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Tumor Morphology for Prediction of Poor Responses Early in Neoadjuvant Chemotherapy for Breast Cancer: A Multicenter Retrospective Study

  • 0Department of Radiology and Biomedical Imaging, University of California, 550 16th Street, San Francisco, CA 94158, USA.
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November 26, 2024

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November 26, 2024

View abstract on PubMed

Summary

This summary is machine-generated.

Adding tumor shape features to functional tumor volume (FTV) analysis significantly improves prediction of poor treatment response in breast cancer patients. Early treatment imaging is key for identifying patients likely to have residual cancer burden class III (RCB-III).

Area Of Science

  • Radiology
  • Oncology
  • Medical Imaging

Background

  • Investigated the additive value of tumor morphologic features from functional tumor volume (FTV) masks.
  • Focused on pre-treatment (T0) and early treatment (T1) time points for breast cancer patients.
  • Utilized data from the multicenter I-SPY 2 trial involving 910 patients.

Purpose Of The Study

  • To assess if tumor morphologic features enhance prediction of pathologic outcomes.
  • To determine the predictive performance of FTV and morphologic features in neoadjuvant chemotherapy.
  • To evaluate prediction in various hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) subgroups.

Main Methods

  • Calculated FTV and morphologic features from dynamic contrast-enhanced (DCE) MRI.
  • Defined poor response as residual cancer burden class III (RCB-III).
  • Used area under the receiver operating characteristic curve (AUC) for performance evaluation.

Main Results

  • Morphologic features significantly increased AUC from 0.64 to 0.76 (p < 0.001) in the full cohort.
  • The surface area to volume ratio between T0 and T1 was the most predictive feature.
  • Significant AUC improvements were observed in HR+/HER2- and triple-negative subgroups.

Conclusions

  • Tumor morphologic features improve the prediction of RCB-III.
  • Adding morphologic features to FTV analysis enhances early treatment response prediction.
  • Early treatment imaging provides valuable insights into pathologic outcomes.

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