@article {1677601,
	title = {3D Pulmonary Artery Segmentation from CTA Scans Using Deep Learning with Realistic Data Augmentation},
	journal = {Image Anal Mov Organ Breast Thorac Images (2018)},
	volume = {11040},
	year = {2018},
	month = {2018 Sep},
	pages = {225-237},
	abstract = {The characterization of the vasculature in the mediastinum, more specifically the pulmonary artery, is of vital importance for the evaluation of several pulmonary vascular diseases. Thus, the goal of this study is to automatically segment the pulmonary artery (PA) from computed tomography angiography images, which opens up the opportunity for more complex analysis of the evolution of the PA geometry in health and disease and can be used in complex fluid mechanics models or individualized medicine. For that purpose, a new 3D convolutional neural network architecture is proposed, which is trained on images coming from different patient cohorts. The network makes use a strong data augmentation paradigm based on realistic deformations generated by applying principal component analysis to the deformation fields obtained from the affine registration of several datasets. The network is validated on 91 datasets by comparing the automatic segmentations with semi-automatically delineated ground truths in terms of mean Dice and Jaccard coefficients and mean distance between surfaces, which yields values of 0.89, 0.80 and 1.25 mm, respectively. Finally, a comparison against a Unet architecture is also included.},
	doi = {10.1007/978-3-030-00946-5_23},
	author = {Rom{\'a}n, Karen L{\'o}pez-Linares and De La Bruere, Isaac and Onieva, Jorge and Andresen, Lasse and Holsting, Jakob Qvortrup and Rahaghi, Farbod N and Mac{\'\i}a, Iv{\'a}n and Gonz{\'a}lez Ballester, Miguel A and Jos{\'e} Estepar, Ra{\'u}l San}
}
@article {1677606,
	title = {Diagnosis of Deep Venous Thrombosis and Pulmonary Embolism: New Imaging Tools and Modalities},
	journal = {Clin Chest Med},
	volume = {39},
	number = {3},
	year = {2018},
	month = {2018 Sep},
	pages = {493-504},
	abstract = {Imaging continues to be the modality of choice for the diagnosis of venous thromboembolic disease, particularly when incorporated into diagnostic algorithms. Improvement in imaging techniques as well as new imaging modalities and processing methods have improved diagnostic accuracy and additionally are being leveraged in prognostication and decision making for choice of intervention. In this article, we review the role of imaging in diagnosis and prognostication of venous thromboembolism. We also discuss emerging imaging approaches that may in the near future find clinical usefulness in improving diagnosis and prognostication as well as differentiating disease phenotypes.},
	keywords = {Aged, Humans, Magnetic Resonance Imaging, Male, Pulmonary Embolism, Tomography, Emission-Computed, Ultrasonography, Venous Thrombosis},
	issn = {1557-8216},
	doi = {10.1016/j.ccm.2018.04.003},
	author = {Rahaghi, Farbod Nicholas and Minhas, Jasleen Kaur and Heresi, Gustavo A}
}
@article {1433560,
	title = {Airway fractal dimension predicts respiratory morbidity and mortality in COPD},
	journal = {J Clin Invest},
	volume = {128},
	number = {12},
	year = {2018},
	month = {2018 12 03},
	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.

METHODS: 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.

RESULTS: 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.

CONCLUSION: 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.

TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT00608764.

FUNDING: 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.},
	issn = {1558-8238},
	doi = {10.1172/JCI120693},
	author = {Bodduluri, Sandeep and Puliyakote, Abhilash S Kizhakke and Gerard, Sarah E and Reinhardt, Joseph M and Hoffman, Eric A and Newell, John D and Nath, Hrudaya P and Han, MeiLan K and Washko, George R and San Jos{\'e} Est{\'e}par, Ra{\'u}l and Dransfield, Mark T and Bhatt, Surya P}
}
@article {1433559,
	title = {Airway fractal dimension predicts respiratory morbidity and mortality in COPD},
	journal = {J Clin Invest},
	volume = {128},
	number = {12},
	year = {2018},
	month = {2018 12 03},
	pages = {5676},
	issn = {1558-8238},
	doi = {10.1172/JCI125987},
	author = {Bodduluri, Sandeep and Puliyakote, Abhilash S Kizhakke and Gerard, Sarah E and Reinhardt, Joseph M and Hoffman, Eric A and Newell, John D and Nath, Hrudaya P and Han, MeiLan K and Washko, George R and San Jos{\'e} Est{\'e}par, Ra{\'u}l and Dransfield, Mark T and Bhatt, Surya P}
}
@article {1433567,
	title = {Association between acute respiratory disease events and the promoter polymorphism in smokers},
	journal = {Thorax},
	volume = {73},
	number = {11},
	year = {2018},
	month = {2018 11},
	pages = {1071-1074},
	abstract = {A single-nucleotide polymorphism (rs35705950) in the mucin 5B () gene promoter is associated with pulmonary fibrosis and interstitial features on chest CT but may also have beneficial effects. In non-Hispanic whites in the COPDGene cohort with interstitial features (n=454), the promoter polymorphism was associated with a 61\% lower odds of a prospectively reported acute respiratory disease event (P=0.001), a longer time-to-first event (HR=0.57; P=0.006) and 40\% fewer events (P=0.016). The promoter polymorphism may have a beneficial effect on the risk of acute respiratory disease events in smokers with interstitial CT features.},
	keywords = {Acute Disease, DNA, Female, Genetic Predisposition to Disease, Genotype, Humans, Mucin-5B, Polymorphism, Single Nucleotide, Promoter Regions, Genetic, Respiratory Tract Diseases, Smokers, Smoking},
	issn = {1468-3296},
	doi = {10.1136/thoraxjnl-2017-211208},
	author = {Ash, Samuel Y and Harmouche, Rola and Putman, Rachel K and Ross, James C and Martinez, Fernando J and Choi, Augustine M and Bowler, Russell P and Regan, Elizabeth A and Curtis, Jeffrey L and Han, MeiLan K and Boucher, Richard C and O{\textquoteright}Neal, Wanda K and Hatabu, Hiroto and Lynch, David A and Rosas, Ivan O and Hunninghake, Gary M and San Jos{\'e} Est{\'e}par, Ra{\'u}l and Washko, George R and COPDGene investigators}
}
@article {1433588,
	title = {Autocalibration method for non-stationary CT bias correction},
	journal = {Med Image Anal},
	volume = {44},
	year = {2018},
	month = {2018 02},
	pages = {115-125},
	abstract = {Computed tomography (CT) is a widely used imaging modality for screening and diagnosis. However, the deleterious effects of radiation exposure inherent in CT imaging require the development of image reconstruction methods which can reduce exposure levels. The development of iterative reconstruction techniques is now enabling the acquisition of low-dose CT images whose quality is comparable to that of CT images acquired with much higher radiation dosages. However, the characterization and calibration of the CT signal due to changes in dosage and reconstruction approaches is crucial to provide clinically relevant data. Although CT scanners are calibrated as part of the imaging workflow, the calibration is limited to select global reference values and does not consider other inherent factors of the acquisition that depend on the subject scanned (e.g. photon starvation, partial volume effect, beam hardening) and result in a non-stationary noise response. In this work, we analyze the effect of reconstruction biases caused by non-stationary noise and propose an autocalibration methodology to compensate it. Our contributions are: 1) the derivation of a functional relationship between observed bias and non-stationary noise, 2) a robust and accurate method to estimate the local variance, 3) an autocalibration methodology that does not necessarily rely on a calibration phantom, attenuates the bias caused by noise and removes the systematic bias observed in devices from different vendors. The validation of the proposed methodology was performed with a physical phantom and clinical CT scans acquired with different configurations (kernels, doses, algorithms including iterative reconstruction). The results confirmed the suitability of the proposed methods for removing the intra-device and inter-device reconstruction biases.},
	keywords = {Algorithms, Calibration, Humans, Lung, Observer Variation, Phantoms, Imaging, Radiation Dosage, Radiographic Image Interpretation, Computer-Assisted, Signal-To-Noise Ratio, Tomography, X-Ray Computed},
	issn = {1361-8423},
	doi = {10.1016/j.media.2017.12.004},
	author = {Vegas-S{\'a}nchez-Ferrero, Gonzalo and Ledesma-Carbayo, Maria J and Washko, George R and San Jos{\'e} Est{\'e}par, Ra{\'u}l}
}
@article {1433590,
	title = {Automated Agatston Score Computation in non-ECG Gated CT Scans Using Deep Learning},
	journal = {Proc SPIE Int Soc Opt Eng},
	volume = {10574},
	year = {2018},
	month = {2018 Feb},
	abstract = {Introduction: The Agatston score is a well-established metric of cardiovascular disease related to clinical outcomes. It is computed from CT scans by a) measuring the volume and intensity of the atherosclerotic plaques and b) aggregating such information in an index.

