Keywords: Diagnosis/Prediction, Radiomics, Rectal cancer; Neoadjuvant chemoradiotherapy; Distant metastasis; Pathomics; Immunosocre
Motivation: Identifying high-risk patients for distant metastasis (DM) before treatment can facilitate the development of personalized neoadjuvant treatment and improve the prognosis of patients with locally advanced rectal cancer (LARC).
Goal(s): This study aimed to construct a predictive model that integrates radiological information at the macroscale and pathological information at the microscale to estimate the probability of DM in LARC patients after neoadjuvant chemoradiotherapy, using radiomics, pathomics, and biopsy-adapted immunoscore.
Approach: Feature selection and signature construction were performed using the least absolute shrinkage and selection operator (LASSO)-Cox analysis.
Results: The results demonstrated the effectiveness of the nomogram in identifying high-risk DM patients.
Impact: Incorporating multiscale information, including radiomics, pathomics, and the immune microenvironment, enhances the characterization of tumors and provides a robust model for identifying high-risk DM patients in LARC. This approach aids in the development of personalized neoadjuvant treatment strategies.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords