Microvascular vasoregulatory dysfunction in African Americans - An enhanced opportunity for early prevention and treatment of atherosclerotic cardiovascular disease.

Atherosclerotic cardiovascular disease and its risk factors and precursors are a major driver of disparities in cardiovascular health. This review examines reported evidence that vascular endothelial dysfunction, and its manifestation as coronary microvascular dysfunction, underlies observed excess morbidity and mortality in African Americans. Advanced imaging insights that reveal patho-mechanisms, along with population evidence from the Jackson Heart Study, and the growing evidence emanating from national and international clinical trials and registries are presented. We examine a physiological framework that recognizes insulin-resistant cardiometabolic underpinnings of the conditions of the American Heart Associations' Life's Essential Eight construct of cardiovascular health as a unifying basis that affords early prevention. Mechanistic-based therapeutic approaches, can subsequently be implemented to interrupt progression to adverse outcomes employing layered, or personalized, treatment strategies of a well-defined set of conditions or diseases. Remaining knowledge gaps are acknowledged.

ACR Appropriateness Criteria® Suspected Acute Aortic Syndrome.

Acute aortic syndrome (AAS) includes the entities of acute aortic dissection, intramural hematoma, and penetrating atherosclerotic ulcer. AAS typically presents with sudden onset of severe, tearing, anterior, or interscapular back pain. Symptoms may be dominated by malperfusion syndrome, due to obstruction of the lumen of the aorta and/or a side branch when the intimal and medial layers are separated. Timely diagnosis of AAS is crucial to permit prompt management; for example, early mortality rates are reported to be 1% to 2% per hour after the onset of symptoms for untreated ascending aortic dissection. The appropriateness assigned to each imaging procedure was based on the ability to obtain key information that is used to plan open surgical, endovascular, or medical therapy. This includes, but is not limited to, confirming the presence of AAS; classification; characterization of entry and reentry sites; false lumen patency; and branch vessel compromise. Using this approach, CT, CTA, and MRA are all considered usually appropriate in the initial evaluation of AAS if those procedures include intravenous contrast administration. Ultrasound is also considered usually appropriate if the acquisition is via a transesophageal approach. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

ACR Appropriateness Criteria® Asymptomatic Patient at Risk for Coronary Artery Disease: 2021 Update.

Coronary atherosclerotic disease is a leading cause of mortality and morbidity due to major cardiovascular events in the United States and abroad. Risk stratification and early preventive measures can reduce major cardiovascular events given the long latent asymptomatic period. Imaging tests can detect subclinical coronary atherosclerosis and aid initiation of targeted preventative efforts based on patient risk. A summary of available imaging tests for low-, intermediate-, and high-risk asymptomatic patients is outlined in this document. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

ACR Appropriateness Criteria® Infective Endocarditis.

Infective endocarditis can involve a normal, abnormal, or prosthetic cardiac valve. The diagnosis is typically made clinically with persistently positive blood cultures, characteristic signs and symptoms, and echocardiographic evidence of valvular vegetations or valvular complications such as abscess, dehiscence, or new regurgitation. Imaging plays an important role in the initial diagnosis of infective endocarditis, identifying complications, prognostication, and informing the next steps in therapy. This document outlines the initial imaging appropriateness of a patient with suspected infective endocarditis and for additional imaging in a patient with known or suspected infective endocarditis. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

ACR appropriateness criteria infective endocarditis

Infective endocarditis can involve a normal, abnormal, or prosthetic cardiac valve. The diagnosis is typically made clinically with persistently positive blood cultures, characteristic signs and symptoms, and echocardiographic evidence of valvular vegetations or valvular complications such as abscess, dehiscence, or new regurgitation. Imaging plays an important role in the initial diagnosis of infective endocarditis, identifying complications, prognostication, and informing the next steps in therapy. This document outlines the initial imaging appropriateness of a patient with suspected infective endocarditis and for additional imaging in a patient with known or suspected infective endocarditis. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

ACR appropriateness criteria asymptomatic patient at risk for coronary artery disease: 2021 update

Coronary atherosclerotic disease is a leading cause of mortality and morbidity due to major cardiovascular events in the United States and abroad. Risk stratification and early preventive measures can reduce major cardiovascular events given the long latent asymptomatic period. Imaging tests can detect subclinical coronary atherosclerosis and aid initiation of targeted preventative efforts based on patient risk. A summary of available imaging tests for low-, intermediate-, and high-risk asymptomatic patients is outlined in this document. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

ACR Appropriateness Criteria® Acute Nonspecific Chest Pain-Low Probability of Coronary Artery Disease.