Objective: To generate a convolutional neural network that inputs a non-contrast chest CT scan and outputs the Agatston score associated with it directly, without a prior segmentation of Coronary Artery Calcifications (CAC).

Materials and methods: We use a database of 5973 non-contrast non-ECG gated chest CT scans where the Agatston score has been manually computed. The heart of each scan is cropped automatically using an object detector. The database is split in 4973 cases for training and 1000 for testing. We train a 3D deep convolutional neural network to regress the Agatston score directly from the extracted hearts.

Results: The proposed method yields a Pearson correlation coefficient of  = 0.93;  <= 0.0001 against manual reference standard in the 1000 test cases. It further stratifies correctly 72.6\% of the cases with respect to standard risk groups. This compares to more complex state-of-the-art methods based on prior segmentations of the CACs, which achieve  = 0.94 in ECG-gated pulmonary CT.

Conclusions: A convolutional neural network can regress the Agatston score from the image of the heart directly, without a prior segmentation of the CACs. This is a new and simpler paradigm in the Agatston score computation that yields similar results to the state-of-the-art literature.},
	issn = {0277-786X},
	doi = {10.1117/12.2293681},
	author = {Cano-Espinosa, Carlos and Gonz{\'a}lez, Germ{\'a}n and Washko, George R and Cazorla, Miguel and San Jos{\'e} Est{\'e}par, Ra{\'u}l}
}
@article {1433594,
	title = {The Case of Missing Airways in Chronic Obstructive Pulmonary Disease},
	journal = {Am J Respir Crit Care Med},
	volume = {197},
	number = {1},
	year = {2018},
	month = {2018 01 01},
	pages = {4-6},
	issn = {1535-4970},
	doi = {10.1164/rccm.201708-1585ED},
	author = {D{\'\i}az, Alejandro A}
}
@article {1433595,
	title = {Chronic Obstructive Pulmonary Disease in Hispanics. A 9-Year Update},
	journal = {Am J Respir Crit Care Med},
	volume = {197},
	number = {1},
	year = {2018},
	month = {2018 01 01},
	pages = {15-21},
	keywords = {Aged, Aged, 80 and over, Combined Modality Therapy, Female, Follow-Up Studies, Hispanic Americans, Humans, Male, Middle Aged, Prevalence, Pulmonary Disease, Chronic Obstructive, Risk Assessment, Severity of Illness Index, Smoking Cessation, Survival Rate, Time Factors, Treatment Outcome},
	issn = {1535-4970},
	doi = {10.1164/rccm.201708-1615PP},
	author = {D{\'\i}az, Alejandro A and Celli, Bartolom{\'e} and Celed{\'o}n, Juan C}
}
@article {1433563,
	title = {COPD biomarkers and phenotypes: opportunities for better outcomes with precision imaging},
	journal = {Eur Respir J},
	volume = {52},
	number = {5},
	year = {2018},
	month = {2018 Nov},
	abstract = {A number of chronic diseases have benefited from both imaging and personalised medicine, but unfortunately, for patients with chronic obstructive pulmonary disease (COPD), there has been little clinical uptake or recognition of the key advances in thoracic imaging that might help detect disease early, or, perhaps more importantly, might help develop and phenotype patients for novel or personalised therapies that may halt disease progression. We outline our vision for how computed tomography and magnetic resonance imaging may be used to better inform COPD patient care, and, perhaps more importantly, how these may be used to help develop new therapies directed at early disease. We think that imaging and precision medicine should be considered and used together as "precision imaging" at specific stages of COPD when the major pathologies may be more responsive to therapy. While "precision medicine" is the tailoring of medical treatment to individual patients, we define "precision imaging" as the tailoring of specific therapies and interventions to individual patients with a detailed quantitative understanding of their specific imaging phenotypes and measurements. Finally, we stress the importance of "seeing" the pathology, because without this understanding, you can neither treat nor cure patients with COPD.},
	issn = {1399-3003},
	doi = {10.1183/13993003.01570-2018},
	author = {Washko, George R and Parraga, Grace}
}
@article {1433589,
	title = {Deep learning for biomarker regression: application to osteoporosis and emphysema on chest CT scans},
	journal = {Proc SPIE Int Soc Opt Eng},
	volume = {10574},
	year = {2018},
	month = {2018 Feb},
	abstract = {Introduction: Biomarker computation using deep-learning often relies on a two-step process, where the deep learning algorithm segments the region of interest and then the biomarker is measured. We propose an alternative paradigm, where the biomarker is estimated directly using a regression network. We showcase this image-to-biomarker paradigm using two biomarkers: the estimation of bone mineral density (BMD) and the estimation of lung percentage of emphysema from CT scans.

Materials and methods: We use a large database of 9,925 CT scans to train, validate and test the network for which reference standard BMD and percentage emphysema have been already computed. First, the 3D dataset is reduced to a set of canonical 2D slices where the organ of interest is visible (either spine for BMD or lungs for emphysema). This data reduction is performed using an automatic object detector. Second, The regression neural network is composed of three convolutional layers, followed by a fully connected and an output layer. The network is optimized using a momentum optimizer with an exponential decay rate, using the root mean squared error as cost function.

Results: The Pearson correlation coefficients obtained against the reference standards are  = 0.940 ( < 0.00001) and  = 0.976 ( < 0.00001) for BMD and percentage emphysema respectively.

Conclusions: The deep-learning regression architecture can learn biomarkers from images directly, without indicating the structures of interest. This approach simplifies the development of biomarker extraction algorithms. The proposed data reduction based on object detectors conveys enough information to compute the biomarkers of interest.},
	issn = {0277-786X},
	doi = {10.1117/12.2293455},
	author = {Gonz{\'a}lez, Germ{\'a}n and Washko, George R and San Jos{\'e} Est{\'e}par, Ra{\'u}l}
}
@article {1433571,
	title = {Defining Impaired Respiratory Health. A Paradigm Shift for Pulmonary Medicine},
	journal = {Am J Respir Crit Care Med},
	volume = {198},
	number = {4},
	year = {2018},
	month = {2018 Aug 15},
	pages = {440-446},
	issn = {1535-4970},
	doi = {10.1164/rccm.201801-0120PP},
	author = {Reyfman, Paul A and Washko, George R and Dransfield, Mark T and Spira, Avrum and Han, MeiLan K and Kalhan, Ravi}
}
@article {1433585,
	title = {Disease Severity Dependence of the Longitudinal Association Between CT Lung Density and Lung Function in Smokers},
	journal = {Chest},
	volume = {153},
	number = {3},
	year = {2018},
	month = {2018 Mar},
	pages = {638-645},
	abstract = {BACKGROUND: In smokers, the lung parenchyma is characterized by inflammation and emphysema, processes that can result in local gain and loss of lung tissue. CT measures of lung density might reflect lung tissue changes; however, longitudinal data regarding the effects of CT lung tissue on FEV in smokers with and without COPD are scarce.

METHODS: The 15th percentile of CT lung density was obtained from the scans of 3,390 smokers who completed baseline and 5-year follow-up of the Genetic Epidemiology of COPD (COPDGene) study visits. The longitudinal relationship between total lung capacity-adjusted lung density (TLC-PD15) and FEV was assessed by using multivariable mixed models. Separate models were performed in smokers at risk, smokers with preserved ratio and impaired spirometry (PRISm), and smokers with COPD according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) staging system.

RESULTS: The direction of the relationship between lung density and lung function was GOLD stage dependent. In smokers with PRISm, a 1-g/L decrease in TLC-PD15 was associated with an increase of 2.8~mL FEV (P~= .02). In contrast, among smokers with GOLD III to IV COPD, a 1-g/L decrease in TLC-PD15 was associated with a decrease of 4.1~mL FEV (P~= .002).

CONCLUSIONS: A decline in TLC-PD15 was associated with an increase or decrease in FEV depending on disease severity. The associations are GOLD stage specific, and their presence might influence the interpretation of future studies that use CT lung density as an intermediate study end point for a decline in lung function.

