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Diagnostic Performance of MRI to Differentiate Uterine Leiomyosarcoma from Benign Leiomyoma: A Meta-Analysis

PURPOSE: To perform a meta-analysis comparing the diagnostic performance of increased signal intensity on T1- and T2-weighted magnetic resonance images and apparent diffusion coefficient (ADC) values in differentiating uterine leiomyosarcoma (LMS) from benign leiomyoma (LM). METHODS: A systematic li...

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Autores principales: Virarkar, Mayur, Diab, Radwan, Palmquist, Sarah, Bassett, Roland, Bhosale, Priya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Ubiquity Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7693867/
https://www.ncbi.nlm.nih.gov/pubmed/33283149
http://dx.doi.org/10.5334/jbsr.2275
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author Virarkar, Mayur
Diab, Radwan
Palmquist, Sarah
Bassett, Roland
Bhosale, Priya
author_facet Virarkar, Mayur
Diab, Radwan
Palmquist, Sarah
Bassett, Roland
Bhosale, Priya
author_sort Virarkar, Mayur
collection PubMed
description PURPOSE: To perform a meta-analysis comparing the diagnostic performance of increased signal intensity on T1- and T2-weighted magnetic resonance images and apparent diffusion coefficient (ADC) values in differentiating uterine leiomyosarcoma (LMS) from benign leiomyoma (LM). METHODS: A systematic literature search for original studies was performed using PubMed/MEDLINE, the Cochrane Library, Embase, and Web of Science. Data necessary for the meta-analysis was extracted from the selected articles and analyzed. RESULTS: Eight studies with 795 patients met our predefined inclusion criteria and were included in the analysis. Increased signal on T1-weighted imaging had a pooled sensitivity of 56.8% (95% CI: 20%–87.4%) for LMS (n = 60) which was significantly higher than 7.6% (95% CI: 2.2%–22.7%) for LM (n = 1272) (p = 0.0094). Increased signal analysis on T2-weighted imaging had a pooled sensitivities of 93.2% and 93.2% (95% CI: 45.7%–99.6% and 42.9%–99.6%) for LMS (n = 90), which were not significantly different from the 54.5% and 53.9% (95% CI: 33.6%–74%, 32%–74%) for LM (n = 215) (p = 0.102 and 0.112). On ADC value analysis, LMS (n = 43) had a weighted mean and standard deviation of 0.896 ± 0.19 10(–3) mm(2)/s, 0.929 ± 0.182 10(–3) mm(2)/s, which were significantly lower from 1.258 ± 0.303 10(–3) mm(2)/s, 1.304 ± 0.303 10(–3) mm(2)/s for LM (n = 159) (p = < 0.0001, < 0.0001). CONCLUSION: Our meta-analysis demonstrated that high signal intensity on T1-weighted images and low ADC values can accurately differentiate LMS from LM. Although, LMS had a higher pooled sensitivity for T2-weighted increased signal intensity compared to LM, there was no statistical significance.
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spelling pubmed-76938672020-12-04 Diagnostic Performance of MRI to Differentiate Uterine Leiomyosarcoma from Benign Leiomyoma: A Meta-Analysis Virarkar, Mayur Diab, Radwan Palmquist, Sarah Bassett, Roland Bhosale, Priya J Belg Soc Radiol Original Article PURPOSE: To perform a meta-analysis comparing the diagnostic performance of increased signal intensity on T1- and T2-weighted magnetic resonance images and apparent diffusion coefficient (ADC) values in differentiating uterine leiomyosarcoma (LMS) from benign leiomyoma (LM). METHODS: A systematic literature search for original studies was performed using PubMed/MEDLINE, the Cochrane Library, Embase, and Web of Science. Data necessary for the meta-analysis was extracted from the selected articles and analyzed. RESULTS: Eight studies with 795 patients met our predefined inclusion criteria and were included in the analysis. Increased signal on T1-weighted imaging had a pooled sensitivity of 56.8% (95% CI: 20%–87.4%) for LMS (n = 60) which was significantly higher than 7.6% (95% CI: 2.2%–22.7%) for LM (n = 1272) (p = 0.0094). Increased signal analysis on T2-weighted imaging had a pooled sensitivities of 93.2% and 93.2% (95% CI: 45.7%–99.6% and 42.9%–99.6%) for LMS (n = 90), which were not significantly different from the 54.5% and 53.9% (95% CI: 33.6%–74%, 32%–74%) for LM (n = 215) (p = 0.102 and 0.112). On ADC value analysis, LMS (n = 43) had a weighted mean and standard deviation of 0.896 ± 0.19 10(–3) mm(2)/s, 0.929 ± 0.182 10(–3) mm(2)/s, which were significantly lower from 1.258 ± 0.303 10(–3) mm(2)/s, 1.304 ± 0.303 10(–3) mm(2)/s for LM (n = 159) (p = < 0.0001, < 0.0001). CONCLUSION: Our meta-analysis demonstrated that high signal intensity on T1-weighted images and low ADC values can accurately differentiate LMS from LM. Although, LMS had a higher pooled sensitivity for T2-weighted increased signal intensity compared to LM, there was no statistical significance. Ubiquity Press 2020-11-24 /pmc/articles/PMC7693867/ /pubmed/33283149 http://dx.doi.org/10.5334/jbsr.2275 Text en Copyright: © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/.
spellingShingle Original Article
Virarkar, Mayur
Diab, Radwan
Palmquist, Sarah
Bassett, Roland
Bhosale, Priya
Diagnostic Performance of MRI to Differentiate Uterine Leiomyosarcoma from Benign Leiomyoma: A Meta-Analysis
title Diagnostic Performance of MRI to Differentiate Uterine Leiomyosarcoma from Benign Leiomyoma: A Meta-Analysis
title_full Diagnostic Performance of MRI to Differentiate Uterine Leiomyosarcoma from Benign Leiomyoma: A Meta-Analysis
title_fullStr Diagnostic Performance of MRI to Differentiate Uterine Leiomyosarcoma from Benign Leiomyoma: A Meta-Analysis
title_full_unstemmed Diagnostic Performance of MRI to Differentiate Uterine Leiomyosarcoma from Benign Leiomyoma: A Meta-Analysis
title_short Diagnostic Performance of MRI to Differentiate Uterine Leiomyosarcoma from Benign Leiomyoma: A Meta-Analysis
title_sort diagnostic performance of mri to differentiate uterine leiomyosarcoma from benign leiomyoma: a meta-analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7693867/
https://www.ncbi.nlm.nih.gov/pubmed/33283149
http://dx.doi.org/10.5334/jbsr.2275
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