Patients with acute nonspecific chest pain and low probability for coronary disease remain an important clinical management dilemma. We focus on evidence for imaging, in an integrated decision-making setting. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

ACR Appropriateness Criteria® Blunt Chest Trauma-Suspected Cardiac Injury.

Blunt cardiac injuries range from myocardial concussion (commotio cordis) leading to fatal ventricular arrhythmias to myocardial contusion, cardiac chamber rupture, septal rupture, pericardial rupture, and valvular injuries. Blunt injuries account for one-fourth of the traumatic deaths in the United States. Chest radiography, transthoracic echocardiography, CT chest with and without contrast, and CT angiography are usually appropriate as the initial examination in patients with suspected blunt cardiac injury who are both hemodynamically stable and unstable. Transesophageal echocardiography and CT heart may be appropriate as examination in patients with suspected blunt cardiac injuries. This publication of blunt chest trauma-suspected cardiac injuries summarizes the literature and makes recommendations for imaging based on the available data and expert opinion. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

A deep learning-based approach for automatic segmentation and quantification of the left ventricle from cardiac cine MR images.

Cardiac MRI has been widely used for noninvasive assessment of cardiac anatomy and function as well as heart diagnosis. The estimation of physiological heart parameters for heart diagnosis essentially require accurate segmentation of the Left ventricle (LV) from cardiac MRI. Therefore, we propose a novel deep learning approach for the automated segmentation and quantification of the LV from cardiac cine MR images. We aim to achieve lower errors for the estimated heart parameters compared to the previous studies by proposing a novel deep learning segmentation method. Our framework starts by an accurate localization of the LV blood pool center-point using a fully convolutional neural network (FCN) architecture called FCN1. Then, a region of interest (ROI) that contains the LV is extracted from all heart sections. The extracted ROIs are used for the segmentation of LV cavity and myocardium via a novel FCN architecture called FCN2. The FCN2 network has several bottleneck layers and uses less memory footprint than conventional architectures such as U-net. Furthermore, a new loss function called radial loss that minimizes the distance between the predicted and true contours of the LV is introduced into our model. Following myocardial segmentation, functional and mass parameters of the LV are estimated. Automated Cardiac Diagnosis Challenge (ACDC-2017) dataset was used to validate our framework, which gave better segmentation, accurate estimation of cardiac parameters, and produced less error compared to other methods applied on the same dataset. Furthermore, we showed that our segmentation approach generalizes well across different datasets by testing its performance on a locally acquired dataset. To sum up, we propose a deep learning approach that can be translated into a clinical tool for heart diagnosis.

ACR Appropriateness Criteria® Known or Suspected Congenital Heart Disease in the Adult.

The incidence of congenital heart disease (CHD) has been increasing in the adult patient population in part as a result of better patient survival. Patients with more severe CHD are living longer. Nearly all adults with known CHD require periodic imaging as a means of monitoring their disease process. Furthermore, adult patients with suspected CHD require imaging as a means of definitive diagnosis. As a result, it is important for both the referring clinician and the imager to be aware of the most appropriate imaging modality needed to obtain the data most needed to direct the next steps in patient care. Imaging procedures for the diagnosis of known or suspected CHD in the adult include chest radiography, fluoroscopy, echocardiography, nuclear scintigraphy, cardiac-gated CT, MRI, and cardiac catheterization/angiography. The physician trying to diagnose these often complex conditions needs complete and reliable information that includes details about intracardiac and vascular anatomy, hemodynamics, and function. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer-reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

ACR Appropriateness Criteria® Chronic Chest Pain-High Probability of Coronary Artery Disease.

In patients with chronic chest pain in the setting of high probability of coronary artery disease (CAD), imaging has major and diverse roles. First, imaging is valuable in determining and documenting the presence, extent, and severity of myocardial ischemia, hibernation, scarring, and/or the presence, site, and severity of obstructive coronary lesions. Second, imaging findings are important in determining the course of management of patients with suspected chronic myocardial ischemia and better defining those patients best suited for medical therapy, angioplasty/stenting, or surgery. Third, imaging is also necessary to determine the long-term prognosis and likely benefit from various therapeutic options by evaluating ventricular function, diastolic relaxation, and end-systolic volume. Imaging studies are also required to demonstrate other abnormalities, such as congenital/acquired coronary anomalies and severe left ventricular hypertrophy, that can produce angina in the absence of symptomatic coronary obstructive disease due to atherosclerosis. Clinical risk assessment is necessary to determine the pretest probability of CAD. Multiple methods are available to categorize patients as low, medium, or high risk for developing CAD. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

Intramyocardial strain estimation from cardiac cine MRI.

