School of Biomedical Engineering & Imaging Sciences, King's College London, King's Health Partners, 4th Floor Lambeth Wing, St Thomas' Hospital, London, SE1 7EH, UK.
Cardiology Department of the Basingstoke and North Hampshire Hospital, Basingstoke, UK.
J Cardiovasc Magn Reson. 2018 Nov 19;20(1):74. doi: 10.1186/s12968-018-0493-4.
Clinical evaluation of stress perfusion cardiovascular magnetic resonance (CMR) is currently based on visual assessment and has shown high diagnostic accuracy in previous clinical trials, when performed by expert readers or core laboratories. However, these results may not be generalizable to clinical practice, particularly when less experienced readers are concerned. Other factors, such as the level of training, the extent of ischemia, and image quality could affect the diagnostic accuracy. Moreover, the role of rest images has not been clarified. The aim of this study was to assess the diagnostic accuracy of visual assessment for operators with different levels of training and the additional value of rest perfusion imaging, and to compare visual assessment and automated quantitative analysis in the assessment of coronary artery disease (CAD).
We evaluated 53 patients with known or suspected CAD referred for stress-perfusion CMR. Nine operators (equally divided in 3 levels of competency) blindly reviewed each case twice with a 2-week interval, in a randomised order, with and without rest images. Semi-automated Fermi deconvolution was used for quantitative analysis and estimation of myocardial perfusion reserve as the ratio of stress to rest perfusion estimates.
Level-3 operators correctly identified significant CAD in 83.6% of the cases. This percentage dropped to 65.7% for Level-2 operators and to 55.7% for Level-1 operators (p < 0.001). Quantitative analysis correctly identified CAD in 86.3% of the cases and was non-inferior to expert readers (p = 0.56). When rest images were available, a significantly higher level of confidence was reported (p = 0.022), but no significant differences in diagnostic accuracy were measured (p = 0.34).
Our study demonstrates that the level of training is the main determinant of the diagnostic accuracy in the identification of CAD. Level-3 operators performed at levels comparable with the results from clinical trials. Rest images did not significantly improve diagnostic accuracy, but contributed to higher confidence in the results. Automated quantitative analysis performed similarly to level-3 operators. This is of increasing relevance as recent technical advances in image reconstruction and analysis techniques are likely to permit the clinical translation of robust and fully automated quantitative analysis into routine clinical practice.
目前，临床评估压力灌注心血管磁共振（CMR）是基于视觉评估的，并且在之前的临床试验中，当由专家读者或核心实验室进行时，已显示出较高的诊断准确性。然而，这些结果可能不适用于临床实践，尤其是在涉及经验较少的读者时。其他因素，如培训水平、缺血程度和图像质量，可能会影响诊断准确性。此外，静息图像的作用尚未阐明。本研究旨在评估不同培训水平的操作者进行视觉评估的诊断准确性，以及静息灌注成像的附加价值，并比较视觉评估和自动定量分析在评估冠状动脉疾病（CAD）中的应用。
我们评估了 53 名已知或疑似 CAD 的患者，这些患者因压力灌注 CMR 而就诊。9 名操作者（分为 3 个能力水平）以随机顺序，在 2 周间隔内，两次分别对每个病例进行盲法评估，评估时使用半自动化的 Fermi 去卷积进行定量分析，并估计心肌灌注储备，即压力与静息灌注估计的比值。
第 3 级操作者正确识别出 83.6%的有意义 CAD 病例。这一百分比降至第 2 级操作者的 65.7%和第 1 级操作者的 55.7%（p<0.001）。定量分析正确识别出 86.3%的 CAD 病例，与专家读者的结果相当（p=0.56）。当有静息图像时，报告的信心水平显著提高（p=0.022），但诊断准确性无显著差异（p=0.34）。
我们的研究表明，培训水平是识别 CAD 时诊断准确性的主要决定因素。第 3 级操作者的表现与临床试验结果相当。静息图像并未显著提高诊断准确性，但有助于提高对结果的信心。自动定量分析的表现与第 3 级操作者相似。随着图像重建和分析技术的最新技术进步，可能会将强大的全自动定量分析技术转化为常规临床实践，这一点变得越来越重要。
