MR perfusion imaging, along with intracoronary pressure data, may help identify hemodynamically relevant coronary artery diseases, according to a study presented this week at the North American Society for Cardiac Imaging meeting in Amelia Island, FL.
MR perfusion imaging, along with intracoronary pressure data, may help identify hemodynamically relevant coronary artery diseases, according to a study presented this week at the North American Society for Cardiac Imaging meeting in Amelia Island, FL.
Dr. Armin M. Huber and colleagues from the Klinikum Grosshadern and Klinikum Innenstadt in Munich found that semiquantitative MR perfusion parameters with results from intracoronary pressure-derived fractional flow reserve correctly assessed the hemodynamic relevance of known coronary artery lesions.
Twenty-one patients underwent coronary MR angiography with intracoronary pressure wire examination for determination of fractional flow reserve in 23 stenotic lesions. SI curves of the first-pass MR perfusion imaging (SR-turboFLASH) of the myocardium were analyzed at rest and under adenosine-induced hyperemia.
Researchers determined time-to-peak, maximum signal intensity, and upslope values using a 16-segment model. They divided lesions into three groups:
A total of 336 perfusion areas were evaluated. Time-to-peak and upslope at rest values were not significantly different among the three groups. Stress upslope measurements of normal coronary arteries and severe coronary stenoses, however, were significantly different.
The ratio for upslope at stress and rest was 3.4 (2.0-6.3) for normal coronary arteries and 1.7 (1.2-1.7) and 1.1 (1.0-1.3) for intermediate and severe coronary lesions (p
Time-to-peak and upslope at rest measurements were not able to discriminate between normal and severely stenosed coronary arteries, Huber said. Measurements for upslope under stress and the ratio between upslope under stress and upslope at rest were significantly different between normal and significantly functionally diseased coronary arteries.
"The use of these MRI parameters may therefore improve the sensitivity and specificity of noninvasive identification of hemodynamically relevant CAD," he said.
Emerging MRI Scoring System May Help Predict Recurrent and Metastatic Hepatocellular Carcinoma
February 12th 2025Preoperative use of the scoring system for gadoxetic acid-enhanced MRI demonstrated an average AUC of 85 percent and average specificity of 89 percent in external validation cohorts for pathologic features of hepatocellular carcinoma.
Can MRI-Based Deep Learning Improve Risk Stratification in PI-RADS 3 Cases?
January 30th 2025In external validation testing, a deep learning model demonstrated an average AUC of 87.6 percent for detecting clinically significant prostate cancer (csPCA) on prostate MRI for patients with PI-RADS 3 assessments.