PURPOSE: Functional strain is one of the important clinical indicators for the quantification of heart performance and the early detection of cardiovascular diseases, and functional strain parameters are used to aid therapeutic decisions and follow-up evaluations after cardiac surgery. A comprehensive framework for deriving functional strain parameters at the endocardium, epicardium, and mid-wall of the left ventricle (LV) from conventional cine MRI data was developed and tested. METHODS: Cine data were collected using short TR-/TE-balanced steady-state free precession acquisitions on a 1.5T Siemens Espree scanner. The LV wall borders are segmented using a level set-based deformable model guided by a stochastic force derived from a second-order Markov-Gibbs random field model that accounts for the object shape and appearance features. Then, the mid-wall of the segmented LV is determined based on estimating the centerline between the endocardium and epicardium of the LV. Finally, a geometrical Laplace-based method is proposed to track corresponding points on successive myocardial contours throughout the cardiac cycle in order to characterize the strain evolutions. The method was tested using simulated phantom images with predefined point locations of the LV wall throughout the cardiac cycle. The method was tested on 30 in vivo datasets to evaluate the feasibility of the proposed framework to index functional strain parameters. RESULTS: The cine MRI-based model agreed with the ground truth for functional metrics to within 0.30 % for indexing the peak systolic strain change and 0.29 % (per unit time) for indexing systolic and diastolic strain rates. The method was feasible for in vivo extraction of functional strain parameters. CONCLUSION: Strain indexes of the endocardium, mid-wall, and epicardium can be derived from routine cine images using automated techniques, thereby improving the utility of cine MRI data for characterization of myocardial function. Unlike traditional texture-based tracking, the proposed geometrical method showed the ability to track the LV wall points throughout the cardiac cycle, thus permitting more accurate strain estimation.

Fully automated framework for the analysis of myocardial first-pass perfusion MR images.

PURPOSE: To develop an automated framework for accurate analysis of myocardial perfusion using first-pass magnetic resonance imaging. METHODS: The proposed framework consists of four processing stages. First, in order to account for heart deformations due to respiratory motion and heart contraction, a two-step registration methodology is proposed, which has the ability to account for the global and local motions of the heart. The methodology involves an affine-based registration followed by a local B-splines alignment to maximize a new similarity function based on the first- and second-order normalized mutual information. Then the myocardium is segmented using a level-set function, its evolution being constrained by three features, namely, a weighted shape prior, a pixelwise mixed object/background image intensity distribution, and an energy of a second-order binary Markov-Gibbs random field spatial model. At the third stage, residual segmentation errors and imperfection of image alignment are reduced by employing a Laplace-based registration refinement step that provides accurate pixel-on-pixel matches on all segmented frames to generate accurate parametric perfusion maps. Finally, physiology is characterized by pixel-by-pixel mapping of empirical indexes (peak signal intensity, time-to-peak, initial upslope, and the average signal change of the slowly varying agent delivery phase), based on contrast agent dynamics. RESULTS: The authors tested our framework on 24 perfusion data sets from 8 patients with ischemic damage who are undergoing a novel myoregeneration therapy. The performance of the processing steps of our framework is evaluated using both synthetic and in-vivo data. First, our registration methodology is evaluated using realistic synthetic phantoms and a distance-based error metric, and an improvement of registration is documented using the proposed similarity measure (P-value ≤10(-4)). Second, evaluation of our segmentation using the Dice similarity coefficient, documented an average of 0.910 ± 0.037 compared to two other segmentation methods that achieved average values of 0.862 ± 0.045 and 0.844 ± 0.047. Also, the receiver operating characteristic (ROC) analysis of our multifeature segmentation yielded an area under the ROC curve of 0.92, while segmentation based intensity alone showed low performance (an area of 0.69). Moreover, our framework indicated the ability, using empirical perfusion indexes, to reveal regional perfusion improvements with therapy and transmural perfusion differences across the myocardial wall. CONCLUSIONS: By quantitative and visual assessment, our framework documented the ability to characterize regional and transmural perfusion, thereby it augmenting the ability to assess follow-up treatment for patients undergoing myoregeneration therapy. This is afforded by our framework being able to handle both global and local deformations of the heart, segment accurately the myocardial wall, and provide accurate pixel-on-pixel matches of registered perfusion images.

