Publications (16)22.22 Total impact
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Article: Prognostic value of adenosine stress cardiovascular magnetic resonance and dobutamine stress echocardiography in patients with low-risk chest pain.
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ABSTRACT: Excluding obstructive coronary artery disease (CAD) as the etiology of acute chest pain in patients without diagnostic electrocardiographic changes or elevated serum cardiac biomarkers is challenging. Stress testing is a valuable risk-stratifying technique reserved for the subset of these patients with low-risk chest pain who have an intermediate clinical probability of obstructive CAD. Given the risks of radiation inherent to nuclear and computed tomography imaging, both adenosine stress cardiovascular magnetic resonance (AS-CMR) imaging and dobutamine stress echocardiography (DSE) are attractive alternative stress modalities. An essential characteristic of stress modalities is their negative prognostic value; as one must exclude clinically-relevant CAD such that patients can be discharged safely. Therefore, the aim of this study was to validate a favorable negative prognostic value for both AS-CMR and DSE in patients presenting with low-risk acute chest pain. This retrospective study included 255 patients with low-risk acute chest pain and no prior history of CAD presenting to the emergency department at our institution, with 89 patients evaluated by AS-CMR and 166 by DSE. Median follow-up was 292 days, and consisted of medical record review. The primary end-point was the composite of cardiac death, nonfatal acute myocardial infarction, obstructive CAD on invasive coronary angiography (ICA) or recurrent chest pain requiring hospital admission. Test characteristics such as sensitivity and specificity could not be evaluated as patients were not routinely evaluated with ICA. All patients completed the stress protocol without adverse events during testing. 82/89 patients (92.1%) and 164/166 patients (98.8%) had negative AS-CMR and DSE studies, respectively. Both AS-CMR and DSE had excellent negative prognostic values for the primary endpoint, 100 and 99%, respectively. Both AS-CMR and DSE are effective stress modalities for excluding clinically significant coronary artery disease in patients presenting acute low-risk chest pain. Patients without findings to suggest ischemia have an excellent intermediate-term prognosis.The international journal of cardiovascular imaging 05/2011; 28(4):803-12. · 2.15 Impact Factor -
Article: Estimation of Myocardial Volume at Risk from CT Angiography.
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ABSTRACT: The determination of myocardial volume at risk distal to coronary stenosis provides important information for prognosis and treatment of coronary artery disease. In this paper, we present a novel computational framework for estimating the myocardial volume at risk in computed tomography angiography (CTA) imagery. Initially, epicardial and endocardial surfaces, and coronary arteries are extracted using an active contour method. Then, the extracted coronary arteries are projected onto the epicardial surface, and each point on this surface is associated with its closest coronary artery using the geodesic distance measurement. The likely myocardial region at risk on the epicardial surface caused by a stenosis is approximated by the region in which all its inner points are associated with the sub-branches distal to the stenosis on the coronary artery tree. Finally, the likely myocardial volume at risk is approximated by the volume in between the region at risk on the epicardial surface and its projection on the endocardial surface, which is expected to yield computational savings over risk volume estimation using the entire image volume. Furthermore, we expect increased accuracy since, as compared to prior work using the Euclidean distance, we employ the geodesic distance in this work. The experimental results demonstrate the effectiveness of the proposed approach on pig heart CTA datasets.Proc SPIE 03/2011; 7963:79632A-79632A6. -
Article: A case of a rare coronary artery anomaly.
The international journal of cardiovascular imaging 08/2010; 26(6):621-3. · 2.15 Impact Factor -
Article: Use of cardiac MRI for low gradient aortic stenosis
Journal of Cardiovascular Magnetic Resonance. 01/2010; -
Article: Absent coronary artery calcium excludes inducible myocardial ischemia on computed tomography/positron emission tomography.
