Developing an Ultrasound Scoring System for Adenomyosis Based on Morphological Uterus Sonographic Assessment (MUSA)

目的：基于子宫形态学超声评估共识(Morphological Uterus Sonographic Assessment, MUSA)中描述的9种超声征象，构建并验证子宫腺肌病子宫超声评分系统。资料与方法：选取2023年1月~2024年6月于青岛大学附属医院因良性子宫肌层病变行全子宫切除术患者，收集其临床病理资料，评估二维经阴超声图像中9种MUSA征象的存在情况，计算各征象的敏感性、特异性、阳性预测值(PPV)、阴性预测值(NPV)及对应的95%置信区间(95%CI)。将患者随机分为训练队列和测试队列(7:3)，对训练队列通过Firth回归分析评估每种征象的回归系数并赋分，绘制受试者工作特征曲线(ROC)，确定最佳截断值。随后应用Bootstrap方法在测试队列中进行内部验证。结果：岛样高回声、贯穿血流、JZ区中断或不规则的评分权重较高。训练队列中，ROC的曲线下面积(AUC)为0.907，敏感性为75.0%，特异性为89.9%，PPV为88.1%，NPV为78.4%；测试队列中，AUC为0.873，敏感性为79.6%，特异性为83.6%，PPV为82.7%，NPV为80.7%。结论：基于MUSA共识的超声评分系统对于子宫腺肌病具有较高的诊断性能，有利于统一术语和量化标准，提高超声诊断的一致性和准确性。Objective: To construct and validate a uterine ultrasound scoring system for adenomyosis, based on the nine sonographic features described in the Morphological Uterus Sonographic Assessment (MUSA) consensus. Materials and Methods: We retrospectively enrolled patients who underwent total hysterectomy for benign uterine myometrial lesions at The Affiliated Hospital of Qingdao University between January 2023 and June 2024. Clinical and pathological data were collected, and two-dimensional transvaginal ultrasound images were reviewed for the presence of each of the nine MUSA features. For each feature, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and their corresponding 95% confidence intervals (95%CI) were calculated. Patients were randomly split into a training cohort and a validation cohort (7:3). In the training cohort, Firth regression analysis was used to estimate regression coefficients for each feature, which were then converted into item scores. Receiver operating characteristic (ROC) curves were plotted to determine the optimal cut-off. Internal validation in the test cohort was performed using the Bootstrap method. Results: Islands of hyperechogenicity, penetrating vessels, and interruption or irregularity of the JZ zone carried the highest weighting in the scoring system. In the training cohort, the area under the ROC curve (AUC) was 0.907, with a sensitivity of 75.0%, specificity of 89.9%, PPV of 88.1%, and NPV of 78.4%. In the validation cohort, the AUC was 0.873, with a sensitivity of 79.6%, specificity of 83.6%, PPV of 82.7%, and NPV of 80.7%. Conclusion: The ultrasound scoring system for adenomyosis, derived from the MUSA consensus, demonstrates high diagnostic performance. It facilitates standardized terminology and quantitative assessment, thereby improving consistency and accuracy in sonographic diagnosis.