A complete system for automatic extraction of left ventricular myocardium from CT images using shape segmentation and contour evolution.

The left ventricular myocardium plays a key role in the entire circulation system and an automatic delineation of the myocardium is a prerequisite for most of the subsequent functional analysis. In this paper, we present a complete system for an automatic segmentation of the left ventricular myocardium from cardiac computed tomography (CT) images using the shape information from images to be segmented. The system follows a coarse-to-fine strategy by first localizing the left ventricle and then deforming the myocardial surfaces of the left ventricle to refine the segmentation. In particular, the blood pool of a CT image is extracted and represented as a triangulated surface. Then, the left ventricle is localized as a salient component on this surface using geometric and anatomical characteristics. After that, the myocardial surfaces are initialized from the localization result and evolved by applying forces from the image intensities with a constraint based on the initial myocardial surface locations. The proposed framework has been validated on 34-human and 12-pig CT images, and the robustness and accuracy are demonstrated.

Automatic detection of left and right ventricles from CTA enables efficient alignment of anatomy with myocardial perfusion data.

BACKGROUND: Accurate alignment between cardiac CT angiographic studies (CTA) and nuclear perfusion images is crucial for improved diagnosis of coronary artery disease. This study evaluated in an animal model the accuracy of a CTA fully automated biventricular segmentation algorithm, a necessary step for automatic and thus efficient PET/CT alignment. METHODS AND RESULTS: Twelve pigs with acute infarcts were imaged using Rb-82 PET and 64-slice CTA. Post-mortem myocardium mass measurements were obtained. Endocardial and epicardial myocardial boundaries were manually and automatically detected on the CTA and both segmentations used to perform PET/CT alignment. To assess the segmentation performance, image-based myocardial masses were compared to experimental data; the hand-traced profiles were used as a reference standard to assess the global and slice-by-slice robustness of the automated algorithm in extracting myocardium, LV, and RV. Mean distances between the automated and the manual 3D segmented surfaces were computed. Finally, differences in rotations and translations between the manual and automatic surfaces were estimated post-PET/CT alignment. The largest, smallest, and median distances between interactive and automatic surfaces averaged 1.2 ± 2.1, 0.2 ± 1.6, and 0.7 ± 1.9 mm. The average angular and translational differences in CT/PET alignments were 0.4°, -0.6°, and -2.3° about x, y, and z axes, and 1.8, -2.1, and 2.0 mm in x, y, and z directions. CONCLUSIONS: Our automatic myocardial boundary detection algorithm creates surfaces from CTA that are similar in accuracy and provide similar alignments with PET as those obtained from interactive tracing. Specific difficulties in a reliable segmentation of the apex and base regions will require further improvements in the automated technique.

Post-traumatic stress disorder and incidence of coronary heart disease: a twin study.

OBJECTIVES: The aim of this study was to determine whether post-traumatic stress disorder (PTSD) is associated with coronary heart disease (CHD) using a prospective twin study design and objective measures of CHD. BACKGROUND: It has long been hypothesized that PTSD increases the risk of CHD, but empirical evidence using objective measures is limited. METHODS: We conducted a prospective study of middle-aged male twins from the Vietnam Era Twin Registry. Among twin pairs without self-reported CHD at baseline, we selected pairs discordant for a lifetime history of PTSD, pairs discordant for a lifetime history of major depression, and pairs without either condition. All underwent a clinic visit after a median follow-up of 13 years. Outcomes included clinical events (myocardial infarction, other hospitalizations for CHD and coronary revascularization) and quantitative measures of myocardial perfusion by [(13)N] ammonia positron emission tomography, including a stress total severity score and coronary flow reserve. RESULTS: A total of 562 twins (281 pairs) with a mean age of 42.6 years at baseline were included in this study. The incidence of CHD was more than double in twins with PTSD (22.6%) than in those without PTSD (8.9%; p < 0.001). The association remained robust after adjusting for lifestyle factors, other risk factors for CHD, and major depression (odds ratio: 2.2; 95% confidence interval: 1.2 to 4.1). Stress total severity score was significantly higher (+95%, p = 0.001) and coronary flow reserve was lower (-0.21, p = 0.02) in twins with PTSD than in those without PTSD, denoting worse myocardial perfusion. Associations were only mildly attenuated in 117 twin pairs discordant for PTSD. CONCLUSIONS: Among Vietnam-era veterans, PTSD is a risk factor for CHD.

