BACKGROUND AND PURPOSE:Right Ventricular to Left Ventricular (RV/LV) diameter ratio has been shown to be a prognostic biomarker for patients suffering from acute Pulmonary Embolism (PE). While Computed Tomography Pulmonary Angiography (CTPA) images used to confirm a clinical suspicion of PE do include information of the heart, a numerical RV/LV diameter ratio is not universally reported, likely because of lack in training, inter-reader variability in the measurements, and additional effort by the radiologist. This study designs and validates a completely automated Computer Aided Detection (CAD) system to compute the axial RV/LV diameter ratio from CTPA images so that the RV/LV diameter ratio can be a more objective metric that is consistently reported in patients for whom CTPA diagnoses PE.MATERIALS AND METHODS:The CAD system was designed specifically for RV/LV measurements. The system was tested in 198 consecutive CTPA patients with acute PE. Its accuracy was evaluated using reference standard RV/LV radiologist measurements and its prognostic value was established for 30-day PE-specific mortality and a composite outcome of 30-day PE-specific mortality or the need for intensive therapies. The study was Institutional Review Board (IRB) approved and HIPAA compliant.RESULTS:The CAD system analyzed correctly 92.4% (183/198) of CTPA studies. The mean difference between automated and manually computed axial RV/LV ratios was 0.03±0.22. The correlation between the RV/LV diameter ratio obtained by the CAD system and that obtained by the radiologist was high (r=0.81). Compared to the radiologist, the CAD system equally achieved high accuracy for the composite outcome, with areas under the receiver operating characteristic curves of 0.75 vs. 0.78. Similar results were found for 30-days PE-specific mortality, with areas under the curve of 0.72 vs. 0.75.CONCLUSIONS:An automated CAD system for determining the CT derived RV/LV diameter ratio in patients with acute PE has high accuracy when compared to manual measurements and similar prognostic significance for two clinical outcomes.

This paper proposes an inference method well-suited to large sets of medical images. The method is based upon a framework where distinctive 3D scale-invariant features are indexed efficiently to identify approximate nearest-neighbor (NN) feature matches in O(log N) computational complexity in the number of images N. It thus scales well to large data sets, in contrast to methods based on pair-wise image registration or feature matching requiring O(N) complexity. Our theoretical contribution is a density estimator based on a generative model that generalizes kernel density estimation and K-nearest neighbor (KNN) methods. The estimator can be used for on-the-fly queries, without requiring explicit parametric models or an off-line training phase. The method is validated on a large multi-site data set of 95,000,000 features extracted from 19,000 lung CT scans. Subject-level classification identifies all images of the same subjects across the entire data set despite deformation due to breathing state, including unintentional duplicate scans. State-of-the-art performance is achieved in predicting chronic pulmonary obstructive disorder (COPD) severity across the 5-category GOLD clinical rating, with an accuracy of 89% if both exact and one-off predictions are considered correct.

RATIONALE:Chronic obstructive pulmonary disease (COPD) is defined by the presence of airflow limitation on spirometry, yet COPD subjects can have marked differences in CT imaging. These differences may be driven by genetic factors. We hypothesized that a genome-wide association study of quantitative imaging would identify loci not previously identified in analyses of COPD or spirometry. In addition, we sought to determine whether previously described genome-wide significant COPD and spirometric loci were associated with emphysema or airway phenotypes.OBJECTIVE:To identify genetic determinants of quantitative imaging phenotypes.METHODS:We performed a genome-wide association study on two quantitative emphysema and two quantitative airway imaging phenotypes in the COPDGene (non-Hispanic white and African-American), ECLIPSE, NETT, and GenKOLS studies; and on % gas trapping in COPDGene. We also examined specific loci reported as genome-wide significant for spirometric phenotypes related to airflow limitation or COPD.RESULTS:The total sample size across all cohorts was 12,031, of which 9,338 were from COPDGene. We identified five loci associated with emphysema-related phenotypes, one with airway-related phenotypes, and two with gas trapping. These loci included previously reported associations, including the HHIP, 15q25, and AGER loci, as well as novel associations near SERPINA10 and DLC1. All previously reported COPD and a significant number of spirometric GWAS loci were at least nominally (P < 0.05) associated with either emphysema or airway phenotypes.CONCLUSIONS:Genome-wide analysis may identify novel risk factors for quantitative imaging characteristics in COPD, and also identify imaging features associated with previously identified lung function loci. .

