Respiratory Symptoms in Young Adults and Future Lung Disease. The CARDIA Lung Study.

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 FEV1 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 FEV1 (P < 0.001) and -2.18 in FVC (P < 0.001) as well as greater odds of incident (prebronchodilator) obstructive (odds ratio [OR], 1.63; 95% confidence interval [CI], 1.24-2.14) and restrictive (OR, 1.40; 95% CI, 1.09-1.80) physiology. Cough-related symptoms (OR, 1.56; 95% CI, 1.13-2.16) were associated with greater odds of future emphysema. CONCLUSIONS: Persistent respiratory symptoms in young adults are associated with accelerated decline in lung function, incident obstructive and restrictive physiology, and greater odds of future radiographic emphysema.

Association between acute respiratory disease events and the MUC5B promoter polymorphism in smokers.

A single-nucleotide polymorphism (rs35705950) in the mucin 5B (MUC5B) 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 MUC5B 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 MUC5B promoter polymorphism may have a beneficial effect on the risk of acute respiratory disease events in smokers with interstitial CT features.

Interstitial Features at Chest CT Enhance the Deleterious Effects of Emphysema in the COPDGene Cohort.

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 < .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 < .001), a 5.9-point higher St George's Respiratory Questionnaire (SGRQ) score (P < .001), and 82% higher mortality (P < .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 < .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.

Pectoralis muscle area and mortality in smokers without airflow obstruction.

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/height2) 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.

Chest computed tomography-derived low fat-free mass index and mortality in COPD.

Low fat-free mass index (FFMI) is an independent risk factor for mortality in chronic obstructive pulmonary disease (COPD) not typically measured during routine care. In the present study, we aimed to derive fat-free mass from the pectoralis muscle area (FFMPMA) and assess whether low FFMIPMA is associated with all-cause mortality in COPD cases. We used data from two independent COPD cohorts, ECLIPSE and COPDGene.Two equal sized groups of COPD cases (n=759) from the ECLIPSE study were used to derive and validate an equation to calculate the FFMPMA measured using bioelectrical impedance from PMA. We then applied the equation in COPD cases (n=3121) from the COPDGene cohort, and assessed survival. Low FFMIPMA was defined, using the Schols classification (FFMI <16 in men, FFMI <15 in women) and the fifth percentile normative values of FFMI from the UK Biobank.The final regression model included PMA, weight, sex and height, and had an adjusted R2 of 0.92 with fat-free mass (FFM) as the outcome. In the test group, the correlation between FFMPMA and FFM remained high (Pearson correlation=0.97). In COPDGene, COPD cases with a low FFMIPMA had an increased risk of death (HR 1.6, p<0.001).We demonstrated COPD cases with a low FFMIPMA have an increased risk of death.

Densitometric and local histogram based analysis of computed tomography images in patients with idiopathic pulmonary fibrosis.

BACKGROUND: Prior studies of clinical prognostication in idiopathic pulmonary fibrosis (IPF) using computed tomography (CT) have often used subjective analyses or have evaluated quantitative measures in isolation. This study examined associations between both densitometric and local histogram based quantitative CT measurements with pulmonary function test (PFT) parameters and mortality. In addition, this study sought to compare risk prediction scores that incorporate quantitative CT measures with previously described systems. METHODS: Forty six patients with biopsy proven IPF were identified from a registry of patients with interstitial lung disease at Brigham and Women's Hospital in Boston, MA. CT scans for each subject were visually scored using a previously published method. After a semi-automated method was used to segment the lungs from the surrounding tissue, densitometric measurements including the percent high attenuating area, mean lung density, skewness and kurtosis were made for the entirety of each patient's lungs. A separate, automated tool was used to detect and quantify the percent of lung occupied by interstitial lung features. These analyses were used to create clinical and quantitative CT based risk prediction scores, and the performance of these was compared to the performance of clinical and visual analysis based methods. RESULTS: All of the densitometric measures were correlated with forced vital capacity and diffusing capacity, as were the total amount of interstitial change and the percentage of interstitial change that was honeycombing measured using the local histogram method. Higher percent high attenuating area, higher mean lung density, lower skewness, lower kurtosis and a higher percentage of honeycombing were associated with worse transplant free survival. The quantitative CT based risk prediction scores performed similarly to the clinical and visual analysis based methods. CONCLUSIONS: Both densitometric and feature based quantitative CT measures correlate with pulmonary function test measures and are associated with transplant free survival. These objective measures may be useful for identifying high risk patients and monitoring disease progression. Further work will be needed to validate these measures and the quantitative imaging based risk prediction scores in other cohorts.

