An approach to evaluate myocardial perfusion defect assessment for projection-based DECT: A phantom study.

INTRODUCTION: Dual-energy CT (DECT) can improve the accuracy of myocardial perfusion CT with projection-based monochromatic (DECT-MCE) and quantification of myocardial iodine in material decomposition (DECT-MD) reconstructions. However, evaluation of multiple reconstructions is laborious and the optimal reconstruction to detect myocardial perfusion defects is unknown. METHODS: Left ventricular (LV) phantoms with artificial perfusion defects were scanned using DECT and single energy cardiac computed tomography angiography (SECT). Reconstructions of DECT-MCE at 40, 70, 100 and 140 keV, DECT-MD pairs of water, iodine, iron and fat, and SECT were evaluated using a 17-segment myocardial model. The diagnostic performance of each reconstruction was calculated on a per-segment basis and compared across DECT reconstructions. RESULTS: Over 34 phantoms with artificial perfusion defects were found in 64/578 (11%) of segments, the sensitivity of DECT-MCE at 40, 70, 100, and 140 keV was 100% (95% confidence interval (CI): 93-100), 100% (95% CI: 93-100), 71% (95% CI: 56-83), and 25% (95% CI: 14-40), respectively, with a significant decline between 70 keV and 100 keV (p < 0.001). The specificity of DECT-MCE was 100% at all energies (95% CI: 99-100). As a group, the DECT-MD iodine background reconstructions had significantly lower sensitivity than the remaining modes (2.1% [95% CI, 0.05-11.1], vs. 100% [95% CI, 92.6-100], p < 0.001). Specificity of all material pair modes remained 100%. CONCLUSIONS: Using LV phantom models, the approach with the best sensitivity and specificity to assess myocardial perfusion defects with DECT are reconstructions of DECT-MCE at 40 or 70 KeV and DECT-MD without iodine background.

Association between epicardial fat volume and fractional flow reserve: An analysis of the determination of fractional flow reserve (DeFACTO) study.

BACKGROUND: This study examines the relationship between epicardial fat volume (EFV) and lesion-specific ischemia by fractional flow reserve (FFR). METHODS: In a study of 173 patients (63.0 ±â€¯8.3 years) undergoing FFR, EFV was determined using cardiac computed tomography. Relationships between EFV and FFR were assessed using multivariable linear and logistic regression. RESULTS: Using multivariable linear and logistic regression, no association between EFV and FFR was observed (ß [SE] = -0.001 [0.003], P = 0.6, OR [95% CI]: 1.02 [0.94-1.11], P = 0.64, respectively). CONCLUSION: In patients with suspected or known coronary artery disease undergoing invasive angiography, EFV was not associated with FFR.

Comparative diagnostic accuracy of dual-energy CT myocardial perfusion imaging by monochromatic energy versus material decomposition methods.

PURPOSE: To compare the diagnostic value of monochromatic and material decomposition (MD) dual- energy computed tomography (DECT) imaging for the evaluation of ischemia. METHODS: Patients with suspected coronary artery disease underwent rest-stress DECT and SPECT perfusion imaging. DECT images were reconstructed between 40 and 140keV and through MD of iodine/muscle. RESULTS: MD and monochromatic imaging had a sensitivity, specificity, negative predictive, positive predictive value, and accuracy of 89%, 40%, 67%, 73% and 71%; and 91%, 67%, 67%, 91% and 86%, respectively (p=0.05). CONCLUSION: DECT using monochromatic energy displayed a non-significantly higher diagnostic accuracy for myocardial ischemia as compared with DECT MD.

Comparison of Coronary CT Angiography, SPECT, PET, and Hybrid Imaging for Diagnosis of Ischemic Heart Disease Determined by Fractional Flow Reserve.