PURPOSE:MRI-based skull segmentation is a useful procedure for many imaging applications. This study describes a methodology for automatic segmentation of the complete skull from a single T1-weighted volume.METHODS:The skull is estimated using a multi-atlas segmentation approach. Using a whole head computed tomography (CT) scan database, the skull in a new MRI volume is detected by nonrigid image registration of the volume to every CT, and combination of the individual segmentations by label-fusion. We have compared Majority Voting, Simultaneous Truth and Performance Level Estimation (STAPLE), Shape Based Averaging (SBA), and the Selective and Iterative Method for Performance Level Estimation (SIMPLE) algorithms.RESULTS:The pipeline has been evaluated quantitatively using images from the Retrospective Image Registration Evaluation database (reaching an overlap of 72.46 ± 6.99%), a clinical CT-MR dataset (maximum overlap of 78.31 ± 6.97%), and a whole head CT-MRI pair (maximum overlap 78.68%). A qualitative evaluation has also been performed on MRI acquisition of volunteers.CONCLUSION:It is possible to automatically segment the complete skull from MRI data using a multi-atlas and label fusion approach. This will allow the creation of complete MRI-based tissue models that can be used in electromagnetic dosimetry applications and attenuation correction in PET/MR. Magn Reson Med, 2015. © 2015 Wiley Periodicals, Inc.

BACKGROUND:Chronic obstructive pulmonary disease causes significant morbidity and concomitant pulmonary vascular disease and cardiac dysfunction are associated with poor prognosis. Computed tomography-detected relative pulmonary artery (PA) enlargement defined as a PA to ascending aorta diameter ratio >1 (PA:A>1) is a marker for pulmonary hypertension and predicts chronic obstructive pulmonary disease exacerbations. However, little is known about the relationship between the PA:A ratio, pulmonary blood volume, and cardiac function.METHODS AND RESULTS:A single-center prospective cohort study of patients with chronic obstructive pulmonary disease was conducted. Clinical characteristics and computed tomography metrics, including the PA:A and pulmonary blood vessel volume, were measured. Ventricular functions, volumes, and dimensions were measured by cine cardiac MRI with 3-dimensional analysis. Linear regression examined the relationships between clinical characteristics, computed tomography and cardiac MRI metrics, and 6-minute walk distance. Twenty-four patients were evaluated and those with PA:A>1 had higher right ventricular (RV) end-diastolic and end-systolic volume indices accompanied by lower RV ejection fraction (52±7% versus 60±9%; P=0.04). The PA:A correlated inversely with total intraparenchymal pulmonary blood vessel volume and the volume of distal vessels with a cross-sectional area of <5 mm(2). Lower forced expiratory volume, PA:A>1, and hyperinflation correlated with reduced RV ejection fraction. Both PA diameter and reduced RV ejection fraction were independently associated with reduced 6-minute walk distance.CONCLUSIONS:The loss of blood volume in distal pulmonary vessels is associated with PA enlargement on computed tomography. Cardiac MRI detects early RV dysfunction and remodeling in nonsevere chronic obstructive pulmonary disease patients with a PA:A>1. Both RV dysfunction and PA enlargement are independently associated with reduced walk distance.CLINICAL TRIAL REGISTRATION:URL: http://www.clinicaltrials.gov. Unique identifier: NCT00608764.