TRIAL REGISTRY: ClinicalTrials.gov; No.: NCT00608764; URL: www.clinicaltrials.gov.},
	issn = {1931-3543},
	doi = {10.1016/j.chest.2017.10.012},
	author = {Diaz, Alejandro A and Strand, Matthew and Coxson, Harvey O and Ross, James C and Estepar, Raul San Jose and Lynch, David and van Rikxoort, Eva M and Rosas, Ivan O and Hunninghake, Gary M and Putman, Rachel K and Hatabu, Hiroto and Yen, Andrew and Kinney, Gregory L and Hokanson, John E and Silverman, Edwin K and Crapo, James and Washko, George R}
}
@article {1433592,
	title = {Disease Staging and Prognosis in Smokers Using Deep Learning in Chest Computed Tomography},
	journal = {Am J Respir Crit Care Med},
	volume = {197},
	number = {2},
	year = {2018},
	month = {2018 Jan 15},
	pages = {193-203},
	abstract = {RATIONALE: Deep learning is a powerful tool that may allow for improved outcome prediction.

OBJECTIVES: To determine if deep learning, specifically convolutional neural network (CNN) analysis, could detect and stage chronic obstructive pulmonary disease (COPD) and predict acute respiratory disease (ARD) events and mortality in smokers.

METHODS: A CNN was trained using computed tomography scans from 7,983 COPDGene participants and evaluated using 1,000 nonoverlapping COPDGene participants and 1,672 ECLIPSE participants. Logistic regression (C statistic and the Hosmer-Lemeshow test) was used to assess COPD diagnosis and ARD prediction. Cox regression (C index and the Greenwood-Nam-D{\textquoteright}Agnostino test) was used to assess mortality.

MEASUREMENTS AND MAIN RESULTS: In COPDGene, the C statistic for the detection of COPD was 0.856. A total of 51.1\% of participants in COPDGene were accurately staged and 74.95\% were within one stage. In ECLIPSE, 29.4\% were accurately staged and 74.6\% were within one stage. In COPDGene and ECLIPSE, the C statistics for ARD events were 0.64 and 0.55, respectively, and the Hosmer-Lemeshow P values were 0.502 and 0.380, respectively, suggesting no evidence of poor calibration. In COPDGene and ECLIPSE, CNN predicted mortality with fair discrimination (C indices, 0.72 and 0.60, respectively), and without evidence of poor calibration (Greenwood-Nam-D{\textquoteright}Agnostino P values, 0.307 and 0.331, respectively).

CONCLUSIONS: A deep-learning approach that uses only computed tomography imaging data can identify those smokers who have COPD and predict who are most likely to have ARD events and those with the highest mortality. At a population level CNN analysis may be a powerful tool for risk assessment.},
	keywords = {Aged, Databases, Factual, Deep Learning, Female, Humans, Logistic Models, Male, Middle Aged, Predictive Value of Tests, Prognosis, Pulmonary Disease, Chronic Obstructive, Respiratory Distress Syndrome, Respiratory Function Tests, Risk Assessment, Severity of Illness Index, Smoking, Survival Rate, Tomography, X-Ray Computed},
	issn = {1535-4970},
	doi = {10.1164/rccm.201705-0860OC},
	author = {Gonz{\'a}lez, Germ{\'a}n and Ash, Samuel Y and Vegas-S{\'a}nchez-Ferrero, Gonzalo and Onieva Onieva, Jorge and Rahaghi, Farbod N and Ross, James C and D{\'\i}az, Alejandro and San Jos{\'e} Est{\'e}par, Ra{\'u}l and Washko, George R}
}
@article {1433593,
	title = {Ensemble genomic analysis in human lung tissue identifies novel genes for chronic obstructive pulmonary disease},
	journal = {Hum Genomics},
	volume = {12},
	number = {1},
	year = {2018},
	month = {2018 01 15},
	pages = {1},
	abstract = {BACKGROUND: Genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) significantly associated with chronic obstructive pulmonary disease (COPD). However, many genetic variants show suggestive evidence for association but do not meet the strict threshold for genome-wide significance. Integrative analysis of multiple omics datasets has the potential to identify novel genes involved in disease pathogenesis by leveraging these variants in a functional, regulatory context.

RESULTS: We performed expression quantitative trait locus (eQTL) analysis using genome-wide SNP genotyping and gene expression profiling of lung tissue samples from 86 COPD cases and 31 controls, testing for SNPs associated with gene expression levels. These results were integrated with a prior COPD GWAS using an ensemble statistical and network methods approach to identify relevant genes and observe them in the context of overall genetic control of gene expression to highlight co-regulated genes and disease pathways. We identified 250,312 unique SNPs and 4997 genes in the cis(local)-eQTL analysis (5\% false discovery rate). The top gene from the integrative analysis was MAPT, a gene recently identified in an independent GWAS of lung function. The genes HNRNPAB and PCBP2 with RNA binding activity and the gene ACVR1B were identified in network communities with validated disease relevance.

CONCLUSIONS: The integration of lung tissue gene expression with genome-wide SNP genotyping and subsequent intersection with prior GWAS and omics studies highlighted candidate genes within COPD loci and in communities harboring known COPD genes. This~integration also identified novel disease genes in sub-threshold regions that would otherwise have been missed through GWAS.},
	keywords = {Activin Receptors, Type I, Adult, Aged, Female, Gene Expression Regulation, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Genomics, Heterogeneous-Nuclear Ribonucleoprotein Group A-B, Humans, Lung, Male, Middle Aged, Polymorphism, Single Nucleotide, Pulmonary Disease, Chronic Obstructive, Quantitative Trait Loci, RNA-Binding Proteins, tau Proteins},
	issn = {1479-7364},
	doi = {10.1186/s40246-018-0132-z},
	author = {Morrow, Jarrett D and Cho, Michael H and Platig, John and Zhou, Xiaobo and DeMeo, Dawn L and Qiu, Weiliang and Celli, Bartholome and Marchetti, Nathaniel and Criner, Gerard J and Bueno, Raphael and Washko, George R and Glass, Kimberly and Quackenbush, John and Silverman, Edwin K and Hersh, Craig P}
}
@article {1433579,
	title = {Exposure to Traffic Emissions and Fine Particulate Matter and Computed Tomography Measures of the Lung and Airways},
	journal = {Epidemiology},
	volume = {29},
	number = {3},
	year = {2018},
	month = {2018 05},
	pages = {333-341},
	abstract = {BACKGROUND: Exposure to ambient air pollution has been associated with lower lung function in adults, but few studies have investigated associations with radiographic lung and airway measures.

METHODS: We ascertained lung volume, mass, density, visual emphysema, airway size, and airway wall area by computed tomography (CT) among 2,545 nonsmoking Framingham CT substudy participants. We examined associations of home distance to major road and PM2.5 (2008 average from a spatiotemporal model using satellite data) with these outcomes using linear and logistic regression models adjusted for age, sex, height, weight, census tract median household value and population density, education, pack-years of smoking, household tobacco exposure, cohort, and date. We tested for differential susceptibility by sex, smoking status (former vs. never), and cohort.

RESULTS: The mean participant age was 60.1 years (standard deviation 11.9 years). Median PM2.5 level was 9.7 {\textmu}g/m (interquartile range, 1.6). Living ,
	keywords = {Adolescent, Adult, Air Pollution, Denmark, Environmental Exposure, Female, Humans, Lung Neoplasms, Male, Odds Ratio, particulate matter, Registries, Tomography, X-Ray Computed, Vehicle Emissions, Young Adult},
	issn = {1531-5487},
	doi = {10.1097/EDE.0000000000000809},
	author = {Rice, Mary B and Li, Wenyuan and Dorans, Kirsten S and Wilker, Elissa H and Ljungman, Petter and Gold, Diane R and Schwartz, Joel and Koutrakis, Petros and Kloog, Itai and Araki, Tetsuro and Hatabu, Hiroto and Estepar, Raul San Jose and O{\textquoteright}Connor, George T and Mittleman, Murray A and Washko, George R}
}
@article {1433575,
	title = {A Genome-Wide Association Study in Hispanics/Latinos Identifies Novel Signals for Lung Function. The Hispanic Community Health Study/Study of Latinos},
	journal = {Am J Respir Crit Care Med},
	volume = {198},
	number = {2},
	year = {2018},
	month = {2018 Jul 15},
	pages = {208-219},
	abstract = {RATIONALE: Lung function and chronic obstructive pulmonary disease (COPD) are heritable traits. Genome-wide association studies (GWAS) have identified numerous pulmonary function and COPD loci, primarily in cohorts of European ancestry.

OBJECTIVES: Perform a GWAS of COPD phenotypes in Hispanic/Latino populations to identify loci not previously detected in European populations.

METHODS: GWAS of lung function and COPD in Hispanic/Latino participants from a population-based cohort. We performed replication studies of novel loci in independent studies.

