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冠状动脉计算机断层摄影术光子计数探测器技术的钙评分:性能预测因素。

Calcium scoring on coronary computed angiography tomography with photon-counting detector technology: Predictors of performance.

机构信息

Heart and Vascular Center of Semmelweis University, Budapest, Hungary; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA.

Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA.

出版信息

J Cardiovasc Comput Tomogr. 2023 Sep-Oct;17(5):328-335. doi: 10.1016/j.jcct.2023.08.004. Epub 2023 Aug 25.

Abstract

INTRODUCTION

Obtaining accurate coronary artery calcium (CAC) score measurements from CCTA datasets with virtual non-iodine (VNI) algorithms would reduce acquisition time and radiation dose. We aimed to assess the agreement of VNI-derived and conventional true non-contrast (TNC)-based CAC scores and to identify the predictors of accuracy.

METHODS

CCTA datasets were acquired with either 120 or 140 ​kVp. CAC scores and volumes were calculated from TNC and VNI images in 197 consecutive patients undergoing CCTA. CAC density score, mean volume/lesion, aortic Hounsfield units and standard deviations were then measured. Finally, percentage deviation (VNI - TNC/TNC∗100) of CTA-derived CAC scores from non-enhanced scans was calculated for each patient. Predictors (including anthropometric and acquisition parameters, as well as CAC characteristics) of the degree of discrepancy were evaluated using linear regression analysis.

RESULTS

While the agreement between TNC and VNI was substantial (mean bias, 6.6; limits of agreement, 178.5/145.3), a non-negligible proportion of patients (36/197, 18.3%) were falsely reclassified as CAC score ​= ​0 on VNI. The use of higher tube voltage significantly decreased the percentage deviation relative to TNC-based values (β ​= ​-0.21 [95%CI: 0.38 to -0.03], p ​= ​0.020) and a higher CAC density score also proved to be an independent predictor of a smaller difference (β ​= ​-0.22 [95%CI: 0.37 to -0.07], p ​= ​0.006).

CONCLUSION

The performance of VNI-based calcium scoring may be improved by increased tube voltage protocols, while the accuracy may be compromised for calcified lesions of lower density. The implementation of VNI in clinical routine, however, needs to be preceded by a solution for detecting smaller lesions as well.

摘要

简介

使用虚拟非碘(VNI)算法从 CCTA 数据集获取准确的冠状动脉钙(CAC)评分测量值可以减少采集时间和辐射剂量。我们旨在评估 VNI 衍生和传统真实非对比(TNC)基础 CAC 评分的一致性,并确定准确性的预测因素。

方法

使用 120 或 140 kVp 采集 CCTA 数据集。在 197 名连续接受 CCTA 检查的患者中,从 TNC 和 VNI 图像计算 CAC 评分和体积。然后测量 CAC 密度评分、平均体积/病变、主动脉亨氏单位和标准差。最后,为每位患者计算 CTA 衍生 CAC 评分与非增强扫描的百分比偏差(VNI - TNC/TNC∗100)。使用线性回归分析评估差异程度的预测因素(包括人体测量和采集参数以及 CAC 特征)。

结果

虽然 TNC 和 VNI 之间的一致性很强(平均偏差,6.6;一致性界限,178.5/145.3),但相当比例的患者(36/197,18.3%)在 VNI 上被错误地重新归类为 CAC 评分=0。使用更高的管电压可显著降低相对于基于 TNC 的值的百分比偏差(β=-0.21[95%CI:0.38 至-0.03],p=0.020),并且较高的 CAC 密度评分也被证明是差异较小的独立预测因素(β=-0.22[95%CI:0.37 至-0.07],p=0.006)。

结论

通过增加管电压方案,可以提高基于 VNI 的钙评分的性能,而对于密度较低的钙化病变,准确性可能会受到影响。然而,在将 VNI 应用于临床常规之前,需要先解决检测较小病变的问题。

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