BACKGROUND:Computed tomographic (CT) airway lumen narrowing is associated with lower lung function. Although volumetric CT measures of airways (wall volume [WV] and lumen volume [LV]) compared to cross sectional measures can more accurately reflect bronchial morphology, data of their use in never smokers is scarce. We hypothesize that native tracheobronchial tree morphology as assessed by volumetric CT metrics play a significant role in determining lung function in normal subjects. We aimed to assess the relationships between airway size, the projected branching generation number (BGN) to reach airways of <2mm lumen diameter -the site for airflow obstruction in smokers- and measures of lung function including forced expiratory volume in 1 second (FEV1) and forced expiratory flow between 25% and 75% of vital capacity (FEF 25-75).METHODS:We assessed WV and LV of segmental and subsegmental airways from six bronchial paths as well as lung volume on CT scans from 106 never smokers. We calculated the lumen area ratio of the subsegmental to segmental airways and estimated the projected BGN to reach a <2mm-lumen-diameter airway assuming a dichotomized tracheobronchial tree model. Regression analysis was used to assess the relationships between airway size, BGN, FEF 25-75, and FEV1.RESULTS:We found that in models adjusted for demographics, LV and WV of segmental and subsegmental airways were directly related to FEV1 (P <0.05 for all the models). In adjusted models for age, sex, race, LV and lung volume or height, the projected BGN was directly associated with FEF 25-75 and FEV1 (P=0.001) where subjects with lower FEV1 had fewer calculated branch generations between the subsegmental bronchus and small airways. There was no association between airway lumen area ratio and lung volume.CONCLUSION:We conclude that in never smokers, those with smaller central airways had lower airflow and those with lower airflow had less parallel airway pathways independent of lung size. These findings suggest that variability in the structure of the tracheobronchial tree may influence the risk of developing clinically relevant smoking related airway obstruction.

Genetic risk loci have been identified for a wide range of diseases through genome-wide association studies (GWAS), but the relevant functional mechanisms have been identified for only a small proportion of these GWAS-identified loci. By integrating results from the largest current GWAS of chronic obstructive disease (COPD) with expression quantitative trait locus (eQTL) analysis in whole blood and sputum from 121 subjects with COPD from the ECLIPSE Study, this analysis identifies loci that are simultaneously associated with COPD and the expression of nearby genes (COPD eQTLs). After integrative analysis, 19 COPD eQTLs were identified, including all four previously identified genome-wide significant loci near HHIP, FAM13A, and the 15q25 and 19q13 loci. For each COPD eQTL, fine mapping and colocalization analysis to identify causal shared eQTL and GWAS variants identified a subset of sites with moderate-to-strong evidence of harboring at least one shared variant responsible for both the eQTL and GWAS signals. Transcription factor binding site (TFBS) analysis confirms that multiple COPD eQTL lead SNPs disrupt TFBS, and enhancer enrichment analysis for loci with the strongest colocalization signals showed enrichment for blood-related cell types (CD3 and CD4+ T cells, lymphoblastoid cell lines). In summary, integrative eQTL and GWAS analysis confirms that genetic control of gene expression plays a key role in the genetic architecture of COPD and identifies specific blood-related cell types as likely participants in the functional pathway from GWAS-associated variant to disease phenotype.

RATIONALE: Chronic lung diseases are associated with cardiovascular disease. How these associations evolve from young adulthood forward is unknown. Understanding the preclinical history of these associations could inform prevention strategies for common heart-lung conditions. OBJECTIVES: To use the Coronary Artery Risk Development in Young Adults (CARDIA) study to explore the development of heart-lung interactions. METHODS: We analyzed cardiac structural and functional measurements determined by echocardiography at Year 25 of CARDIA and measures of pulmonary function over 20 years in 3,000 participants. MEASUREMENTS AND MAIN RESULTS: Decline in FVC from peak was associated with larger left ventricular mass (β = 6.05 g per SD of FVC decline; P < 0.0001) and greater cardiac output (β = 0.109 L/min per SD of FVC decline; P = 0.001). Decline in FEV1/FVC ratio was associated with smaller left atrial internal dimension (β = -0.038 cm per SD FEV1/FVC decline; P < 0.0001) and lower cardiac output (β = -0.070 L/min per SD of FEV1/FVC decline; P = 0.03). Decline in FVC was associated with diastolic dysfunction (odds ratio, 3.39; 95% confidence interval, 1.37-8.36; P = 0.006). CONCLUSIONS: Patterns of loss of lung health are associated with specific cardiovascular phenotypes in middle age. Decline in FEV1/FVC ratio is associated with underfilling of the left heart and low cardiac output. Decline in FVC with preserved FEV1/FVC ratio is associated with left ventricular hypertrophy and diastolic dysfunction. Cardiopulmonary interactions apparent with common complex heart and lung diseases evolve concurrently from early adulthood forward.