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We have developed the method for dynamic 320-row multidetector computed tomography (MDCT)-derived quantitative coronary flow reserve (CFRCT) and hyperemic myocardial blood flow (MBFCT). We evaluated diagnostic value of CFRCT and hyperemic MBFCT for detecting obstructive coronary artery disease (CAD) in per-patient and per-vessel analysis, and their relations with the severity of CAD burden.Adenosine stressed and rest dynamic myocardial perfusion MDCT were prospectively performed in patients with known or suspected CAD. Per-patient and per-vessel MBFCT were estimated from dynamic perfusion images in rest and hyperemic phases, and per-patient and per-vessel CFRCT were calculated from the ratio of rest and hyperemic MBFCT. Degree of stenosis was evaluated by coronary CT angiography (CTA) and invasive coronary angiography (ICA). Obstructive stenosis was defined as ≥70% stenosis in ICA. CAD burden with MDCT was calculated by logarithm transformed coronary artery calcium (CAC) score and the CTA-adapted Leaman risk score (CT-LeSc). A logistic regression analysis was used to measure the receiver-operating characteristic curve and corresponding area under the curve (AUC) for the detection of obstructive CAD.Twenty-seven patients and 81 vessels were eligible for this study. Sixteen patients had obstructive CAD, and 31 vessels had obstructive stenosis. Using an optimal cutoff, the CFRCT and hyperemic MBFCT had the moderate diagnostic values in per-patient (AUC = 0.89 and 0.86, respectively) and per-vessel (AUC = 0.79 and 0.76, respectively). Per-patient CFRCT and hyperemic MBFCT exhibited a moderate inverse correlation with CAC score and the CT-LeSc.Per-patient and per-vessel CFRCT as well as hyperemic MBFCT had moderate diagnostic value for detecting obstructive CAD. These per-patient values exhibited a moderate inverse correlation with CAD burden. CFRCT and hyperemic MBFCT might add quantitative functional information for evaluating patients with CAD.
Pubmed ID: 29979416
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View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
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