Association Between Interstitial Lung Abnormalities and All-Cause Mortality.

IMPORTANCE: Interstitial lung abnormalities have been associated with lower 6-minute walk distance, diffusion capacity for carbon monoxide, and total lung capacity. However, to our knowledge, an association with mortality has not been previously investigated. OBJECTIVE: To investigate whether interstitial lung abnormalities are associated with increased mortality. DESIGN, SETTING, AND POPULATION: Prospective cohort studies of 2633 participants from the FHS (Framingham Heart Study; computed tomographic [CT] scans obtained September 2008-March 2011), 5320 from the AGES-Reykjavik Study (Age Gene/Environment Susceptibility; recruited January 2002-February 2006), 2068 from the COPDGene Study (Chronic Obstructive Pulmonary Disease; recruited November 2007-April 2010), and 1670 from ECLIPSE (Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints; between December 2005-December 2006). EXPOSURES: Interstitial lung abnormality status as determined by chest CT evaluation. MAIN OUTCOMES AND MEASURES: All-cause mortality over an approximate 3- to 9-year median follow-up time. Cause-of-death information was also examined in the AGES-Reykjavik cohort. RESULTS: Interstitial lung abnormalities were present in 177 (7%) of the 2633 participants from FHS, 378 (7%) of 5320 from AGES-Reykjavik, 156 (8%) of 2068 from COPDGene, and in 157 (9%) of 1670 from ECLIPSE. Over median follow-up times of approximately 3 to 9 years, there were more deaths (and a greater absolute rate of mortality) among participants with interstitial lung abnormalities when compared with those who did not have interstitial lung abnormalities in the following cohorts: 7% vs 1% in FHS (6% difference [95% CI, 2% to 10%]), 56% vs 33% in AGES-Reykjavik (23% difference [95% CI, 18% to 28%]), and 11% vs 5% in ECLIPSE (6% difference [95% CI, 1% to 11%]). After adjustment for covariates, interstitial lung abnormalities were associated with a higher risk of death in the FHS (hazard ratio [HR], 2.7 [95% CI, 1.1 to 6.5]; P = .03), AGES-Reykjavik (HR, 1.3 [95% CI, 1.2 to 1.4]; P < .001), COPDGene (HR, 1.8 [95% CI, 1.1 to 2.8]; P = .01), and ECLIPSE (HR, 1.4 [95% CI, 1.1 to 2.0]; P = .02) cohorts. In the AGES-Reykjavik cohort, the higher rate of mortality could be explained by a higher rate of death due to respiratory disease, specifically pulmonary fibrosis. CONCLUSIONS AND RELEVANCE: In 4 separate research cohorts, interstitial lung abnormalities were associated with a greater risk of all-cause mortality. The clinical implications of this association require further investigation.

Understanding the contribution of native tracheobronchial structure to lung function: CT assessment of airway morphology in never smokers.

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.

Integrating Explainable Machine Learning in Clinical Decision Support Systems: Study Involving a Modified Design Thinking Approach.

