医学
旁体
子宫内膜异位症
接收机工作特性
弹性成像
泌尿科
阴道
核医学
妇科
内科学
外科
放射科
超声波
子宫颈
癌症
作者
Anjeza Xholli,Ambrogio P. Londero,Elena Cavalli,Umberto Scovazzi,Mattia Francesco Ferraro,Ilaria Vacca,Maria Giulia Schiaffino,Francesca Oppedisano,Giorgio Sirito,Filippo Molinari,Angelo Cagnacci
出处
期刊:Ultraschall in Der Medizin
[Georg Thieme Verlag KG]
日期:2023-02-06
卷期号:45 (01): 69-76
被引量:6
摘要
Abstract Objectives This study aimed to evaluate elastography features of deep infiltrating endometriosis (DIE), and to define whether this technique may discriminate lesions from surrounding non-endometriotic tissue. Methods This was an exploratory observational study on women affected by DIE treated in a third-level academic hospital gynaecology outpatient facility between 2020 and 2021. Strain elastography (SE) was conducted via transvaginal probe. Tissue deformation of DIE and surrounding tissue was expressed as percentage tissue deformation or as subjective colour score (CS; from blue=stiff to red=soft, assigned numerical values from 0 to 3). Ratios of normal tissue/DIE were compared to ratio of normal tissue/stiffer normal tissue area. Results Evaluations were performed on 46 DIE nodules and surrounding tissue of the uterosacral ligaments (n=21), parametrium (n=7), rectum (n=14), and recto-vaginal septum (n =4). Irrespective of location, DIE strain ratio (3.09, IQR 2.38–4.14 vs. 1.25, IQR 1.11–1.48; p<0.001) and CS ratio (4.62, IQR 3.83–6.94 vs. 1.13, IQR 1.06–1.29; p<0.001) was significantly higher than that of normal tissue. ROC AUC of CS ratio was higher than ROC AUC of strain ratio (99.76%, CI.95 99.26–100% vs. 91.35%, CI.95 85.23–97.47%; p=0.007), and best ROC threshold for CS ratio was 1.82, with a sensitivity of 97.83% (CI.95 93.48–100%) and a specificity of 100% (CI.95 100–100%). Conclusions Both strain and CS ratios accurately distinguish DIE nodules at various locations. Applications of elastography in improving the diagnosis DIE, in distinguishing different DIE lesions and in monitoring DIE evolution can be envisioned and are worthy of further evaluation.
科研通智能强力驱动
Strongly Powered by AbleSci AI