5 research outputs found
Myocardial extracellular volume fraction to differentiate healthy from cardiomyopathic myocardium using dual-source dual-energy CT
Objective: To evaluate the feasibility of dual-energy CT (DECT)-based iodine quantification to estimate myocardial extracellular volume (ECV) fraction in patients with and without cardiomyopathy (CM), as well as to assess its ability to distinguish healthy myocardial tissue from cardiomyopathic, with the goal of defining a threshold ECV value for disease detection. Methods: Ten subjects free of heart disease and 60 patients with CM (mean age 66.4 ± 9.4; 59 males and 11 females; 40 ischemic and 20 non-ischemic CM) underwent late iodine enhanced DECT imaging. Myocardial iodine maps were obtained using 3-material decomposition. ECV of the left ventricle was estimated from hematocrit levels and the iodine maps using the AHA 16-segment model. Receiver operating characteristic curve analysis was performed, with corresponding area under the curve, along with Youden's index assessment, to establish a threshold for CM detection. Results: The median ECV for healthy myocardium, non-ischemic CM, and ischemic CM were 25.4% (22.9–27.3), 38.3% (33.7–43.0), and 36.9% (32.4–41.1), respectively. Healthy myocardium showed significantly lower ECV values compared to ischemic and non-ischemic CM (p 29.5% would indicate the presence of CM in the myocardium (sensitivity = 90.3; specificity = 90.3); the AUC for this criterion was 0.950 (p < 0.001). Conclusion: The findings of this study resulted in a statistically significant distinction between healthy myocardium and CM ECVs. This led to the establishment of a promising threshold ECV value that could facilitate the differentiation between healthy and diseased myocardium, and highlights the potential of this DECT methodology to detect cardiomyopathic tissue
Non-invasive fractional flow reserve (FFRCT) in the evaluation of acute chest pain ? Concepts and first experiences
Objective: To evaluate 30 day rate of major adverse cardiac events (MACE) utilizing cCTA and FFRCT for evaluation of patients presenting to the Emergency Department (ED) with acute chest pain. Materials and methods: Patients between the ages of 18?95 years who underwent clinically indicated cCTA and FFRCT in the evaluation of acute chest pain in the emergency department were retrospectively evaluated for 30 day MACE, repeat presentation/admission for chest pain, revascularization, and additional testing. Results: A total of 59 patients underwent CCTA and subsequent FFRCT for the evaluation of acute chest pain in the ED over the enrollment period. 32 out of 59 patients (54 %) had negative FFRCT (>0.80) out of whom 18 patients (55 %) were discharged from the ED. Out of the 32 patients without functionally significant CAD by FFRCT, 32 patients (100 %) underwent no revascularization and 32 patients (100 %) had no MACE at the 30-day follow-up period. Conclusion: In this limited retrospective study, patients presenting to the ED with acute chest pain and with CCTA with subsequent FFRCT of >0.8 had no MACE at 30 days; however, for many of these patients results were not available at time of clinical decision making by the ED physician
Optimization of contrast material administration for coronary CT angiography using a software-based test-bolus evaluation algorithm
Impact of Coronary Computerized Tomography Angiography-Derived Plaque Quantification and Machine-Learning Computerized Tomography Fractional Flow Reserve on Adverse Cardiac Outcome
This study investigated the impact of coronary CT angiography (cCTA)-derived plaque markers and machine-learning-based CT-derived fractional flow reserve (CT-FFR) to identify adverse cardiac outcome. Data of 82 patients (60 +/- 11 years, 62% men) who underwent cCTA and invasive coronary angiography (ICA) were analyzed in this single-center retrospective, institutional review board-approved, HIPAA-compliant study. Follow-up was performed to record major adverse cardiac events (MACE). Plaque quantification of lesions responsible for MACE and control lesions was retrospectively performed semiautomatically from cCTA together with machine-learning based CT-FFR. The discriminatory value of plaque markers and CT-FFR to predict MACE was evaluated. After a median follow-up of 18.5 months (interquartile range 11.5 to 26.6 months), MACE was observed in 18 patients (21 %). In a multivariate analysis the following markers were predictors of MACE (odds ratio [OR]): lesion length (OR 1.16, p = 0.018), low-attenuation plaque (= 50% (OR 3.83, p 0.042), and CT-FFR = 50%, plaque markers and CT-FFR = 50% alone (Area under the curve 0.60,