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The added value of S-detect in the diagnostic accuracy of breast masses by senior and junior radiologist groups: a systematic review and meta-analysis

BACKGROUND: S-detect is an emerging computer-aided diagnosis (CAD) technique that provides a reference for radiologists to identify breast cancer. Some studies have shown that US (ultrasound) + S-detect can improve the diagnostic accuracy of junior radiologists more than senior radiologists, but the...

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Autores principales: Chen, Peijun, Tong, Jiahui, Lin, Ting, Wang, Ying, Yu, Yuehui, Chen, Menghan, Yang, Gaoyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AME Publishing Company 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9840989/
https://www.ncbi.nlm.nih.gov/pubmed/36654955
http://dx.doi.org/10.21037/gs-22-643
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author Chen, Peijun
Tong, Jiahui
Lin, Ting
Wang, Ying
Yu, Yuehui
Chen, Menghan
Yang, Gaoyi
author_facet Chen, Peijun
Tong, Jiahui
Lin, Ting
Wang, Ying
Yu, Yuehui
Chen, Menghan
Yang, Gaoyi
author_sort Chen, Peijun
collection PubMed
description BACKGROUND: S-detect is an emerging computer-aided diagnosis (CAD) technique that provides a reference for radiologists to identify breast cancer. Some studies have shown that US (ultrasound) + S-detect can improve the diagnostic accuracy of junior radiologists more than senior radiologists, but the results are inconsistent in various studies. Therefore, this meta-analysis aimed to assess the value of S-detect combined with the US outcomes from senior and junior radiologists for the diagnosis of breast cancer. METHODS: We searched the PubMed, Cochrane Library, Embase, Web of Science, and Wanfang databases, China Biology Medicine disc, China National Knowledge Infrastructure (CNKI), and VIP database for trials on the diagnostic accuracy of US + S-detect for the diagnosis of breast masses. The search time frame was from the date of establishment of the database to August 20, 2022. Two researchers independently screened the literature, extracted the information, and evaluated the quality of the included literature using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) scale. StataSE 15.1 software was utilized to assess pooled metrics, including sensitivity, specificity, and the area under the curve (AUC). RESULTS: A total of 19 articles with 3,349 patients and 3,895 breast masses were included in this meta-analysis. Of these, seventeen articles evaluated the diagnostic performance of senior radiologists’ US + S-detect for breast cancer, while twelve articles reported junior radiologists’ diagnostic performance. The risk of bias was primarily attributed to patient selection, flow and timing. In the senior radiologist group, the pooled sensitivity and specificity of US + S-detect were 0.93 [95% confidence interval (CI): 0.89–0.95] and 0.86 (95% CI: 0.80–0.90), respectively, with an AUC of 0.96. As for the junior radiologist group, the pooled sensitivity and specificity of US + S-detect were 0.89 (95% CI: 0.83–0.93) and 0.79 (95% CI: 0.72–0.84), respectively, and the AUC was 0.91. CONCLUSIONS: The results of this meta-analysis showed that the pooled sensitivity and the AUC of both the senior and junior radiologist groups were high, with good diagnostic efficacy and high clinical application. However, the results of this study are highly heterogeneous and need to be validated by collecting more high-quality studies and accumulating a larger sample size.
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spelling pubmed-98409892023-01-17 The added value of S-detect in the diagnostic accuracy of breast masses by senior and junior radiologist groups: a systematic review and meta-analysis Chen, Peijun Tong, Jiahui Lin, Ting Wang, Ying Yu, Yuehui Chen, Menghan Yang, Gaoyi Gland Surg Original Article BACKGROUND: S-detect is an emerging computer-aided diagnosis (CAD) technique that provides a reference for radiologists to identify breast cancer. Some studies have shown that US (ultrasound) + S-detect can improve the diagnostic accuracy of junior radiologists more than senior radiologists, but the results are inconsistent in various studies. Therefore, this meta-analysis aimed to assess the value of S-detect combined with the US outcomes from senior and junior radiologists for the diagnosis of breast cancer. METHODS: We searched the PubMed, Cochrane Library, Embase, Web of Science, and Wanfang databases, China Biology Medicine disc, China National Knowledge Infrastructure (CNKI), and VIP database for trials on the diagnostic accuracy of US + S-detect for the diagnosis of breast masses. The search time frame was from the date of establishment of the database to August 20, 2022. Two researchers independently screened the literature, extracted the information, and evaluated the quality of the included literature using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) scale. StataSE 15.1 software was utilized to assess pooled metrics, including sensitivity, specificity, and the area under the curve (AUC). RESULTS: A total of 19 articles with 3,349 patients and 3,895 breast masses were included in this meta-analysis. Of these, seventeen articles evaluated the diagnostic performance of senior radiologists’ US + S-detect for breast cancer, while twelve articles reported junior radiologists’ diagnostic performance. The risk of bias was primarily attributed to patient selection, flow and timing. In the senior radiologist group, the pooled sensitivity and specificity of US + S-detect were 0.93 [95% confidence interval (CI): 0.89–0.95] and 0.86 (95% CI: 0.80–0.90), respectively, with an AUC of 0.96. As for the junior radiologist group, the pooled sensitivity and specificity of US + S-detect were 0.89 (95% CI: 0.83–0.93) and 0.79 (95% CI: 0.72–0.84), respectively, and the AUC was 0.91. CONCLUSIONS: The results of this meta-analysis showed that the pooled sensitivity and the AUC of both the senior and junior radiologist groups were high, with good diagnostic efficacy and high clinical application. However, the results of this study are highly heterogeneous and need to be validated by collecting more high-quality studies and accumulating a larger sample size. AME Publishing Company 2022-12 /pmc/articles/PMC9840989/ /pubmed/36654955 http://dx.doi.org/10.21037/gs-22-643 Text en 2022 Gland Surgery. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) .
spellingShingle Original Article
Chen, Peijun
Tong, Jiahui
Lin, Ting
Wang, Ying
Yu, Yuehui
Chen, Menghan
Yang, Gaoyi
The added value of S-detect in the diagnostic accuracy of breast masses by senior and junior radiologist groups: a systematic review and meta-analysis
title The added value of S-detect in the diagnostic accuracy of breast masses by senior and junior radiologist groups: a systematic review and meta-analysis
title_full The added value of S-detect in the diagnostic accuracy of breast masses by senior and junior radiologist groups: a systematic review and meta-analysis
title_fullStr The added value of S-detect in the diagnostic accuracy of breast masses by senior and junior radiologist groups: a systematic review and meta-analysis
title_full_unstemmed The added value of S-detect in the diagnostic accuracy of breast masses by senior and junior radiologist groups: a systematic review and meta-analysis
title_short The added value of S-detect in the diagnostic accuracy of breast masses by senior and junior radiologist groups: a systematic review and meta-analysis
title_sort added value of s-detect in the diagnostic accuracy of breast masses by senior and junior radiologist groups: a systematic review and meta-analysis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9840989/
https://www.ncbi.nlm.nih.gov/pubmed/36654955
http://dx.doi.org/10.21037/gs-22-643
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