Ota Takashi, Nakamoto Atsushi, Hori Masatoshi, Fukui Hideyuki, Onishi Hiromitsu, Tatsumi Mitsuaki, Tomiyama Noriyuki
Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, D1, 2-2, Yamadaoka, Suita, Osaka, 565-0871, Japan.
Department of Artificial Intelligence in Diagnostic Radiology, Osaka University Graduate School of Medicine, Suita, Japan.
Radiol Med. 2025 Mar 28. doi: 10.1007/s11547-025-01978-0.
To evaluate abdominal aortic calcification parameters derived from 3D volumetric analysis using photon-counting CT (PCCT) angiography-based virtual non-calcium (VNCa) algorithm as an imaging biomarker for high-risk cardiovascular disease (CVD) patients.
This retrospective study included patients who underwent abdominal PCCT angiography and non-contrast-enhanced chest CT (nCE-CCT, including CT scanners other than PCCT) between March 2023 and June 2024. Abdominal aortic calcification maps were generated by subtracting VNCa from the corresponding CTA images to calculate the abdominal calcification volume (ACV) and aortic wall volume (AWV). Percentage calcification volume (PCV) was calculated as ACV/AWV. Agatston scores from nCE-CCT classified patients into low- (≤ 100) and high-risk (> 100) CVD groups. Correlations between Agatston score, ACV, and PCV were analyzed using Spearman's rank correlation, and receiver operating characteristic analysis was used to determine the performance and cutoff values of ACV and PCV, with McNemar's test comparing sensitivities and specificities.
The study included 200 patients, 163 low- and 37 high-risk patients. Agatston score correlations with ACV and PCV were 0.75 and 0.78, respectively (p < 0.0001). PCV showed a superior AUC (0.94) than ACV (0.90, p = 0.0002). Cutoff values were 5.74 mL for ACV (75.7% sensitivity, 89.0% specificity) and 14.81% for PCV (73.0% sensitivity, 99.4% specificity), and PCV specificity was significantly higher than ACV specificity (p < 0.0001).
PCV > 14.81% indicates an increased CVD risk, suggesting that PCV is a potential imaging biomarker for high-risk patients with CVD. Abdominal CTA alone may identify high-risk patients with CVD, warranting further cardiovascular screening.
评估基于光子计数CT(PCCT)血管造影的虚拟去钙(VNCa)算法从三维容积分析得出的腹主动脉钙化参数,作为高危心血管疾病(CVD)患者的成像生物标志物。
这项回顾性研究纳入了2023年3月至2024年6月期间接受腹部PCCT血管造影和非增强胸部CT(nCE-CCT,包括PCCT以外的CT扫描仪)的患者。通过从相应的CTA图像中减去VNCa来生成腹主动脉钙化图,以计算腹部钙化体积(ACV)和主动脉壁体积(AWV)。钙化体积百分比(PCV)计算为ACV/AWV。nCE-CCT的阿加斯顿评分将患者分为低危(≤100)和高危(>100)CVD组。使用Spearman等级相关性分析阿加斯顿评分、ACV和PCV之间的相关性,并使用受试者工作特征分析来确定ACV和PCV的性能及临界值,采用McNemar检验比较敏感性和特异性。
该研究纳入了200例患者,其中163例低危患者和37例高危患者。阿加斯顿评分与ACV和PCV的相关性分别为0.75和0.78(p<0.0001)。PCV的曲线下面积(AUC)(0.94)优于ACV(0.90,p=0.0002)。ACV的临界值为5.74 mL(敏感性75.7%,特异性89.0%),PCV的临界值为14.81%(敏感性73.0%,特异性99.4%),且PCV的特异性显著高于ACV的特异性(p<0.0001)。
PCV>14.81%表明CVD风险增加,提示PCV是高危CVD患者的潜在成像生物标志物。仅腹部CTA可能识别出高危CVD患者,需要进一步进行心血管筛查。