometric examinations through a mean age of 55 years. Trajectories for the change in percent-predicted forced expiratory volume in one second (FEV) were determined by fitting a mixture model via maximum likelihood. Emphysema was visually identified on computed tomographic scans and its prevalence reported at mean ages of 40, 45, and 50 years.nnRESULTS: We identified 5 trajectories describing peak and change in FEV: "Preserved Ideal," "Preserved Good," "Preserved Impaired," "Worsening," and "Persistently Poor." Ever smokers comprised part of all 5 trajectories. The prevalence of emphysema was 1.7% (n = 46; mean age of 40 years), 2.5% (n = 67; mean age of 45 years), and 7.1% (n = 189; mean age of 50 years). Of those with emphysema at a mean age of 50 years, 18.0% were never smokers. Worsening and poor lung health trajectories were associated with increased odds of future emphysema independent of chronic tobacco smoke exposure (odds ratio 5.06; confidence interval, 1.84-13.96; odds ratio 4.85; confidence interval, 1.43-16.44).nnCONCLUSIONS: Lower peak and accelerated decline in FEV are risk factors for future emphysema independent of smoking status.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33758787,

title = {Advances in Chronic Obstructive Pulmonary Disease Imaging},

author = {Wojciech R Dolliver and Alejandro A Diaz},

doi = {10.23866/brnrev:2019-0023},

issn = {2385-7110},

year  = {2020},

date = {2020-01-01},

journal = {Barc Respir Netw Rev},

volume = {6},

number = {2},

pages = {128--143},

abstract = {Chest computed tomography (CT) imaging is a useful tool that provides  information regarding lung structure. Imaging has contributed to a better understanding of COPD, allowing for the detection of early structural changes and the quantification of extra-pulmonary structures. Novel CT imaging techniques have provided insight into the progression of the main COPD subtypes, such as emphysema and small airway disease. This article serves as a review of new information relevant to COPD imaging. CT abnormalities, such as emphysema and loss of airways, are present even in smokers who do not meet the criteria for COPD and in those with mild-to-moderate disease. Subjects with mild-to-moderate COPD, with the highest loss of airways, also experience the highest decline in lung function. Extra-pulmonary manifestations of COPD, such as right ventricle enlargement and low muscle mass measured on CT, are associated with increased risk for all-cause mortality. CT longitudinal data has also given insight into the progression of COPD. Mechanically affected areas of lung parenchyma adjacent to emphysematous areas are associated with a greater decline in FEV. Subjects with the greatest percentage of small airway disease, as measured on matched inspiratory-expiratory CT scan, also present with the greatest decline in lung function.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31699836,

title = {Biobanking and cryopreservation of human lung explants for omic analysis},

author = {Sarah G Chu and Sergio Poli De Frias and Yuichi Sakairi and Rachel S Kelly and Robert Chase and Kazuhisa Konishi and Ashley Blau and Ellen Tsai and Konstantin Tsoyi and Robert F Padera and Lynette M Sholl and Hilary J Goldberg and Hari R Mallidi and Phillip C Camp and Souheil Y El-Chemaly and Mark A Perrella and Augustine M K Choi and George R Washko and Benjamin A Raby and Ivan O Rosas},

doi = {10.1183/13993003.01635-2018},

issn = {1399-3003},

year  = {2020},

date = {2020-01-01},

journal = {Eur Respir J},

volume = {55},

number = {1},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32984450,

title = {The Framingham Heart Study: Populational CT-based phenotyping in the lungs and mediastinum},

author = {Tetsuro Araki and George R Washko and Mark L Schiebler and George T O'Connor and Hiroto Hatabu},

doi = {10.1016/j.ejro.2020.100260},

issn = {2352-0477},

year  = {2020},

date = {2020-01-01},

journal = {Eur J Radiol Open},

volume = {7},

pages = {100260},

abstract = {The Framingham Heart Study (FHS) is one of the largest and established longitudinal populational cohorts. CT cohorts of the FHS since 2002 provided a unique opportunity to assess non-cardiac thoracic imaging findings. This review deals with image-based phenotyping studies from recent major publications regarding interstitial lung abnormalities (ILAs), pulmonary cysts, emphysema, pulmonary nodules, pleural plaques, normal spectrum of the thymus, and anterior mediastinal masses, concluding with the discussion of future directions of FHS CT cohorts studies in the era of radiomics and artificial intelligence.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33521399,

title = {Artificial Intelligence in COPD: New Venues to Study a Complex Disease},

author = {Raúl San José Estépar},

doi = {10.23866/BRNRev:2019-0014},

issn = {2385-7110},

year  = {2020},

date = {2020-01-01},

journal = {Barc Respir Netw Rev},

volume = {6},

number = {2},

pages = {144--160},

abstract = {Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous disease that can benefit from novel approaches to understanding its evolution and divergent trajectories. Artificial intelligence (AI) has revolutionized how we can use clinical, imaging, and molecular data to understand and model complex systems. AI has shown impressive results in areas related to automated clinical decision making, radiological interpretation and prognostication. The unique nature of COPD and the accessibility to well-phenotyped populations result in an ideal scenario for AI development. This review provides an introduction to AI and deep learning and presents some recent successes in applying AI in COPD. Finally, we will discuss some of the opportunities, challenges, and limitations for AI applications in the context of COPD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31941918,

title = {Classification of Interstitial Lung Abnormality Patterns with an Ensemble of Deep Convolutional Neural Networks},

author = {David Bermejo-Peláez and Samuel Y Ash and George R Washko and Raúl San José Estépar and María J Ledesma-Carbayo},

doi = {10.1038/s41598-019-56989-5},

issn = {2045-2322},

year  = {2020},

date = {2020-01-01},

journal = {Sci Rep},

volume = {10},

number = {1},

pages = {338},

abstract = {Subtle interstitial changes in the lung parenchyma of smokers, known as Interstitial Lung Abnormalities (ILA), have been associated with clinical outcomes, including mortality, even in the absence of Interstitial Lung Disease (ILD). Although several methods have been proposed for the automatic identification of more advanced Interstitial Lung Disease (ILD) patterns, few have tackled ILA, which likely precedes the development ILD in some cases. In this context, we propose a novel methodology for automated identification and classification of ILA patterns in computed tomography (CT) images. The proposed method is an ensemble of deep convolutional neural networks (CNNs) that detect more discriminative features by incorporating two, two-and-a-half and three- dimensional architectures, thereby enabling more accurate classification. This technique is implemented by first training each individual CNN, and then combining its output responses to form the overall ensemble output. To train and test the system we used 37424 radiographic tissue samples corresponding to eight different parenchymal feature classes from 208 CT scans. The resulting ensemble performance including an average sensitivity of 91,41% and average specificity of 98,18% suggests it is potentially a viable method to identify radiographic patterns that precede the development of ILD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid33521399b,

title = {Artificial Intelligence in COPD: New Venues to Study a Complex Disease},

author = {Raúl San José Estépar},

doi = {10.23866/BRNRev:2019-0014},

issn = {2385-7110},

year  = {2020},

date = {2020-01-01},

journal = {Barc Respir Netw Rev},

volume = {6},

number = {2},

pages = {144--160},

abstract = {Chronic obstructive pulmonary disease (COPD) is a complex and heterogeneous disease that can benefit from novel approaches to understanding its evolution and divergent trajectories. Artificial intelligence (AI) has revolutionized how we can use clinical, imaging, and molecular data to understand and model complex systems. AI has shown impressive results in areas related to automated clinical decision making, radiological interpretation and prognostication. The unique nature of COPD and the accessibility to well-phenotyped populations result in an ideal scenario for AI development. This review provides an introduction to AI and deep learning and presents some recent successes in applying AI in COPD. Finally, we will discuss some of the opportunities, challenges, and limitations for AI applications in the context of COPD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31339356,

title = {Overlap of Genetic Risk between Interstitial Lung Abnormalities and Idiopathic Pulmonary Fibrosis},

author = {Brian D Hobbs and Rachel K Putman and Tetsuro Araki and Mizuki Nishino and Gunnar Gudmundsson and Vilmundur Gudnason and Gudny Eiriksdottir and Nuno Rodrigues Zilhao Nogueira and Josée Dupuis and Hanfei Xu and George T O'Connor and Ani Manichaikul and Jennifer Nguyen and Anna J Podolanczuk and Purnema Madahar and Jerome I Rotter and David J Lederer and R Graham Barr and Stephen S Rich and Elizabeth J Ampleford and Victor E Ortega and Stephen P Peters and Wanda K O'Neal and John D Newell and Eugene R Bleecker and Deborah A Meyers and Richard J Allen and Justin M Oldham and Shwu-Fan Ma and Imre Noth and R Gisli Jenkins and Toby M Maher and Richard B Hubbard and Louise V Wain and Tasha E Fingerlin and David A Schwartz and George R Washko and Ivan O Rosas and Edwin K Silverman and Hiroto Hatabu and Michael H Cho and Gary M Hunninghake},