Importance: At present, the choice of noninvasive testing for a diagnosis of significant coronary artery disease (CAD) is ambiguous, but nuclear myocardial perfusion imaging with single-photon emission tomography (SPECT) or positron emission tomography (PET) and coronary computed tomography angiography (CCTA) is predominantly used for this purpose. However, to date, prospective head-to-head studies are lacking regarding the diagnostic accuracy of these imaging modalities. Furthermore, the combination of anatomical and functional assessments configuring a hybrid approach may yield improved accuracy. Objectives: To establish the diagnostic accuracy of CCTA, SPECT, and PET and explore the incremental value of hybrid imaging compared with fractional flow reserve. Design, Setting, and Participants: A prospective clinical study involving 208 patients with suspected CAD who underwent CCTA, technetium 99m/tetrofosmin-labeled SPECT, and [15O]H2O PET with examination of all coronary arteries by fractional flow reserve was performed from January 23, 2012, to October 25, 2014. Scans were interpreted by core laboratories on an intention-to-diagnose basis. Hybrid images were generated in case of abnormal noninvasive anatomical or functional test results. Main Outcomes and Measures: Hemodynamically significant stenosis in at least 1 coronary artery as indicated by a fractional flow reserve of 0.80 or less and relative diagnostic accuracy of SPECT, PET, and CCTA in detecting hemodynamically significant CAD. Results: Of the 208 patients in the study (76 women and 132 men; mean [SD] age, 58 [9] years), 92 (44.2%) had significant CAD (fractional flow reserve ≤0.80). Sensitivity was 90% (95% CI, 82%-95%) for CCTA, 57% (95% CI, 46%-67%) for SPECT, and 87% (95% CI, 78%-93%) for PET, whereas specificity was 60% (95% CI, 51%-69%) for CCTA, 94% (95% CI, 88%-98%) for SPECT, and 84% (95% CI, 75%-89%) for PET. Single-photon emission tomography was found to be noninferior to PET in terms of specificity (P < .001) but not in terms of sensitivity (P > .99) using the predefined absolute margin of 10%. Diagnostic accuracy was highest for PET (85%; 95% CI, 80%-90%) compared with that of CCTA (74%; 95% CI, 67%-79%; P = .003) and SPECT (77%; 95% CI, 71%-83%; P = .02). Diagnostic accuracy was not enhanced by either hybrid SPECT and CCTA (76%; 95% CI, 70%-82%; P = .75) or by PET and CCTA (84%; 95% CI, 79%-89%; P = .82), but resulted in an increase in specificity (P = .004) at the cost of a decrease in sensitivity (P = .001). Conclusions and Relevance: This controlled clinical head-to-head comparative study revealed PET to exhibit the highest accuracy for diagnosis of myocardial ischemia. Furthermore, a combined anatomical and functional assessment does not add incremental diagnostic value but guides clinical decision-making in an unsalutary fashion.

Subclinical atherosclerosis detected by coronary computed tomographic angiography in Qatar: a comparison between Qataris and south Asian migrants.

PURPOSE: There are limited data regarding subclinical atherosclerosis in Middle Eastern countries. We aimed to describe and compare coronary computed tomographic angiography (CCTA) findings in Qatari native and South Asian migrants at increased risk of coronary artery disease (CAD). METHODS: We performed CCTA in 251 consecutive volunteers (126 South Asian, 125 Qatari, mean age 50.0 ± 7.3 years, 27.1% female) at increased risk of cardiovascular disease. Given differences in baseline risk factors, we employed propensity score matching to create a cohort of 162 subjects for comparative analyses. We compared CAD severity, extent, plaque morphology, adverse plaque characteristics, and quantitative measures of atherosclerotic burden in both subgroups. RESULTS: After matching, no CAD was seen in 58.0% of South Asians and 49.4% of Qataris (p = 0.3), while obstructive CAD (≥50% luminal stenosis) was present in 40.7% of South Asians and 49.4% of Qataris (p = 0.3). There was a high prevalence of adverse plaque characteristics in both ethnicities, particularly positive remodeling. South Asians had significantly smaller vessel and lumen volumes, but the percent aggregate plaque volumes were not significantly different (2.9 ± 6.3% vs. 3.8 ± 8.0%, p = 0.4). CONCLUSIONS: In this first study of CCTA findings performed in a Middle Eastern country, we observed a high prevalence of obstructive CAD in a middle-aged cohort. There were no significant differences in CCTA findings between Qataris and South Asians after adjustment for clinical risk factors. Future studies are needed to identify patterns of coronary atherosclerosis by CCTA in non-European populations where cardiovascular disease is increasingly prevalent.

Effects of Liver Transplantation on Lipids and Cardiovascular Disease in Children With Homozygous Familial Hypercholesterolemia.

Homozygous familial hypercholesterolemia (HoFH) is a rare, inherited, life-threatening, metabolic disorder of low-density lipoprotein (LDL) receptor function characterized by elevated serum LDL cholesterol (LDL-C) and rapidly progressive atherosclerotic cardiovascular disease (ACVD). Since LDL receptors are predominantly found on hepatocytes, orthotopic liver transplantation (OLT) has emerged as a viable intervention for HoFH because LDL receptor activity is restored. This study assessed the effects of OLT on ACVD and ACVD risk factors in pediatric patients with HoFH. We analyzed lipids, lipoproteins, body mass index, glucose, blood pressure, and cardiovascular imaging in 8 pediatric patients who underwent OLT for HoFH. Total serum cholesterol, LDL-C, lipoprotein (a), and apolipoprotein B/apolipoprotein A1 ratio decreased to normal values in all subjects (p values <0.001) at 1 month after OLT and were maintained for the length of follow-up (2 to 6 years). There were few complications related to surgery or immunosuppressive therapy. Two patients developed mild hypertension. In the first 4 subjects monitored for 4 to 6 years after OLT, coronary artery disease did not develop or progress except in 1 minor artery in 1 subject and actually regressed in 2 subjects with >50% stenosis. However, aortic valve stenosis progressed in 2 of 4 subjects. In conclusion, OLT is an effective therapeutic option for patients with HoFH with coronary artery disease and persistently elevated serum LDL-C despite maximum medical therapy. Aortic valvular disease may progress. Long-term data are needed to evaluate the true risk-benefit ratio of this surgical approach.