BACKGROUND: Though there has been considerable effort to implement machine learning (ML) methods for health care, clinical implementation has lagged. Incorporating explainable machine learning (XML) methods through the development of a decision support tool using a design thinking approach is expected to lead to greater uptake of such tools. OBJECTIVE: This work aimed to explore how constant engagement of clinician end users can address the lack of adoption of ML tools in clinical contexts due to their lack of transparency and address challenges related to presenting explainability in a decision support interface. METHODS: We used a design thinking approach augmented with additional theoretical frameworks to provide more robust approaches to different phases of design. In particular, in the problem definition phase, we incorporated the nonadoption, abandonment, scale-up, spread, and sustainability of technology in health care (NASSS) framework to assess these aspects in a health care network. This process helped focus on the development of a prognostic tool that predicted the likelihood of admission to an intensive care ward based on disease severity in chest x-ray images. In the ideate, prototype, and test phases, we incorporated a metric framework to assess physician trust in artificial intelligence (AI) tools. This allowed us to compare physicians' assessments of the domain representation, action ability, and consistency of the tool. RESULTS: Physicians found the design of the prototype elegant, and domain appropriate representation of data was displayed in the tool. They appreciated the simplified explainability overlay, which only displayed the most predictive patches that cumulatively explained 90% of the final admission risk score. Finally, in terms of consistency, physicians unanimously appreciated the capacity to compare multiple x-ray images in the same view. They also appreciated the ability to toggle the explainability overlay so that both options made it easier for them to assess how consistently the tool was identifying elements of the x-ray image they felt would contribute to overall disease severity. CONCLUSIONS: The adopted approach is situated in an evolving space concerned with incorporating XML or AI technologies into health care software. We addressed the alignment of AI as it relates to clinician trust, describing an approach to wire framing and prototyping, which incorporates the use of a theoretical framework for trust in the design process itself. Moreover, we proposed that alignment of AI is dependent upon integration of end users throughout the larger design process. Our work shows the importance and value of engaging end users prior to tool development. We believe that the described approach is a unique and valuable contribution that outlines a direction for ML experts, user experience designers, and clinician end users on how to collaborate in the creation of trustworthy and usable XML-based clinical decision support tools.

Multimodal image registration of the scoliotic torso for surgical planning.

BACKGROUND: This paper presents a method that registers MRIs acquired in prone position, with surface topography (TP) and X-ray reconstructions acquired in standing position, in order to obtain a 3D representation of a human torso incorporating the external surface, bone structures, and soft tissues. METHODS: TP and X-ray data are registered using landmarks. Bone structures are used to register each MRI slice using an articulated model, and the soft tissue is confined to the volume delimited by the trunk and bone surfaces using a constrained thin-plate spline. RESULTS: The method is tested on 3 pre-surgical patients with scoliosis and shows a significant improvement, qualitatively and using the Dice similarity coefficient, in fitting the MRI into the standing patient model when compared to rigid and articulated model registration. The determinant of the Jacobian of the registration deformation shows higher variations in the deformation in areas closer to the surface of the torso. CONCLUSIONS: The novel, resulting 3D full torso model can provide a more complete representation of patient geometry to be incorporated in surgical simulators under development that aim at predicting the effect of scoliosis surgery on the external appearance of the patient's torso.

Quantitative Interstitial Abnormality Progression and Outcomes in the Genetic Epidemiology of COPD and Pittsburgh Lung Screening Study Cohorts.

BACKGROUND: The risk factors and clinical outcomes of quantitative interstitial abnormality progression over time have not been characterized. RESEARCH QUESTIONS: What are the associations of quantitative interstitial abnormality progression with lung function, exercise capacity, and mortality? What are the demographic and genetic risk factors for quantitative interstitial abnormality progression? STUDY DESIGN AND METHODS: Quantitative interstitial abnormality progression between visits 1 and 2 was assessed from 4,635 participants in the Genetic Epidemiology of COPD (COPDGene) cohort and 1,307 participants in the Pittsburgh Lung Screening Study (PLuSS) cohort. We used multivariable linear regression to determine the risk factors for progression and the longitudinal associations between progression and FVC and 6-min walk distance, and Cox regression models for the association with mortality. RESULTS: Age at enrollment, female sex, current smoking status, and the MUC5B minor allele were associated with quantitative interstitial abnormality progression. Each percent annual increase in quantitative interstitial abnormalities was associated with annual declines in FVC (COPDGene: 8.5 mL/y; 95% CI, 4.7-12.4 mL/y; P < .001; PLuSS: 9.5 mL/y; 95% CI, 3.7-15.4 mL/y; P = .001) and 6-min walk distance, and increased mortality (COPDGene: hazard ratio, 1.69; 95% CI, 1.34-2.12; P < .001; PLuSS: hazard ratio, 1.28; 95% CI, 1.10-1.49; P = .001). INTERPRETATION: The objective, longitudinal measurement of quantitative interstitial abnormalities may help identify people at greatest risk for adverse events and most likely to benefit from early intervention.

An open-source framework for pulmonary fissure completeness assessment.

