Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, Republic of Korea.
Department of Radiology, Soonchunhyang University Cheonan Hospital, Soonchunhyang University College of Medicine, Cheonan, Republic of Korea.
Abdom Radiol (NY). 2021 Mar;46(3):1137-1147. doi: 10.1007/s00261-020-02761-7. Epub 2020 Sep 15.
To define and weight the preoperative CT findings for ovarian torsion and to develop an integrated nomogram for estimating the probability of ovarian torsion in women with ovarian lesion and pelvic pain.
This retrospective study included 218 women with surgically resected ovarian lesions who underwent preoperative contrast-enhanced CT for pelvic pain from January 2014 to February 2019. Significant imaging findings for torsion were extracted using regression analyses and a regression coefficient-based nomogram was constructed. The diagnostic performance with sensitivity, specificity, and accuracy of the significant imaging findings and the nomogram were assessed.
A total of 255 ovarian lesions (123 lesions with torsion and 132 lesions without torsion) were evaluated. Multivariable regression analysis showed that whirl sign (odds ratio [OR] 11.000; p < 0.001), tubal thickening (OR 4.621; p = 0.001), unusual location of ovarian lesion (OR 2.712; p = 0.020), and hemorrhagic component within adnexal lesion (OR 2.537; p = 0.028) were independent significant parameters predicting ovarian torsion. Tubal thickening showed the highest sensitivity (91.1%) and whirl sign showed the highest specificity (94.7%). When probabilities of ovarian torsion of 0.5 or more in the nomogram were diagnosed as ovarian torsion, sensitivity, specificity, and accuracy of the nomogram were 78.1%, 91.7%, and 85.1%, respectively.
The whirl sign, tubal thickening, unusual location of ovarian lesion, and hemorrhagic component within adnexal lesion, and an integrated nomogram derived from these significant findings can be useful for predicting ovarian torsion.
定义并加权卵巢扭转的术前 CT 表现，并为有卵巢病变和盆腔疼痛的女性开发一种综合列线图来估计卵巢扭转的概率。
本回顾性研究纳入了 218 名因盆腔疼痛接受术前增强 CT 检查并手术切除卵巢病变的女性，时间为 2014 年 1 月至 2019 年 2 月。使用回归分析提取扭转的显著影像学表现，并构建基于回归系数的列线图。评估显著影像学表现和列线图的诊断性能，包括敏感性、特异性和准确性。
共评估了 255 个卵巢病变（123 个扭转病变和 132 个非扭转病变）。多变量回归分析表明，漩涡征（优势比 [OR] 11.000；p<0.001）、输卵管增厚（OR 4.621；p=0.001）、卵巢病变的异常位置（OR 2.712；p=0.020）和附件病变内出血成分（OR 2.537；p=0.028）是预测卵巢扭转的独立显著参数。输卵管增厚的敏感性最高（91.1%），漩涡征的特异性最高（94.7%）。当列线图中卵巢扭转的概率为 0.5 或更高时，列线图的敏感性、特异性和准确性分别为 78.1%、91.7%和 85.1%。
漩涡征、输卵管增厚、卵巢病变的异常位置、附件病变内出血成分以及由此得出的综合列线图可用于预测卵巢扭转。