doi = {10.1164/rccm.201903-0511OC},

issn = {1535-4970},

year  = {2019},

date = {2019-12-01},

journal = {Am J Respir Crit Care Med},

volume = {200},

number = {11},

pages = {1402--1413},

abstract = { Interstitial lung abnormalities (ILAs) are associated with the highest genetic risk locus for idiopathic pulmonary fibrosis (IPF); however, the extent to which there are unique associations among individuals with ILAs or additional overlap with IPF is not known. To perform a genome-wide association study (GWAS) of ILAs. ILAs and a subpleural-predominant subtype were assessed on chest computed tomography (CT) scans in the AGES (Age Gene/Environment Susceptibility), COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease [COPD]), Framingham Heart, ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate End-points), MESA (Multi-Ethnic Study of Atherosclerosis), and SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study) studies. We performed a GWAS of ILAs in each cohort and combined the results using a meta-analysis. We assessed for overlapping associations in independent GWASs of IPF. Genome-wide genotyping data were available for 1,699 individuals with ILAs and 10,274 control subjects. The  (mucin 5B) promoter variant rs35705950 was significantly associated with both ILAs ( = 2.6 × 10) and subpleural ILAs ( = 1.6 × 10). We discovered novel genome-wide associations near  (rs6886640,  = 3.8 × 10) and  (rs73199442,  = 4.8 × 10) with ILAs, and near  (rs7744971,  = 4.2 × 10) with subpleural-predominant ILAs. These novel associations were not associated with IPF. Among 12 previously reported IPF GWAS loci, five (, , , , and ) were significantly associated ( < 0.05/12) with ILAs. In a GWAS of ILAs in six studies, we confirmed the association with a  promoter variant and found strong evidence for an effect of previously described IPF loci; however, novel ILA associations were not associated with IPF. These findings highlight common genetically driven biologic pathways between ILAs and IPF, and also suggest distinct ones.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31103695,

title = {Right Ventricular-Arterial Uncoupling During Exercise in Heart Failure With Preserved Ejection Fraction: Role of Pulmonary Vascular Dysfunction},

author = {Inderjit Singh and Farbod N Rahaghi and Robert Naeije and Rudolf K F Oliveira and David M Systrom and Aaron B Waxman},

doi = {10.1016/j.chest.2019.04.109},

issn = {1931-3543},

year  = {2019},

date = {2019-11-01},

journal = {Chest},

volume = {156},

number = {5},

pages = {933--943},

abstract = {BACKGROUND: Right ventricular (RV) dysfunction is associated with shortened life expectancy in heart failure with preserved ejection fraction (HFpEF). The contribution of pulmonary vascular dysfunction to RV dysfunction in HFpEF is not well understood.nnMETHODS: We investigated rest and exercise invasive pulmonary hemodynamics, ventilation, and gas exchange in 67 patients with HFpEF (of whom 28 had an abnormal pulmonary vascular response during exercise referred to as HFpEF+PVR group and 39 had a normal pulmonary vascular response during exercise referred to as HFpEF group) and in 21 matched control subjects.nnRESULTS: Both groups of patients with HFpEF had a markedly decreased peak oxygen consumption (Vo), decreased oxygen delivery, and impaired chronotropic response. Single beat analysis of RV pressure waveforms was used to compute the end-systolic elastance (Ees) and pulmonary arterial elastance (Ea). Right ventricular-pulmonary artery (RV-PA) coupling was measured as the ratio of Ees/Ea. Exercise was associated with a preserved Ees response but a decreased Ees/Ea in patients with HFpEF with a normal PVR response, indicating partially preserved RV contractile reserve. In HFpEF+PVR, exercise-induced increase in Ees was markedly reduced, resulting in decreased Ees/Ea and RV-PA uncoupling. Patients with HFpEF+PVR with an exercise-induced decrease in Ees/Ea had lower pulmonary artery compliance, lower peak Vo, and lower stroke volume than patients with HFpEF.nnCONCLUSIONS: We conclude that RV-PA uncoupling is common in HFpEF and is caused by both intrinsic RV contractile impairment and afterload mismatch. Resting and dynamic RV-PA uncoupling in HFpEF is driven by an increase in RV pulsatile rather than resistive afterload. However, with the additive effects of increased RV resistive afterload, RV-PA uncoupling worsens dynamically during exercise.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31391318,

title = {Ambient air pollution exposure and risk and progression of interstitial lung abnormalities: the Framingham Heart Study},

author = {Mary B Rice and Wenyuan Li and Joel Schwartz and Qian Di and Itai Kloog and Petros Koutrakis and Diane R Gold and Robert W Hallowell and Chunyi Zhang and George O'Connor and George R Washko and Gary M Hunninghake and Murray A Mittleman},

doi = {10.1136/thoraxjnl-2018-212877},

issn = {1468-3296},

year  = {2019},

date = {2019-11-01},

journal = {Thorax},

volume = {74},

number = {11},

pages = {1063--1069},

abstract = {BACKGROUND: Ambient air pollution accelerates lung function decline among adults, however, there are limited data about its role in the development and progression of early stages of interstitial lung disease.nnAIMS: To evaluate associations of long-term exposure to traffic and ambient pollutants with odds of interstitial lung abnormalities (ILA) and progression of ILA on repeated imaging.nnMETHODS: We ascertained ILA on chest CT obtained from 2618 Framingham participants from 2008 to 2011. Among 1846 participants who also completed a cardiac CT from 2002 to 2005, we determined interval ILA progression. We assigned distance from home address to major roadway, and the 5-year average of fine particulate matter (PM), elemental carbon (EC, a traffic-related PM constituent) and ozone using spatio-temporal prediction models. Logistic regression models were adjusted for age, sex, body mass index, smoking status, packyears of smoking, household tobacco exposure, neighbourhood household value, primary occupation, cohort and date.nnRESULTS: Among 2618 participants with a chest CT, 176 (6.7%) had ILA, 1361 (52.0%) had no ILA, and the remainder were indeterminate. Among 1846 with a preceding cardiac CT, 118 (6.4%) had ILA with interval progression. In adjusted logistic regression models, an IQR difference in 5-year EC exposure of 0.14 µg/m was associated with a 1.27 (95% CI 1.04 to 1.55) times greater odds of ILA, and a 1.33 (95% CI 1.00 to 1.76) times greater odds of ILA progression. PM and O were not associated with ILA or ILA progression.nnCONCLUSIONS: Exposure to EC may increase risk of progressive ILA, however, associations with other measures of ambient pollution were inconclusive.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31710795,

title = {Subtypes of COPD Have Unique Distributions and Differential Risk of Mortality},

author = {Kendra A Young and Elizabeth A Regan and MeiLan K Han and Sharon M Lutz and Margaret Ragland and Peter J Castaldi and George R Washko and Michael H Cho and Mathew Strand and Douglas Curran-Everett and Terri H Beaty and Russell P Bowler and Emily S Wan and David A Lynch and Barry J Make and Edwin K Silverman and James D Crapo and John E Hokanson and Gregory L Kinney and },

doi = {10.15326/jcopdf.6.5.2019.0150},

issn = {2372-952X},

year  = {2019},

date = {2019-11-01},

journal = {Chronic Obstr Pulm Dis},

volume = {6},

number = {5},

pages = {400--413},

abstract = {BACKGROUND: Previous attempts to explore the heterogeneity of chronic obstructive pulmonary disease (COPD) clustered individual patients using clinical, demographic, and disease features. We developed continuous multidimensional disease axes based on radiographic and spirometric variables that split into an airway-predominant axis and an emphysema-predominant axis.nnMETHODS: The COPD Genetic Epidemiology study (COPDGene) is a cohort of current and former smokers, > 45 years, with at least 10 pack years of smoking history. Spirometry measures, blood pressure and body mass were directly measured. Mortality was assessed through continuing longitudinal follow-up and cause of death was adjudicated. Among 8157 COPDGene participants with complete spirometry and computed tomography (CT) measures, the top 2 deciles of the airway-predominant and emphysema-predominant axes previously identified were used to categorize individuals into 3 groups having the highest risk for mortality using Cox proportional hazard ratios. These groups were also assessed for causal mortality. Biomarkers of COPD (fibrinogen, soluble receptor for advanced glycation end products [sRAGE], C-reactive protein [CRP], clara cell secretory protein [CC16], surfactant-D [SP-D]) were compared by group.nnFINDINGS: High-risk subtype classification was defined for 2638 COPDGene participants who were in the highest 2 deciles of either the airway-predominant and/or emphysema-predominant axis (32% of the cohort). These high-risk participants fell into 3 groups: airway-predominant disease only (APD-only), emphysema-predominant disease only (EPD-only) and combined APD-EPD. There was 26% mortality for the APD-only group, 21% mortality for the EPD-only group, and 54% mortality for the combined APD-EPD group. The APD-only group (n=1007) was younger, had a lower forced expiratory volume in 1 second (FEV) percent (%) predicted and a strong association with the preserved ratio-impaired spirometry (PRISm) quadrant. The EPD-only group (n=1006) showed a relatively higher FEV % predicted and included largely GOLD stage 0, 1 and 2 partipants. Individuals in each of the 3 high-risk groups were at greater risk for respiratory mortality, while those in the APD-only group were additionally at greater risk for cardiovascular mortality. Biomarker analysis demonstrated a significant association of the APD-only group with CRP, and sRAGE demonstrated greatest significance with both the EPD-only and the combined APD-EPD groups.nnINTERPRETATION: Among current and former smokers, individuals in the highest 2 deciles for mortality risk on the airway-predominant axis and the emphysema-predominant axis have unique associations to spirometric patterns, different imaging characteristics, biomarkers and causal mortality.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31710793,

