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Diagnostic Performance of US and MRI in Predicting Malignancy of Soft Tissue Masses: Using a Scoring System

OBJECTIVE: To assess the diagnostic performance of US and MRI in predicting malignancy of soft tissue masses by using a scoring system. METHODS: A total of 120 cases of pathologically confirmed soft tissue masses (71 cases of malignant lesions and 49 cases of benign lesions) were enrolled. All patie...

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Autores principales: Shu, Hua, Ma, Qian, Li, Ao, Wang, Pingping, Gao, Yingqian, Yao, Qiyu, Hu, Yu, Ye, Xinhua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104333/
https://www.ncbi.nlm.nih.gov/pubmed/35574339
http://dx.doi.org/10.3389/fonc.2022.853232
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author Shu, Hua
Ma, Qian
Li, Ao
Wang, Pingping
Gao, Yingqian
Yao, Qiyu
Hu, Yu
Ye, Xinhua
author_facet Shu, Hua
Ma, Qian
Li, Ao
Wang, Pingping
Gao, Yingqian
Yao, Qiyu
Hu, Yu
Ye, Xinhua
author_sort Shu, Hua
collection PubMed
description OBJECTIVE: To assess the diagnostic performance of US and MRI in predicting malignancy of soft tissue masses by using a scoring system. METHODS: A total of 120 cases of pathologically confirmed soft tissue masses (71 cases of malignant lesions and 49 cases of benign lesions) were enrolled. All patients underwent ultrasound and MRI examination prior to biopsy or surgical excision. A scoring system based on the parameters of conventional US and MRI to distinguish malignant and benign masses was established by the regression model. The receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of US and MRI. RESULTS: Multivariate analysis showed that margin, maximum diameter, and vascular density were independent predictors for malignancy found by US, while maximum diameter, margin, and affected peripheral soft tissue were independent predictors for malignancy found by MRI. The mean scores of the benign and malignant groups were 2.8 ± 1.6, 5.1 ± 1.1 on US and 1.3 ± 1.2, 3.5 ± 0.9 on MRI. Based on the cut-off score of 3.5 and 2.5 calculated by ROC analysis, US and MRI had 92% and 87% sensitivity, 72% and 76% specificity, 86% and 89% accuracy, respectively. The combination of these two modalities achieved the sensitivity of 91%, specificity of 82%, and accuracy of 93%. CONCLUSIONS: Both US and MRI can provide valuable information about the differential diagnosis between benign and malignant soft tissue masses. The combination of the two imaging-based scoring systems can increase the diagnostic performance, especially in specificity.
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spelling pubmed-91043332022-05-14 Diagnostic Performance of US and MRI in Predicting Malignancy of Soft Tissue Masses: Using a Scoring System Shu, Hua Ma, Qian Li, Ao Wang, Pingping Gao, Yingqian Yao, Qiyu Hu, Yu Ye, Xinhua Front Oncol Oncology OBJECTIVE: To assess the diagnostic performance of US and MRI in predicting malignancy of soft tissue masses by using a scoring system. METHODS: A total of 120 cases of pathologically confirmed soft tissue masses (71 cases of malignant lesions and 49 cases of benign lesions) were enrolled. All patients underwent ultrasound and MRI examination prior to biopsy or surgical excision. A scoring system based on the parameters of conventional US and MRI to distinguish malignant and benign masses was established by the regression model. The receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of US and MRI. RESULTS: Multivariate analysis showed that margin, maximum diameter, and vascular density were independent predictors for malignancy found by US, while maximum diameter, margin, and affected peripheral soft tissue were independent predictors for malignancy found by MRI. The mean scores of the benign and malignant groups were 2.8 ± 1.6, 5.1 ± 1.1 on US and 1.3 ± 1.2, 3.5 ± 0.9 on MRI. Based on the cut-off score of 3.5 and 2.5 calculated by ROC analysis, US and MRI had 92% and 87% sensitivity, 72% and 76% specificity, 86% and 89% accuracy, respectively. The combination of these two modalities achieved the sensitivity of 91%, specificity of 82%, and accuracy of 93%. CONCLUSIONS: Both US and MRI can provide valuable information about the differential diagnosis between benign and malignant soft tissue masses. The combination of the two imaging-based scoring systems can increase the diagnostic performance, especially in specificity. Frontiers Media S.A. 2022-04-29 /pmc/articles/PMC9104333/ /pubmed/35574339 http://dx.doi.org/10.3389/fonc.2022.853232 Text en Copyright © 2022 Shu, Ma, Li, Wang, Gao, Yao, Hu and Ye 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
Shu, Hua
Ma, Qian
Li, Ao
Wang, Pingping
Gao, Yingqian
Yao, Qiyu
Hu, Yu
Ye, Xinhua
Diagnostic Performance of US and MRI in Predicting Malignancy of Soft Tissue Masses: Using a Scoring System
title Diagnostic Performance of US and MRI in Predicting Malignancy of Soft Tissue Masses: Using a Scoring System
title_full Diagnostic Performance of US and MRI in Predicting Malignancy of Soft Tissue Masses: Using a Scoring System
title_fullStr Diagnostic Performance of US and MRI in Predicting Malignancy of Soft Tissue Masses: Using a Scoring System
title_full_unstemmed Diagnostic Performance of US and MRI in Predicting Malignancy of Soft Tissue Masses: Using a Scoring System
title_short Diagnostic Performance of US and MRI in Predicting Malignancy of Soft Tissue Masses: Using a Scoring System
title_sort diagnostic performance of us and mri in predicting malignancy of soft tissue masses: using a scoring system
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9104333/
https://www.ncbi.nlm.nih.gov/pubmed/35574339
http://dx.doi.org/10.3389/fonc.2022.853232
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