Myocardial borders segmentation from cine MR images using bidirectional coupled parametric deformable models.

PURPOSE: The authors propose 3D (2D + time) novel, fast, robust, bidirectional coupled parametric deformable models that are capable of segmenting left ventricle (LV) wall borders using first- and second-order visual appearance features. The authors examine the effect of the proposed segmentation method on the estimation of global cardiac performance indexes. METHODS: First-order visual appearance of the cine cardiac magnetic resonance (CMR) signals (inside and outside the boundary of the deformable model) is modeled with an adaptive linear combination of discrete Gaussians (LCDG). Second-order visual appearance of the LV wall is accurately modeled with a translational and rotation-invariant second-order Markov-Gibbs random field (MGRF). The LCDG parameters are estimated using our previously proposed modification of the EM algorithm, and the potentials of rotationally invariant MGRF are computed analytically. RESULTS: The authors tested the proposed segmentation approach on 15 cine CMR data sets using the Dice similarity coefficient (DSC) and the average distance (AD) between the ground truth and automated segmentation contours. The authors documented an average DSC value of 0.926 ± 0.022 and an average AD value of 2.16 ± 0.60 mm compared to two other level set methods that achieve an average DSC values of 0.904 ± 0.033 and 0.885 ± 0.02; and an average AD values of 2.86 ± 1.35 mm and 5.72 ± 4.70 mm, respectively. CONCLUSIONS: The proposed segmentation approach demonstrated superior performance over other methods. Specifically, the comparative results on the publicly available MICCAI 2009 Cardiac MR Left Ventricle Segmentation database documented superior performance of the proposed approach over published methods. Additionally, the high accuracy of our segmentation approach leads to accurate estimation of the global performance indexes, as evidenced by the Bland-Altman analyses of the end-systolic volume (ESV), end-diastolic volume (EDV), and the ejection fraction (EF) ratio.

Dynamic contrast-enhanced MRI-based early detection of acute renal transplant rejection.

A novel framework for the classification of acute rejection versus nonrejection status of renal transplants from 2-D dynamic contrast-enhanced magnetic resonance imaging is proposed. The framework consists of four steps. First, kidney objects are segmented from adjacent structures with a level set deformable boundary guided by a stochastic speed function that accounts for a fourth-order Markov-Gibbs random field model of the kidney/background shape and appearance. Second, a Laplace-based nonrigid registration approach is used to account for local deformations caused by physiological effects. Namely, the target kidney object is deformed over closed, equispaced contours (iso-contours) to closely match the reference object. Next, the cortex is segmented as it is the functional kidney unit that is most affected by rejection. To characterize rejection, perfusion is estimated from contrast agent kinetics using empirical indexes, namely, the transient phase indexes (peak signal intensity, time-to-peak, and initial up-slope), and a steady-phase index defined as the average signal change during the slowly varying tissue phase of agent transit. We used a kn-nearest neighbor classifier to distinguish between acute rejection and nonrejection. Performance of our method was evaluated using the receiver operating characteristics (ROC). Experimental results in 50 subjects, using a combinatoric kn-classifier, correctly classified 92% of training subjects, 100% of the test subjects, and yielded an area under the ROC curve that approached the ideal value. Our proposed framework thus holds promise as a reliable noninvasive diagnostic tool.

Computer-aided diagnosis systems for lung cancer: challenges and methodologies.

This paper overviews one of the most important, interesting, and challenging problems in oncology, the problem of lung cancer diagnosis. Developing an effective computer-aided diagnosis (CAD) system for lung cancer is of great clinical importance and can increase the patient's chance of survival. For this reason, CAD systems for lung cancer have been investigated in a huge number of research studies. A typical CAD system for lung cancer diagnosis is composed of four main processing steps: segmentation of the lung fields, detection of nodules inside the lung fields, segmentation of the detected nodules, and diagnosis of the nodules as benign or malignant. This paper overviews the current state-of-the-art techniques that have been developed to implement each of these CAD processing steps. For each technique, various aspects of technical issues, implemented methodologies, training and testing databases, and validation methods, as well as achieved performances, are described. In addition, the paper addresses several challenges that researchers face in each implementation step and outlines the strengths and drawbacks of the existing approaches for lung cancer CAD systems.

Administration of cardiac stem cells in patients with ischemic cardiomyopathy: the SCIPIO trial: surgical aspects and interim analysis of myocardial function and viability by magnetic resonance.