We present an open-source framework for pulmonary fissure completeness assessment. Fissure incompleteness has been shown to associate with emphysema treatment outcomes, motivating the development of tools that facilitate completeness estimation. Generally, the task of fissure completeness assessment requires accurate detection of fissures and definition of the boundary surfaces separating the lung lobes. The framework we describe acknowledges a) the modular nature of fissure detection and lung lobe segmentation (lobe boundary detection), and b) that methods to address these challenges are varied and continually developing. It is designed to be readily deployable on existing lung lobe segmentation and fissure detection data sets. The framework consists of multiple components: a flexible quality control module that enables rapid assessment of lung lobe segmentations, an interactive lobe segmentation tool exposed through 3D Slicer for handling challenging cases, a flexible fissure representation using particles-based sampling that can handle fissure feature-strength or binary fissure detection images, and a module that performs fissure completeness estimation using voxel counting and a novel surface area estimation approach. We demonstrate the usage of the proposed framework by deploying on 100 cases exhibiting various levels of fissure completeness. We compare the two completeness level approaches and also compare to visual reads. The code is available to the community via github as part of the Chest Imaging Platform and a 3D Slicer extension module.

Objectively Measured Chronic Lung Injury on Chest CT.

BACKGROUND: Tobacco smoke exposure is associated with emphysema and pulmonary fibrosis, both of which are irreversible. We have developed a new objective CT analysis tool that combines densitometry with machine learning to detect high attenuation changes in visually normal appearing lung (NormHA) that may precede these diseases. METHODS: We trained the classification tool by placing 34,528 training points in chest CT scans from 297 COPDGene participants. The tool was then used to classify lung tissue in 9,038 participants as normal, emphysema, fibrotic/interstitial, or NormHA. Associations between the quartile of NormHA and plasma-based biomarkers, clinical severity, and mortality were evaluated using Jonckheere-Terpstra, pairwise Wilcoxon rank-sum tests, and multivariable linear and Cox regression. RESULTS: A higher percentage of lung occupied by NormHA was associated with higher C-reactive protein and intercellular adhesion molecule 1 (P for trend for both < .001). In analyses adjusted for multiple covariates, including high and low attenuation area, compared with those in the lowest quartile of NormHA, those in the highest quartile had a 6.50 absolute percent lower percent predicted lower FEV1 (P < .001), an 8.48 absolute percent lower percent predicted forced expiratory volume, a 10.78-meter shorter 6-min walk distance (P = .011), and a 56% higher risk of death (P = .003). These findings were present even in those individuals without visually defined interstitial lung abnormalities. CONCLUSIONS: A new class of NormHA on CT may represent a unique tissue class associated with adverse outcomes, independent of emphysema and fibrosis.

Clinical and Genetic Associations of Objectively Identified Interstitial Changes in Smokers.

BACKGROUND: Smoking-related lung injury may manifest on CT scans as both emphysema and interstitial changes. We have developed an automated method to quantify interstitial changes and hypothesized that this measurement would be associated with lung function, quality of life, mortality, and a mucin 5B (MUC5B) polymorphism. METHODS: Using CT scans from the Genetic Epidemiology of COPD Study, we objectively labeled lung parenchyma as a tissue subtype. We calculated the percentage of the lung occupied by interstitial subtypes. RESULTS: A total of 8,345 participants had clinical and CT scanning data available. A 5% absolute increase in interstitial changes was associated with an absolute decrease in FVC % predicted of 2.47% (P < .001) and a 1.36-point higher St. George's Respiratory Questionnaire score (P < .001). Among the 6,827 participants with mortality data, a 5% increase in interstitial changes was associated with a 29% increased risk of death (P < .001). These associations were present in a subgroup without visually defined interstitial lung abnormalities, as well as in those with normal spirometric test results, and in those without chronic respiratory symptoms. In non-Hispanic whites, for each copy of the minor allele of the MUC5B promoter polymorphism, there was a 0.64% (P < .001) absolute increase in the percentage of lung with interstitial changes. CONCLUSIONS: Objective interstitial changes on CT scans were associated with impaired lung function, worse quality of life, increased mortality, and more copies of a MUC5B promoter polymorphism, suggesting that these changes may be a marker of susceptibility to smoking-related lung injury, detectable even in those who are healthy by other measures.

The Objective Identification and Quantification of Interstitial Lung Abnormalities in Smokers.

