Publications

Diffusion magnetic resonance imaging (dMRI) is an important tool that allows non-invasive investigation of neural architecture of the brain. The data obtained from these in-vivo scans provides important information about the integrity and connectivity of neural fiber bundles in the brain. A multi-shell imaging (MSI) scan can be of great value in the study of several psychiatric and neurological disorders, yet its usability has been limited due to the long acquisition times required. A typical MSI scan involves acquiring a large number of gradient directions for the 2 (or more) spherical shells (several b-values), making the acquisition time significantly long for clinical application. In this work, we propose to use results from the theory of compressive sampling and determine the minimum number of gradient directions required to attain signal reconstruction similar to a traditional MSI scan. In particular, we propose a generalization of the single shell spherical ridgelets basis for sparse representation of multi shell signals. We demonstrate its efficacy on several synthetic and in-vivo data sets and perform quantitative comparisons with solid spherical harmonics based representation. Our preliminary results show that around 20-24 directions per shell are enough for robustly recovering the diffusion propagator.

Despite the relative recency of its inception, the theory of compressive sampling (aka compressed sensing) (CS) has already revolutionized multiple areas of applied sciences, a particularly important instance of which is medical imaging. Specifically, the theory has provided a different perspective on the important problem of optimal sampling in magnetic resonance imaging (MRI), with an ever-increasing body of works reporting stable and accurate reconstruction of MRI scans from the number of spectral measurements which would have been deemed unacceptably small as recently as five years ago. In this paper, the theory of CS is employed to palliate the problem of long acquisition times, which is known to be a major impediment to the clinical application of high angular resolution diffusion imaging (HARDI). Specifically, we demonstrate that a substantial reduction in data acquisition times is possible through minimization of the number of diffusion encoding gradients required for reliable reconstruction of HARDI scans. The success of such a minimization is primarily due to the availability of spherical ridgelet transformation, which excels in sparsifying HARDI signals. What makes the resulting reconstruction procedure even more accurate is a combination of the sparsity constraints in the diffusion domain with additional constraints imposed on the estimated diffusion field in the spatial domain. Accordingly, the present paper describes an original way to combine the diffusion- and spatial-domain constraints to achieve a maximal reduction in the number of diffusion measurements, while sacrificing little in terms of reconstruction accuracy. Finally, details are provided on an efficient numerical scheme which can be used to solve the aforementioned reconstruction problem by means of standard and readily available estimation tools. The paper is concluded with experimental results which support the practical value of the proposed reconstruction methodology.

BACKGROUND: Cigarette smoking is associated with emphysema and radiographic interstitial lung abnormalities. The degree to which interstitial lung abnormalities are associated with reduced total lung capacity and the extent of emphysema is not known. METHODS: We looked for interstitial lung abnormalities in 2416 (96%) of 2508 high-resolution computed tomographic (HRCT) scans of the lung obtained from a cohort of smokers. We used linear and logistic regression to evaluate the associations between interstitial lung abnormalities and HRCT measurements of total lung capacity and emphysema. RESULTS: Interstitial lung abnormalities were present in 194 (8%) of the 2416 HRCT scans evaluated. In statistical models adjusting for relevant covariates, interstitial lung abnormalities were associated with reduced total lung capacity (-0.444 liters; 95% confidence interval [CI], -0.596 to -0.292; P

RATIONALE AND OBJECTIVES: The relationship between chronic obstructive pulmonary disease (COPD) and atherosclerosis has been suggested; this association may relate to systemic inflammation and endothelial dysfunction, which can lead to alteration of small pulmonary vessels. The relationship between atherosclerosis and small pulmonary vessel alteration, however, has not been assessed in COPD patients. We tested the hypothesis that the severity of thoracic aortic calcification measured by computed tomography (CT) would be associated with the total cross-sectional area of small pulmonary vessels (CSA) on CT images. MATERIALS AND METHODS: The study was approved by the institutional review board and was Health Insurance Portability and Accountability Act-compliant. Informed consent was waived. For 51 COPD patients enrolled in the National Heart, Lung, and Blood Institute Lung Tissue Research Consortium, we calculated the percentage of total CSAs of less than 5 mm² for the total lung area (%CSA

We describe a technique that uses tractography to visualize neural pathways in human brains by extending an existing framework that uses overlapping Gaussian tensors to model the signal. At each point on the fiber, an unscented Kalman filter is used to find the most consistent direction as a mixture of previous estimates and of the local model. In our previous framework, the diffusion ellipsoid had a cylindrical shape, i.e., the diffusion tensor’s second and third eigenvalues were identical. In this paper, we extend the tensor representation so that the diffusion tensor is represented by an arbitrary ellipsoid. Experiments on synthetic data show a reduction in the angular error at fiber crossings and branchings. Tests on in vivo data demonstrate the ability to trace fibers in areas containing crossings or branchings, and the tests also confirm the superiority of using a full tensor representation over the simplified model.

Background Cigarette smoking is a major risk factor for chronic obstructive pulmonary disease (COPD) and COPD severity. Previous genome-wide association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) associated with the number of cigarettes smoked per day (CPD) and a dopamine beta-hydroxylase (DBH) locus associated with smoking cessation in multiple populations. Objective To identify SNPs associated with lifetime average and current CPD, age at smoking initiation, and smoking cessation in patients with COPD. Methods GWAS were conducted in four independent cohorts encompassing 3441 ever-smoking patients with COPD (Global Initiative for Obstructive Lung Disease stage II or higher). Untyped SNPs were imputed using the HapMap (phase II) panel. Results from all cohorts were meta-analysed. Results Several SNPs near the HLA region on chromosome 6p21 and in an intergenic region on chromosome 2q21 showed associations with age at smoking initiation, both with the lowest p=2×10(-7). No SNPs were associated with lifetime average CPD, current CPD or smoking cessation with p

RATIONALE AND OBJECTIVES: To evaluate the correlations of tracheal volume and collapsibility on inspiratory and end-expiratory computed tomography (CT) with lung volume and with lung function in smokers. MATERIALS AND METHODS: The institutional review board approved this study at each institution. 85 smokers (mean age 68, range 45-87 years; 40 females and 45 males) underwent pulmonary function tests and chest CT at full inspiration and end-expiration. On both scans, intrathoracic tracheal volume and lung volume were measured. Collapsibility of the trachea and the lung was expressed as expiratory/inspiratory (E/I) ratios of these volumes. Correlations of the tracheal measurements with the lung measurements and with lung function were evaluated by the linear regression analysis.

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