Automatic delineation of the myocardial wall from CT images via shape segmentation and variational region growing.

Prognosis and diagnosis of cardiac diseases frequently require quantitative evaluation of the ventricle volume, mass, and ejection fraction. The delineation of the myocardial wall is involved in all of these evaluations, which is a challenging task due to large variations in myocardial shapes and image quality. In this paper, we present an automatic method for extracting the myocardial wall of the left and right ventricles from cardiac CT images. In the method, the left and right ventricles are located sequentially, in which each ventricle is detected by first identifying the endocardium and then segmenting the epicardium. To this end, the endocardium is localized by utilizing its geometric features obtained on-line from a CT image. After that, a variational region-growing model is employed to extract the epicardium of the ventricles. In particular, the location of the endocardium of the left ventricle is determined via using an active contour model on the blood-pool surface. To localize the right ventricle, the active contour model is applied on a heart surface extracted based on the left ventricle segmentation result. The robustness and accuracy of the proposed approach is demonstrated by experimental results from 33 human and 12 pig CT images.

An automatic alignment tool to improve repeatability of left ventricular function and dyssynchrony parameters in serial gated myocardial perfusion SPECT studies.

OBJECTIVE: Left ventricular (LV) function and dyssynchrony parameters measured from serial gated single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) using blinded processing had a poorer repeatability than when manual side-by-side processing was used. The objective of this study was to validate whether an automatic alignment tool can reduce the variability of LV function and dyssynchrony parameters in serial gated SPECT MPI. METHODS: Thirty patients who had undergone serial gated SPECT MPI were prospectively enrolled in this study. Thirty minutes after the first acquisition, each patient was repositioned and a gated SPECT MPI image was reacquired. The two data sets were first processed blinded from each other by the same technologist in different weeks. These processed data were then realigned by the automatic tool, and manual side-by-side processing was carried out. All processing methods used standard iterative reconstruction and Butterworth filtering. The Emory Cardiac Toolbox was used to measure the LV function and dyssynchrony parameters. RESULTS: The automatic tool failed in one patient, who had a large, severe scar in the inferobasal wall. In the remaining 29 patients, the repeatability of the LV function and dyssynchrony parameters after automatic alignment was significantly improved from blinded processing and was comparable to manual side-by-side processing. CONCLUSION: The automatic alignment tool can be an alternative method to manual side-by-side processing to improve the repeatability of LV function and dyssynchrony measurements by serial gated SPECT MPI.

Measurement of heritability of myocardial blood flow by positron emission tomography: the Twins Heart Study.

OBJECTIVE: To estimate the heritability of myocardial blood flow (MBF) and coronary flow reserve (CFR) measured with positron emission tomography (PET). DESIGN: Cross-sectional twin study. SETTING: General clinical research centre of a university hospital at Atlanta, USA. PATIENTS: A sample of 180 middle-aged (mean±SD 55±2.9 years) male twins, including 107 monozygotic and 73 dizygotic twins. MAIN OUTCOME MEASURES: All twins underwent imaging of MBF with PET (13)NH(3) at rest and after adenosine stress during a single imaging session. Structural equation modelling was used to estimate the heritability of MBF at rest and during adenosine stress, as well as of CFR. RESULTS: The basal MBF (mean±SD) was 0.69±0.20 ml/min/g, and the MBF during adenosine stress was 1.70±0.49 ml/min/g; the CFR was 2.62±0.99. There was substantial heritability for MBF both at rest (0.48, 95% CI 0.29 to 0.64) and during adenosine stress (0.51, 95% CI 0.29 to 0.68), as well as CFR (0.48, 95% CI 0.26 to 0.65). CONCLUSIONS: For the first time, a substantial genetic contribution to the interindividual variation in MBF and CFR measured with PET in middle-aged men has been demonstrated. The data suggest that a fruitful direction for future work would be the identification of genetic variants for early atherosclerotic stages assessed by PET imaging.

Habitual dietary sodium intake is inversely associated with coronary flow reserve in middle-aged male twins.

