Fully automated deep learning powered calcium scoring in patients undergoing myocardial perfusion imaging.
Fully automated deep learning powered calcium scoring in patients undergoing myocardial perfusion imaging.
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DOI：
10.1007/s12350-022-02940-7
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发表时间：
2023-03
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评估基于全自动深度学习（DL）的非对比计算机断层扫描（CT）冠状动脉钙评分（CACS）的准确性，该评分用于心脏单光子发射计算机断层扫描心肌灌注成像（SPECT-MPI）的衰减校正（AC）。患者被纳入这项研究，作为一项更大的前瞻性研究（NCT03637231）的一部分。在这项研究中，56例因疑似冠状动脉疾病（CAD）而接受心脏SPECT-MPI的患者被前瞻性纳入研究。所有患者均行2次SPECT-MPI非对比CT检查。在CT数据集（n = 112）和基于云的DL工具上手动评估CACS（作为参考标准）。对CAC评分与CAC评分风险分类的一致性进行量化。对于纳入分析的112次扫描，参考标准和DL工具的CAC评分之间的分间一致性为0.986。风险分类一致性为0.977，重分类率为3.6%。心率、图像噪声、身体质量指数（BMI）和扫描对CAC评分的绝对百分比差异无显著影响（p=0.09 - p=0.76）。DL工具可以完全自动化和准确地估计接受非对比CT检查SPECT-MPI AC的患者的CAC评分。在线版本包含补充材料，可在10.1007/s12350-022-02940-7获得。
To assess the accuracy of fully automated deep learning (DL) based coronary artery calcium scoring (CACS) from non-contrast computed tomography (CT) as acquired for attenuation correction (AC) of cardiac single-photon-emission computed tomography myocardial perfusion imaging (SPECT-MPI). Patients were enrolled in this study as part of a larger prospective study (NCT03637231). In this study, 56 Patients who underwent cardiac SPECT-MPI due to suspected coronary artery disease (CAD) were prospectively enrolled. All patients underwent non-contrast CT for AC of SPECT-MPI twice. CACS was manually assessed (serving as standard of reference) on both CT datasets (n = 112) and by a cloud-based DL tool. The agreement in CAC scores and CAC score risk categories was quantified. For the 112 scans included in the analysis, interscore agreement between the CAC scores of the standard of reference and the DL tool was 0.986. The agreement in risk categories was 0.977 with a reclassification rate of 3.6%. Heart rate, image noise, body mass index (BMI), and scan did not significantly impact (p=0.09 - p=0.76) absolute percentage difference in CAC scores. A DL tool enables a fully automated and accurate estimation of CAC scores in patients undergoing non-contrast CT for AC of SPECT-MPI. The online version contains supplementary material available at 10.1007/s12350-022-02940-7.
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