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ABSTRACT: We set out to determine whether a coronary artery calcium (CAC) score of zero on computed tomography (CT) would predict a normal myocardial perfusion positron emission tomography (PET) in a population mostly at intermediate pretest likelihood of coronary artery disease (CAD). We enrolled 206 outpatients (36% men, mean age 60 ± 13 years) referred for Rb-82 myocardial perfusion PET/CT for suspected CAD. CAC scoring was performed by the Agatston method. The PET images were scored on a 5-point scale using a 17-segment left ventricular model. A summed stress score ≥ 2 was considered abnormal. Multivariable logistic regression analysis was used to test the independent predictive value of a CAC score of zero to exclude inducible myocardial ischemia. Ninety-nine of 206 patients (48%) had a CAC score of zero and of these only 1 had inducible ischemia on PET. This yielded a negative predictive value of 99% (95% CI 95%-100%). CAC score of zero was the strongest independent predictor of a normal myocardial perfusion PET (OR = 0.05; 95% CI = 0.006-0.38; p = 0.004). In a population of predominately intermediate likelihood of CAD, a CAC score of zero excludes inducible ischemia on myocardial perfusion PET.International journal of cardiology 11/2009; 147(3):424-7. · 7.08 Impact Factor -
Article: Prognostic value of adenosine stress cardiovascular magnetic resonance in patients with low-risk chest pain.
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ABSTRACT: Approximately 5% of patients with an acute coronary syndrome are discharged from the emergency room with an erroneous diagnosis of non-cardiac chest pain. Highly accurate non-invasive stress imaging is valuable for assessment of low-risk chest pain patients to prevent these errors. Adenosine stress cardiovascular magnetic resonance (AS-CMR) is an imaging modality with increasing application. The goal of this study was to evaluate the negative prognostic value of AS-CMR among low-risk acute chest pain patients. We studied 103 patients, mean 56.7 + or - 12.3 years of age, with chest pain and no electrocardiographic evidence of ischemia and negative cardiac biomarkers of necrosis, who were admitted to the Cardiac Decision Unit of our institution. All patients underwent AS-CMR. A negative AS-CMR was defined as absence of all the following: regional wall motion abnormalities at rest; perfusion defects during stress (adenosine) and rest; and myocardial scar on late gadolinium enhancement images. The patients were followed for a mean of 277 (range 161-462) days. The primary end point was defined as the combination of cardiac death, nonfatal acute myocardial infarction, re-hospitalization for chest pain, obstructive coronary artery disease (>50% coronary stenosis on invasive angiography) and coronary revascularization. In 14 patients (13.6%), AS-CMR was positive. The remaining 89 patients (86.4%), who had negative AS-CMR, were discharged. No patient with negative AS-CMR reached the primary end-point during follow-up. The negative predictive value of AS-CMR was 100%. AS-CMR holds promise as a useful tool to rule out significant coronary artery disease in patients with low-risk chest pain. Patients with negative AS-CMR have an excellent short and mid-term prognosis.Journal of Cardiovascular Magnetic Resonance 09/2009; 11:37. · 3.72 Impact Factor -
Article: Reproducibility of aortic pulse wave velocity measurements obtained with Phase Contrast Magnetic Resonance (PCMR) and applanation tonometry
Journal of Cardiovascular Magnetic Resonance. 01/2009; -
Article: Adenosine magnetic resonance imaging versus dobutamine stress echocardiography in patients with low probability for coronary artery disease
Journal of Cardiovascular Magnetic Resonance. 01/2009; -
Article: 310 Cross correlation on 2D PCMR velocity data to determine aortic pulse wave velocity
Journal of Cardiovascular Magnetic Resonance. 01/2008; -
Article: Coronary vessel trees from 3D imagery: a topological approach.
