Publications by Year: 2011

The aim of this study is to evaluate the relationship between lung function and kurtosis or skewness of lung density histograms on computed tomography (CT) in smokers. Forty-six smokers (age range 46?81 years), enrolled in the Lung Tissue Research Consortium, underwent pulmonary function tests (PFT) and chest CT at full inspiration and full expiration. On both inspiratory and expiratory scans, kurtosis and skewness of the density histograms were automatically measured by open-source software. Correlations between CT measurements and lung function were evaluated by the linear regression analysis. Although no significant correlations were found between inspiratory kurtosis or skewness and PFT results, expiratory kurtosis significantly correlated with the following: the percentage of predicted value of forced expiratory volume in the first second (FEV(1)), the ratio of FEV(1) to forced vital capacity (FVC), and the ratio of residual volume (RV) to total lung capacity (TLC) (FEV(1)%predicted, R = -0.581, p 0.001; FEV(1)/FVC, R = -0.612, p 0.001; RV/TLC, R = 0.613, p 0.001, respectively). Similarly, expiratory skewness showed significant correlations with PFT results (FEV(1)%predicted, R = -0.584, p 0.001; FEV(1)/FVC, R = -0.619, p 0.001; RV/TLC, R = 0.585, p 0.001, respectively). Also, the expiratory/inspiratory (E/I) ratios of kurtosis and skewness significantly correlated with FEV(1)%predicted (p 0.001), FEV(1)/FVC (p 0.001), RV/TLC (p 0.001), and the percentage of predicted value of diffusing capacity for carbon monoxide (kurtosis E/I ratio, p = 0.001; skewness E/I ratio, p = 0.03, respectively). We conclude therefore that expiratory values and the E/I ratios of kurtosis and skewness of CT densitometry reflect airflow limitation and air-trapping. Higher kurtosis or skewness on expiratory CT scan indicates more severe conditions in smokers.

BACKGROUND: Cigarette smoking is the principal environmental risk factor for developing COPD, and nicotine dependence strongly influences smoking behavior. This study was performed to elucidate the relationship between nicotine dependence, genetic susceptibility to nicotine dependence, and volumetric CT findings in smokers.

BACKGROUND: Colonoscopy requires training and experience to ensure accuracy and safety. Currently, no objective, validated process exists to determine when an endoscopist has attained technical competence. Kinematics data describing movements of laparoscopic instruments have been used in surgical skill assessment to define expert surgical technique. We have developed a novel system to record kinematics data during colonoscopy and quantitatively assess colonoscopist performance. OBJECTIVE: To use kinematic analysis of colonoscopy to quantitatively assess endoscopic technical performance. DESIGN: Prospective cohort study. SETTING: Tertiary-care academic medical center. POPULATION: This study involved physicians who perform colonoscopy. INTERVENTION: Application of a kinematics data collection system to colonoscopy evaluation. MAIN OUTCOME MEASUREMENTS: Kinematics data, validated task load assessment instrument, and technical difficulty visual analog scale. RESULTS: All 13 participants completed the colonoscopy to the terminal ileum on the standard colon model. Attending physicians reached the terminal ileum quicker than fellows (median time, 150.19 seconds vs 299.86 seconds; p

RATIONALE AND OBJECTIVES: There are limited data on, and controversies regarding gender differences in the airway dimensions of smokers. Multi-detector CT (MDCT) images were analyzed to examine whether gender could explain differences in airway dimensions of anatomically matched airways in smokers. MATERIALS AND METHODS: We used VIDA imaging software to analyze MDCT scans from 2047 smokers (M:F, 1021:1026) from the COPDGene® cohort. The airway dimensions were analyzed from segmental to subsubsegmental bronchi. We compared the differences of luminal area, inner diameter, wall thickness, wall area percentage (WA%) for each airway between men and women, and multiple linear regression including covariates (age, gender, body sizes, and other relevant confounding factors) was used to determine the predictors of each airway dimensions. RESULTS: Lumen area, internal diameter and wall thickness were smaller for women than men in all measured airway (18.4 vs 22.5 mm(2) for segmental bronchial lumen area, 10.4 vs 12.5 mm(2) for subsegmental bronchi, 6.5 vs 7.7 mm(2) for subsubsegmental bronchi, respectively p 0.001). However, women had greater WA% in subsegmental and subsubsegmental bronchi. In multivariate regression, gender remained one of the most significant predictors of WA%, lumen area, inner diameter and wall thickness. CONCLUSION: Women smokers have higher WA%, but lower luminal area, internal diameter and airway thickness in anatomically matched airways as measured by CT scan than do male smokers. This difference may explain, in part, gender differences in the prevalence of COPD and airflow limitation.