MEASUREMENTS AND MAIN RESULTS: Among 11,822 Hispanic/Latino participants, we identified eight novel signals; three replicated in independent populations of European Ancestry. A novel locus for FEV in ZSWIM7 (rs4791658; P = 4.99 {\texttimes} 10) replicated. A rare variant (minor allele frequency = 0.002) in HAL (rs145174011) was associated with FEV/FVC (P = 9.59 {\texttimes} 10) in a region previously identified for COPD-related phenotypes; it remained significant in conditional analyses but did not replicate. Admixture mapping identified a novel region, with a variant in AGMO (rs41331850), associated with Amerindian ancestry and FEV, which replicated. A novel locus for FEV identified among ever smokers (rs291231; P = 1.92 {\texttimes} 10) approached statistical significance for replication in admixed populations of African ancestry, and a novel SNP for COPD in PDZD2 (rs7709630; P = 1.56 {\texttimes} 10) regionally replicated. In addition, loci previously identified for lung function in European samples were associated in Hispanic/Latino participants in the Hispanic Community Health Study/Study of Latinos at the genome-wide significance level.

CONCLUSIONS: We identified novel signals for lung function and COPD in a Hispanic/Latino cohort. Including admixed populations when performing genetic studies may identify variants contributing to genetic etiologies of COPD.},
	issn = {1535-4970},
	doi = {10.1164/rccm.201707-1493OC},
	author = {Burkart, Kristin M and Sofer, Tamar and London, Stephanie J and Manichaikul, Ani and Hartwig, Fernando P and Yan, Qi and Soler Artigas, Mar{\'\i}a and Avila, Lydiana and Chen, Wei and Davis Thomas, Sonia and Diaz, Alejandro A and Hall, Ian P and Horta, Bernardo L and Kaplan, Robert C and Laurie, Cathy C and Menezes, Ana M and Morrison, Jean V and Oelsner, Elizabeth C and Rastogi, Deepa and Rich, Stephen S and Soto-Quiros, Manuel and Stilp, Adrienne M and Tobin, Martin D and Wain, Louise V and Celed{\'o}n, Juan C and Barr, R Graham}
}
@article {1433582,
	title = {Histopathology of Interstitial Lung Abnormalities in the Context of Lung Nodule Resections},
	journal = {Am J Respir Crit Care Med},
	volume = {197},
	number = {7},
	year = {2018},
	month = {2018 Apr 01},
	pages = {955-958},
	issn = {1535-4970},
	doi = {10.1164/rccm.201708-1679LE},
	author = {Miller, Ezra R and Putman, Rachel K and Vivero, Marina and Hung, Yin and Araki, Tetsuro and Nishino, Mizuki and Washko, George R and Rosas, Ivan O and Hatabu, Hiroto and Sholl, Lynette M and Hunninghake, Gary M}
}
@article {1433569,
	title = {Identification of Chronic Obstructive Pulmonary Disease Axes That Predict All-Cause Mortality: The COPDGene Study},
	journal = {Am J Epidemiol},
	volume = {187},
	number = {10},
	year = {2018},
	month = {2018 Oct 01},
	pages = {2109-2116},
	abstract = {Chronic obstructive pulmonary disease (COPD) is a syndrome caused by damage to the lungs that results in decreased pulmonary function and reduced structural integrity. Pulmonary function testing (PFT) is used to diagnose and stratify COPD into severity groups, and computed tomography (CT) imaging of the chest is often used to assess structural changes in the lungs. We hypothesized that the combination of PFT and CT phenotypes would provide a more powerful tool for assessing underlying morphologic differences associated with pulmonary function in COPD than does PFT alone. We used factor analysis of 26 variables to classify 8,157 participants recruited into the COPDGene cohort between January 2008 and June 2011 from 21 clinical centers across the United States. These factors were used as predictors of all-cause mortality using Cox proportional hazards modeling. Five factors explained 80\% of the covariance and represented the following domains: factor 1, increased emphysema and decreased pulmonary function; factor 2, airway disease and decreased pulmonary function; factor 3, gas trapping; factor 4, CT variability; and factor 5, hyperinflation. After more than 46,079 person-years of follow-up, factors 1 through 4 were associated with mortality and there was a significant synergistic interaction between factors 1 and 2 on death. Considering CT measures along with PFT in the assessment of COPD can identify patients at particularly high risk for death.},
	issn = {1476-6256},
	doi = {10.1093/aje/kwy087},
	author = {Kinney, Gregory L and Santorico, Stephanie A and Young, Kendra A and Cho, Michael H and Castaldi, Peter J and San Jos{\'e} Est{\'e}par, Raul and Ross, James C and Dy, Jennifer G and Make, Barry J and Regan, Elizabeth A and Lynch, David A and Everett, Douglas C and Lutz, Sharon M and Silverman, Edwin K and Washko, George R and Crapo, James D and Hokanson, John E}
}
@article {1433587,
	title = {Imaging approaches to understand disease complexity: chronic obstructive pulmonary disease as a clinical model},
	journal = {J Appl Physiol (1985)},
	volume = {124},
	number = {2},
	year = {2018},
	month = {2018 Feb 01},
	pages = {512-520},
	abstract = {The clinical manifestations of chronic obstructive pulmonary disease (COPD) reflect an aggregate of multiple pulmonary and extrapulmonary processes. It is increasingly clear that full assessment of these processes is essential to characterize disease burden and to tailor therapy. Medical imaging has advanced such that it is now possible to obtain in vivo insight in the presence and severity of lung disease-associated features. In this review, we have assembled data from multiple disciplines of medical imaging research to review the role of imaging in characterization of COPD. Topics include imaging of the lungs, body composition, and extrapulmonary tissue metabolism. The primary focus is on imaging modalities that are widely available in clinical care settings and that potentially contribute to describing COPD heterogeneity and enhance our insight in underlying pathophysiological processes and their structural and functional effects.},
	issn = {1522-1601},
	doi = {10.1152/japplphysiol.00143.2017},
	author = {Sanders, Karin J C and Ash, Samuel Y and Washko, George R and Mottaghy, Felix M and Schols, Annemie M W J}
}
@article {1433573,
	title = {Increased Airway Wall Thickness is Associated with Adverse Longitudinal First-Second Forced Expiratory Volume Trajectories of Former World Trade Center workers},
	journal = {Lung},
	volume = {196},
	number = {4},
	year = {2018},
	month = {2018 08},
	pages = {481-489},
	abstract = {RATIONALE: Occupational exposures at the WTC site after September 11, 2001 have been associated with several presumably inflammatory lower airway diseases. In this study, we describe the trajectories of expiratory air flow decline, identify subgroups with adverse progression, and investigate the association of a quantitative computed tomography (QCT) imaging measurement of airway wall thickness, and other risk factors for adverse progression.

METHODS: We examined the trajectories of expiratory air flow decline in a group of 799 former WTC workers and volunteers with QCT-measured (with two independent systems) wall area percent (WAP) and at least 3 periodic spirometries. We calculated individual regression lines for first-second forced expiratory volume (FEV), identified subjects with rapidly declining and increasing ("gainers"), and compared them to subjects with normal and "stable" FEV decline. We used multivariate logistic regression to model decliner vs. stable trajectories.

RESULTS: The mean longitudinal FEVslopes for the entire study population, and its stable, decliner, and gainer subgroups were, respectively, - 35.8, - 8, - 157.6, and + 173.62~ml/year. WAP was associated with "decliner" status (OR 1.08, 95\% CI 1.02, 1.14, per 5\% increment) compared to stable. Age, weight gain, baseline FEV percent predicted, bronchodilator response, and pre-WTC occupational exposures were also significantly associated with accelerated FEV decline. Analyses of gainers vs. stable subgroup showed WAP as a significant predictor in unadjusted but not consistently in adjusted analyses.