BACKGROUND: Evidence links dietary sodium to hypertension and cardiovascular disease (CVD), but investigation of its influence on cardiovascular function is limited. OBJECTIVE: We examined the relation between habitual dietary sodium and coronary flow reserve (CFR), which is a measure of overall coronary vasodilator capacity and microvascular function. We hypothesized that increased sodium consumption is associated with lower CFR. DESIGN: Habitual daily sodium intake for the previous 12 mo was measured in 286 male middle-aged twins (133 monozygotic and dizygotic pairs and 20 unpaired twins) by using the Willett food-frequency questionnaire. CFR was measured by positron emission tomography [N(13)]-ammonia, with quantitation of myocardial blood flow at rest and after adenosine stress. Mixed-effects regression analysis was used to assess the association between dietary sodium and CFR. RESULTS: An increase in dietary sodium of 1000 mg/d was associated with a 10.0% lower CFR (95% CI: -17.0%, -2.5%) after adjustment for demographic, lifestyle, nutritional, and CVD risk factors (P = 0.01). Across quintiles of sodium consumption, dietary sodium was inversely associated with CFR (P-trend = 0.03), with the top quintile (>1456 mg/d) having a 20% lower CFR than the bottom quintile (<732 mg /d). This association also persisted within pairs: a 1000-mg/d difference in dietary sodium between brothers was associated with a 10.3% difference in CFR after adjustment for potential confounders (P = 0.02). CONCLUSIONS: Habitual dietary sodium is inversely associated with CFR independent of CVD risk factors and shared familial and genetic factors. Our study suggests a potential novel mechanism for the adverse effects of dietary sodium on the cardiovascular system. This trial was registered at clinicaltrials.gov as NCT00017836.

The performance of phase analysis of gated SPECT myocardial perfusion imaging in the presence of perfusion defects: a simulation study.

BACKGROUND: Phase analysis has been developed and validated to measure left-ventricular dyssynchrony from gated SPECT myocardial perfusion imaging. The purpose of this study is to evaluate its performance in regions with perfusion defects. METHODS: A special version of the eXtended CArdiac Torso digital phantom was developed to track B-spline points in each temporal frame. A region of 35 B-spline points in the inferior wall with normal and abnormal perfusion uptakes were simulated. Phase shifts were simulated in the same region, representing dyssynchronous contraction. Gated SPECT data were analyzed using a modified phase analysis algorithm, which tracked the same 35 B-spline points to calculate their phases. RESULTS: Phases and phase shifts measured in the B-spline points with perfusion uptake in the range of 50%-10% did not significantly differ from those measured in the same B-spline points with normal perfusion uptake. CONCLUSION: Phase analysis can accurately measure phases in regions with abnormal perfusion uptake as low as 10% of the perfusion uptake in the normal regions, which corresponded to a regional signal-to-noise ratio (SNR) of 12.0 or greater. In 42 consecutive patients with myocardial infarction >20% of the left ventricle, only two patients had a SNR within the perfusion defects below that threshold.

Estimation of Myocardial Volume at Risk from CT Angiography.

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.

Inflammation is related to coronary flow reserve detected by positron emission tomography in asymptomatic male twins.

OBJECTIVES: This study sought to examine the relationship between inflammation and coronary microvascular function in asymptomatic individuals using positron emission tomography (PET) and assessment of coronary flow reserve (CFR). BACKGROUND: Coronary microvascular dysfunction is an early precursor of coronary artery disease (CAD) thought to result from endothelial cell activation and inflammation, but data are limited. METHODS: We examined 268 asymptomatic male monozygotic and dizygotic twins. Plasma biomarkers of inflammation and endothelial cell activation included C-reactive protein (CRP), interleukin (IL)-6, white blood cell count (WBC), vascular cell adhesion molecule (VCAM)-1, and intercellular adhesion molecule (ICAM)-1. Blood flow quantitation was obtained with [¹³N] ammonia PET at rest and after adenosine stress. CFR was measured as the ratio of maximum flow to baseline flow at rest; abnormal CFR was defined as a ratio < 2.5. A summed stress score for visible perfusion defects was calculated. RESULTS: In within-pair analyses, all biomarkers, except VCAM-1, were higher in twins with lower CFR than their brothers with higher CFR (p < 0.05). This was observed in the entire sample, as well as within pairs discordant for a CFR of <2.5. Associations persisted after adjusting for summed stress score and CAD risk factors. In contrast no biomarker, except IL-6, was related to the summed stress score of visible defects. CONCLUSIONS: Even in asymptomatic subjects, a decrease in coronary microvascular function is accompanied by a systemic inflammatory response, independent of CAD risk factors. Our results, using a controlled twin design, highlight the importance of coronary microvascular function in the early phases of CAD.

Effects of smoking on coronary microcirculatory function: a twin study.

