Predicting Patterns of Breast Tumor Shrinkage using MRI Models

In a groundbreaking development, a team of researchers, led by Yuhong Huang, MD from Southern Medical University in Guangzhou, China, have developed and tested an MRI model that predicts the shrinkage patterns of breast tumors following neoadjuvant therapy. The findings of this study were published on August 26 in the prestigious journal Radiology.

The research involved a comprehensive analysis of 2,249 women with breast cancer, with a median age of 49. The training set for the study included 671 women, internal validation included 335 women, and external validation included 1,243 women.

The MRI model, which incorporates the intratumoral microbiome count, habitat radiomic features, and deep-learning features, demonstrates high accuracy and overall performance. It predicts the tumor shrinkage patterns following neoadjuvant therapy, providing valuable insights for surgical planning.

The study authors, including Ying Tang, Kyunghyun Yum, and others, noted that this approach not only improves efficiency but also captures a broader range of tumor features through habitat radiomics. The fusion model eliminates the need for manual segmentation and feature extraction, further streamlining the process.

The model's performance was consistent across molecular subtypes and clinical stages in the validation sets. The fusion model achieved the highest area under the receiver operating characteristic curve (AUC) in the internal validation (0.89, p < 0.05) and external validation sets (0.87, p < 0.001).

Interestingly, the study found that tumors with concentric shrinkage had a higher microbiome abundance compared to others (p < 0.001). In total, 1,238 (55%) of the total women showed concentric tumor shrinkage.

The authors of the study highlighted the potential of this model to help guide surgical planning following neoadjuvant therapy and increase breast-conserving surgery success rates. However, they called for prospective studies to confirm the model's clinical impact and its potential use in surgical workflows.

For those interested in learning more about this innovative MRI model, the full study can be found at the provided link. This breakthrough could revolutionise the way breast cancer is treated and managed, offering a more personalised and effective approach to neoadjuvant therapy.