CONCLUSIONS: The apparent normal age-related rate of FEV decline results from averaging widely divergent trajectories. WAP is significantly associated with accelerated air flow decline in WTC workers.},
	issn = {1432-1750},
	doi = {10.1007/s00408-018-0125-7},
	author = {de la Hoz, Rafael E and Liu, Xiaoyu and Doucette, John T and Reeves, Anthony P and Bienenfeld, Laura A and Wisnivesky, Juan P and Celed{\'o}n, Juan C and Lynch, David A and San Jos{\'e} Est{\'e}par, Ra{\'u}l}
}
@article {1433574,
	title = {Interstitial Features at Chest CT Enhance the Deleterious Effects of Emphysema in the COPDGene Cohort},
	journal = {Radiology},
	volume = {288},
	number = {2},
	year = {2018},
	month = {2018 Aug},
	pages = {600-609},
	abstract = {Purpose To determine if interstitial features at chest CT enhance the effect of emphysema on clinical disease severity in smokers without clinical pulmonary fibrosis. Materials and Methods In this retrospective cohort study, an objective CT analysis tool was used to measure interstitial features (reticular changes, honeycombing, centrilobular nodules, linear scar, nodular changes, subpleural lines, and ground-glass opacities) and emphysema in 8266 participants in a study of chronic obstructive pulmonary disease (COPD) called COPDGene (recruited between October 2006 and January 2011). Additive differences in patients with emphysema with interstitial features and in those without interstitial features were analyzed by using t tests, multivariable linear regression, and Kaplan-Meier analysis. Multivariable linear and Cox regression were used to determine if interstitial features modified the effect of continuously measured emphysema on clinical measures of disease severity and mortality. Results Compared with individuals with emphysema alone, those with emphysema and interstitial features had a higher percentage predicted forced expiratory volume in 1 second (absolute difference, 6.4\%; P \&lt; .001), a lower percentage predicted diffusing capacity of lung for carbon monoxide (DLCO) (absolute difference, 7.4\%; P = .034), a 0.019 higher right ventricular-to-left ventricular (RVLV) volume ratio (P = .029), a 43.2-m shorter 6-minute walk distance (6MWD) (P \&lt; .001), a 5.9-point higher St George{\textquoteright}s Respiratory Questionnaire (SGRQ) score (P \&lt; .001), and 82\% higher mortality (P \&lt; .001). In addition, interstitial features modified the effect of emphysema on percentage predicted DLCO, RVLV volume ratio, 6WMD, SGRQ score, and mortality (P for interaction \&lt; .05 for all). Conclusion In smokers, the combined presence of interstitial features and emphysema was associated with worse clinical disease severity and higher mortality than was emphysema alone. In addition, interstitial features enhanced the deleterious effects of emphysema on clinical disease severity and mortality.},
	keywords = {Aged, Aged, 80 and over, Cohort Studies, Female, Forced Expiratory Volume, Humans, Lung, Male, Middle Aged, Pulmonary Disease, Chronic Obstructive, Pulmonary Emphysema, Retrospective Studies, Severity of Illness Index, Tomography, X-Ray Computed},
	issn = {1527-1315},
	doi = {10.1148/radiol.2018172688},
	author = {Ash, Samuel Y and Harmouche, Rola and Ross, James C and Diaz, Alejandro A and Rahaghi, Farbod N and Vegas Sanchez-Ferrero, Gonzalo and Putman, Rachel K and Hunninghake, Gary M and Onieva Onieva, Jorge and Martinez, Fernando J and Choi, Augustine M and Bowler, Russell P and Lynch, David A and Hatabu, Hiroto and Bhatt, Surya P and Dransfield, Mark T and Wells, J Michael and Rosas, Ivan O and Estepar, Raul San Jose and Washko, George R}
}
@article {1433596,
	title = {Lobar Emphysema Distribution Is Associated With 5-Year Radiological Disease Progression},
	journal = {Chest},
	volume = {153},
	number = {1},
	year = {2018},
	month = {2018 Jan},
	pages = {65-76},
	abstract = {BACKGROUND: Emphysema has considerable variability in its regional distribution. Craniocaudal emphysema distribution is an important predictor of the response to lung volume reduction. However, there is little consensus regarding how to define upper lobe-predominant and lower lobe-predominant emphysema subtypes. Consequently, the clinical and genetic associations with these subtypes are poorly characterized.

METHODS: We sought to identify subgroups characterized by upper-lobe or lower-lobe emphysema predominance and comparable amounts of total emphysema by analyzing data from 9,210 smokers without alpha-1-antitrypsin deficiency in the Genetic Epidemiology of COPD (COPDGene) cohort. CT densitometric emphysema was measured in each lung lobe. Random forest clustering was applied to lobar emphysema variables after regressing out the effects of total emphysema. Clusters were tested for association with clinical and imaging outcomes at baseline and at 5-year follow-up. Their associations with genetic variants were also compared.

RESULTS: Three clusters were identified: minimal emphysema (n~= 1,312), upper lobe-predominant emphysema (n~= 905), and lower lobe-predominant emphysema (n~= 796). Despite a similar amount of total emphysema, the lower-lobe group had more severe airflow obstruction at baseline and higher rates of metabolic syndrome compared with subjects with upper-lobe predominance. The group with upper-lobe predominance had greater 5-year progression of emphysema, gas trapping, and dyspnea. Differential associations with known COPD genetic risk variants were noted.

CONCLUSIONS: Subgroups of smokers defined by upper-lobe or lower-lobe emphysema predominance exhibit different functional and radiological disease progression rates, and the upper-lobe predominant subtype shows evidence of association with known COPD genetic risk variants. These subgroups may be useful in the development of personalized treatments for COPD.},
	issn = {1931-3543},
	doi = {10.1016/j.chest.2017.09.022},
	author = {Boueiz, Adel and Chang, Yale and Cho, Michael H and Washko, George R and San Jos{\'e} Est{\'e}par, Raul and Bowler, Russell P and Crapo, James D and DeMeo, Dawn L and Dy, Jennifer G and Silverman, Edwin K and Castaldi, Peter J}
}
@article {1433568,
	title = {Longitudinal Modeling of Lung Function Trajectories in Smokers with and without Chronic Obstructive Pulmonary Disease},
	journal = {Am J Respir Crit Care Med},
	volume = {198},
	number = {8},
	year = {2018},
	month = {2018 Oct 15},
	pages = {1033-1042},
	abstract = {RATIONALE: The relationship between longitudinal lung function trajectories, chest computed tomography (CT) imaging, and genetic predisposition to chronic obstructive pulmonary disease (COPD) has not been explored.

OBJECTIVES: 1) To model trajectories using a data-driven approach applied to longitudinal data spanning adulthood in the Normative Aging Study (NAS), and 2) to apply these models to demographically similar subjects in the COPDGene (Genetic Epidemiology of COPD) Study with detailed phenotypic characterization including chest CT.

METHODS: We modeled lung function trajectories in 1,060 subjects in NAS with a median follow-up time of 29 years. We assigned 3,546 non-Hispanic white males in COPDGene to these trajectories for further analysis. We assessed phenotypic and genetic differences between trajectories and across age strata.

MEASUREMENTS AND MAIN RESULTS: We identified four trajectories in NAS with differing levels of maximum lung function and rate of decline. In COPDGene, 617 subjects (17\%) were assigned to the lowest trajectory and had the greatest radiologic burden of disease (P \&lt; 0.01); 1,283 subjects (36\%) were assigned to a low trajectory with evidence of airway disease preceding emphysema on CT; 1,411 subjects (40\%) and 237 subjects (7\%) were assigned to the remaining two trajectories and tended to have preserved lung function and negligible emphysema. The genetic contribution to these trajectories was as high as 83\% (P = 0.02), and membership in lower lung function trajectories was associated with greater parental histories of COPD, decreased exercise capacity, greater dyspnea, and more frequent COPD exacerbations.

