Kurogi Kazumasa, Ishii Masanobu, Nagatomo Toshiki, Tokai Tatsuya, Kaichi Ryota, Takae Masafumi, Mori Takayuki, Komaki Soichi, Yamamoto Nobuyasu, Tsujita Kenichi
Department of Cardiovascular Medicine, Miyazaki Prefectural, Nobeoka Hospital, Miyazaki, Japan.
Department of Cardiovascular Medicine, Graduate School of Medical Sciences, Kumamoto University, Kumamoto, Japan.
J Cardiovasc Comput Tomogr. 2023 Mar-Apr;17(2):120-129. doi: 10.1016/j.jcct.2023.02.002. Epub 2023 Feb 10.
Multi-slice computed tomography (CT) allows noninvasive evaluation of the severity of coronary calcification. However, there has yet to be a definitive parameter based on the cross-sectional CT image for predicting the need for rotational atherectomy (RA). Therefore, we aimed to investigate the mean density of cross-sectional CT images to predict the need for RA during percutaneous coronary intervention (PCI).
A total of 154 lesions with moderate to severe calcification detected in coronary angiography were identified in 126 patients who underwent coronary CT prior to PCI for stable angina. PCI with RA was performed for 48 lesions, and the remaining 106 were treated without RA. Multi-slice CT was retrospectively evaluated for its ability to predict the use of RA. We chose the most severely calcified cross-sectional image for each lesion. The mean density within the outer vessel contour, calcium arc quadrant of the cross-sectional CT image, calcium length, calcification remodeling index, and per-lesion coronary artery calcium score was studied.
Receiver-operator characteristic curve analysis revealed 637 Hounsfield units (HU) (area under the curve = 0.98, 95% confidence interval: 0.97-1.00, p < 0.001) as the best mean density cutoff value for predicting RA. Multivariate logistic regression analysis showed that a mean calcium level >637 HU was a strong independent predictor (odds ratio: 32.8, 95% confidence interval: 7.0-153, p < 0.001) for using RA.
The mean density of the cross-sectional CT image, a simple quantitative parameter, was the strongest predictor of the need for RA during PCI.
多层螺旋计算机断层扫描（CT）能够对冠状动脉钙化的严重程度进行无创评估。然而，基于CT横断面图像，尚未有一个明确的参数来预测旋磨术（RA）的必要性。因此，我们旨在研究CT横断面图像的平均密度，以预测经皮冠状动脉介入治疗（PCI）期间是否需要进行RA。
在126例因稳定型心绞痛在PCI术前接受冠状动脉CT检查的患者中，共识别出154个在冠状动脉造影中检测到的中度至重度钙化病变。对48个病变进行了RA辅助的PCI治疗，其余106个病变未进行RA治疗。对多层CT预测RA使用的能力进行了回顾性评估。我们为每个病变选择了钙化最严重的横断面图像。研究了血管外轮廓内的平均密度、横断面CT图像的钙弧象限、钙长度、钙化重塑指数和每个病变的冠状动脉钙化积分。
受试者工作特征曲线分析显示，637亨氏单位（HU）（曲线下面积=0.98，95%置信区间：0.97-1.00，p<0.001）是预测RA的最佳平均密度临界值。多因素逻辑回归分析表明，平均钙水平>637 HU是使用RA的强有力独立预测因素（优势比：32.8，95%置信区间：7.0-153，p<0.001）。
横断面CT图像的平均密度作为一个简单的定量参数，是PCI期间RA必要性的最强预测因素。