Using edge-preserving algorithm with non-local mean for significantly improved image-domain material decomposition in dual-energy CT.

Increased noise is a general concern for dual-energy material decomposition. Here, we develop an image-domain material decomposition algorithm for dual-energy CT (DECT) by incorporating an edge-preserving filter into the Local HighlY constrained backPRojection reconstruction (HYPR-LR) framework. With effective use of the non-local mean, the proposed algorithm, which is referred to as HYPR-NLM, reduces the noise in dual-energy decomposition while preserving the accuracy of quantitative measurement and spatial resolution of the material-specific dual-energy images. We demonstrate the noise reduction and resolution preservation of the algorithm with an iodine concentrate numerical phantom by comparing the HYPR-NLM algorithm to the direct matrix inversion, HYPR-LR and iterative image-domain material decomposition (Iter-DECT). We also show the superior performance of the HYPR-NLM over the existing methods by using two sets of cardiac perfusing imaging data. The DECT material decomposition comparison study shows that all four algorithms yield acceptable quantitative measurements of iodine concentrate. Direct matrix inversion yields the highest noise level, followed by HYPR-LR and Iter-DECT. HYPR-NLM in an iterative formulation significantly reduces image noise and the image noise is comparable to or even lower than that generated using Iter-DECT. For the HYPR-NLM method, there are marginal edge effects in the difference image, suggesting the high-frequency details are well preserved. In addition, when the search window size increases from to , there are no significant changes or marginal edge effects in the HYPR-NLM difference images. The reference drawn from the comparison study includes: (1) HYPR-NLM significantly reduces the DECT material decomposition noise while preserving quantitative measurements and high-frequency edge information, and (2) HYPR-NLM is robust with respect to parameter selection.

Myocardial perfusion analysis in cardiac computed tomography angiographic images at rest.

Cardiac computed tomography angiography (CTA) is a non-invasive method for anatomic evaluation of coronary artery stenoses. However, CTA is prone to artifacts that reduce the diagnostic accuracy to identify stenoses. Further, CTA does not allow for determination of the physiologic significance of the visualized stenoses. In this paper, we propose a new system to determine the physiologic manifestation of coronary stenoses by assessment of myocardial perfusion from typically acquired CTA images at rest. As a first step, we develop an automated segmentation method to delineate the left ventricle. Both endocardium and epicardium are compactly modeled with subdivision surfaces and coupled by explicit thickness representation. After initialization with five anatomical landmarks, the model is adapted to a target image by deformation increments including control vertex displacements and thickness variations guided by trained AdaBoost classifiers, and regularized by a prior of deformation increments from principal component analysis (PCA). The evaluation using a 5-fold cross-validation demonstrates the overall segmentation error to be 1.00 ± 0.39 mm for endocardium and 1.06 ± 0.43 mm for epicardium, with a boundary contour alignment error of 2.79 ± 0.52. Based on our LV model, two types of myocardial perfusion analyzes have been performed. One is a perfusion network analysis, which explores the correlation (as network edges) pattern of perfusion between all pairs of myocardial segments (as network nodes) defined in AHA 17-segment model. We find perfusion network display different patterns in the normal and disease groups, as divided by whether significant coronary stenosis is present in quantitative coronary angiography (QCA). The other analysis is a clinical validation assessment of the ability of the developed algorithm to predict whether a patient has significant coronary stenosis when referenced to an invasive QCA ground truth standard. By training three machine learning techniques using three features of normalized perfusion intensity, transmural perfusion ratio, and myocardial wall thickness, we demonstrate AdaBoost to be slightly better than Naive Bayes and Random Forest by the area under receiver operating characteristics (ROC) curve. For the AdaBoost algorithm, an optimal cut-point reveals an accuracy of 0.70, with sensitivity and specificity of 0.79 and 0.64, respectively. Our study shows perfusion analysis from CTA images acquired at rest is useful for providing physiologic information in diagnosis of obstructive coronary artery stenoses.

Heart-rate dependent improvement in image quality and diagnostic accuracy of coronary computed tomographic angiography by novel intracycle motion correction algorithm.

BACKGROUND: To determine the effect of a novel intracycle motion correction algorithm (MCA) on diagnostic accuracy of coronary computed tomographic angiography. METHODS: Coronary artery phantom models were scanned at static and heart rate (HR) simulation of 60-100 beat/min and reconstructed with a conventional algorithm and MCA. RESULTS: Among 144 coronary segments, improvements in image interpretability, quality, and diagnostic accuracy by MCA were observed for HRs of 80 and 100 (P<.05 for all), but not for HR of 60. CONCLUSION: Novel intracycle MCA demonstrates improved HR-dependent image interpretability, and quality and accuracy, particularly at higher HRs.