CONCLUSIONS: Data-driven analysis identifies four lung function trajectories. Trajectory membership has a genetic basis and is associated with distinct lung structural abnormalities.},
	keywords = {Adult, Aged, Aged, 80 and over, Case-Control Studies, Disease Progression, Forced Expiratory Volume, Humans, Longitudinal Studies, Lung, Male, Middle Aged, Pulmonary Disease, Chronic Obstructive, Respiratory Function Tests, Smoking, Young Adult},
	issn = {1535-4970},
	doi = {10.1164/rccm.201707-1405OC},
	author = {Ross, James C and Castaldi, Peter J and Cho, Michael H and Hersh, Craig P and Rahaghi, Farbod N and S{\'a}nchez-Ferrero, Gonzalo V and Parker, Margaret M and Litonjua, Augusto A and Sparrow, David and Dy, Jennifer G and Silverman, Edwin K and Washko, George R and San Jos{\'e} Est{\'e}par, Ra{\'u}l}
}
@article {1433584,
	title = {Lung, Fat and Bone: Increased Adiponectin Associates with the Combination of Smoking-Related Lung Disease and Osteoporosis},
	journal = {Chronic Obstr Pulm Dis},
	volume = {5},
	number = {2},
	year = {2018},
	month = {2018 Apr 01},
	pages = {134-143},
	abstract = { Adiponectin has been proposed as a biomarker of disease severity and progression in chronic obstructive pulmonary disease (COPD) and associated with spirometry-defined COPD and with computed tomography (CT)-measured emphysema. Increased adiponectin plays a role in other diseases including diabetes/metabolic syndrome, cardiovascular disease and osteoporosis. Previous studies of adiponectin and COPD have not assessed the relationship of adiponectin to airway disease in smokers and have not evaluated the effect of other comorbid diseases on the relationship of adiponectin and lung disease. We postulated that adiponectin levels would associate with both airway disease and emphysema in smokers with and without COPD, and further postulated that body composition and the comorbid diseases of osteoporosis, cardiovascular disease and diabetes might influence adiponectin levels.  Current and former smokers from the COPD Genetic Epidemiology study (COPDGene) (n= 424) were assigned to 4 groups based on CT lung characteristics and volumetric Bone Density (vBMD). Emphysema (\% low attenuation area at -950) and airway disease (Wall area \%) were used to assess smoking-related lung disease (SRLD). Group 1) Normal Lung with Normal vBMD; Group 2) Normal Lung and Osteoporosis; Group 3) SRLD with Normal vBMD; Group 4) SRLD with Osteoporosis. Cardiovascular disease (CVD), diabetes, C-reactive protein (CRP) and T-cadherin (soluble receptor for adiponectin) levels were defined for each group. Body composition was derived from chest CT. Multivariable regression assessed effects of emphysema, wall area \%, bone density, comorbid diseases and other key factors on log adiponectin.  Group 4, SRLD with Osteoporosis, had significantly higher adiponectin levels compared to other groups and the effect persisted in adjusted models. Systemic inflammation (by CRP) was associated with SRLD in Groups 3 and 4 but not with osteoporosis alone. In regression models, lower bone density and worse emphysema were associated with higher adiponectin. Airway disease was associated with higher adiponectin levels when T-cadherin was added to the model. Male gender, greater muscle and fat were associated with lower adiponectin.  Adiponectin is increased with both airway disease and emphysema in smokers. Bone density, and fat and muscle composition are all significant factors predicting adiponectin that should be considered when it is used as a biomarker of COPD. Increased adiponectin from chronic inflammation may play a role in the progression of bone loss in COPD and other lung diseases.},
	issn = {2372-952X},
	doi = {10.15326/jcopdf.5.2.2016.0174},
	author = {Suh, Young Ju and McDonald, Merry-Lynn N and Washko, George R and Carolan, Brendan J and Bowler, Russell P and Lynch, David A and Kinney, Gregory L and Bon, Jessica M and Cho, Michael H and Crapo, James D and Regan, Elizabeth A}
}
@article {1433591,
	title = {Multiorgan structures detection using deep convolutional neural networks},
	journal = {Proc SPIE Int Soc Opt Eng},
	volume = {10574},
	year = {2018},
	month = {2018 Feb},
	abstract = {Many automatic image analysis algorithms in medical imaging require a good initialization to work properly. A similar problem occurs in many imaging-based clinical workflows, which depend on anatomical landmarks. The localization of anatomic structures based on a defined context provides with a solution to that problem, which turns out to be more challenging in medical imaging where labeled images are difficult to obtain. We propose a two-stage process to detect and regress 2D bounding boxes of predefined anatomical structures based on a 2D surrounding context. First, we use a deep convolutional neural network (DCNN) architecture to detect the optimal slice where an anatomical structure is present, based on relevant landmark features. After this detection, we employ a similar architecture to perform a 2D regression with the aim of proposing a bounding box where the structure is encompassed. We trained and tested our system for 57 anatomical structures defined in axial, sagittal and coronal planes with a dataset of 504 labeled Computed Tomography (CT) scans. We compared our method with a well-known object detection algorithm (Viola Jones) and with the inter-rater error for two human experts. Despite the relatively small number of scans and the exhaustive number of structures analyzed, our method obtained promising and consistent results, which proves our architecture very generalizable to other anatomical structures.},
	issn = {0277-786X},
	doi = {10.1117/12.2293761},
	author = {Onieva Onieva, Jorge and Serrano, Germ{\'a}n Gonz{\'a}lez and Young, Thomas P and Washko, George R and Carbayo, Mar{\'\i}a Jes{\'u}s Ledesma and San Jos{\'e} Est{\'e}par, Ra{\'u}l}
}
@article {1433566,
	title = {NOVIFAST: A Fast Algorithm for Accurate and Precise VFA MRI Mapping},
	journal = {IEEE Trans Med Imaging},
	volume = {37},
	number = {11},
	year = {2018},
	month = {2018 11},
	pages = {2414-2427},
	abstract = {In quantitative magnetic resonance mapping, the variable flip angle (VFA) steady state spoiled gradient recalled echo (SPGR) imaging technique is popular as it provides a series of high resolution weighted images in a clinically feasible time. Fast, linear methods that estimate maps from these weighted images have been proposed, such as DESPOT1 and iterative re-weighted linear least squares. More accurate, non-linear least squares (NLLS) estimators are in play, but these are generally much slower and require careful initialization. In this paper, we present NOVIFAST, a novel NLLS-based algorithm specifically tailored to VFA SPGR mapping. By exploiting the particular structure of the SPGR model, a computationally efficient, yet accurate and precise map estimator is derived. Simulation and in vivo human brain experiments demonstrate a twenty-fold speed gain of NOVIFAST compared with conventional gradient-based NLLS estimators while maintaining a high precision and accuracy. Moreover, NOVIFAST is eight times faster than the efficient implementations of the variable projection (VARPRO) method. Furthermore, NOVIFAST is shown to be robust against initialization.},
	issn = {1558-254X},
	doi = {10.1109/TMI.2018.2833288},
	author = {Ramos-Llorden, Gabriel and Vegas-Sanchez-Ferrero, Gonzalo and Bjork, Marcus and Vanhevel, Floris and Parizel, Paul M and Estepar, Raul San Jose and den Dekker, Arnold J and Sijbers, Jan}
}
@article {1433583,
	title = {Paratracheal Paraseptal Emphysema and Expiratory Central Airway Collapse in Smokers},
	journal = {Ann Am Thorac Soc},
	volume = {15},
	number = {4},
	year = {2018},
	month = {2018 04},
	pages = {479-484},
	abstract = {RATIONALE: Expiratory central airway collapse is associated with respiratory morbidity independent of underlying lung disease. However, not all smokers develop expiratory central airway collapse, and the etiology of expiratory central airway collapse in adult smokers is unclear. Paraseptal emphysema in the paratracheal location, by untethering airway walls, may predispose smokers to developing expiratory central airway collapse.

OBJECTIVES: To evaluate whether paratracheal paraseptal emphysema is associated with expiratory central airway collapse.

METHODS: We analyzed paired inspiratory and expiratory computed tomography scans from participants enrolled in a multicenter study (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease) of smokers aged 45 to 80 years. Expiratory central airway collapse was defined as greater than or equal to 50\% reduction in cross-sectional area of the trachea during expiration. In a nested case-control design, participants with and without expiratory central airway collapse were included in a 1:2 fashion, and inspiratory scans were further analyzed using the Fleischner Society criteria for presence of centrilobular emphysema, paraseptal emphysema, airway wall thickening, and paratracheal paraseptal emphysema (maximal diameter >= 0.5 cm).

RESULTS: A total of 1,320 patients were included, 440 with and 880 without expiratory central airway collapse. Those with expiratory central airway collapse were older, had higher body mass index, and were less likely to be men or current smokers. Paratracheal paraseptal emphysema was more frequent in those with expiratory central airway collapse than control subjects (16.6 vs. 11.8\%; P = 0.016), and after adjustment for age, race, sex, body mass index, smoking pack-years, and forced expiratory volume in 1 second, paratracheal paraseptal emphysema was independently associated with expiratory central airway collapse (adjusted odds ratio, 1.53; 95\% confidence interval, 1.18-1.98; P = 0.001). Furthermore, increasing size of paratracheal paraseptal emphysema (maximal diameter of at least 1 cm and 1.5 cm) was associated with greater odds of expiratory central airway collapse (adjusted odds ratio, 1.63; 95\% confidence interval, 1.18-2.25; P = 0.003 and 1.77; 95\% confidence interval, 1.19-2.64; P = 0.005, respectively).

CONCLUSIONS: Paraseptal emphysema adjacent to the trachea is associated with expiratory central airway collapse. The identification of this risk factor on inspiratory scans should prompt further evaluation for expiratory central airway collapse. Clinical trial registered with ClinicalTrials.gov (NCT 00608764).},
	issn = {2325-6621},
	doi = {10.1513/AnnalsATS.201709-713OC},
	author = {Copeland, Carla R and Nath, Hrudaya and Terry, Nina L J and Wilson, Carla G and Kim, Young-Il and Lynch, David A and Bodduluri, Sandeep and Wells, J Michael and Dransfield, Mark T and D{\'\i}az, Alejandro A and Washko, George R and Foreman, Marilyn G and Bhatt, Surya P}
}
@article {1433581,
	title = {Pectoralis muscle area and mortality in smokers without airflow obstruction},
	journal = {Respir Res},
	volume = {19},
	number = {1},
	year = {2018},
	month = {2018 04 10},
	pages = {62},
	abstract = {BACKGROUND: Low muscle mass is associated with increased mortality in the general population but its prognostic value in at-risk smokers, those without expiratory airflow obstruction, is unknown. We aimed to test the hypothesis that reduced muscle mass is associated with increased mortality in at-risk smokers.

