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Background <p>Early prediction of pathologic complete response (pCR) during neoadjuvant chemotherapy (NAC) in HER2-positive breast cancer remains challenging using conventional whole-tumor imaging approaches, particularly when substantial tumor shrinkage occurs on mid-NAC MRI (acquired after two cycles of NAC).</p> Methods <p>This retrospective study included 163 patients with HER2-positive breast cancer who underwent dynamic contrast-enhanced MRI at pre-NAC and mid-NAC. A therapy-induced tumor regression region (TRR) was defined as the regressed tumor volume between pre- and mid-NAC MRI. Tumor regression heterogeneity (TRH) was quantified within this region using a habitat-based radiomic approach. Logistic regression models were constructed and evaluated in training (<i>n</i> = 115) and validation (<i>n</i> = 48) cohorts.</p> Results <p>pCR was achieved in 71 patients (43.6%). The TRH model demonstrated superior predictive performance compared with pre-NAC, mid-NAC, tumor regression region–based, and delta models, achieving an AUC of 0.83 (95% CI: 0.70–0.97) in the validation cohort. An integrated nomogram combining TRH with clinicopathologic factors further improved predictive performance.</p> Conclusions <p>Quantification of spatial heterogeneity within therapy-induced tumor regression regions on mid-NAC MRI may enable improved prediction of treatment response during neoadjuvant therapy.</p>

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Therapy-induced tumor regression heterogeneity for early prediction of response and prognosis in HER2-positive breast cancer

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月20日

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  • Zewen Liu,
  • Qin Li,
  • Juntao Zhang,
  • Xiaomei Jiang,
  • Xiqing Wu,
  • Haitong Yu,
  • Shasha Wu,
  • Chengsheng Li,
  • Ying Chen,
  • Peng Dong,
  • Qingliang Niu

摘要

Background

Early prediction of pathologic complete response (pCR) during neoadjuvant chemotherapy (NAC) in HER2-positive breast cancer remains challenging using conventional whole-tumor imaging approaches, particularly when substantial tumor shrinkage occurs on mid-NAC MRI (acquired after two cycles of NAC).

Methods

This retrospective study included 163 patients with HER2-positive breast cancer who underwent dynamic contrast-enhanced MRI at pre-NAC and mid-NAC. A therapy-induced tumor regression region (TRR) was defined as the regressed tumor volume between pre- and mid-NAC MRI. Tumor regression heterogeneity (TRH) was quantified within this region using a habitat-based radiomic approach. Logistic regression models were constructed and evaluated in training (n = 115) and validation (n = 48) cohorts.

Results

pCR was achieved in 71 patients (43.6%). The TRH model demonstrated superior predictive performance compared with pre-NAC, mid-NAC, tumor regression region–based, and delta models, achieving an AUC of 0.83 (95% CI: 0.70–0.97) in the validation cohort. An integrated nomogram combining TRH with clinicopathologic factors further improved predictive performance.

Conclusions

Quantification of spatial heterogeneity within therapy-induced tumor regression regions on mid-NAC MRI may enable improved prediction of treatment response during neoadjuvant therapy.