BACKGROUND: SCIPIO is a first-in-human, phase 1, randomized, open-label trial of autologous c-kit(+) cardiac stem cells (CSCs) in patients with heart failure of ischemic etiology undergoing coronary artery bypass grafting (CABG). In the present study, we report the surgical aspects and interim cardiac magnetic resonance (CMR) results. METHODS AND RESULTS: A total of 33 patients (20 CSC-treated and 13 control subjects) met final eligibility criteria and were enrolled in SCIPIO. CSCs were isolated from the right atrial appendage harvested and processed during surgery. Harvesting did not affect cardiopulmonary bypass, cross-clamp, or surgical times. In CSC-treated patients, CMR showed a marked increase in both LVEF (from 27.5 ± 1.6% to 35.1 ± 2.4% [P=0.004, n=8] and 41.2 ± 4.5% [P=0.013, n=5] at 4 and 12 months after CSC infusion, respectively) and regional EF in the CSC-infused territory. Infarct size (late gadolinium enhancement) decreased after CSC infusion (by manual delineation: -6.9 ± 1.5 g [-22.7%] at 4 months [P=0.002, n=9] and -9.8 ± 3.5 g [-30.2%] at 12 months [P=0.039, n=6]). LV nonviable mass decreased even more (-11.9 ± 2.5 g [-49.7%] at 4 months [P=0.001] and -14.7 ± 3.9 g [-58.6%] at 12 months [P=0.013]), whereas LV viable mass increased (+11.6 ± 5.1 g at 4 months after CSC infusion [P=0.055] and +31.5 ± 11.0 g at 12 months [P=0.035]). CONCLUSIONS: Isolation of CSCs from cardiac tissue obtained in the operating room is feasible and does not alter practices during CABG surgery. CMR shows that CSC infusion produces a striking improvement in both global and regional LV function, a reduction in infarct size, and an increase in viable tissue that persist at least 1 year and are consistent with cardiac regeneration. CLINICAL TRIAL REGISTRATION: This study is registered with clinicaltrials.gov, trial number NCT00474461.

New automated Markov-Gibbs random field based framework for myocardial wall viability quantification on agent enhanced cardiac magnetic resonance images.

A novel automated framework for detecting and quantifying viability from agent enhanced cardiac magnetic resonance images is proposed. The framework identifies the pathological tissues based on a joint Markov-Gibbs random field (MGRF) model that accounts for the 1st-order visual appearance of the myocardial wall (in terms of the pixel-wise intensities) and the 2nd-order spatial interactions between pixels. The pathological tissue is quantified based on two metrics: the percentage area in each segment with respect to the total area of the segment, and the trans-wall extent of the pathological tissue. This transmural extent is estimated using point-to-point correspondences based on a Laplace partial differential equation. Transmural extent was validated using a simulated phantom. We tested the proposed framework on 14 datasets (168 images) and validated against manual expert delineation of the pathological tissue by two observers. Mean Dice similarity coefficients (DSC) of 0.90 and 0.88 were obtained for the observers, approaching the ideal value, 1. The Bland-Altman statistic of infarct volumes estimated by manual versus the MGRF estimation revealed little bias difference, and most values fell within the 95% confidence interval, suggesting very good agreement. Using the DSC measure we documented statistically significant superior segmentation performance for our MGRF method versus established intensity-based methods (greater DSC, and smaller standard deviation). Our Laplace method showed good operating characteristics across the full range of extent of transmural infarct, outperforming conventional methods. Phantom validation and experiments on patient data confirmed the robustness and accuracy of the proposed framework.

Coronary artery fistula: 64-slice computed tomographic delineation and correlation with multiplane transesophageal echocardiography and surgical findings.

A 49-year-old female who presented with 3 weeks of exertional chest pain had an abnormal mediastinal finding at chest x-ray imaging. Conventional, nongated computed tomography of the chest revealed a "mass" in proximity to the right atrium. 64-slice, cardiac gated computed tomographic coronary angiography, and transesophageal echocardiography delineated the "mass" as a coronary artery fistula structure. The fistula originated from the left main as a tubular vessel that continued into an aneurysmal sac-like cavity that emptied into the superior vena cava near the right atrium. Computed tomographic coronary angiography showed otherwise normal coronary arteries. Findings were ultimately confirmed at cardiac catheterization. Coronary steal was clinically diagnosed and she underwent surgical ligation and resection of the fistula and aneurysm. Her subsequent course was uncomplicated.