Journal of Nuclear Cardiology

http://link.springer.com/journal/12350

List of Papers (Total 724)

Dual-time-point FDG PET/CT imaging in prosthetic heart valve endocarditis

Purpose FDG PET/CT has been of increasing interest in the diagnostic workup of prosthetic heart valve endocarditis (PVE). Some reports advocate later imaging time points to improve the diagnostic accuracy for PVE. In this study, we compared standard and late FDG PET/CT images in patients with a clinical suspicion of PVE. Materials and Methods Fourteen scans in 13 patients referred ...

Prognostic study of cardiac events in Japanese patients with chronic kidney disease using ECG-gated myocardial Perfusion imaging: Final 3-year report of the J-ACCESS 3 study

Background Myocardial perfusion imaging (MPI) is considered useful for risk stratification among patients with chronic kidney disease (CKD), without renal deterioration by contrast media. Methods and Results The Japanese Assessment of Cardiac Events and Survival Study by Quantitative Gated SPECT (J-ACCESS 3) is a multicenter, prospective cohort study investigating the ability of ...

Automatic determination of cardiovascular risk by CT attenuation correction maps in Rb-82 PET/CT

Background We investigated fully automatic coronary artery calcium (CAC) scoring and cardiovascular disease (CVD) risk categorization from CT attenuation correction (CTAC) acquired at rest and stress during cardiac PET/CT and compared it with manual annotations in CTAC and with dedicated calcium scoring CT (CSCT). Methods and Results We included 133 consecutive patients undergoing ...

Incremental role of resting myocardial computed tomography perfusion for predicting physiologically significant coronary artery disease: A machine learning approach

Background Evaluation of resting myocardial computed tomography perfusion (CTP) by coronary CT angiography (CCTA) might serve as a useful addition for determining coronary artery disease. We aimed to evaluate the incremental benefit of resting CTP over coronary stenosis for predicting ischemia using a computational algorithm trained by machine learning methods. Methods 252 patients ...