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® 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.

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.

Accurate automatic analysis of cardiac cine images.

Acquisition of noncontrast agent cine cardiac magnetic resonance (CMR) gated images through the cardiac cycle is, at present, a well-established part of examining cardiac global function. However, regional quantification is less well established. We propose a new automated framework for analyzing the wall thickness and thickening function on these images that consists of three main steps. First, inner and outer wall borders are segmented from their surrounding tissues with a geometric deformable model guided by a special stochastic speed relationship. The latter accounts for Markov-Gibbs shape and appearance models of the object-of-interest and its background. In the second step, point-to-point correspondences between the inner and outer borders are found by solving the Laplace equation and provide initial estimates of the local wall thickness and the thickening function index. Finally, the effects of the segmentation error is reduced and a continuity analysis of the LV wall thickening is performed through iterative energy minimization using a generalized Gauss-Markov random field (GGMRF) image model. The framework was evaluated on 26 datasets from clinical cine CMR images that have been collected from patients with eleven independent studies, with chronic ischemic heart disease and heart damage. The performance evaluation of the proposed segmentation approach, based on the receiver operating characteristic (ROC) and Dice similarity coefficients (DSC) between manually drawn and automatically segmented contours, confirmed a high robustness and accuracy of the proposed segmentation approach. Furthermore, the Bland-Altman plot is used to assess the limit of agreement of our measurements of the global function parameters compared to the ground truth. Importantly, comparative results on the publicly available database (MICCAI 2009 Cardiac MR Left Ventricle Segmentation) demonstrated a superior performance of the proposed segmentation approach over published methods.

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.

Cardiac stem cells in patients with ischaemic cardiomyopathy (SCIPIO): initial results of a randomised phase 1 trial.

BACKGROUND: c-kit-positive, lineage-negative cardiac stem cells (CSCs) improve post-infarction left ventricular (LV) dysfunction when administered to animals. We undertook a phase 1 trial (Stem Cell Infusion in Patients with Ischemic cardiOmyopathy [SCIPIO]) of autologous CSCs for the treatment of heart failure resulting from ischaemic heart disease. METHODS: In stage A of the SCIPIO trial, patients with post-infarction LV dysfunction (ejection fraction [EF] ≤40%) before coronary artery bypass grafting were consecutively enrolled in the treatment and control groups. In stage B, patients were randomly assigned to the treatment or control group in a 2:3 ratio by use of a computer-generated block randomisation scheme. 1 million autologous CSCs were administered by intracoronary infusion at a mean of 113 days (SE 4) after surgery; controls were not given any treatment. Although the study was open label, the echocardiographic analyses were masked to group assignment. The primary endpoint was short-term safety of CSCs and the secondary endpoint was efficacy. A per-protocol analysis was used. This study is registered with ClinicalTrials.gov, number NCT00474461. FINDINGS: This study is still in progress. 16 patients were assigned to the treatment group and seven to the control group; no CSC-related adverse effects were reported. In 14 CSC-treated patients who were analysed, LVEF increased from 30·3% (SE 1·9) before CSC infusion to 38·5% (2·8) at 4 months after infusion (p=0·001). By contrast, in seven control patients, during the corresponding time interval, LVEF did not change (30·1% [2·4] at 4 months after CABG vs 30·2% [2·5] at 8 months after CABG). Importantly, the salubrious effects of CSCs were even more pronounced at 1 year in eight patients (eg, LVEF increased by 12·3 ejection fraction units [2·1] vs baseline, p=0·0007). In the seven treated patients in whom cardiac MRI could be done, infarct size decreased from 32·6 g (6·3) by 7·8 g (1·7; 24%) at 4 months (p=0·004) and 9·8 g (3·5; 30%) at 1 year (p=0·04). INTERPRETATION: These initial results in patients are very encouraging. They suggest that intracoronary infusion of autologous CSCs is effective in improving LV systolic function and reducing infarct size in patients with heart failure after myocardial infarction, and warrant further, larger, phase 2 studies. FUNDING: University of Louisville Research Foundation and National Institutes of Health.

3D kidney segmentation from CT images using a level set approach guided by a novel stochastic speed function.

Kidney segmentation is a key step in developing any noninvasive computer-aided diagnosis (CAD) system for early detection of acute renal rejection. This paper describes a new 3-D segmentation approach for the kidney from computed tomography (CT) images. The kidney borders are segmented from the surrounding abdominal tissues with a geometric deformable model guided by a special stochastic speed relationship. The latter accounts for a shape prior and appearance features in terms of voxel-wise image intensities and their pair-wise spatial interactions integrated into a two-level joint Markov-Gibbs random field (MGRF) model of the kidney and its background. The segmentation approach was evaluated on 21 CT data sets with available manual expert segmentation. The performance evaluation based on the receiver operating characteristic (ROC) and Dice similarity coefficient (DSC) between manually drawn and automatically segmented contours confirm the robustness and accuracy of the proposed segmentation approach.

Fast method for correcting image misregistration due to organ motion in time-series MRI data.

Time-series MRI data often suffers from image misalignment due to patient movement and respiratory and other physiologic motion during the acquisition process. It is necessary that this misalignment be corrected prior to any automated quantitative analysis. In this article a fast and automated technique for removing in-plane misalignment from time-series MRI data is presented. The method is computationally efficient, robust, and fine-tuned for the clinical setting. The method was implemented and tested on data from 21 human subjects, including myocardial perfusion imaging, renal perfusion imaging, and blood-oxygen level-dependent cardiac T(2*) imaging. In these applications 10-fold or better reduction in image misalignment is reported. The improvement after registration on representative time-intensity curves is shown. Although the method currently corrects translation motion using image center of mass, the mathematical framework of our approach may be extended to correct rotation and other higher-order displacements.