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Differentiating cellular leiomyoma from uterine sarcoma and atypical leiomyoma using multi-parametric MRI

OBJECTIVES: To evaluate the diagnostic performance of conventional magnetic resonance imaging (cMRI) combined with diffusion-weighted MRI (DWI) in discrimination of cellular leiomyoma, uterine sarcoma, and atypical leiomyoma. METHODS: This retrospective study enrolled 106 patients with uterine masse...

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Autores principales: Wang, Cong, Zheng, Xianying, Zhou, Zuofu, Shi, Yuequan, Wu, Qin, Lin, Kaiwu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9582758/
https://www.ncbi.nlm.nih.gov/pubmed/36276145
http://dx.doi.org/10.3389/fonc.2022.1005191
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author Wang, Cong
Zheng, Xianying
Zhou, Zuofu
Shi, Yuequan
Wu, Qin
Lin, Kaiwu
author_facet Wang, Cong
Zheng, Xianying
Zhou, Zuofu
Shi, Yuequan
Wu, Qin
Lin, Kaiwu
author_sort Wang, Cong
collection PubMed
description OBJECTIVES: To evaluate the diagnostic performance of conventional magnetic resonance imaging (cMRI) combined with diffusion-weighted MRI (DWI) in discrimination of cellular leiomyoma, uterine sarcoma, and atypical leiomyoma. METHODS: This retrospective study enrolled 106 patients with uterine masses, including 51 cellular leiomyomas (CLs), 32 uterine sarcomas (USs) and 23 degenerated leiomyomas (LMs) confirmed by histopathologic examination. Clinical data and imaging findings were assessed. Chi-squared test for qualitative variables and one way ANOVA analysis for quantitative variables were performed. Logistic regression analysis and the receiver operating characteristic (ROC) analysis were performed to determine the cut-off point and diagnostic performances for significant numeric values or multiple models. RESULTS: Morphology (Odds ratio [OR] = 6.36) and margin (OR = 13.84) derived from cMRI were independent indicators for differentiating CLs from USs, and T2WI signal (OR = 0.23) were an independent indicator for differentiating CLs from degenerated LMs (all P < 0.05). The cutoff value of apparent diffusion coefficient (ADC) derived from DWI for differentiating CLs from USs was 839 ×10(-6) mm(2)/sec and was 1239 ×10(-6) mm(2)/sec for differentiating CLs from degenerated LMs. Compared with the use of cMRI features and ADC value alone, combination of independent indicators and ADC value achieved higher AUCs for both differentiations (all P < 0.05). CONCLUSIONS: cMRI is a reliable tool for differentiating CLs from USs and atypical leiomyoma, especially degenerated LMs. The combined use of cMRI and DWI can improve the differential diagnostic performance.
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spelling pubmed-95827582022-10-21 Differentiating cellular leiomyoma from uterine sarcoma and atypical leiomyoma using multi-parametric MRI Wang, Cong Zheng, Xianying Zhou, Zuofu Shi, Yuequan Wu, Qin Lin, Kaiwu Front Oncol Oncology OBJECTIVES: To evaluate the diagnostic performance of conventional magnetic resonance imaging (cMRI) combined with diffusion-weighted MRI (DWI) in discrimination of cellular leiomyoma, uterine sarcoma, and atypical leiomyoma. METHODS: This retrospective study enrolled 106 patients with uterine masses, including 51 cellular leiomyomas (CLs), 32 uterine sarcomas (USs) and 23 degenerated leiomyomas (LMs) confirmed by histopathologic examination. Clinical data and imaging findings were assessed. Chi-squared test for qualitative variables and one way ANOVA analysis for quantitative variables were performed. Logistic regression analysis and the receiver operating characteristic (ROC) analysis were performed to determine the cut-off point and diagnostic performances for significant numeric values or multiple models. RESULTS: Morphology (Odds ratio [OR] = 6.36) and margin (OR = 13.84) derived from cMRI were independent indicators for differentiating CLs from USs, and T2WI signal (OR = 0.23) were an independent indicator for differentiating CLs from degenerated LMs (all P < 0.05). The cutoff value of apparent diffusion coefficient (ADC) derived from DWI for differentiating CLs from USs was 839 ×10(-6) mm(2)/sec and was 1239 ×10(-6) mm(2)/sec for differentiating CLs from degenerated LMs. Compared with the use of cMRI features and ADC value alone, combination of independent indicators and ADC value achieved higher AUCs for both differentiations (all P < 0.05). CONCLUSIONS: cMRI is a reliable tool for differentiating CLs from USs and atypical leiomyoma, especially degenerated LMs. The combined use of cMRI and DWI can improve the differential diagnostic performance. Frontiers Media S.A. 2022-10-06 /pmc/articles/PMC9582758/ /pubmed/36276145 http://dx.doi.org/10.3389/fonc.2022.1005191 Text en Copyright © 2022 Wang, Zheng, Zhou, Shi, Wu and Lin https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Wang, Cong
Zheng, Xianying
Zhou, Zuofu
Shi, Yuequan
Wu, Qin
Lin, Kaiwu
Differentiating cellular leiomyoma from uterine sarcoma and atypical leiomyoma using multi-parametric MRI
title Differentiating cellular leiomyoma from uterine sarcoma and atypical leiomyoma using multi-parametric MRI
title_full Differentiating cellular leiomyoma from uterine sarcoma and atypical leiomyoma using multi-parametric MRI
title_fullStr Differentiating cellular leiomyoma from uterine sarcoma and atypical leiomyoma using multi-parametric MRI
title_full_unstemmed Differentiating cellular leiomyoma from uterine sarcoma and atypical leiomyoma using multi-parametric MRI
title_short Differentiating cellular leiomyoma from uterine sarcoma and atypical leiomyoma using multi-parametric MRI
title_sort differentiating cellular leiomyoma from uterine sarcoma and atypical leiomyoma using multi-parametric mri
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9582758/
https://www.ncbi.nlm.nih.gov/pubmed/36276145
http://dx.doi.org/10.3389/fonc.2022.1005191
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