Assessment of Myocardial Bridge by Cardiac CT: Intracoronary Transluminal Attenuation Gradient Derived from Diastolic Phase Predicts Systolic Compression

Assessment of Myocardial Bridge by Cardiac CT: Intracoronary Transluminal Attenuation Gradient Derived from Diastolic Phase Predicts Systolic Compression.

OBJECTIVE To study the predictive value of transluminal attenuation gradient (TAG) derived from diastolic phase of coronary computed tomography angiography (CCTA) for identifying systolic compression of myocardial bridge (MB). MATERIALS AND METHODS Consecutive patients diagnosed with MB based on CCTA findings and without obstructive coronary artery disease were retrospectively enrolled. In to...

Assessment of diastolic function using myocardial velocity gradient.

Assessment of left ventricular systolic and diastolic function by tissue Doppler imaging after acute myocardial infarction.

OBJECTIVE To evaluate left ventricular systolic and diastolic function by Tissue Doppler imaging after acute myocardial infarction. METHODS It was a hospital based, prospective descriptive study, from 1st July 2010 to 31st Dec. 2010. Total of 200 patients having acute myocardial infarction underwent detailed tissue Doppler imaging (TDI) echocardiographic examination for evaluation of left ven...

Main pulmonary artery diameter from attenuation correction CT scans in cardiac SPECT accurately predicts pulmonary hypertension.

OBJECTIVES To establish the value of the main pulmonary artery (MPA) diameter assessed from unenhanced computer tomography (CT) scans used for attenuation correction (AC) of single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) to predict pulmonary hypertension (PHT). BACKGROUND In contrast-enhanced chest CT scans an MPA diameter of 29 mm or greater is an estab...

extremal region detection guided by maxima of gradient magnitude

a problem of computer vision applications is to detect regions of interest under dif- ferent imaging conditions. the state-of-the-art maximally stable extremal regions (mser) detects affine covariant regions by applying all possible thresholds on the input image, and through three main steps including: 1) making a component tree of extremal regions’ evolution (enumeration), 2) obtaining region ...