title = {COPDGene 2019: Redefining the Diagnosis of Chronic Obstructive Pulmonary Disease},

author = {Katherine E Lowe and Elizabeth A Regan and Antonio Anzueto and Erin Austin and John H M Austin and Terri H Beaty and Panayiotis V Benos and Christopher J Benway and Surya P Bhatt and Eugene R Bleecker and Sandeep Bodduluri and Jessica Bon and Aladin M Boriek and Adel Re Boueiz and Russell P Bowler and Matthew Budoff and Richard Casaburi and Peter J Castaldi and Jean-Paul Charbonnier and Michael H Cho and Alejandro Comellas and Douglas Conrad and Corinne Costa Davis and Gerard J Criner and Douglas Curran-Everett and Jeffrey L Curtis and Dawn L DeMeo and Alejandro A Diaz and Mark T Dransfield and Jennifer G Dy and Ashraf Fawzy and Margaret Fleming and Eric L Flenaugh and Marilyn G Foreman and Spyridon Fortis and Hirut Gebrekristos and Sarah Grant and Philippe A Grenier and Tian Gu and Abhya Gupta and MeiLan K Han and Nicola A Hanania and Nadia N Hansel and Lystra P Hayden and Craig P Hersh and Brian D Hobbs and Eric A Hoffman and James C Hogg and John E Hokanson and Karin F Hoth and Albert Hsiao and Stephen Humphries and Kathleen Jacobs and Francine L Jacobson and Ella A Kazerooni and Victor Kim and Woo Jin Kim and Gregory L Kinney and Harald Koegler and Sharon M Lutz and David A Lynch and Neil R MacIntye and Barry J Make and Nathaniel Marchetti and Fernando J Martinez and Diego J Maselli and Anne M Mathews and Meredith C McCormack and Merry-Lynn N McDonald and Charlene E McEvoy and Matthew Moll and Sarah S Molye and Susan Murray and Hrudaya Nath and John D Newell and Mariaelena Occhipinti and Matteo Paoletti and Trisha Parekh and Massimo Pistolesi and Katherine A Pratte and Nirupama Putcha and Margaret Ragland and Joseph M Reinhardt and Stephen I Rennard and Richard A Rosiello and James C Ross and Harry B Rossiter and Ingo Ruczinski and Raul San Jose Estepar and Frank C Sciurba and Jessica C Sieren and Harjinder Singh and Xavier Soler and Robert M Steiner and Matthew J Strand and William W Stringer and Ruth Tal-Singer and Byron Thomashow and Gonzalo Vegas Sánchez-Ferrero and John W Walsh and Emily S Wan and George R Washko and J Michael Wells and Chris H Wendt and Gloria Westney and Ava Wilson and Robert A Wise and Andrew Yen and Kendra Young and Jeong Yun and Edwin K Silverman and James D Crapo},

doi = {10.15326/jcopdf.6.5.2019.0149},

issn = {2372-952X},

year  = {2019},

date = {2019-11-01},

journal = {Chronic Obstr Pulm Dis},

volume = {6},

number = {5},

pages = {384--399},

abstract = {BACKGROUND: Chronic obstructive pulmonary disease (COPD) remains a major cause of morbidity and mortality. Present-day diagnostic criteria are largely based solely on spirometric criteria. Accumulating evidence has identified a substantial number of individuals without spirometric evidence of COPD who suffer from respiratory symptoms and/or increased morbidity and mortality. There is a clear need for an expanded definition of COPD that is linked to physiologic, structural (computed tomography [CT]) and clinical evidence of disease. Using data from the COPD Genetic Epidemiology study (COPDGene), we hypothesized that an integrated approach that includes environmental exposure, clinical symptoms, chest CT imaging and spirometry better defines disease and captures the likelihood of progression of respiratory obstruction and mortality.nnMETHODS: Four key disease characteristics - environmental exposure (cigarette smoking), clinical symptoms (dyspnea and/or chronic bronchitis), chest CT imaging abnormalities (emphysema, gas trapping and/or airway wall thickening), and abnormal spirometry - were evaluated in a group of 8784 current and former smokers who were participants in COPDGene Phase 1. Using these 4 disease characteristics, 8 categories of participants were identified and evaluated for odds of spirometric disease progression (FEV > 350 ml loss over 5 years), and the hazard ratio for all-cause mortality was examined.nnRESULTS: Using smokers without symptoms, CT imaging abnormalities or airflow obstruction as the reference population, individuals were classified as Possible COPD, Probable COPD and Definite COPD. Current Global initiative for obstructive Lung Disease (GOLD) criteria would diagnose 4062 (46%) of the 8784 study participants with COPD. The proposed COPDGene 2019 diagnostic criteria would add an additional 3144 participants. Under the new criteria, 82% of the 8784 study participants would be diagnosed with Possible, Probable or Definite COPD. These COPD groups showed increased risk of disease progression and mortality. Mortality increased in patients as the number of their COPD characteristics increased, with a maximum hazard ratio for all cause-mortality of 5.18 (95% confidence interval [CI]: 4.15-6.48) in those with all 4 disease characteristics.nnCONCLUSIONS: A substantial portion of smokers with respiratory symptoms and imaging abnormalities do not manifest spirometric obstruction as defined by population normals. These individuals are at significant risk of death and spirometric disease progression. We propose to redefine the diagnosis of COPD through an integrated approach using environmental exposure, clinical symptoms, CT imaging and spirometric criteria. These expanded criteria offer the potential to stimulate both current and future interventions that could slow or halt disease progression in patients before disability or irreversible lung structural changes develop.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31121149,

title = {Pulmonary Vascular Distensibility and Early Pulmonary Vascular Remodeling in Pulmonary Hypertension},

author = {Inderjit Singh and Rudolf K F Oliveira and Robert Naeije and Farbod N Rahaghi and William M Oldham and David M Systrom and Aaron B Waxman},

doi = {10.1016/j.chest.2019.04.111},

issn = {1931-3543},

year  = {2019},

date = {2019-10-01},

journal = {Chest},

volume = {156},

number = {4},

pages = {724--732},

abstract = {BACKGROUND: Exercise stress testing of the pulmonary circulation may uncover decreased pulmonary vascular (PV) distensibility as a cause of impaired aerobic exercise capacity and right ventricular (RV)-pulmonary arterial (PA) uncoupling. As such, it may help in the differential diagnosis of unexplained dyspnea, including pulmonary hypertension (PH) and/or heart failure with preserved ejection fraction (HFpEF). We investigated rest and exercise invasive pulmonary hemodynamics, ventilation, and gas exchange in patients with unexplained dyspnea, including 44 patients with HFpEF (of whom 20 had a normal pulmonary vascular resistance [PVR] during exercise [ie, passive HFpEF] and 24 had a higher than normal exercise PVR), 22 patients with exercise PH, 19 patients with pulmonary arterial hypertension (PAH), and 24 age- and sex-matched normal control subjects.nnMETHODS: A PV distensibility coefficient α (%/mm Hg) was determined from multipoint PV pressure-flow plots. RV-PA coupling was quantified from the analysis of RV pressure curves to determine ratios of end-systolic to arterial elastances (Ees/Ea). Aerobic exercise capacity was estimated by peak oxygen consumption.nnRESULTS: The α coefficient decreased from 1.35 ± 0.58%/mm Hg in control subjects and 1.1 ± 0.48%/mm Hg in patients with passive HFpEF to 0.62 ± 0.32%/mm Hg in exercise PH, 0.54 ± 0.27%/mm Hg in HFpEF with high exercise PVR, and 0.18 ± 0.16%/mm Hg in PAH. On multivariate analysis, PV distensibility was associated with decreased Ees/Ea and maximal volume of oxygen consumed.nnCONCLUSIONS: PV distensibility is an early and sensitive hemodynamic marker of PV disease that is associated with RV-PA uncoupling and decreased aerobic exercise capacity.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32490437,

