Diagnostic interpretation of non-contrast qualitative MR imaging features for characterisation of uterine leiomyosarcoma.
Br J Radiol
; 94(1125): 20210115, 2021 Sep 01.
Article
em En
| MEDLINE
| ID: mdl-34111973
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.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias Uterinas
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Imageamento por Ressonância Magnética
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Interpretação de Imagem Assistida por Computador
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Leiomiossarcoma
Tipo de estudo:
Diagnostic_studies
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Evaluation_studies
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Observational_studies
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Prognostic_studies
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Qualitative_research
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Risk_factors_studies
Limite:
Adult
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Aged
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Female
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Humans
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Middle aged
Idioma:
En
Revista:
Br J Radiol
Ano de publicação:
2021
Tipo de documento:
Article