Department of Medical Imaging, Henan Provincial People's Hospital & Zhengzhou University People's Hospital, Zhengzhou, China.
Laboratory of Brain Science and Brain-Like Intelligence Technology, Institute for Integrated Medical Science and Engineering, Henan Academy of Sciences, Zhengzhou, China.
Cancer Imaging. 2024 Mar 4;24(1):33. doi: 10.1186/s40644-024-00677-9.
To differentiate benign and malignant solitary pulmonary lesions (SPLs) by amide proton transfer-weighted imaging (APTWI), mono-exponential model DWI (MEM-DWI), stretched exponential model DWI (SEM-DWI), and F-FDG PET-derived parameters.
A total of 120 SPLs patients underwent chest F-FDG PET/MRI were enrolled, including 84 in the training set (28 benign and 56 malignant) and 36 in the test set (13 benign and 23 malignant). MTRasym(3.5 ppm), ADC, DDC, α, SUV, MTV, and TLG were compared. The area under receiver-operator characteristic curve (AUC) was used to assess diagnostic efficacy. The Logistic regression analysis was used to identify independent predictors and establish prediction model.
SUV, MTV, TLG, α, and MTRasym(3.5 ppm) values were significantly lower and ADC, DDC values were significantly higher in benign SPLs than malignant SPLs (all P < 0.01). SUV, ADC, and MTRasym(3.5 ppm) were independent predictors. Within the training set, the prediction model based on these independent predictors demonstrated optimal diagnostic efficacy (AUC, 0.976; sensitivity, 94.64%; specificity, 92.86%), surpassing any single parameter with statistical significance. Similarly, within the test set, the prediction model exhibited optimal diagnostic efficacy. The calibration curves and DCA revealed that the prediction model not only had good consistency but was also able to provide a significant benefit to the related patients, both in the training and test sets.
The SUV, ADC, and MTRasym(3.5 ppm) were independent predictors for differentiation of benign and malignant SPLs, and the prediction model based on them had an optimal diagnostic efficacy.
通过酰胺质子转移加权成像（APTWI）、单指数模型弥散加权成像（MEM-DWI）、拉伸指数模型弥散加权成像（SEM-DWI）和 F-FDG PET 衍生参数区分良性和恶性孤立性肺病变（SPL）。
共纳入 120 例接受胸部 F-FDG PET/MRI 的 SPL 患者，包括训练集 84 例（28 例良性，56 例恶性）和测试集 36 例（13 例良性，23 例恶性）。比较 MTRasym（3.5 ppm）、ADC、DDC、α、SUV、MTV 和 TLG。采用受试者工作特征曲线（ROC）下面积（AUC）评估诊断效能。采用 Logistic 回归分析识别独立预测因子并建立预测模型。
良性 SPL 的 SUV、MTV、TLG、α 和 MTRasym（3.5 ppm）值显著低于恶性 SPL，ADC、DDC 值显著高于恶性 SPL（均 P < 0.01）。SUV、ADC 和 MTRasym（3.5 ppm）是独立的预测因子。在训练集中，基于这些独立预测因子的预测模型显示出最佳的诊断效能（AUC：0.976；敏感性：94.64%；特异性：92.86%），具有统计学意义，优于任何单一参数。同样，在测试集中，预测模型也显示出最佳的诊断效能。校准曲线和 DCA 表明，该预测模型不仅具有良好的一致性，而且在训练集和测试集中均能为相关患者提供显著的获益。
SUV、ADC 和 MTRasym（3.5 ppm）是区分良性和恶性 SPL 的独立预测因子，基于这些因素的预测模型具有最佳的诊断效能。
