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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.

2024-04Text Open access
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dc.contributor.authorFreitas, Patrícia
dc.contributor.authorResende-Neves, Teresa
dc.contributor.authorLameira, Pedro
dc.contributor.authorCosta, Marta
dc.contributor.authorDias, Paulo
dc.contributor.authorFilipe, Juliana
dc.contributor.authorFerreira, Joana
dc.contributor.authorFélix, Ana
dc.contributor.authorCunha, Teresa Margarida
dc.date.accessioned2025-10-24T15:15:11Z
dc.date.available2025-10-24T15:15:11Z
dc.date.issued2024-04
dc.description.abstractPurpose: 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). 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. 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 × 10-3 mm2/s (p = 0.002). Conclusion: With our work, we demonstrate the presence of seven MRI features that are statistically significant in differentiating between LMS and ALM.eng
dc.identifier.citationArch Gynecol Obstet . 2024 Apr;309(4):1551-1560. doi: 10.1007/s00404-023-07294-0.
dc.identifier.doi10.1007/s00404-023-07294-0.
dc.identifier.pmid38055011
dc.identifier.urihttp://hdl.handle.net/10400.17/5194
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectHSJ IMA
dc.subjectHCC IMA
dc.subjectHSM IMA
dc.subjectFemale
dc.subjectHumans
dc.subjectPortugal
dc.subjectNecrosis
dc.subjectDiagnosis
dc.subjectDifferential
dc.subjectDiffusion Magnetic Resonance Imaging
dc.subjectLeiomyoma* / pathology
dc.subjectLeiomyosarcoma* / diagnostic imaging
dc.subjectLeiomyosarcoma* / pathology
dc.subjectMagnetic Resonance Imaging / methods
dc.subjectMyometrium / pathology
dc.subjectRetrospective Studies
dc.subjectSmooth Muscle Tumor* / diagnostic imaging
dc.subjectSmooth Muscle Tumor* / pathology
dc.subjectUterine Neoplasms* / pathology
dc.titleSmooth Muscle Tumours of the Uterus: MR Imaging Malignant Predictive Features-a 12-Year Analysis in a Referral Hospital in Portugal.eng
dc.typetext
dspace.entity.typePublication
oaire.citation.endPage1560
oaire.citation.issue4
oaire.citation.startPage1551
oaire.citation.titleArchives of Gynecology and Obstetrics
oaire.citation.volume309
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85

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