99m Tc-MIBI myocardial imaging combined with clinical features can effectively predict coronary artery disease
CHEN Yuan
LI Dong
LUO Xiaoqin
LING Yuanna
OUYANG Wei
Abstract：Objective To develop a diagnostic prediction model for coronary artery disease(CAD)based on 99mTc-methoxyisobutylisonitrile(MIBI)gated myocardial perfusion imaging(GMPI)and clinical features,and to perform internal validation to assess its utility in predicting the risk of CAD.Methods A retrospective analysis was conducted to collect GMPI parameters and clinical characteristics of 116 patients suspected of having CAD who underwent 99mTc-MIBI SPECT/CT gated myocardial resting perfusion imaging at Zhujiang Hospital of Southern Medical University from January 2023 to November 2023.Among the patients,77 were male and 39 were female,with an age range of 23-93(62.66±12.22)years old.Predictive factors for CAD were identified using stepwise regression and multivariate logistic regression analysis,and a diagnostic prediction model was constructed and presented in the form of a nomogram.The predictive performance of the model was evaluated by calculating the area under the ROC curve(AUC).Internal validation was performed using k-fold cross-validation.The calibration and clinical utility of the model were assessed through calibration curves,decision curve analysis(DCA),and clinical impact curves.Results Stepwise regression analysis identified left ventricular end-diastolic volume,peak filling rate,histogram skewness,and histogram kurtosis among the GMPI parameters as effective diagnostic predictors of CAD.Incorporating clinical characteristics(gender,smoking history,cardiac troponin,hypertension),a predictive model was constructed with an AUC of 0.731(95%CI:0.636-0.825),specificity of 0.735,and sensitivity of 0.642.The average AUC from k-fold cross-validation was 0.699.Calibration curves demonstrated good calibration of the CAD diagnostic prediction model,while decision curve analysis and clinical impact curves indicated its high clinical utility.Conclusion The diagnostic prediction model based on 99mTc-MIBI GMPI parameters and clinical characteristics(gender,smoker,cardiac troponin,hypertension)demonstrates good performance in assessing patients with CAD,offering potential for developing more personalized diagnostic strategies for CAD.
Keywords：myocardial perfusion imagingcoronary artery diseaseprediction modelnomogram
Publication Date：2025-02-27
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 145-151 )