METHODS: Measures of both pectoralis and paravertebral erector spinae muscle cross-sectional area (PMA and PVMA, respectively) as well as emphysema on chest computed tomography (CT) scans were performed in 3705 current and former at-risk smokers (>=10 pack-years) aged 45-80~years enrolled into the COPDGene Study between 2008 and 2013. Vital status was ascertained through death certificate. The association between low muscle mass and mortality was assessed using Cox regression analysis.

RESULTS: During a median of 6.5~years of follow-up, 212 (5.7\%) at-risk smokers died. At-risk smokers in the lowest (vs. highest) sex-specific quartile of PMA but not PVMA had 84\% higher risk of death in adjusted models for demographics, smoking, dyspnea, comorbidities, exercise capacity, lung function, emphysema on CT, and coronary artery calcium content (hazard ratio [HR] 1.85 95\% Confidence interval [1.14-3.00] P = 0.01). Results were consistent when the PMA index (PMA/height) was used instead of quartiles. The association between PMA and death was modified by smoking status (P = 0.04). Current smokers had a significantly increased risk of death (lowest vs. highest PMA quartile, HR 2.25 [1.25-4.03] P = 0.007) while former smokers did not.

CONCLUSIONS: Low muscle mass as measured on chest CT scans is associated with increased mortality in current smokers without airflow obstruction.

TRIAL REGISTRATION: NCT00608764.},
	keywords = {Aged, Aged, 80 and over, Cross-Sectional Studies, Female, Follow-Up Studies, Humans, Male, Middle Aged, Mortality, Muscle Strength, Pectoralis Muscles, Pulmonary Disease, Chronic Obstructive, Risk Factors, Smokers, Smoking, Tomography, X-Ray Computed},
	issn = {1465-993X},
	doi = {10.1186/s12931-018-0771-6},
	author = {Diaz, Alejandro A and Martinez, Carlos H and Harmouche, Rola and Young, Thomas P and McDonald, Merry-Lynn and Ross, James C and Han, Mei Lan and Bowler, Russell and Make, Barry and Regan, Elizabeth A and Silverman, Edwin K and Crapo, James and Boriek, Aladin M and Kinney, Gregory L and Hokanson, John E and Estepar, Raul San Jose and Washko, George R}
}
@article {1433562,
	title = {POINT: Should Chest CT Be Part of Routine Clinical Care for COPD? Yes},
	journal = {Chest},
	volume = {154},
	number = {6},
	year = {2018},
	month = {2018 Dec},
	pages = {1276-1278},
	issn = {1931-3543},
	doi = {10.1016/j.chest.2018.08.1053},
	author = {Washko, George R}
}
@article {1433572,
	title = {Predicting Mortality with Percent Predicted and z-Scores of FEV: Not an EZ Task},
	journal = {Ann Am Thorac Soc},
	volume = {15},
	number = {8},
	year = {2018},
	month = {2018 Aug},
	pages = {912-913},
	issn = {2325-6621},
	doi = {10.1513/AnnalsATS.201805-356ED},
	author = {Diaz, Alejandro A}
}
@article {1433576,
	title = {Pruning of the Pulmonary Vasculature in Asthma. The Severe Asthma Research Program (SARP) Cohort},
	journal = {Am J Respir Crit Care Med},
	volume = {198},
	number = {1},
	year = {2018},
	month = {2018 Jul 01},
	pages = {39-50},
	abstract = {RATIONALE: Loss of the peripheral pulmonary vasculature, termed vascular pruning, is associated with disease severity in patients with chronic obstructive pulmonary disease.

OBJECTIVES: To determine if pulmonary vascular pruning is associated with asthma severity and exacerbations.

METHODS: We measured the total pulmonary blood vessel volume (TBV) and the blood vessel volume of vessels less than 5 mm2 in cross-sectional area (BV5) and of vessels less than 10 mm2 (BV10) in cross-sectional area on noncontrast computed tomographic scans of participants from the Severe Asthma Research Program. Lower values of the BV5 to TBV ratio (BV5/TBV) and the BV10 to TBV ratio (BV10/TBV) represented vascular pruning (loss of the peripheral pulmonary vasculature).

MEASUREMENTS AND MAIN RESULTS: Compared with healthy control subjects, patients with severe asthma had more pulmonary vascular pruning. Among those with asthma, those with poor asthma control had more pruning than those with well-controlled disease. Pruning of the pulmonary vasculature was also associated with lower percent predicted FEV1 and FVC, greater peripheral and sputum eosinophilia, and higher BAL serum amyloid A/lipoxin A4 ratio but not with low-attenuation area or with sputum neutrophilia. Compared with individuals with less pruning, individuals with the most vascular pruning had 150\% greater odds of reporting an asthma exacerbation (odds ratio, 2.50; confidence interval, 1.05-5.98; P = 0.039 for BV10/TBV) and reported 45\% more asthma exacerbations during follow-up (incidence rate ratio, 1.45; confidence interval, 1.02-2.06; P = 0.036 for BV10/TBV).

CONCLUSIONS: Pruning of the peripheral pulmonary vasculature is associated with asthma severity, control, and exacerbations, and with lung function and eosinophilia.},
	keywords = {Adult, Aged, Aged, 80 and over, Asthma, Blood Vessels, Cohort Studies, Cross-Sectional Studies, Disease Progression, Female, Forced Expiratory Volume, Humans, Lung, Male, Middle Aged, Severity of Illness Index},
	issn = {1535-4970},
	doi = {10.1164/rccm.201712-2426OC},
	author = {Ash, Samuel Y and Rahaghi, Farbod N and Come, Carolyn E and Ross, James C and Colon, Alysha G and Cardet-Guisasola, Juan Carlos and Dunican, Eleanor M and Bleecker, Eugene R and Castro, Mario and Fahy, John V and Fain, Sean B and Gaston, Benjamin M and Hoffman, Eric A and Jarjour, Nizar N and Mauger, David T and Wenzel, Sally E and Levy, Bruce D and Estepar, Raul San Jose and Israel, Elliot and Washko, George R}
}
@article {1433565,
	title = {Pulmonary Artery-Vein Classification in CT Images Using Deep Learning},
	journal = {IEEE Trans Med Imaging},
	volume = {37},
	number = {11},
	year = {2018},
	month = {2018 Nov},
	pages = {2428-2440},
	abstract = {Recent studies show that pulmonary vascular diseases may specifically affect arteries or veins through different physiologic mechanisms. To detect changes in the two vascular trees, physicians manually analyze the chest computed tomography (CT) image of the patients in search of abnormalities. This process is time consuming, difficult to standardize, and thus not feasible for large clinical studies or useful in real-world clinical decision making. Therefore, automatic separation of arteries and veins in CT images is becoming of great interest, as it may help physicians to accurately diagnose pathological conditions. In this paper, we present a novel, fully automatic approach to classify vessels from chest CT images into arteries and veins. The algorithm follows three main steps: first, a scale-space particles segmentation to isolate vessels; then a 3-D convolutional neural network (CNN) to obtain a first classification of vessels; finally, graph-cuts{\textquoteright} optimization to refine the results. To justify the usage of the proposed CNN architecture, we compared different 2-D and 3-D CNNs that may use local information from bronchus- and vessel-enhanced images provided to the network with different strategies. We also compared the proposed CNN approach with a random forests (RFs) classifier. The methodology was trained and evaluated on the superior and inferior lobes of the right lung of 18 clinical cases with noncontrast chest CT scans, in comparison with manual classification. The proposed algorithm achieves an overall accuracy of 94\%, which is higher than the accuracy obtained using other CNN architectures and RF. Our method was also validated with contrast-enhanced CT scans of patients with chronic thromboembolic pulmonary hypertension to demonstrate that our model generalizes well to contrast-enhanced modalities. The proposed method outperforms state-of-the-art methods, paving the way for future use of 3-D CNN for artery/vein classification in CT images.},
	keywords = {Algorithms, Deep Learning, Humans, Image Processing, Computer-Assisted, Pulmonary Artery, Pulmonary Disease, Chronic Obstructive, Pulmonary Veins, Tomography, X-Ray Computed},
	issn = {1558-254X},
	doi = {10.1109/TMI.2018.2833385},
	author = {Nardelli, Pietro and Jimenez-Carretero, Daniel and Bermejo-Pelaez, David and Washko, George R and Rahaghi, Farbod N and Ledesma-Carbayo, Maria J and Estepar, Raul San Jose}
}
@article {1433564,
	title = {Pulmonary vascular pruning in smokers with bronchiectasis},
	journal = {ERJ Open Res},
	volume = {4},
	number = {4},
	year = {2018},
	month = {2018 Oct},
	abstract = {There are few studies looking at the pulmonary circulation in subjects with bronchiectasis. We aimed to evaluate the intraparenchymal pulmonary vascular structure, using noncontrast chest computed tomography (CT), and its clinical implications in smokers with radiographic bronchiectasis. Visual bronchiectasis scoring and quantitative assessment of the intraparenchymal pulmonary vasculature were performed on CT scans from 486 smokers. Clinical, lung function and 6-min walk test (6MWT) data were also collected. The ratio of blood vessel volume in vessels ,
	issn = {2312-0541},
	doi = {10.1183/23120541.00044-2018},
	author = {Diaz, Alejandro A and Maselli, Diego J and Rahaghi, Farbod and Come, Carolyn E and Yen, Andrew and Maclean, Erick S and Okajima, Yuka and Martinez, Carlos H and Yamashiro, Tsuneo and Lynch, David A and Wang, Wei and Kinney, Gregory L and Washko, George R and San Jos{\'e} Est{\'e}par, Ra{\'u}l}
}
@article {1433561,
	title = {Rebuttal From Dr Washko},
	journal = {Chest},
	volume = {154},
	number = {6},
	year = {2018},
	month = {2018 Dec},
	pages = {1281-1282},
	issn = {1931-3543},
	doi = {10.1016/j.chest.2018.08.1054},
	author = {Washko, George R}
}
@article {1433570,
	title = {Reply to Mummadi et al.: Overfitting and Use of Mismatched Cohorts in Deep Learning Models: Preventable Design Limitations},
	journal = {Am J Respir Crit Care Med},
	volume = {198},
	number = {4},
	year = {2018},
	month = {2018 Aug 15},
	pages = {545},
	issn = {1535-4970},
	doi = {10.1164/rccm.201803-0540LE},
	author = {Gonz{\'a}lez, Germ{\'a}n and Ash, Samuel Y and San Jos{\'e} Est{\'e}par, Ra{\'u}l and Washko, George}
}
@article {1433577,
	title = {Respiratory Symptoms in Young Adults and Future Lung Disease. The CARDIA Lung Study},
	journal = {Am J Respir Crit Care Med},
	volume = {197},
	number = {12},
	year = {2018},
	month = {2018 Jun 15},
	pages = {1616-1624},
	abstract = {RATIONALE: There are limited data on factors in young adulthood that predict future lung disease.

