Radiomic signatures from baseline CT predict chemotherapy response in unresectable colorectal liver metastases
Our findings demonstrate that radiomic features from baseline CT scans can serve as robust, interpretable biomarkers for predicting chemotherapy response, offering insights to guide personalized treatment in unresectable CRLM.
Authors
- Mohammad Hamghalam (ORCID: https://orcid.org/0000-0003-2543-0712)
- Jacob Peoples (ORCID: https://orcid.org/0000-0003-0191-7446)
- Natalie Gangai (ORCID: https://orcid.org/0000-0003-0603-7165)
- Ramtin Mojtahedi
- Mane Piliposyan
- Christian Muise
- Yun Shin Chun
- Kaitlyn Kobayashi
- E. Claire Bunker
- Hyunseon C. Kang
- Amber L. Simpson
- Richard K. G. Do
Institutions
- Memorial Sloan Kettering Cancer Center (US)
- The University of Texas MD Anderson Cancer Center (US)
- Queen's University (CA)
Publication Details
- Journal
- Journal of Medical Imaging
- Published
- 2026-01-13
- DOI
- https://doi.org/10.1117/1.jmi.13.1.014505
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00