title = {Bronchial Cartilage Assessment with Model-Based GAN Regressor},

author = {Pietro Nardelli and George R Washko and Raúl San José Estépar},

doi = {10.1007/978-3-030-32226-7_40},

year  = {2019},

date = {2019-10-01},

journal = {Med Image Comput Comput Assist Interv},

volume = {11769},

pages = {357--365},

abstract = {In the last two decades, several methods for airway segmentation from chest CT images have been proposed. The following natural step is the development of a tool to accurately assess the morphology of the bronchial system in all its aspects to help physicians better diagnosis and prognosis complex pulmonary diseases such as COPD, chronic bronchitis and bronchiectasis. Traditional methods for the assessment of airway morphology usually focus on lumen and wall thickness and are often limited due to resolution and artifacts of the CT image. Airway wall cartilage is an important characteristic related to airway integrity that has shown to be deteriorated during the airway disease process. In this paper, we propose the development of a Model-Based GAN Regressor (MBGR) that, thanks to a model-based GAN generator, generate synthetic airway samples with the morphological components necessary to resemble the appearance of real airways on CT at will and that simultaneously measures lumen, wall thickness, and amount of cartilage on pulmonary CT images. The method is evaluated by first computing the relative error on generated images to show that simulating the cartilage helps improve the morphological quantification of the airway structure. We then propose a cartilage index that summarizes the degree of cartilage of bronchial trees structures and perform an indirect validation with subjects with COPD. As shown by the results, the proposed approach paves the way for the use of CNNs to precisely and accurately measure small lung airways morphology, with the final goal to improve the diagnosis and prognosis of pulmonary diseases.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31347281,

title = {Increased pulmonary artery diameter is associated with reduced FEV in former World Trade Center workers},

author = {Rafael E de la Hoz and Yunho Jeon and Anthony P Reeves and Raúl San José Estépar and Xiaoyu Liu and John T Doucette and Juan C Celedón and Anna Nolan},

doi = {10.1111/crj.13067},

issn = {1752-699X},

year  = {2019},

date = {2019-10-01},

journal = {Clin Respir J},

volume = {13},

number = {10},

pages = {614--623},

abstract = {RATIONALE: Occupational exposures at the WTC site after September 11, 2001 have been associated with several presumably inflammatory lower airway diseases. Pulmonary arterial enlargement, as suggested by an increased ratio of the diameter of the pulmonary artery to the diameter of the aorta (PAAr) has been reported as a computed tomographic (CT) scan marker of adverse respiratory health outcomes, including WTC-related disease. In this study, we sought to utilize a novel quantitative CT (QCT) measurement of PAAr to test the hypothesis that an increased ratio is associated with FEV below each subject's statistically determined lower limit of normal (FEV  < LLN).nnMETHODS: In a group of 1,180 WTC workers and volunteers, we examined whether FEV  < LLN was associated with an increased QCT-measured PAAr, adjusting for previously identified important covariates.nnRESULTS: Unadjusted analyses showed a statistically significant association of FEV  < LLN with PAAr (35.3% vs 24.7%, P = 0.0001), as well as with height, body mass index, early arrival at the WTC disaster site, shorter WTC exposure duration, post-traumatic stress disorder checklist (PCL) score, wall area percent and evidence of bronchodilator response. The multivariate logistic regression model confirmed the association of FEV  < LLN with PAAr (OR 1.63, 95% CI 1.21, 2.20, P = 0.0015) and all the unadjusted associations, except for PCL score.nnCONCLUSIONS: In WTC workers, FEV  < LLN is associated with elevated PAAr which, although likely multifactorial, may be related to distal vasculopathy, as has been hypothesized for chronic obstructive pulmonary disease.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31606045,

title = {Semi-quantitative visual assessment of chest radiography is associated with clinical outcomes in critically ill patients},

author = {Stefanie E Mason and Paul B Dieffenbach and Joshua A Englert and Angela A Rogers and Anthony F Massaro and Laura E Fredenburgh and Angelica Higuera and Mayra Pinilla-Vera and Marta Vilas and Raul San Jose Estepar and George R Washko and Rebecca M Baron and Samuel Y Ash},

doi = {10.1186/s12931-019-1201-0},

issn = {1465-993X},

year  = {2019},

date = {2019-10-01},

journal = {Respir Res},

volume = {20},

number = {1},

pages = {218},

abstract = {BACKGROUND: Respiratory pathology is a major driver of mortality in the intensive care unit (ICU), even in the absence of a primary respiratory diagnosis. Prior work has demonstrated that a visual scoring system applied to chest radiographs (CXR) is associated with adverse outcomes in ICU patients with Acute Respiratory Distress Syndrome (ARDS). We hypothesized that a simple, semi-quantitative CXR score would be associated with clinical outcomes for the general ICU population, regardless of underlying diagnosis.nnMETHODS: All individuals enrolled in the Registry of Critical Illness at Brigham and Women's Hospital between June 2008 and August 2018 who had a CXR within 24 h of admission were included. Each patient's CXR was assigned an opacification score of 0-4 in each of four quadrants with the total score being the sum of all four quadrants. Multivariable negative binomial, logistic, and Cox regression, adjusted for age, sex, race, immunosuppression, a history of chronic obstructive pulmonary disease, a history of congestive heart failure, and APACHE II scores, were used to assess the total score's association with ICU length of stay (LOS), duration of mechanical ventilation, in-hospital mortality, 60-day mortality, and overall mortality, respectively.nnRESULTS: A total of 560 patients were included. Higher CXR scores were associated with increased mortality; for every one-point increase in score, in-hospital mortality increased 10% (OR 1.10, CI 1.05-1.16, p < 0.001) and 60-day mortality increased by 12% (OR 1.12, CI 1.07-1.17, p < 0.001). CXR scores were also independently associated with both ICU length of stay (rate ratio 1.06, CI 1.04-1.07, p < 0.001) and duration of mechanical ventilation (rate ratio 1.05, CI 1.02-1.07, p < 0.001).nnCONCLUSIONS: Higher values on a simple visual score of a patient's CXR on admission to the medical ICU are associated with increased in-hospital mortality, 60-day mortality, overall mortality, length of ICU stay, and duration of mechanical ventilation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32455347,

title = {Targeting Precision with Data Augmented Samples in Deep Learning},

author = {Pietro Nardelli and Raúl San José Estépar},

doi = {10.1007/978-3-030-32226-7_32},

year  = {2019},

date = {2019-10-01},

journal = {Med Image Comput Comput Assist Interv},

volume = {11769},

pages = {284--292},

abstract = {In the last five years, deep learning (DL) has become the state-of-the-art tool for solving various tasks in medical image analysis. Among the different methods that have been proposed to improve the performance of Convolutional Neural Networks (CNNs), one typical approach is the augmentation of the training data set through various transformations of the input image. Data augmentation is typically used in cases where a small amount of data is available, such as the majority of medical imaging problems, to present a more substantial amount of data to the network and improve the overall accuracy. However, the ability of the network to improve the accuracy of the results when a slightly modified version of the same input is presented is often overestimated. This overestimation is the result of the strong correlation between data samples when they are considered independently in the training phase. In this paper, we emphasize the importance of optimizing for accuracy as well as precision among multiple replicates of the same training data in the context of data augmentation. To this end, we propose a new approach that leverages the augmented data to help the network focus on the precision through a specifically-designed loss function, with the ultimate goal to improve both the overall performance and the network's precision at the same time. We present two different applications of DL (regression and segmentation) to demonstrate the strength of the proposed strategy. We think that this work will pave the way to a explicit use of data augmentation within the loss function that helps the network to be invariant to small variations of the same input samples, a characteristic that is always required to every application in the medical imaging field.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31248956,

title = {Radiographic pulmonary vessel volume, lung function and airways disease in the Framingham Heart Study},

author = {Andrew J Synn and Wenyuan Li and Raúl San José Estépar and Chunyi Zhang and George R Washko and George T O'Connor and Tetsuro Araki and Hiroto Hatabu and Alexander A Bankier and Murray A Mittleman and Mary B Rice},

doi = {10.1183/13993003.00408-2019},

issn = {1399-3003},

year  = {2019},

date = {2019-09-01},

journal = {Eur Respir J},

volume = {54},

number = {3},

abstract = {Radiographic abnormalities of the pulmonary vessels, such as vascular pruning, are common in advanced airways disease, but it is unknown if pulmonary vascular volumes are related to measures of lung health and airways disease in healthier populations.In 2388 participants of the Framingham Heart Study computed tomography (CT) sub-study, we calculated total vessel volumes and the small vessel fraction using automated CT image analysis. We evaluated associations with measures of lung function, airflow obstruction on spirometry and emphysema on CT. We further tested if associations of vascular volumes with lung function were present among those with normal forced expiratory volume in 1 s and forced vital capacity.In fully adjusted linear and logistic models, we found that lower total and small vessel volumes were consistently associated with worse measures of lung health, including lower spirometric volumes, lower diffusing capacity and/or higher odds of airflow obstruction. For example, each standard deviation lower small vessel fraction (indicating more severe pruning) was associated with a 37% greater odds of obstruction (OR 1.37, 95% CI 1.11-1.71, p=0.004). A similar pattern was observed in the subset of participants with normal spirometry.Lower total and small vessel pulmonary vascular volumes were associated with poorer measures of lung health and/or greater odds of airflow obstruction in this cohort of generally healthy adults without high burdens of smoking or airways disease. Our findings suggest that quantitative CT assessment may detect subtle pulmonary vasculopathy that occurs in the setting of subclinical and early pulmonary and airways pathology.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30836008,