RATIONALE AND OBJECTIVES: Previous investigation suggests that visually detected interstitial changes in the lung parenchyma of smokers are highly clinically relevant and predict outcomes, including death. Visual subjective analysis to detect these changes is time-consuming, insensitive to subtle changes, and requires training to enhance reproducibility. Objective detection of such changes could provide a method of disease identification without these limitations. The goal of this study was to develop and test a fully automated image processing tool to objectively identify radiographic features associated with interstitial abnormalities in the computed tomography scans of a large cohort of smokers. MATERIALS AND METHODS: An automated tool that uses local histogram analysis combined with distance from the pleural surface was used to detect radiographic features consistent with interstitial lung abnormalities in computed tomography scans from 2257 individuals from the Genetic Epidemiology of COPD study, a longitudinal observational study of smokers. The sensitivity and specificity of this tool was determined based on its ability to detect the visually identified presence of these abnormalities. RESULTS: The tool had a sensitivity of 87.8% and a specificity of 57.5% for the detection of interstitial lung abnormalities, with a c-statistic of 0.82, and was 100% sensitive and 56.7% specific for the detection of the visual subtype of interstitial abnormalities called fibrotic parenchymal abnormalities, with a c-statistic of 0.89. CONCLUSIONS: In smokers, a fully automated image processing tool is able to identify those individuals who have interstitial lung abnormalities with moderate sensitivity and specificity.

A Robust Emphysema Severity Measure Based on Disease Subtypes.

RATIONALE AND OBJECTIVES: We propose a novel single index for the quantification of emphysema severity based on an aggregation of multiple computed tomographic features evident in the lung parenchyma of smokers. Our goal was to demonstrate that this single index provides complementary information to the current standard measure of emphysema, percent emphysema (percent low attenuation areas [LAA%]), and may be superior in its association with clinically relevant outcomes. MATERIALS AND METHODS: The inputs to our algorithm were objective assessments of multiple emphysema subtypes (normal tissue; panlobular; paraseptal; and mild, moderate, and severe centrilobular emphysema). We applied dimensionality reduction techniques to the emphysema quantities to find a space that maximizes the variance of these subtypes. A single emphysema severity index was then derived from a parametrization of the reduced space, and the clinical utility of the measure was explored in a large cross-sectional cohort of 8914 subjects from the COPDGene Study. RESULTS: There was a statistically significant association between the severity index and the LAA%. Subjects with more severe chronic obstructive pulmonary disease (higher Global initiative for Obstructive Lung Disease stage) tended to have a higher computed tomography severity index. Finally, the severity index was associated with clinical outcomes such as lung function and provided a stronger association to these measures than the LAA%. CONCLUSIONS: The method provides a single clinically relevant index that can assess the severity of emphysema and that provides information that is complimentary to the more commonly used LAA%.

Probabilistic multiple sclerosis lesion classification based on modeling regional intensity variability and local neighborhood information.

GOAL: In this paper, a fully automatic probabilistic method for multiple sclerosis (MS) lesion classification is presented, whereby the posterior probability density function over healthy tissues and two types of lesions (T1-hypointense and T2-hyperintense) is generated at every voxel. METHODS: During training, the system explicitly models the spatial variability of the intensity distributions throughout the brain by first segmenting it into distinct anatomical regions and then building regional likelihood distributions for each tissue class based on multimodal magnetic resonance image (MRI) intensities. Local class smoothness is ensured by incorporating neighboring voxel information in the prior probability through Markov random fields. The system is tested on two datasets from real multisite clinical trials consisting of multimodal MRIs from a total of 100 patients with MS. Lesion classification results based on the framework are compared with and without the regional information, as well as with other state-of-the-art methods against the labels from expert manual raters. The metrics for comparison include Dice overlap, sensitivity, and positive predictive rates for both voxel and lesion classifications. RESULTS: Statistically significant improvements in Dice values ( ), for voxel-based and lesion-based sensitivity values ( ), and positive predictive rates ( and respectively) are shown when the proposed method is compared to the method without regional information, and to a widely used method [1]. This holds particularly true in the posterior fossa, an area where classification is very challenging. SIGNIFICANCE: The proposed method allows us to provide clinicians with accurate tissue labels for T1-hypointense and T2-hyperintense lesions, two types of lesions that differ in appearance and clinical ramifications, and with a confidence level in the classification, which helps clinicians assess the classification results.

Morphologic Response of the Pulmonary Vasculature to Endoscopic Lung Volume Reduction.

