ArticleNPJ precision oncology2025
Fractal analysis of longitudinal MRI for predicting response to neoadjuvant chemotherapy in breast cancer.
Article in NPJ precision oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- A fractal-enhanced deep learning framework for forecasting agricultural production in India.Scientific reports · 2026Article
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Authors and funding
10 authors.
Funding
Abstract
Breast cancer is a highly heterogeneous disease, and accurate prediction of pathological complete response (pCR) at an early stage of neoadjuvant chemotherapy (NAC) is of great clinical importance. This study aims to predict pCR to NAC in breast cancer using longitudinal MRI-based fractal features, while exploring their biological relevance. Fractal dimension and fractal abundance were calculated from pre-treatment and early-treatment MRI scans of 911 patients across three institutions. A nomogram integrating delta fractal features and clinicopathologic variables was developed and validated in three cohorts, achieving AUCs of 0.781-0.807. Delta fractal features were independent predictors of pCR. Transcriptomic analysis in a genomics cohort revealed associations between delta fractal features and immune infiltration, particularly activated natural killer cells and naïve CD4 + T cells. These findings suggest that longitudinal fractal analysis provides two noninvasive biomarkers for early prediction of treatment response and may reflect the tumor immune microenvironment in breast cancer.
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