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Diagnostic interpretation of non-contrast qualitative MR imaging features for characterisation of uterine leiomyosarcoma.

Accepted version
Peer-reviewed

Type

Article

Change log

Authors

Sahin, Hilal 
Smith, Janette 
Zawaideh, Jeries Paolo 
Shakur, Amreen 
Carmisciano, Luca 

Abstract

OBJECTIVE: To assess the value of non-contrast MRI features for characterisation of uterine leiomyosarcoma (LMS) and differentiation from atypical benign leiomyomas. METHODS: This study included 57 atypical leiomyomas and 16 LMS which were referred pre-operatively for management review to the specialist gynaeoncology multidisciplinary team meeting. Non-contrast MRIs were retrospectively reviewed by five independent readers (three senior, two junior) and a 5-level Likert score (1-low/5-high) was assigned to each mass for likelihood of LMS. Evaluation of qualitative and quantitative MRI features was done using uni- and multivariable regression analysis. Inter-reader reliability for the assessment of MRI features was calculated by using Cohen's κ values. RESULTS: In the univariate analysis, interruption of the endometrial interface and irregular tumour shape had the highest odds ratios (ORs) (64.00, p < 0.001 and 12.00, p = 0.002, respectively) for prediction of LMS. Likert score of the mass was significant in prediction (OR, 3.14; p < 0.001) with excellent reliability between readers (ICC 0.86; 95% CI, 0.76-0.92). The post-menopausal status, interruption of endometrial interface and thickened endometrial stripe were the most predictive independent variables in multivariable estimation of the risk of leiomyosarcoma with an accuracy of 0.88 (95%CI, 0.78-0.94). CONCLUSION: At any level of expertise as a radiologist reader, the loss of the normal endometrial stripe (either thickened or not seen) in a post-menopausal patient with a myometrial mass was highly likely to be LMS. ADVANCES IN KNOWLEDGE: This study demonstrates the potential utility of non-contrast MRI features in characterisation of LMS over atypical leiomyomas, and therefore influence on optimal management of these cases.

Description

Keywords

Adult, Aged, Diagnosis, Differential, Evaluation Studies as Topic, Female, Humans, Image Interpretation, Computer-Assisted, Leiomyosarcoma, Magnetic Resonance Imaging, Middle Aged, Reproducibility of Results, Retrospective Studies, Uterine Neoplasms, Uterus

Journal Title

Br J Radiol

Conference Name

Journal ISSN

0007-1285
1748-880X

Volume Title

94

Publisher

Oxford University Press (OUP)

Rights

All rights reserved