Department of Nuclear Medicine, The Third Affiliated Hospital of Soochow University, No.185, Juqian Street, Changzhou, 213003, Jiangsu Province, China.
The Nuclear Medicine and Molecular Imaging Clinical Translation Institute of Soochow University, Changzhou, Jiangsu Province, China.
BMC Cardiovasc Disord. 2022 Jun 15;22(1):268. doi: 10.1186/s12872-022-02712-8.
The rest-only single photon emission computerized tomography (SPECT) myocardial perfusion imaging (MPI) had low sensitivity in diagnosing obstructive coronary artery disease (CAD). Improving the efficacy of resting MPI in diagnosing CAD has important clinical significance for patients with contraindications to stress. The purpose of this study was to develop and validate a model predicting obstructive CAD in suspected CAD patients, based on rest-only MPI and cardiovascular risk factors.
A consecutive retrospective cohort of 260 suspected CAD patients who underwent rest-only gated SPECT MPI and coronary angiography was constructed. All enrolled patients had stress MPI contraindications. Clinical data such as age and gender were collected. Automated quantitative analysis software QPS and QGS were used to evaluate myocardial perfusion and function parameters. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used to select the variables and build the prediction model.
Among the enrolled 260 patients with suspected CAD, there were 95 (36.5%, 95/260) patients with obstructive CAD. The prediction model was presented in the form of a nomogram and developed based on selected predictors, including age, sex, SRS ≥ 4, SMS ≥ 2, STS ≥ 2, hypertension, diabetes, and hyperlipidemia. The AUC of the prediction model was 0.795 (95% CI: 0.741-0.843), which was better than the traditional models. The AUC calculated by enhanced bootstrapping validation (500 bootstrap resamples) was 0.785. Subsequently, the calibration curve (intercept = - 0.106; slope = 0.843) showed a good calibration of the model. The decision curve analysis (DCA) shows that the constructed clinical prediction model had good clinical applications.
In patients with suspected CAD and contraindications to stress MPI, a prediction model based on rest-only ECG-gated SPECT MPI and cardiovascular risk factors have been developed and validated to predict obstructive CAD effectively.
仅行静息单光子发射计算机断层扫描（SPECT）心肌灌注显像（MPI）诊断阻塞性冠状动脉疾病（CAD）的敏感性较低。提高静息 MPI 诊断 CAD 的效能对于有应激禁忌的患者具有重要的临床意义。本研究旨在建立并验证一种基于仅行静息 MPI 和心血管危险因素预测可疑 CAD 患者中阻塞性 CAD 的模型。
构建了一个连续回顾性队列，共纳入 260 例因应激禁忌而行仅行静息门控 SPECT MPI 和冠状动脉造影的可疑 CAD 患者。收集所有入组患者的年龄和性别等临床数据。采用自动化定量分析软件 QPS 和 QGS 评估心肌灌注和功能参数。采用最小绝对收缩和选择算子（LASSO）和多变量逻辑回归筛选变量并构建预测模型。
在 260 例可疑 CAD 患者中，有 95 例（36.5%，95/260）患者存在阻塞性 CAD。该预测模型以列线图的形式呈现，基于选定的预测因子构建，包括年龄、性别、SRS≥4、SMS≥2、STS≥2、高血压、糖尿病和高脂血症。预测模型的 AUC 为 0.795（95%CI：0.741-0.843），优于传统模型。通过增强bootstrap 验证（500 次 bootstrap 重采样）计算的 AUC 为 0.785。随后，校准曲线（截距=-0.106；斜率=0.843）显示模型具有良好的校准度。决策曲线分析（DCA）表明所构建的临床预测模型具有良好的临床应用价值。
在因应激禁忌而行仅行静息心电图门控 SPECT MPI 的可疑 CAD 患者中，建立并验证了一种基于仅行静息 ECG-gated SPECT MPI 和心血管危险因素的预测模型，可有效预测阻塞性 CAD。
