My PhD focused on CT-based habitat imaging to quantify intratumor heterogeneity in colorectal liver metastases: whether spatial patterns within a tumor can predict treatment response and survival in patients receiving anti-angiogenic therapy.
The thesis introduces a reproducible, biologically grounded approach to CT habitat computation. Key findings: handcrafted radiomics features outperform deep learning for habitat computation, and rim entropy (a measure of heterogeneity at the tumor boundary) predicts bevacizumab response in metastatic colorectal cancer.
Supervised by Dr. Raquel Pérez López and defended in February 2026 at the Universitat Politècnica de Catalunya.