BACKGROUND: In asymptomatic smokers, coronary microcirculatory dysfunction, assessed by coronary flow reserve (CFR), is an early indicator of cardiovascular risk. Inflammation and oxidative stress may be the mechanisms through which smoking affects the microvasculature. OBJECTIVES: The purpose of this study was to determine the relationship between smoking and CFR, taking into account potential shared genetic effects. METHODS: We examined 360 male middle aged twins (288 non-smokers and 72 smokers), including 46 twin pairs discordant for current smoking. Coronary flow reserve (CFR) in response to adenosine was measured with positron emission tomography [N(13)] ammonia and quantitation of coronary blood flow at rest and after adenosine stress. Inflammation was assessed by measuring interleukin-6 and C-reactive protein, and oxidative stress was determined by measuring plasma hydroperoxides, glutathione (GSH), the oxidized form of GSH, GSSG, and the ratio of GSH to GSSG. RESULTS: CFR was significantly lower in smokers compared to nonsmokers (2.25 vs. 2.75, p<0.01). This relationship persisted after accounting for known cardiovascular disease risk factors, and was marginally affected by adjusting for inflammatory and oxidative stress biomarkers. In addition, in smoking-discordant twin pairs, CFR in the smoking twin was significantly lower than in the non-smoking co-twin (2.25 vs. 2.67, p=0.03) even after adjustment for cardiovascular risk factors. CONCLUSIONS: Our results demonstrate the adverse effects of smoking in the early phases of cardiovascular disease. Mechanisms other than peripherally measured inflammation and oxidative stress are involved.

Cardiac dedicated ultrafast SPECT cameras: new designs and clinical implications.

Myocardial perfusion imaging (MPI) using nuclear cardiology techniques has been widely applied in clinical practice because of its well-documented value in the diagnosis and prognosis of coronary artery disease. Industry has developed innovative designs for dedicated cardiac SPECT cameras that constrain the entire detector area to imaging just the heart. New software that recovers image resolution and limits image noise has also been implemented. These SPECT innovations are resulting in shortened study times or reduced radiation doses to patients, promoting easier scheduling, higher patient satisfaction, and, importantly, higher image quality. This article describes these cardiocentric SPECT software and hardware innovations, which provide a strong foundation for the continued success of myocardial perfusion SPECT.

Correspondence between gated SPECT and cardiac magnetic resonance quantified myocardial wall thickening.

Left ventricular (LV) wall thickening (WT) assessed from myocardial perfusion (MP) gated SPECT data has been reported to be a marker of functional recovery following myocardial damage. However, the accuracy of WT measurements obtained in the clinical setting rarely has been validated against an independent quantitative reference standard. The purpose of this investigation was to assess the degree to which quantified MP WT agrees with cardiac magnetic resonance (CMR) WT measurements, and to determine whether quantitation is as accurate as visual analysis in detecting abnormal regional WT. MP and ECG-gated True-FISP CMR data were analyzed for 20 patients evaluated after myocardial infarction (age 60 ± 11 years; 95% males). An experienced observer visually graded MP WT on a 5-point scale while viewing MP cines. MP WT was quantified using "Emory Cardiac Toolbox" (ECTb) algorithms. MP algorithms isolated myocardial counts and generated polar maps of WT. CMR data were analyzed by Medis "MASS" software. Manually drawn endocardial and epicardial contours were used to compute WT on CMR. CMR data also were processed for 10 age-matched normal volunteers to define the CMR WT threshold of abnormality. All computations were sampled into conventional 17 ACC/AHA LV wall segments. Receiver operating characteristics (ROC) curve analysis provided discrimination thresholds for optimal accuracy, which subsequently were used to dichotomize the MP methods. WT abnormalities also were assessed for the 3 major arterial territories, and for total numbers of abnormal segments per patient. 25% of all segments had abnormally low WT by CMR. While MP quantitation underestimated CMR WT values for segments with normal WT (26 ± 13% vs. 56 ± 28%, P < 0.0001), measurements were similar for segments with abnormal WT (4 ± 12% vs. 5 ± 9%, P = 0.45). On a segment-by-segment basis, detection of abnormal WT was more accurate by quantitative than visual analysis both for continuous variables (ROC area = 88 ± 2% vs. 80 ± 3%, P < 0.0001) and for dichotomized methods (83% vs. 76%, P = 0.04). Agreement of MP versus CMR for discriminating segments with normal from abnormal WT was significantly better for quantitative than visual analysis (κ = 0.59 vs. 0.40, P < 0.0001), with strongest agreement for left anterior descending artery territories (κ = 0.72). Total numbers of segments with abnormal WT per patient demonstrated significant correlation with CMR (r = 0.83, P < 0.0001). MP quantified LV ejection fractions and volumes also correlated well with CMR (r = 0.87 and 0.90, respectively). Quantified MP WT measurements correlated significantly with CMR values, and discriminated segments with abnormal WT from segments with normal WT more accurately than visual analysis. Therefore, quantification should be performed when analyzing regional WT by scintigraphy.

