Computed Tomography-Based Radiomics with Machine Learning Outperforms Radiologist Assessment in Estimating Colorectal Liver Metastases Pathologic Response After Chemotherapy.
Journal:
Annals of surgical oncology
PMID:
39369120
Abstract
OBJECTIVES: This study was designed to assess computed tomography (CT)-based radiomics of colorectal liver metastases (CRLM), extracted from posttreatment scans in estimating pathologic treatment response to neoadjuvant therapy, and to compare treatment response estimates between CT-based radiomics and radiological response assessment by using RECIST 1.1 and CT morphologic criteria.
Authors
Keywords
Adult
Aged
Antineoplastic Combined Chemotherapy Protocols
Colorectal Neoplasms
Female
Follow-Up Studies
Humans
Liver Neoplasms
Machine Learning
Male
Middle Aged
Neoadjuvant Therapy
Prognosis
Radiologists
Radiomics
Response Evaluation Criteria in Solid Tumors
Retrospective Studies
Tomography, X-Ray Computed