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English(EN) Pretreatment DCE-MRI Resolves Response Quality Within Pathologic Endpoints in Neoadjuvant Breast Cancer

新的MRI方法预测乳腺癌复发风险

研究人员开发了一个新的框架,利用预处理的动态对比增强MRI熵来更好地预测接受新辅助治疗的乳腺癌患者的复发风险。该方法分析肿瘤内增强的异质性,以识别具有有利或不利结构状态的患者,即使在达到病理完全缓解的患者中也是如此。该四级框架在总计1200名患者的四个队列中进行了测试,显示复发率存在显著差异,不利的结构状态与较高的风险相关。虽然不能取代pCR或RCB等现有终点,但这种基于MRI的方法为优化反应质量评估和识别可能受益于进一步干预的患者提供了一个有价值的工具。 AI

影响 这项研究为预测乳腺癌的治疗结果提供了一种新颖的影像学生物标志物,有可能改善患者分层和治疗策略。

排序理由 详细介绍新方法及其验证的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]

在 arXiv cs.CV 阅读 →

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新的MRI方法预测乳腺癌复发风险

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详细介绍新方法及其验证的学术论文。[lever_c_demoted from research: ic=1 ai=0.4]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Dattatreya Kantha, Murray H. Loew ·

    预处理DCE-MRI在术前乳腺癌病理终点内解析反应质量

    arXiv:2608.22097v1 Announce Type: cross Abstract: Pathologic complete response (pCR) is a strong neoadjuvant endpoint, yet 5-15% of complete responders recur and clinical/genomic variables do not reliably identify them. We tested whether pretreatment dynamic contrast-enhanced MRI…