INTRODUCTION: Endoscopic Lung Volume Reduction has been used to reduce lung hyperinflation in selected patients with severe emphysema. Little is known about the effect of this procedure on the intraparenchymal pulmonary vasculature. In this study we used CT based vascular reconstruction to quantify the effect of the procedure on the pulmonary vasculature. METHODS: Intraparenchymal vasculature was reconstructed and quantified in 12 patients with CT scans at baseline and 12 weeks following bilateral introduction of sealants in the upper lobes. The volume of each lung and each lobe was measured, and the vascular volume profile was calculated for both lower lobes. The detected vasculature was further labeled manually as arterial or venous in the right lower lobe. RESULTS: There was an increase in the volume of the lower lobes (3.14L to 3.25L, p=0.0005). There was an increase in BV5, defined as the volume of blood vessels with cross sectional area of less than 5mm2, (53.2ml to 57.9ml, p=0.03). This was found to be correlated with the increase in lower lobe volumes (R=0.65, p=0.02). The changes appear to be symmetric for veins and arteries with a correlation coefficient of 0.87 and a slope of near identity. CONCLUSION: In the subjects studied, there was an increase, from baseline, in BV5 in the lower lobes that correlated with the change in the volume of the lower lobes. The change appeared to be symmetric for both arteries and veins. The study illustrates the use of intraparenchymal pulmonary vascular reconstruction to study morphologic changes in response to interventions.

Abdominal Visceral Adipose Tissue is Associated with Myocardial Infarction in Patients with COPD.

BACKGROUND: Cardiovascular diseases are frequent and a major cause of death in patients with chronic obstructive pulmonary disease (COPD). In the general population, various fat depots including abdominal visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT), and liver fat have been linked to increased risk of cardiovascular diseases. We hypothesize that these adipose tissue compartments are associated with myocardial infarction (MI) in patients with COPD. METHODS: We collected measures of VAT and SAT areas and liver attenuation on the computed tomography scan of the chest from 1267 patients with COPD. MI was a self-reported physician-diagnosed outcome. The association between fat depots and self-reported history of MI was assessed by logistic regression analysis in which the patients within the 2 lowest tertiles of VAT and SAT areas were the reference group. RESULTS: Eighty three patients (6.6%) reported a history of MI at the time of enrollment. Compared to patients who did not have an MI episode, those who had a prior MI had a higher VAT area (mean ± SD, 303.4 ± 208.5 vs. 226.8 ± 172.6 cm2; P=0.002) with no differences in SAT area and liver fat. After adjustment for age, gender, obesity, pack years of smoking, hypertension, high cholesterol, and diabetes, patients within the upper tertile (vs. those in the lower tertiles) of VAT area had increased odds of MI (odds ratio [OR] 1.86, 95% confidence interval [CI] 1.02 - 3.41). CONCLUSION: Increased abdominal visceral fat is independently associated with a history of MI in individuals with COPD.

Chest CT measures of muscle and adipose tissue in COPD: gender-based differences in content and in relationships with blood biomarkers.

RATIONALE AND OBJECTIVES: Computed tomography (CT) of the chest can be used to assess pectoralis muscle area (PMA) and subcutaneous adipose tissue (SAT) area. Adipose tissue content is associated with inflammatory mediators in chronic obstructive pulmonary disease (COPD) subjects. Based on gender differences in body composition, we aimed to assess the hypothesis that in subjects with COPD, the relationships between PMA, SAT, and blood biomarkers of inflammation differ by gender. MATERIALS AND METHODS: We compared chest CT measures of PMA and SAT on a single slice at aortic arch and supraesternal notch levels from 73 subjects (28 women) with COPD between genders. The relationships of PMA and SAT area to biomarkers were assessed using within-gender regression models. RESULTS: Women had a lesser PMA and a greater SAT area than men (difference range for PMA, 13.3-22.8 cm²; for SAT, 11.8-12.4 cm²; P < .05 for all comparisons) at both anatomic levels. These differences in PMA and SAT remained significant after adjustment for age and body mass index. Within-gender regression models adjusted for age showed that SAT was directly associated with C-reactive protein (for aortic arch level, P = .04) and fibrinogen (for both anatomic locations, P = .003) only in women, whereas PMA was not associated with any biomarkers in either gender. CONCLUSIONS: It appears that in subjects with COPD, there are gender-based differences in the relationships between subcutaneous adipose tissue and inflammatory biomarkers.