title = {Validation of Imaging Measures in Chronic Obstructive Pulmonary Disease},

author = {Carrie Pistenmaa Aaron and George R Washko},

doi = {10.1164/rccm.201902-0395ED},

issn = {1535-4970},

year  = {2019},

date = {2019-09-01},

journal = {Am J Respir Crit Care Med},

volume = {200},

number = {5},

pages = {524--525},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30758975,

title = {Arterial Vascular Pruning, Right Ventricular Size, and Clinical Outcomes in Chronic Obstructive Pulmonary Disease. A Longitudinal Observational Study},

author = {George R Washko and Pietro Nardelli and Samuel Y Ash and Gonzalo Vegas Sanchez-Ferrero and Farbod N Rahaghi and Carolyn E Come and Mark T Dransfield and Ravi Kalhan and MeiLan K Han and Surya P Bhatt and J Michael Wells and Carrie Pistenmaa Aaron and Alejandro A Diaz and James C Ross and Michael J Cuttica and Wassim W Labaki and Gabriela Querejeta Roca and Amil M Shah and Kendra Young and Gregory L Kinney and John E Hokanson and Alvar Agustí and Raúl San José Estépar},

doi = {10.1164/rccm.201811-2063OC},

issn = {1535-4970},

year  = {2019},

date = {2019-08-01},

journal = {Am J Respir Crit Care Med},

volume = {200},

number = {4},

pages = {454--461},

abstract = { Cor pulmonale (right ventricular [RV] dilation) and cor pulmonale parvus (RV shrinkage) are both described in chronic obstructive pulmonary disease (COPD). The identification of emphysema as a shared risk factor suggests that additional disease characterization is needed to understand these widely divergent cardiac processes. To explore the relationship between computed tomography measures of emphysema and distal pulmonary arterial morphology with RV volume, and their association with exercise capacity and mortality in ever-smokers with COPD enrolled in the COPDGene Study. Epicardial (myocardium and chamber) RV volume (RV), distal pulmonary arterial blood vessel volume (arterial BV5: vessels <5 mm in cross-section), and objective measures of emphysema were extracted from 3,506 COPDGene computed tomography scans. Multivariable linear and Cox regression models and the log-rank test were used to explore the association between emphysema, arterial BV5, and RV with exercise capacity (6-min-walk distance) and all-cause mortality. The RV was approximately 10% smaller in Global Initiative for Chronic Obstructive Lung Disease stage 4 versus stage 1 COPD ( < 0.0001). In multivariable modeling, a 10-ml decrease in arterial BV5 (pruning) was associated with a 1-ml increase in RV. For a given amount of emphysema, relative preservation of the arterial BV5 was associated with a smaller RV. An increased RV was associated with reduced 6-minute-walk distance and in those with arterial pruning an increased mortality. Pulmonary arterial pruning is associated with clinically significant increases in RV volume in smokers with COPD and is related to exercise capacity and mortality in COPD.Clinical trial registered with www.clinicaltrials.gov (NCT00608764).},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31154041,

title = {Clinical Epidemiology of COPD: Insights From 10 Years of the COPDGene Study},

author = {Diego J Maselli and Surya P Bhatt and Antonio Anzueto and Russell P Bowler and Dawn L DeMeo and Alejandro A Diaz and Mark T Dransfield and Ashraf Fawzy and Marilyn G Foreman and Nicola A Hanania and Craig P Hersh and Victor Kim and Gregory L Kinney and Nirupama Putcha and Emily S Wan and J Michael Wells and Gloria E Westney and Kendra A Young and Edwin K Silverman and MeiLan K Han and Barry J Make},

doi = {10.1016/j.chest.2019.04.135},

issn = {1931-3543},

year  = {2019},

date = {2019-08-01},

journal = {Chest},

volume = {156},

number = {2},

pages = {228--238},

abstract = {The Genetic Epidemiology of COPD (COPDGene) study is a noninterventional, multicenter, longitudinal analysis of > 10,000 subjects, including smokers with a ≥ 10 pack-year history with and without COPD and healthy never smokers. The goal was to characterize disease-related phenotypes and explore associations with susceptibility genes. The subjects were extensively phenotyped with the use of comprehensive symptom and comorbidity questionnaires, spirometry, CT scans of the chest, and genetic and biomarker profiling. The objective of this review was to summarize the major advances in the clinical epidemiology of COPD from the first 10 years of the COPDGene study. We highlight the influence of age, sex, and race on the natural history of COPD, and the impact of comorbid conditions, chronic bronchitis, exacerbations, and asthma/COPD overlap.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31254057,

title = {Association of Obesity with Quantitative Chest CT Measured Airway Wall Thickness in WTC Workers with Lower Airway Disease},

author = {Rafael E de la Hoz and Xiaoyu Liu and Juan C Celedón and John T Doucette and Yunho Jeon and Anthony P Reeves and Raúl San José Estépar},

doi = {10.1007/s00408-019-00246-z},

issn = {1432-1750},

year  = {2019},

date = {2019-08-01},

journal = {Lung},

volume = {197},

number = {4},

pages = {517--522},

abstract = {BACKGROUND: We previously reported that wall area percent (WAP), a quantitative CT (QCT) indicator of airway wall thickness and, presumably, inflammation, is associated with adverse longitudinal expiratory flow trajectories in WTC workers, but that obesity and weight gain also seemed to be independently predictive of the latter. Previous studies have reported no association between WAP and obesity, so we investigated that association in nonsmoking WTC-exposed individuals and healthy unexposed controls.nnMETHODS: We assessed WAP using the Chest Imaging Platform QCT system in a segmental bronchus in 118 former WTC workers, and 89 COPDGene® WTC-unexposed and asymptomatic subjects. We used multiple regression to model WAP vs. body mass index (BMI) in the two groups, adjusting for important subject and CT image characteristics.nnRESULTS: Unadjusted analyses revealed significant differences between the two groups with regards to WAP, age, gender, scan pixel spacing and slice interval, but not BMI or total lung capacity. In adjusted analysis, there was a significant interaction between BMI and WTC exposure on WAP. BMI was significantly and positively associated with WAP in the WTC group, but not in the COPDGene® group, but stratified analyses revealed that the effect was significant in WTC subjects with clinical evidence of lower airway disease (LAD).nnDISCUSSION: Unlike non-diseased subjects, BMI was significantly associated with WAP in WTC workers and, in stratified analyses, the association was significant only among those with LAD. Our findings suggest that this adverse effect of obesity on airway structure and inflammation may be confined to already diseased individuals.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31196942,

title = {Pulmonary vascular density: comparison of findings on computed tomography imaging with histology},

author = {Farbod N Rahaghi and Gemma Argemí and Pietro Nardelli and David Domínguez-Fandos and Pedro Arguis and Víctor I Peinado and James C Ross and Samuel Y Ash and Isaac de La Bruere and Carolyn E Come and Alejandro A Diaz and Marcelo Sánchez and George R Washko and Joan Albert Barberà and Raúl San José Estépar},

doi = {10.1183/13993003.00370-2019},

issn = {1399-3003},

year  = {2019},

date = {2019-08-01},

journal = {Eur Respir J},

volume = {54},

number = {2},

abstract = {BACKGROUND: Exposure to cigarette smoke has been shown to lead to vascular remodelling. Computed tomography (CT) imaging measures of vascular pruning have been associated with pulmonary vascular disease, an important morbidity associated with smoking. In this study we compare CT-based measures of distal vessel loss to histological vascular and parenchymal changes.nnMETHODS: A retrospective review of 80 patients who had undergone lung resection identified patients with imaging appropriate for three-dimensional (3D) vascular reconstruction (n=18) and a second group for two-dimensional (2D) analysis (n=19). Measurements of the volume of the small vessels (3D) and the cross-sectional area of the small vessels (<5 mm cross-section) were computed. Histological measures of cross-sectional area of the vasculature and loss of alveoli septa were obtained for all subjects.nnRESULTS: The 2D cross-sectional area of the vasculature on CT imaging was associated with the histological vascular cross-sectional area (r=0.69; p=0.001). The arterial small vessel volume assessed by CT correlated with the histological vascular cross-sectional area (r=0.50; p=0.04), a relationship that persisted even when adjusted for CT-derived measures of emphysema in a regression model.nnCONCLUSIONS: Loss of small vessel volume in CT imaging of smokers is associated with histological loss of vascular cross-sectional area. Imaging-based quantification of pulmonary vasculature provides a noninvasive method to study the multiscale effects of smoking on the pulmonary circulation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31343404,

title = {Identification of an emphysema-associated genetic variant near  with regulatory effects in lung fibroblasts},

author = {Margaret M Parker and Yuan Hao and Feng Guo and Betty Pham and Robert Chase and John Platig and Michael H Cho and Craig P Hersh and Victor J Thannickal and James Crapo and George Washko and Scott H Randell and Edwin K Silverman and Raúl San José Estépar and Xiaobo Zhou and Peter J Castaldi},