Localized Principal Component Analysis based Curve Evolution: A Divide and Conquer Approach.

We propose a novel localized principal component analysis (PCA) based curve evolution approach which evolves the segmenting curve semi-locally within various target regions (divisions) in an image and then combines these locally accurate segmentation curves to obtain a global segmentation. The training data for our approach consists of training shapes and associated auxiliary (target) masks. The masks indicate the various regions of the shape exhibiting highly correlated variations locally which may be rather independent of the variations in the distant parts of the global shape. Thus, in a sense, we are clustering the variations exhibited in the training data set. We then use a parametric model to implicitly represent each localized segmentation curve as a combination of the local shape priors obtained by representing the training shapes and the masks as a collection of signed distance functions. We also propose a parametric model to combine the locally evolved segmentation curves into a single hybrid (global) segmentation. Finally, we combine the evolution of these semilocal and global parameters to minimize an objective energy function. The resulting algorithm thus provides a globally accurate solution, which retains the local variations in shape. We present some results to illustrate how our approach performs better than the traditional approach with fully global PCA.

Automatic Alignment of Myocardial Perfusion Images With Contrast-Enhanced Cardiac Computed Tomography.

Explicit fusion of perfusion data from Positron Emission Tomography (PET) or Single Photon Emission Computed Tomography (SPECT) with coronary artery anatomy from Computed Tomographic Coronary Angiography (CTA) has been shown to improve the diagnostic yield for coronary artery disease (CAD) compared to either modality alone. However, most clinically available methods were developed for multimodal scanners or require interactive alignment prior to display and analysis. A new approach was developed to register the two distributions obtained either from a single multimodal imager or from separate scanners, and a preliminary validation was undertaken to compare the automatic alignment to interactive alignment by two experts.

A Regions of Confidence Based Approach to Enhance Segmentation with Shape Priors.

We propose an improved region based segmentation model with shape priors that uses labels of confidence/interest to exclude the influence of certain regions in the image that may not provide useful information for segmentation. These could be regions in the image which are expected to have weak, missing or corrupt edges or they could be regions in the image which the user is not interested in segmenting, but are part of the object being segmented. In the training datasets, along with the manual segmentations we also generate an auxiliary map indicating these regions of low confidence/interest. Since, all the training images are acquired under similar conditions, we can train our algorithm to estimate these regions as well. Based on this training we will generate a map which indicates the regions in the image that are likely to contain no useful information for segmentation. We then use a parametric model to represent the segmenting curve as a combination of shape priors obtained by representing the training data as a collection of signed distance functions. We evolve an objective energy functional to evolve the global parameters that are used to represent the curve. We vary the influence each pixel has on the evolution of these parameters based on the confidence/interest label. When we use these labels to indicate the regions with low confidence; the regions containing accurate edges will have a dominant role in the evolution of the curve and the segmentation in the low confidence regions will be approximated based on the training data. Since our model evolves global parameters, it improves the segmentation even in the regions with accurate edges. This is because we eliminate the influence of the low confidence regions which may mislead the final segmentation. Similarly when we use the labels to indicate the regions which are not of importance, we will get a better segmentation of the object in the regions we are interested in.

Automatic Alignment of Myocardial Perfusion Images with Contrast Cardiac Tomography.

Explicit fusion of perfusion data from Positron Emission Tomography (PET) or Single Photon Emission Computed Tomography (SPECT) with coronary artery anatomy from Computed Tomographic Coronary Angiography (CTCA) has been shown to improve the diagnostic yield for coronary artery disease (CAD) compared to either modality alone. However, most clinically available methods were developed for multimodal scanners or require interactive alignment prior to display and analysis. A new approach was developed to register and display the two distributions obtained either from a single multimodal imager or from separate scanners, and a preliminary validation was undertaken using interactive alignment by experts.