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Smooth muscle tumours of the uterus: MR imaging malignant predictive features-a 12-year analysis in a referral hospital in Portugal.
- Source :
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Archives of gynecology and obstetrics [Arch Gynecol Obstet] 2024 Apr; Vol. 309 (4), pp. 1551-1560. Date of Electronic Publication: 2023 Dec 06. - Publication Year :
- 2024
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Abstract
- Purpose: To evaluate the magnetic resonance imaging (MRI) features that may help distinguish leiomyosarcomas from atypical leiomyomas (those presenting hyperintensity on T2-W images equal or superior to 50% compared to the myometrium).<br />Materials and Methods: The authors conducted a retrospective single-centre study that included a total of 57 women diagnosed with smooth muscle tumour of the uterus, who were evaluated with pelvic MRI, between January 2009 and March 2020. All cases had a histologically proven diagnosis (31 Atypical Leiomyomas-ALM; 26 Leiomyosarcomas-LMS). The MRI features evaluated in this study included: age at presentation, dimension, contours, intra-tumoral haemorrhagic areas, T2-WI heterogeneity, T2-WI dark areas, flow voids, cyst areas, necrosis, restriction on diffusion-weighted imaging (DWI), apparent diffusion coefficient (ADC) values, signal intensity and heterogeneity after contrast administration in T1-WI, presence and location of unenhanced areas. The association between the MRI characteristics and the histological subtype was evaluated using Chi-Square and ANOVA tests.<br />Results: The MRI parameters that showed a statistically significance correlation with malignant histology and thus most strongly associated with LMS were found to be: irregular contours (p < 0.001), intra-tumoral haemorrhagic areas (p = 0.028), T2-WI dark areas (p = 0.016), high signal intensity after contrast administration (p = 0.005), necrosis (p = 0.001), central location for unenhanced areas (p = 0.026), and ADC value lower than 0.88 × 10 <superscript>-3</superscript> mm <superscript>2</superscript> /s (p = 0.002).<br />Conclusion: With our work, we demonstrate the presence of seven MRI features that are statistically significant in differentiating between LMS and ALM.<br /> (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)
- Subjects :
- Female
Humans
Retrospective Studies
Portugal
Magnetic Resonance Imaging methods
Diffusion Magnetic Resonance Imaging
Myometrium pathology
Diagnosis, Differential
Necrosis
Leiomyosarcoma diagnostic imaging
Leiomyosarcoma pathology
Smooth Muscle Tumor diagnostic imaging
Smooth Muscle Tumor pathology
Uterine Neoplasms pathology
Leiomyoma pathology
Subjects
Details
- Language :
- English
- ISSN :
- 1432-0711
- Volume :
- 309
- Issue :
- 4
- Database :
- MEDLINE
- Journal :
- Archives of gynecology and obstetrics
- Publication Type :
- Academic Journal
- Accession number :
- 38055011
- Full Text :
- https://doi.org/10.1007/s00404-023-07294-0