doi = {10.7554/eLife.42720},

issn = {2050-084X},

year  = {2019},

date = {2019-07-01},

journal = {Elife},

volume = {8},

abstract = {Murine studies have linked TGF-β signaling to emphysema, and human genome-wide association studies (GWAS) studies of lung function and COPD have identified associated regions near genes in the TGF-β superfamily. However, the functional regulatory mechanisms at these loci have not been identified. We performed the largest GWAS of emphysema patterns to date, identifying 10 GWAS loci including an association peak spanning a 200 kb region downstream from . Integrative analysis of publicly available eQTL, DNaseI, and chromatin conformation data identified a putative functional variant, rs1690789, that may regulate  expression in human fibroblasts. Using chromatin conformation capture, we confirmed that the region containing rs1690789 contacts the  promoter in fibroblasts, and CRISPR/Cas-9 targeted deletion of a ~ 100 bp region containing rs1690789 resulted in decreased  expression in primary human lung fibroblasts. These data provide novel mechanistic evidence linking genetic variation affecting the TGF-β pathway to emphysema in humans.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31069809,

title = {Harmonization of chest CT scans for different doses and reconstruction methods},

author = {Gonzalo Vegas-Sánchez-Ferrero and Maria Jesus Ledesma-Carbayo and George R Washko and Raúl San José Estépar},

doi = {10.1002/mp.13578},

issn = {2473-4209},

year  = {2019},

date = {2019-07-01},

journal = {Med Phys},

volume = {46},

number = {7},

pages = {3117--3132},

abstract = {PURPOSE: To develop and validate a computed tomography (CT) harmonization technique by combining noise-stabilization and autocalibration methodologies to provide reliable densitometry measurements in heterogeneous acquisition protocols.nnMETHODS: We propose to reduce the effects of spatially variant noise such as nonuniform patterns of noise and biases. The method combines the statistical characterization of the signal-to-noise relationship in the CT image intensities, which allows us to estimate both the signal and spatially variant variance of noise, with an autocalibration technique that reduces the nonuniform biases caused by noise and reconstruction techniques. The method is firstly validated with anthropomorphic synthetic images that simulate CT acquisitions with variable scanning parameters: different dosage, nonhomogeneous variance of noise, and various reconstruction methods. We finally evaluate these effects and the ability of our method to provide consistent densitometric measurements in a cohort of clinical chest CT scans from two vendors (Siemens, n = 54 subjects; and GE, n = 50 subjects) acquired with several reconstruction algorithms (filtered back-projection and iterative reconstructions) with high-dose and low-dose protocols.nnRESULTS: The harmonization reduces the effect of nonhomogeneous noise without compromising the resolution of the images (25% RMSE reduction in both clinical datasets). An analysis through hierarchical linear models showed that the average biases induced by differences in dosage and reconstruction methods are also reduced up to 74.20%, enabling comparable results between high-dose and low-dose reconstructions. We also assessed the statistical similarity between acquisitions obtaining increases of up to 30% points and showing that the low-dose vs high-dose comparisons of harmonized data obtain similar and even higher similarity than the observed for high-dose vs high-dose comparisons of nonharmonized data.nnCONCLUSION: The proposed harmonization technique allows to compare measures of low-dose with high-dose acquisitions without using a specific reconstruction as a reference. Since the harmonization does not require a precalibration with a phantom, it can be applied to retrospective studies. This approach might be suitable for multicenter trials for which a reference reconstruction is not feasible or hard to define due to differences in vendors, models, and reconstruction techniques.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30673508,

title = {Imaging Patterns Are Associated with Interstitial Lung Abnormality Progression and Mortality},

author = {Rachel K Putman and Gunnar Gudmundsson and Gisli Thor Axelsson and Tomoyuki Hida and Osamu Honda and Tetsuro Araki and Masahiro Yanagawa and Mizuki Nishino and Ezra R Miller and Gudny Eiriksdottir and Elías F Gudmundsson and Noriyuki Tomiyama and Hiroshi Honda and Ivan O Rosas and George R Washko and Michael H Cho and David A Schwartz and Vilmundur Gudnason and Hiroto Hatabu and Gary M Hunninghake},

doi = {10.1164/rccm.201809-1652OC},

issn = {1535-4970},

year  = {2019},

date = {2019-07-01},

journal = {Am J Respir Crit Care Med},

volume = {200},

number = {2},

pages = {175--183},

abstract = { Interstitial lung abnormalities (ILA) are radiologic abnormalities on chest computed tomography scans that have been associated with an early or mild form of pulmonary fibrosis. Although ILA have been associated with radiologic progression, it is not known if specific imaging patterns are associated with progression or risk of mortality.  To determine the role of imaging patterns on the risk of death and ILA progression.  ILA (and imaging pattern) were assessed in 5,320 participants from the AGES-Reykjavik Study, and ILA progression was assessed in 3,167 participants. Multivariable logistic regression was used to assess factors associated with ILA progression, and Cox proportional hazards models were used to assess time to mortality.  Over 5 years, 327 (10%) had ILA on at least one computed tomography, and 1,435 (45%) did not have ILA on either computed tomography. Of those with ILA, 238 (73%) had imaging progression, whereas 89 (27%) had stable to improved imaging; increasing age and copies of  genotype were associated with imaging progression. The definite fibrosis pattern was associated with the highest risk of progression (odds ratio, 8.4; 95% confidence interval, 2.7-25;  = 0.0003). Specific imaging patterns were also associated with an increased risk of death. After adjustment, both a probable usual interstitial pneumonia and usual interstitial pneumonia pattern were associated with an increased risk of death when compared with those indeterminate for usual interstitial pneumonia (hazard ratio, 1.7; 95% confidence interval, 1.2-2.4;  = 0.001; hazard ratio, 3.9; 95% confidence interval, 2.3-6.8; < 0.0001), respectively.  In those with ILA, imaging patterns can be used to help predict who is at the greatest risk of progression and early death.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30714821,

title = {Cigarette Smoke Exposure and Radiographic Pulmonary Vascular Morphology in the Framingham Heart Study},

author = {Andrew J Synn and Chunyi Zhang and George R Washko and Raúl San José Estépar and George T O'Connor and Wenyuan Li and Murray A Mittleman and Mary B Rice},

doi = {10.1513/AnnalsATS.201811-795OC},

issn = {2325-6621},

year  = {2019},

date = {2019-06-01},

journal = {Ann Am Thorac Soc},

volume = {16},

number = {6},

pages = {698--706},

abstract = { Cigarette smoke exposure is a risk factor for many lung diseases, and histologic studies suggest that tobacco-related vasoconstriction and vessel loss plays a role in the development of emphysema. However, it remains unclear how tobacco affects the pulmonary vasculature in general populations with a typical range of tobacco exposure, and whether these changes are detectable by radiographic methods.  To determine whether tobacco exposure in a generally healthy population manifests as lower pulmonary blood vessel volumes and vascular pruning on imaging.  A total of 2,410 Framingham Heart Study participants with demographic data and smoking history underwent volumetric whole-lung computed tomography from 2008 to 2011. Automated algorithms calculated the total blood volume of all intrapulmonary vessels (TBV), smaller peripheral vessels (defined as cross-sectional area <5 mm [BV5]), and the relative fraction of small vessels (BV5/TBV). Tobacco exposure was assessed as smoking status, cumulative pack-years, and second-hand exposure. We constructed multivariable linear regression models to evaluate associations of cigarette exposure and pulmonary blood vessel volume measures, adjusting for demographic covariates, including age, sex, height, weight, education, occupation, and median neighborhood income.  All metrics of tobacco exposure (including smoking status, pack-years, and second-hand exposure) were consistently associated with higher absolute pulmonary blood vessel volume, higher small vessel volume, and/or higher small vessel fraction. For example, ever-smokers had a 4.6 ml higher TBV (95% confidence interval [CI] = 2.9-6.3,  < 0.001), 2.1 ml higher BV5 (95% CI = 1.3-2.9,  < 0.001), and 0.28 percentage-point-higher BV5/TBV (95% CI = 0.03-0.52,  = 0.03) compared with never-smokers. These associations remained significant after adjustment for percent predicted forced expiratory volume in 1 second, cardiovascular comorbidities, and did not differ based on presence or absence of airflow obstruction.  Using computed tomographic imaging, we found that cigarette exposure was associated with higher pulmonary blood vessel volumes, especially in the smaller peripheral vessels. Although, histologically, tobacco-related vasculopathy is characterized by vessel narrowing and loss, our results suggest that radiographic vascular pruning may not be a surrogate of these pathologic changes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32461782,

title = {A SR-NET 3D-TO-2D ARCHITECTURE FOR PARASEPTAL EMPHYSEMA SEGMENTATION},

author = {D Bermejo-Peláez and Y Okajima and G R Washko and M J Ledesma-Carbayo and R San José Estépar},