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ABSTRACT: We propose a simple method for reconstructing vascular trees from 3D images. Our algorithm extracts persistent maxima of the intensity on all axis-aligned 2D slices of the input image. The maxima concentrate along 1D intensity ridges, in particular along blood vessels. We build a forest connecting the persistent maxima with short edges. The forest tends to approximate the blood vessels present in the image, but also contains numerous spurious features and often fails to connect segments belonging to one vessel in low contrast areas. We improve the forest by applying simple geometric filters that trim short branches, fill gaps in blood vessels and remove spurious branches from the vascular tree to be extracted. Experiments show that our technique can be applied to extract coronary trees from heart CT scans.Medical Image Analysis 09/2006; 10(4):548-59. · 4.42 Impact Factor -
Article: Analysis of Myocardial Perfusion Imaging
Journal of Magnetic Resonance Imaging 06/2004; 19(6):758-70. · 2.70 Impact Factor -
Article: Vessel Segmentation with Automatic Centerline Extraction Using Tubular Tree Segmentation
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ABSTRACT: Presented at CI2BM09 - MICCAI Workshop on Cardiovascular Interventional Imaging and Biophysical Modelling, London, UK, September 20, 2009. The study of the coronary vessel structure is crucial to the diagnosis of atherosclerosis and other cardiovascular diseases, which together account for about 35% of all deaths in the United States per year. Vessel Segmentation from CTA data is challenging because of non-uniform image intensity along the vessel, and the branching and thinning geometry of the vessel tree. We present a novel method for vessel extraction that models the vasculature as a tubular tree and individual vessels as 3D tubes. We create an initial tube from a few seed points within the vessel tree, and then evolve this initial tube using a variational energy optimization approach to capture the vessel while automatically detecting branches in the vessel tree. A significant advantage of our proposed framework is that the center-line of the blood vessel tree, which is useful in defining cross sectional area of the vessel and evaluating stenoses, is detected automatically as the tubular tree evolves. Existing approaches on the other hand need an explicit step for skeletonization of the vessel volume after segmentation. Another benefit is that the parent-child relationships between branches are also automatically obtained, which is useful in fly-through visualization as well as clinical reporting. -
Article: Total-variational-based optical flow for cardiac-wall motion tracking
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ABSTRACT: ©2001 SPIE--The International Society for Optical Engineering. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited. The electronic version of this article is the complete one and can be found online at: http://dx.doi.org/10.1117/12.431038 DOI: 10.1117/12.431038 In this note, we apply an L¹ based approach to optical flow to measure heart wall motions. Our method captures discontinuities and sudden changes in the flow field much better than conventional quadratic gradient approaches. -
Article: Soft Plaque Detection and Automatic Vessel Segmentation
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ABSTRACT: The ability to detect and measure non-calcified plaques (also known as soft plaques) may improve physicians’ ability to predict cardiac events. This is a particularly challenging problem in computed tomography angiography (CTA) imagery because plaques may have similar appearance to nearby blood and muscle tissue. This paper presents an effective technique for automatically detecting soft plaques in CTA imagery using active contours driven by spatially localized probabilistic models. The proposed method identifies plaques that exist within the vessel wall by simultaneously segmenting the vessel from the inside-out and the outside-in using carefully chosen localized energies that allow the complex appearances of plaques and vessels to be modeled with simple statistics. This method is shown to be an effective way to detect the minute variations that distinguish plaques from healthy tissue. Experiments demonstrating the effectiveness of the algorithm are performed on eight datasets, and results are compared with detections provided by an expert cardiologist. Presented at PMMIA 2009: Probabilistic Models For Medical Image Analysis: A MICCAI 2009 Workshop, September 20th, 2009 Imperial College, London, UK -
Article: 3D Models of Airway Trees from CT Scans: A Point-Based Approach
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ABSTRACT: We propose an algorithm for building 3D models of the airway tree from Computed Tomographic (CT) images. Our procedure first computes a set of core points that tend to concentrate along the centerlines of the airway tree branches. This point set, after a filtering step, is used to build a set of wall points that concentrate on the walls of the airways. Finally, a triangulated surface is build from the wall points using a Delaunay-based reconstruction procedure. -
Article: Automatic Segmentation of Coronary Arteries Using Bayesian Driven Implicit Surfaces
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ABSTRACT: ©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. Presented at the 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, April 12-15, 2007, Crystal Gateway Marriott, Arlington, Virginia, USA. DOI: 10.1109/ISBI.2007.356820 In this paper, we propose a hybrid approach for the automatic three-dimensional segmentation of coronary arteries using multi-scale vessel filtering and a Bayesian probabilistic approach in a level set image segmentation framework. The initial surface of the coronaries is obtained from the multiscale vessel filter response, and the surface then evolves to capture the exact boundary of the coronaries according to an improved evolution model of implicit surfaces. In our model, the image force and the propagation terms are re-defined using posterior probabilities obtained via Bayes’ rule in order for the surface to approach to the boundaries faster and stop at the boundaries more accurately. The proposed method is tested on seven CT angiography (CTA) data-sets of left and right coronary arteries, and the quantitative comparison of our result against manually delineated contours on two of the data-sets yields a mean error of 0.37mm.
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2010
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Emory University
Atlanta, GA, USA
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