BACKGROUND: The coexistence of COPD and asthma is widely recognized but has not been well described. This study characterizes clinical features, spirometry, and chest CT scans of smoking subjects with both COPD and asthma. METHODS: We performed a cross-sectional study comparing subjects with COPD and asthma to subjects with COPD alone in the COPDGene Study.

RATIONALE: The characterization of young adults who develop late-onset diseases may augment the detection of novel genes and promote new pathogenic insights.

In this paper, we introduce a new approach for tensor field segmentation based on the definition of mixtures of Gaussians on tensors as a statistical model. Working over the well-known Geodesic Active Regions segmentation framework, this scheme presents several interesting advantages. First, it yields a more flexible model than the use of a single Gaussian distribution, which enables the method to better adapt to the complexity of the data. Second, it can work directly on tensor-valued images or, through a parallel scheme that processes independently the intensity and the local structure tensor, on scalar textured images. Two different applications have been considered to show the suitability of the proposed method for medical imaging segmentation. First, we address DT-MRI segmentation on a dataset of 32 volumes, showing a successful segmentation of the corpus callosum and favourable comparisons with related approaches in the literature. Second, the segmentation of bones from hand radiographs is studied, and a complete automatic-semiautomatic approach has been developed that makes use of anatomical prior knowledge to produce accurate segmentation results.

High Angular Resolution Diffusion Imaging (HARDI) demands a higher amount of data measurements compared to Diffusion Tensor Imaging (DTI), restricting its use in practice. We propose to represent the probabilistic Orientation Distribution Function (ODF) in the frame of Spherical Wavelets (SW), where it is highly sparse. From a reduced subset of measurements (nearly four times less than the standard for HARDI), we pose the estimation as an inverse problem with sparsity regularization. This allows the fast computation of a positive, unit-mass, probabilistic ODF from 14-16 samples, as we show with both synthetic diffusion signals and real HARDI data with typical parameters.

In this paper, we propose a new nonparametric Bayesian framework to cluster white matter fiber tracts into bundles using a hierarchical Dirichlet processes mixture (HDPM) model. The number of clusters is automatically learned driven by data with a Dirichlet process (DP) prior instead of being manually specified. After the models of bundles have been learned from training data without supervision, they can be used as priors to cluster/classify fibers of new subjects for comparison across subjects. When clustering fibers of new subjects, new clusters can be created for structures not observed in the training data. Our approach does not require computing pairwise distances between fibers and can cluster a huge set of fibers across multiple subjects. We present results on several data sets, the largest of which has more than 120,000 fibers.

PURPOSE: To test the hypothesis-given the increasing emphasis on quantitative computed tomographic (CT) phenotypes of chronic obstructive pulmonary disease (COPD)-that a relationship exists between COPD exacerbation frequency and quantitative CT measures of emphysema and airway disease. MATERIALS AND METHODS: This research protocol was approved by the institutional review board of each participating institution, and all participants provided written informed consent. One thousand two subjects who were enrolled in the COPDGene Study and met the GOLD (Global Initiative for Chronic Obstructive Lung Disease) criteria for COPD with quantitative CT analysis were included. Total lung emphysema percentage was measured by using the attenuation mask technique with a -950-HU threshold. An automated program measured the mean wall thickness and mean wall area percentage in six segmental bronchi. The frequency of COPD exacerbation in the prior year was determined by using a questionnaire. Statistical analysis was performed to examine the relationship of exacerbation frequency with lung function and quantitative CT measurements.