doi = {10.1109/isbi.2019.8759184},

issn = {1945-7928},

year  = {2019},

date = {2019-04-01},

journal = {Proc IEEE Int Symp Biomed Imaging},

volume = {2019},

pages = {303--306},

abstract = {Paraseptal emphysema (PSE) is a relatively unexplored emphysema subtype that is usually asymptomatic, but recently associated with interstitial lung abnormalities which are related with clinical outcomes, including mortality. Previous local-based methods for emphysema subtype quantification do not properly characterize PSE. This is in part for their inability to properly capture the global aspect of the disease, as some the PSE lesions can involved large regions along the chest wall. It is our assumption, that path-based approaches are not well-suited to identify this subtype and segmentation is a better paradigm. In this work we propose and introduce the Slice-Recovery network () that leverages 3D contextual information for 2D segmentation of PSE lesions in CT images. For that purpose, a novel convolutional network architecture is presented, which follows an encoding-decoding path that processes a 3D volume to generate a 2D segmentation map. The dataset used for training and testing the method comprised 664 images, coming from 111 CT scans. The results demonstrate the benefit of the proposed approach which incorporate 3D context information to the network and the ability of the proposed method to identify and segment PSE lesions with different sizes even in the presence of other emphysema subtypes in an advanced stage.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32454949,

title = {LOCALIZING IMAGE-BASED BIOMARKER REGRESSION WITHOUT TRAINING MASKS: A NEW APPROACH TO BIOMARKER DISCOVERY},

author = {Carlos Cano-Espinosa and Germán González and George R Washko and Miguel Cazorla and Raúl San José Estépar},

doi = {10.1109/isbi.2019.8759474},

issn = {1945-7928},

year  = {2019},

date = {2019-04-01},

journal = {Proc IEEE Int Symp Biomed Imaging},

volume = {2019},

pages = {679--682},

abstract = {Biomarker inference from biomedical images is one of the main tasks of medical image analysis. Standard techniques follow a segmentation-and-measure strategy, where the structure is first segmented and then the measurement is performed. Recent work has shown that such strategy could be replaced by a direct regression of the biomarker value in using regression networks. While achieving high correlation coefficients, such techniques operate as a 'black-box', not offering quality-control images. We present a methodology to regress the biomarker from the image while simultaneously computing the quality control image. Our proposed methodology does not require segmentation masks for training, but infers the segmentations directly from the pixels that used to compute the biomarker value. The network proposed consists of two steps: a segmentation method to an unknown reference and a summation method for the biomarker estimation. The network is optimized using a dual loss function, L2 for the biomarkers and an L1 to enforce sparsity. We showcase our methodology in the problem of pectoralis muscle area (PMA) and subcutaneous fat area (SFA) inference in a single slice from chest-CT images. We use a database of 7000 cases to which only the value of the biomarker is known for training and a test set of 3000 cases with both, biomarkers and segmentations. We achieve a correlation coefficient of 0.97 for PMA and 0.98 for SFA with respect to the reference standard. The average DICE coefficient is of 0.88 (PMA) and 0.89 (SFA). Comparing with standard segment-and-measure techniques, we achieve the same correlation for the biomarkers but smaller DICE coefficients in segmentation. Such is of little surprise, since segmentation networks are the upper limit of performance achievable, and we are not using segmentation masks for training. We can conclude that it is possible to infer segmentation masks from biomarker regression networks.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30543456,

title = {Increased Airway Wall Thickness in Interstitial Lung Abnormalities and Idiopathic Pulmonary Fibrosis},

author = {Ezra R Miller and Rachel K Putman and Alejandro A Diaz and Hanfei Xu and Raúl San José Estépar and Tetsuro Araki and Mizuki Nishino and Sergio Poli de Frías and Tomoyuki Hida and James Ross and Harvey Coxson and Josée Dupuis and George T O'Connor and Edwin K Silverman and Ivan O Rosas and Hiroto Hatabu and George Washko and Gary M Hunninghake},

doi = {10.1513/AnnalsATS.201806-424OC},

issn = {2325-6621},

year  = {2019},

date = {2019-04-01},

journal = {Ann Am Thorac Soc},

volume = {16},

number = {4},

pages = {447--454},

abstract = {RATIONALE: There is increasing evidence that aberrant processes occurring in the airways may precede the development of idiopathic pulmonary fibrosis (IPF); however, there has been no prior confirmatory data derived from imaging studies.nnOBJECTIVES: To assess quantitative measures of airway wall thickness (AWT) in populations characterized for interstitial lung abnormalities (ILA) and for IPF.nnMETHODS: Computed tomographic imaging of the chest and measures of AWT were available for 6,073, 615, 1,167, and 38 participants from COPDGene (Genetic Epidemiology of COPD study), ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints study), and the Framingham Heart Study (FHS) and in patients with IPF from the Brigham and Women's Hospital Herlihy Registry, respectively. To evaluate these associations, we used multivariable linear regression to compare a standardized measure of AWT (the square root of AWT for airways with an internal perimeter of 10 mm [Pi10]) and characterizations of ILA and IPF by computed tomographic imaging of the chest.nnRESULTS: In COPDGene, ECLIPSE, and FHS, research participants with ILA had increased measures of Pi10 compared with those without ILA. Patients with IPF had mean measures of Pi10 that were even greater than those noted in research participants with ILA. After adjustment for important covariates (e.g., age, sex, race, body mass index, smoking behavior, and chronic obstructive pulmonary disease severity when appropriate), research participants with ILA had increased measures of Pi10 compared with those without ILA (0.03 mm in COPDGene, 95% confidence interval [CI], 0.02-0.03; P < 0.001; 0.02 mm in ECLIPSE, 95% CI, 0.005-0.04; P = 0.01; 0.07 mm in FHS, 95% CI, 0.01-0.1; P = 0.01). Compared with COPDGene participants without ILA older than 60 years of age, patients with IPF were also noted to have increased measures of Pi10 (2.0 mm, 95% CI, 2.0-2.1; P < 0.001). Among research participants with ILA, increases in Pi10 were correlated with reductions in lung volumes in some but not all populations.nnCONCLUSIONS: These results demonstrate that measurable increases in AWT are consistently noted in research participants with ILA and in patients with IPF. These findings suggest that abnormalities of the airways may play a role in, or be correlated with, early pathogenesis of pulmonary fibrosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31750077,

title = {Using a spatial point process framework to characterize lung computed tomography scans},

author = {Brian E Vestal and Nichole E Carlson and Raúl San José Estépar and Tasha Fingerlin and Debashis Ghosh and Katerina Kechris and David Lynch},

doi = {10.1016/j.spasta.2018.12.003},

issn = {2211-6753},

year  = {2019},

date = {2019-03-01},

journal = {Spat Stat},

volume = {29},

pages = {243--267},

abstract = {Pulmonary emphysema is a destructive disease of the lungs that is currently diagnosed via visual assessment of lung Computed Tomography (CT) scans by a radiologist. Visual assessment can have poor inter-rater reliability, is time consuming, and requires access to trained assessors. Quantitative methods that reliably summarize the biologically relevant characteristics of an image are needed to improve the way lung diseases are characterized. The goal of this work was to show how spatial point process models can be used to create a set of radiologically derived quantitative lung biomarkers of emphysema. We formalized a general framework for applying spatial point processes to lung CT scans, and developed a Shot Noise Cox Process to quantify how radiologically based emphysematous tissue clusters into larger structures. Bayesian estimation of model parameters was done using spatial Birth-Death MCMC (BD-MCMC). In simulations, we showed the BD-MCMC estimation algorithm is able to accurately recover model parameters. In an application to real lung CT scans from the COPDGene cohort, we showed variability in the clustering characteristics of emphysematous tissue across disease subtypes that were based on visual assessments of the CT scans.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30579223,

title = {A graph-cut approach for pulmonary artery-vein segmentation in noncontrast CT images},

author = {Daniel Jimenez-Carretero and David Bermejo-Peláez and Pietro Nardelli and Patricia Fraga and Eduardo Fraile and Raúl San José Estépar and Maria J Ledesma-Carbayo},

doi = {10.1016/j.media.2018.11.011},

issn = {1361-8423},

year  = {2019},

date = {2019-02-01},

journal = {Med Image Anal},

volume = {52},

pages = {144--159},

abstract = {Lung vessel segmentation has been widely explored by the biomedical image processing community; however, the differentiation of arterial from venous irrigation is still a challenge. Pulmonary artery-vein (AV) segmentation using computed tomography (CT) is growing in importance owing to its undeniable utility in multiple cardiopulmonary pathological states, especially those implying vascular remodelling, allowing the study of both flow systems separately. We present a new framework to approach the separation of tree-like structures using local information and a specifically designed graph-cut methodology that ensures connectivity as well as the spatial and directional consistency of the derived subtrees. This framework has been applied to the pulmonary AV classification using a random forest (RF) pre-classifier to exploit the local anatomical differences of arteries and veins. The evaluation of the system was performed using 192 bronchopulmonary segment phantoms, 48 anthropomorphic pulmonary CT phantoms, and 26 lungs from noncontrast CT images with precise voxel-based reference standards obtained by manually labelling the vessel trees. The experiments reveal a relevant improvement in the accuracy ( ∼ 20%) of the vessel particle classification with the proposed framework with respect to using only the pre-classification based on local information applied to the whole area of the lung under study. The results demonstrated the accurate differentiation between arteries and veins in both clinical and synthetic cases, specifically when the image quality can guarantee a good airway segmentation, which opens a huge range of possibilities in the clinical study of cardiopulmonary diseases.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30304637,

