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<p>This narrative review explores the latest advancements in various imaging modalities combined with artificial intelligence (AI) for monitoring response to neoadjuvant therapy (NT) and predicting pathological complete response (pCR). We provide a detailed analysis of the principles, evaluation metrics, strengths, and limitations of each technique. The integration of multimodal imaging and AI is reshaping the paradigm for evaluating NT efficacy in breast cancer, offering robust support for precision medicine.</p>

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Multimodal imaging and artificial intelligence for response assessment to neoadjuvant therapy in breast cancer: a comprehensive review

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月24日

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  • Linlin Shao,
  • Mingyu Zhang,
  • Lili Zhang,
  • Fangfang Sun,
  • Hongyu Li,
  • Jiangbo Shao,
  • Yansong Liu,
  • Xinyue Liu,
  • Feng Hu,
  • Lirong Zhao

摘要

This narrative review explores the latest advancements in various imaging modalities combined with artificial intelligence (AI) for monitoring response to neoadjuvant therapy (NT) and predicting pathological complete response (pCR). We provide a detailed analysis of the principles, evaluation metrics, strengths, and limitations of each technique. The integration of multimodal imaging and AI is reshaping the paradigm for evaluating NT efficacy in breast cancer, offering robust support for precision medicine.