Liu Anqi, Xu Wenqing, Xi Linfeng, Deng Mei, Yang Haoyu, Huang Qiang, Gao Qian, Zhang Peiyao, Xie Wanmu, Huang Zhenguo, Liu Min
China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China.
Department of Radiology, Peking University China-Japan Friendship School of Clinical Medicine, Beijing, 100191, China.
Insights Imaging. 2023 Oct 23;14(1):179. doi: 10.1186/s13244-023-01535-1.
To re-assess cardiovascular metrics on computed tomography pulmonary angiography (CTPA) in predicting pulmonary hypertension (PH) under the 2022 ESC/ERS guidelines.
This observational study retrospectively included 272 patients (female 143, mean age = 54.9 ± 12.5 years old) with suspected PH. 218 patients were grouped to evaluate cardiovascular metrics on CTPA and develop a binary logistic regression model. The other 54 patients were grouped into the validation group to assess the performance of the prediction model under the updated criteria. Based on mean pulmonary artery pressure (mPAP), patients were divided into three groups: group A consisted of patients with mPAP ≤ 20 mmHg, group B included patients with 20 mmHg < mPAP < 25 mmHg, and group C comprised patients with mPAP ≥ 25 mmHg. Cardiovascular metrics among the three groups were compared, and receiver operating characteristic curves (ROCs) were used to evaluate the performance of cardiovascular metrics in predicting mPAP > 20 mmHg.
The main pulmonary arterial diameter (MPAd), MPAd/ascending aorta diameter ratio (MPAd/AAd ratio), and right ventricular free wall thickness (RVFWT) showed significant differences among the three groups (p < 0.05). The area under curve (AUC) of MPAd was larger than MPAd/AAd ratio and RVFWT. A MPAd cutoff value of 30.0 mm has a sensitivity of 83.1% and a specificity of 90.4%. The AUC of the binary logistic regression model (Z = - 12.98187 + 0.31053 MPAd + 1.04863 RVFWT) was 0.938 ± 0.018. In the validation group, the AUC, sensitivity, specificity, and accuracy of the prediction model were 0.878, 92.7%, 76.9%, and 88.9%, respectively.
Under the updated criteria, MPAd with a threshold value of 30.0 mm has better sensitivity and specificity in predicting PH. The binary logistic regression model may improve the diagnostic accuracy.
Under the updated criteria, the main pulmonary arterial diameter with a threshold value of 30.0 mm has better sensitivity and specificity in predicting pulmonary hypertension. The binary logistic regression model may improve diagnostic accuracy.
• According to 2022 ESC/ERS guidelines, a MPAd cutoff value of 30.0 mm has better sensitivity and specificity in predicting mPAP > 20 mmHg • A binary logistic regression model (Z = - 12.98187 + 0.31053 MPAd + 1.04863 RVFWT) was developed and had a sensitivity, specificity, and accuracy of 92.7%, 76.9%, and 88.9% in predicting mPAP > 20 mmHg. • A binary logistic regression prediction model outperforms MPAd in predicting mPAP > 20 mmHg.
根据2022年欧洲心脏病学会/欧洲呼吸学会（ESC/ERS）指南，重新评估计算机断层扫描肺动脉造影（CTPA）上的心血管指标在预测肺动脉高压（PH）中的作用。
这项观察性研究回顾性纳入了272例疑似PH患者（女性143例，平均年龄=54.9±12.5岁）。218例患者分组以评估CTPA上的心血管指标并建立二元逻辑回归模型。另外54例患者分为验证组，以根据更新标准评估预测模型的性能。根据平均肺动脉压（mPAP），患者分为三组：A组由mPAP≤20 mmHg的患者组成，B组包括20 mmHg＜mPAP＜25 mmHg的患者，C组由mPAP≥25 mmHg的患者组成。比较三组间的心血管指标，采用受试者工作特征曲线（ROC）评估心血管指标预测mPAP＞20 mmHg的性能。
三组间主肺动脉直径（MPAd）、MPAd/升主动脉直径比值（MPAd/AAd比值）和右心室游离壁厚度（RVFWT）存在显著差异（p＜0.05）。MPAd的曲线下面积（AUC）大于MPAd/AAd比值和RVFWT。MPAd截断值为30.0 mm时，敏感性为83.1%，特异性为90.4%。二元逻辑回归模型（Z = - 12.98187 + 0.31053 MPAd + 1.04863 RVFWT）的AUC为0.938±0.018。在验证组中，预测模型的AUC、敏感性、特异性和准确性分别为0.878、92.7%、76.9%和88.9%。
在更新标准下，阈值为30.0 mm的MPAd在预测PH方面具有更好的敏感性和特异性。二元逻辑回归模型可能提高诊断准确性。
在更新标准下，阈值为30.0 mm的主肺动脉直径在预测肺动脉高压方面具有更好的敏感性和特异性。二元逻辑回归模型可能提高诊断准确性。
• 根据2022年ESC/ERS指南，MPAd截断值为30.0 mm在预测mPAP＞20 mmHg方面具有更好的敏感性和特异性 • 建立了二元逻辑回归模型（Z = - 12.98187 + 0.31053 MPAd + 1.04863 RVFWT），其在预测mPAP＞20 mmHg时的敏感性、特异性和准确性分别为92.7%、76.9%和88.9%。 • 二元逻辑回归预测模型在预测mPAP＞20 mmHg方面优于MPAd。
