一种用于识别子宫肉瘤和不确定恶性潜能平滑肌肿瘤的临床超声算法：MYometrial Lesion UltrasouNd And mRi 研究

鉴别良性子宫平滑肌瘤与恶性肿瘤具有一定挑战性。为了评估基于临床和超声的算法在预测间充质性子宫恶性肿瘤（包括不确定恶性潜能平滑肌瘤）方面的准确性，我们报告了一项为期12个月的观察性前瞻性单中心研究的随访结果。该研究纳入了超声检查中子宫肌层病变≥3厘米的女性。患者根据症状和超声特征，采用三分类诊断算法进行分类。“白”组患者接受为期两年的年度电话随访，“绿”组患者在6、12及24个月进行临床和超声随访，“橙”组患者则接受手术。我们进一步开发了风险分类系统以评估恶性风险。共计2268名女性参与，目标病变中，2158例（95.1%）被判定为良性，58例（2.6%）为其他恶性肿瘤，52例（2.3%）为间充质性子宫恶性肿瘤。在多变量分析中，年龄（比值比1.05 [95% CI 1.03-1.07]）、肿瘤直径>8cm（比值比5.92 [95% CI 2.87-12.24]）、边缘不规则（比值比2.34 [95% CI 1.09-4.98]）、色彩分数=4（比值比2.73 [95% CI 1.28-5.82]）被确认为恶性肿瘤的独立危险因素，而声影为独立的保护因素（比值比0.39 [95% CI 0.19-0.82]）。该模型将年龄作为连续变量，病变直径二分类（截断点81mm）后，获得最佳曲线下面积（0.87 [95% CI 0.82-0.91]）。建立的风险分类系统将患者分为低风险（预测值<0.39%，恶性率0%）、中等风险（预测值0.40%-2.2%，恶性率0.8%）和高风险（预测值≥2.3%，恶性率7.6%）。该术前三分类诊断算法和风险分类系统能有效区分女性的恶性风险。如果在多中心研究中得到验证，将实现良性与间充质性子宫恶性肿瘤的差异化诊断，从而实现个性化临床管理。

Differential diagnosis between benign uterine smooth muscle tumors and malignant counterpart is challenging.To evaluate the accuracy of a clinical and ultrasound based algorithm in predicting mesenchymal uterine malignancies, including smooth muscle tumors of uncertain malignant potential.We report the 12-month follow-up of an observational, prospective, single-center study that included women with at least 1 myometrial lesion ≥3 cm on ultrasound examination. These patients were classified according to a 3-class diagnostic algorithm, using symptoms and ultrasound features. "White" patients underwent annual telephone follow-up for 2 years, "Green" patients underwent a clinical and ultrasound follow-up at 6, 12, and 24 months and "Orange" patients underwent surgery. We further developed a risk class system to stratify the malignancy risk.Two thousand two hundred sixty-eight women were included and target lesion was classified as benign in 2158 (95.1%), as other malignancies in 58 (2.6%) an as mesenchymal uterine malignancies in 52 (2.3%) patients. At multivariable analysis, age (odds ratio 1.05 [95% confidence interval 1.03-1.07]), tumor diameter >8 cm (odds ratio 5.92 [95% confidence interval 2.87-12.24]), irregular margins (odds ratio 2.34 [95% confidence interval 1.09-4.98]), color score=4 (odds ratio 2.73 [95% confidence interval 1.28-5.82]), were identified as independent risk factors for malignancies, whereas acoustic shadow resulted in an independent protective factor (odds ratio 0.39 [95% confidence interval 0.19-0.82[). The model, which included age as a continuous variable and lesion diameter as a dichotomized variable (cut-off 81 mm), provided the best area under the curve (0.87 [95% confidence interval 0.82-0.91]). A risk class system was developed, and patients were classified as low-risk (predictive model value <0.39%: 0/606 malignancies, risk 0%), intermediate risk (predictive model value 0.40%-2.2%: 9/1093 malignancies, risk 0.8%), high risk (predictive model value ≥2.3%: 43/566 malignancies, risk 7.6%).The preoperative 3-class diagnostic algorithm and risk class system can stratify women according to risk of malignancy. Our findings, if confirmed in a multicenter study, will permit differentiation between benign and mesenchymal uterine malignancies allowing a personalized clinical approach.