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基于超声的影像组学在预测乳腺癌新辅助化疗早期反应中的应用:系统评价和荟萃分析。

Ultrasound-based radiomics for early predicting response to neoadjuvant chemotherapy in patients with breast cancer: a systematic review with meta-analysis.

机构信息

The First Clinical Medical College of Lanzhou University, Lanzhou, 730000, China.

Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, 730000, China.

出版信息

Radiol Med. 2024 Jun;129(6):934-944. doi: 10.1007/s11547-024-01783-1. Epub 2024 Apr 17.

DOI:10.1007/s11547-024-01783-1
PMID:38630147
Abstract

OBJECTIVE

This study aims to evaluate the diagnostic accuracy of ultrasound imaging (US)-based radiomics for the early prediction of response to neoadjuvant chemotherapy (NAC) in breast cancer patients.

METHODS

We comprehensively searched PubMed, Cochrane Library, Embase, and Web of Science databases up to 1 January 2023 for eligible studies. We assessed the methodological quality of the enrolled studies with Radiomics Quality Score (RQS) and the Quality Assessment of Diagnostic Accuracy Studies-2 tools. We performed meta-analyses to summarize the diagnostic efficacy of US-based radiomics in response to NAC in breast cancer patients.

RESULTS

Eight studies proved eligible. Eligible studies exhibited an average RQS score of 12.88 (35.8% of the total score), with the RQS score ranging from 8 to 19. In the meta-analyses, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.87 (95% CI 0.81-0.92), 0.78 (95% CI 0.72-0.83), 4.02 (95% CI 3.18-5.08), 0.16 (95% CI 0.10-0.25), and 25.17 (95% CI 15.10-41.95), respectively. Results from subgroup analyses indicated that prospective studies apparently exhibited more optimal sensitivity than retrospective studies. Sensitivity analyses exhibited similar results to the primary analyses.

CONCLUSION

US-based radiomics may be a potentially crucial adjuvant method for evaluating the response of breast cancer to NAC. Due to limited data available and low quality of eligible studies, more multicenter prospective studies with rigorous methods are required to confirm our findings.

摘要

目的

本研究旨在评估基于超声成像(US)的放射组学在预测乳腺癌患者新辅助化疗(NAC)早期疗效中的诊断准确性。

方法

我们全面检索了 PubMed、Cochrane 图书馆、Embase 和 Web of Science 数据库,截至 2023 年 1 月 1 日,以确定符合条件的研究。我们使用放射组学质量评分(RQS)和诊断准确性研究质量评估工具-2(QUADAS-2)评估了纳入研究的方法学质量。我们进行了荟萃分析,以总结基于 US 的放射组学在预测乳腺癌患者 NAC 疗效中的诊断效能。

结果

八项研究符合纳入标准。纳入研究的平均 RQS 评分为 12.88(总分的 35.8%),RQS 评分为 8 至 19 分。荟萃分析结果显示,基于 US 的放射组学预测乳腺癌患者 NAC 疗效的敏感度、特异度、阳性似然比、阴性似然比和诊断比值比分别为 0.87(95%CI 0.81-0.92)、0.78(95%CI 0.72-0.83)、4.02(95%CI 3.18-5.08)、0.16(95%CI 0.10-0.25)和 25.17(95%CI 15.10-41.95)。亚组分析结果表明,前瞻性研究的敏感度明显优于回顾性研究。敏感性分析结果与主要分析结果一致。

结论

基于 US 的放射组学可能是评估乳腺癌对 NAC 反应的一种有潜力的重要辅助方法。由于纳入研究的数量有限且质量较低,需要更多采用严格方法的多中心前瞻性研究来验证我们的发现。

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World J Clin Cases. 2022 Apr 16;10(11):3436-3448. doi: 10.12998/wjcc.v10.i11.3436.
2
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Front Oncol. 2022 Feb 7;12:748008. doi: 10.3389/fonc.2022.748008. eCollection 2022.
3
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Abdom Radiol (NY). 2025 Jul 8. doi: 10.1007/s00261-025-05085-6.
4
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Front Oncol. 2025 Jun 5;15:1525285. doi: 10.3389/fonc.2025.1525285. eCollection 2025.
5
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Transl Oncol. 2025 Aug;58:102435. doi: 10.1016/j.tranon.2025.102435. Epub 2025 May 30.
6
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7
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