OBJECTIVES: To determine the relationship between respiratory symptoms, loss of lung health, and incident respiratory disease in a population-based study of young adults.

METHODS: We examined prospective data from 2,749 participants in the CARDIA (Coronary Artery Risk Development in Young Adults) study who completed respiratory symptom questionnaires at baseline and 2 years later and repeated spirometry measurements over 30 years.

MEASUREMENTS AND MAIN RESULTS: Cough or phlegm, episodes of bronchitis, wheeze, shortness of breath, and chest illnesses at both baseline and Year 2 were the main predictor variables in models assessing decline in FEV and FVC from Year 5 to Year 30, incident obstructive and restrictive lung physiology, and visual emphysema on thoracic computed tomography scan. After adjustment for covariates, including body mass index, asthma, and smoking, report of any symptom was associated with -2.71 ml/yr excess decline in FEV (P ,
	issn = {1535-4970},
	doi = {10.1164/rccm.201710-2108OC},
	author = {Kalhan, Ravi and Dransfield, Mark T and Colangelo, Laura A and Cuttica, Michael J and Jacobs, David R and Thyagarajan, Bharat and Estepar, Raul San Jose and Harmouche, Rola and Onieva Onieva, Jorge and Ash, Samuel Y and Okajima, Yuka and Iribarren, Carlos and Sidney, Stephen and Lewis, Cora E and Mannino, David M and Liu, Kiang and Smith, Lewis J and Washko, George R}
}
@article {1433578,
	title = {The Role of Computed Tomography for the Evaluation of Lung Disease in Alpha-1 Antitrypsin Deficiency},
	journal = {Chest},
	volume = {153},
	number = {5},
	year = {2018},
	month = {2018 May},
	pages = {1240-1248},
	abstract = {Alpha-1 antitrypsin deficiency (AATD) is characterized by low serum levels of or dysfunctional alpha-1 proteinase inhibitor. In the lung parenchyma, this results in a loss of protection against the activity of serine proteases, particularly neutrophil elastase. The resultant imbalance in protease and antiprotease activity leads to an increased risk for the development of early-onset emphysema and COPD. As in traditional smoke-related COPD, the assessment of the severity and disease progression of lung disease in AATD is conventionally based on lung function; however, pulmonary function tests are unable to discriminate between emphysema and airways disease, the two hallmark pathologic features of COPD. CT imaging has been used as a tool to further characterize lung structure and evaluate therapeutic interventions in AATD-related COPD. Moreover, recent advances in quantitative CT have significantly improved our assessment of the lung architecture, which has provided investigators and clinicians with a more detailed evaluation of the extent and severity of emphysema and airways disease in AATD. In addition, serial CT imaging measures are becoming increasingly important, as they provide a tool to monitor emphysema progression. This review describes the principles of CT technology and the role of CT imaging in assessing pulmonary disease progression in AATD, including the effect of therapeutic interventions.},
	issn = {1931-3543},
	doi = {10.1016/j.chest.2017.11.017},
	author = {Campos, Michael A and Diaz, Alejandro A}
}
@article {1433580,
	title = {Smoking duration alone provides stronger risk estimates of chronic obstructive pulmonary disease than pack-years},
	journal = {Thorax},
	volume = {73},
	number = {5},
	year = {2018},
	month = {2018 05},
	pages = {414-421},
	abstract = {BACKGROUND: Cigarette smoking is the strongest risk factor for COPD. Smoking burden is frequently measured in pack-years, but the relative contribution of cigarettes smoked per day versus duration towards the development of structural lung disease, airflow obstruction and functional outcomes is not known.

METHODS: We analysed cross-sectional data from a large multicentre cohort (COPDGene) of current and former smokers. Primary outcome was airflow obstruction (FEV/FVC); secondary outcomes included five additional measures of disease: FEV, CT emphysema, CT gas trapping, functional capacity (6 min walk distance, 6MWD) and respiratory morbidity (St George{\textquoteright}s Respiratory Questionnaire, SGRQ). Generalised linear models were estimated to compare the relative contribution of each smoking variable with the outcomes, after adjustment for age, race, sex, body mass index, CT scanner, centre, age of smoking onset and current smoking status. We also estimated adjusted means of each outcome by categories of pack-years and combined groups of categorised smoking duration and cigarettes/day, and estimated linear trends of adjusted means for each outcome by categorised cigarettes/day, smoking duration and pack-years.

RESULTS: 10 187 subjects were included. For FEV/FVC, standardised beta coefficient for smoking duration was greater than for cigarettes/day and pack-years (P,
	keywords = {Aged, Cigarette Smoking, Cohort Studies, Cross-Sectional Studies, Female, Forced Expiratory Volume, Humans, Male, Middle Aged, Pulmonary Disease, Chronic Obstructive, Pulmonary Emphysema, Risk Assessment, Surveys and Questionnaires, Time Factors, Tomography, X-Ray Computed, Vital Capacity, Walk Test},
	issn = {1468-3296},
	doi = {10.1136/thoraxjnl-2017-210722},
	author = {Bhatt, Surya P and Kim, Young-Il and Harrington, Kathy F and Hokanson, John E and Lutz, Sharon M and Cho, Michael H and DeMeo, Dawn L and Wells, James M and Make, Barry J and Rennard, Stephen I and Washko, George R and Foreman, Marilyn G and Tashkin, Donald P and Wise, Robert A and Dransfield, Mark T and Bailey, William C}
}
@article {1433586,
	title = {Susceptibility to Inhalational Lung Injury: We Need More Than the FEV},
	journal = {Ann Am Thorac Soc},
	volume = {15},
	number = {2},
	year = {2018},
	month = {2018 02},
	pages = {156-157},
	keywords = {Bronchoscopy, Humans, Leukocytes, Lung, Lung Injury},
	issn = {2325-6621},
	doi = {10.1513/AnnalsATS.201711-870ED},
	author = {Washko, George R}
}