title = {Imaging Advances in Chronic Obstructive Pulmonary Disease. Insights from the Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) Study},

author = {Surya P Bhatt and George R Washko and Eric A Hoffman and John D Newell and Sandeep Bodduluri and Alejandro A Diaz and Craig J Galban and Edwin K Silverman and Raúl San José Estépar and David A Lynch},

doi = {10.1164/rccm.201807-1351SO},

issn = {1535-4970},

year  = {2019},

date = {2019-02-01},

journal = {Am J Respir Crit Care Med},

volume = {199},

number = {3},

pages = {286--301},

abstract = {The Genetic Epidemiology of Chronic Obstructive Pulmonary Disease (COPDGene) study, which began in 2007, is an ongoing multicenter observational cohort study of more than 10,000 current and former smokers. The study is aimed at understanding the etiology, progression, and heterogeneity of chronic obstructive pulmonary disease (COPD). In addition to genetic analysis, the participants have been extensively characterized by clinical questionnaires, spirometry, volumetric inspiratory and expiratory computed tomography, and longitudinal follow-up, including follow-up computed tomography at 5 years after enrollment. The purpose of this state-of-the-art review is to summarize the major advances in our understanding of COPD resulting from the imaging findings in the COPDGene study. Imaging features that are associated with adverse clinical outcomes include early interstitial lung abnormalities, visual presence and pattern of emphysema, the ratio of pulmonary artery to ascending aortic diameter, quantitative evaluation of emphysema, airway wall thickness, and expiratory gas trapping. COPD is characterized by the early involvement of the small conducting airways, and the addition of expiratory scans has enabled measurement of small airway disease. Computational advances have enabled indirect measurement of nonemphysematous gas trapping. These metrics have provided insights into the pathogenesis and prognosis of COPD and have aided early identification of disease. Important quantifiable extrapulmonary findings include coronary artery calcification, cardiac morphology, intrathoracic and extrathoracic fat, and osteoporosis. Current active research includes identification of novel quantitative measures for emphysema and airway disease, evaluation of dose reduction techniques, and use of deep learning for phenotyping COPD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30578386,

title = {Association of outdoor temperature with lung function in a temperate climate},

author = {Mary B Rice and Wenyuan Li and Elissa H Wilker and Diane R Gold and Joel Schwartz and Antonella Zanobetti and Petros Koutrakis and Itai Kloog and George R Washko and George T O'Connor and Murray A Mittleman},

doi = {10.1183/13993003.00612-2018},

issn = {1399-3003},

year  = {2019},

date = {2019-01-01},

journal = {Eur Respir J},

volume = {53},

number = {1},

abstract = {Acute exposure to cold dry air is a trigger of bronchoconstriction, but little is known about how daily outdoor temperature influences lung function.We investigated associations of temperature from a model using satellite remote sensing data with repeated measures of lung function among 5896 participants of the Framingham Heart Study Offspring and Third Generation cohorts residing in the Northeastern US. We further tested if temperature modified previously reported associations between pollution and lung function. We constructed linear mixed-effects models, and assessed departures from linearity using penalised splines.In fully adjusted linear models, 1-, 2- and 7-day average temperatures were all associated with lower lung function: each 5°C higher previous-week temperature was associated with a 20 mL lower (95% CI -34---6) forced expiratory volume in 1 s. There was significant effect modification by season: negative associations of temperature and lung function were present in winter and spring only. Negative associations between previous-day fine particulate matter and lung function were present during unseasonably warm but not unseasonably cool days, with a similar pattern for other pollutants.We speculate that temperature-related differences in lung function may be explained by behavioural changes on relatively warm days, which may increase outdoor exposures.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid31218910,

title = {Dynamic right ventricular-pulmonary arterial uncoupling during maximum incremental exercise in exercise pulmonary hypertension and pulmonary arterial hypertension},

author = {Inderjit Singh and Farbod N Rahaghi and Robert Naeije and Rudolf K F Oliveira and Rebecca R Vanderpool and Aaron B Waxman and David M Systrom},

doi = {10.1177/2045894019862435},

issn = {2045-8932},

year  = {2019},

date = {2019-01-01},

journal = {Pulm Circ},

volume = {9},

number = {3},

pages = {2045894019862435},

abstract = {Despite recent advances, the prognosis of pulmonary hypertension (PH) remains poor. While the initial insult in PH implicates the pulmonary vasculature, the functional state, exercise capacity, and survival of such patients are closely linked to right ventricular (RV) function. In the current study, we sought to investigate the effects of maximum incremental exercise on the matching of RV contractility and afterload (i.e. right ventricular-pulmonary arterial [RV-PA] coupling) in patients with exercise PH (ePH) and pulmonary arterial hypertension (PAH). End-systolic elastance (Ees), pulmonary arterial elastance (Ea), and RV-PA coupling (Ees/Ea) were determined using single-beat pressure-volume loop analysis in 40 patients that underwent maximum invasive cardiopulmonary exercise testing. Eleven patients had ePH, nine had PAH, and 20 were age-matched controls. During exercise, the impaired exertional contractile reserve in PAH was associated with blunted stroke volume index (SVI) augmentation and reduced peak oxygen consumption (peak VO %predicted). Compared to PAH, ePH demonstrated increased RV contractility in response to increasing RV afterload during exercise; however, this was insufficient and resulted in reduced peak RV-PA coupling. The dynamic RV-PA uncoupling in ePH was associated with similarly blunted SVI augmentation and peak VO as PAH. In conclusion, dynamic rest-to-peak exercise RV-PA uncoupling during maximum exercise blunts SV increase and reduces exercise capacity in exercise PH and PAH. In ePH, the insufficient increase in RV contractility to compensate for increasing RV afterload during maximum exercise leads to deterioration of RV-PA coupling. These data provide evidence that even in the early stages of PH, RV function is compromised.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid30256767,

title = {Airway fractal dimension predicts respiratory morbidity and mortality in COPD},

author = {Sandeep Bodduluri and Abhilash S Kizhakke Puliyakote and Sarah E Gerard and Joseph M Reinhardt and Eric A Hoffman and John D Newell and Hrudaya P Nath and MeiLan K Han and George R Washko and Raúl San José Estépar and Mark T Dransfield and Surya P Bhatt and },

doi = {10.1172/JCI120693},

issn = {1558-8238},

year  = {2018},

date = {2018-12-01},

journal = {J Clin Invest},

volume = {128},

number = {12},

pages = {5374--5382},

abstract = {BACKGROUND: Chronic obstructive pulmonary disease (COPD) is characterized by airway remodeling. Characterization of airway changes on computed tomography has been challenging due to the complexity of the recurring branching patterns, and this can be better measured using fractal dimensions.nnMETHODS: We analyzed segmented airway trees of 8,135 participants enrolled in the COPDGene cohort. The fractal complexity of the segmented airway tree was measured by the Airway Fractal Dimension (AFD) using the Minkowski-Bougliand box-counting dimension. We examined associations between AFD and lung function and respiratory morbidity using multivariable regression analyses. We further estimated the extent of peribronchial emphysema (%) within 5 mm of the airway tree, as this is likely to affect AFD. We classified participants into 4 groups based on median AFD, percentage of peribronchial emphysema, and estimated survival.nnRESULTS: AFD was significantly associated with forced expiratory volume in one second (FEV1; P < 0.001) and FEV1/forced vital capacity (FEV1/FVC; P < 0.001) after adjusting for age, race, sex, smoking status, pack-years of smoking, BMI, CT emphysema, air trapping, airway thickness, and CT scanner type. On multivariable analysis, AFD was also associated with respiratory quality of life and 6-minute walk distance, as well as exacerbations, lung function decline, and mortality on longitudinal follow-up. We identified a subset of participants with AFD below the median and peribronchial emphysema above the median who had worse survival compared with participants with high AFD and low peribronchial emphysema (adjusted hazards ratio [HR]: 2.72; 95% CI: 2.20-3.35; P < 0.001), a substantial number of whom were not identified by traditional spirometry severity grades.nnCONCLUSION: Airway fractal dimension as a measure of airway branching complexity and remodeling in smokers is associated with respiratory morbidity and lung function change, offers prognostic information additional to traditional CT measures of airway wall thickness, and can be used to estimate mortality risk.nnTRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT00608764.nnFUNDING: This study was supported by NIH K23 HL133438 (SPB) and the COPDGene study (NIH Grant Numbers R01 HL089897 and R01 HL089856). The COPDGene project is also supported by the COPD Foundation through contributions made to an Industry Advisory Board comprised of AstraZeneca, Boehringer Ingelheim, Novartis, Pfizer, Siemens, Sunovion and GlaxoSmithKline.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}