Quiescent-Interval Single-Shot Magnetic Resonance Angiography May Outperform Carbon-Dioxide Digital Subtraction Angiography in Chronic Lower Extremity Peripheral Arterial Disease

JOURNAL OF CLINICAL MEDICINE(2022)

引用 1|浏览5
暂无评分
摘要
Nephroprotective imaging in peripheral arterial disease (PAD) is often crucial. We compared the diagnostic performance of non-contrast Quiescent-interval single-shot magnetic resonance angiography (QISS MRA) and carbon-dioxide digital subtraction angiography (CO2 DSA) in chronic lower extremity PAD patients. A 19-segment lower extremity arterial model was used to assess the degree of stenosis (none, <50%, 50-70%, >70%) and the image quality (5-point Likert scale: 1-non-diagnostic, 5-excellent image quality). Intra-class correlation coefficient (ICC) was calculated for inter-rater reliability. Diagnostic accuracy and interpretability were evaluated using CO2 DSA as a reference standard. 523 segments were evaluated in 28 patients (11 male, mean age: 71 +/- 9 years). Median and interquartile range of subjective image quality parameters for QISS MRA were significantly better compared to CO2 DSA for all regions: (aortoiliac: 4 [4-5] vs. 3 [3-4]; femoropopliteal: 4 [4-5] vs. 4 [3-4]; tibioperoneal: 4 [3-5] vs. 3 [2-3]; all regions: 4 [4-5] vs. 3 [3-4], all p < 0.001). QISS MRA out-performed CO2 DSA regarding interpretability (98.3% vs. 86.0%, p < 0.001). Diagnostic accuracy parameters of QISS MRA for the detection of obstructive luminal stenosis (70%<) as compared to CO2 DSA were as follows: sensitivity 82.6%, specificity 96.9%, positive predictive value 89.1%, negative predictive value 94.8%. Regarding the degree of stenosis, interobserver variability for all regions was 0.97 for QISS MRA and 0.82 for CO2 DSA. QISS MRA proved to be superior to CO2 DSA regarding subjective image quality and interpretability for the imaging of chronic lower extremity PAD.
更多
查看译文
关键词
carbon dioxide, digital subtraction angiography, magnetic resonance angiography, peripheral arterial disease, renal insufficiency
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要