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Updated: May 27, 2026

Detection of a Circulating MicroRNA Custom Panel in Patients with Metastatic Colorectal Cancer

Detection of a Circulating MicroRNA Custom Panel in Patients with Metastatic Colorectal Cancer

Published on: March 14, 2019

Integrating CT-Based Radiomics Analysis With Serum CEA Level to Predict Neoadjuvant Chemoradiotherapy Response in

Sin-Hua Moi^1,2,3,4,5,6, Ming-Yii Huang^7,8,9, Shu-Han Yang^7,10

¹Graduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.

The Kaohsiung Journal of Medical Sciences

|May 26, 2026

Summary

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Predicting neoadjuvant chemoradiotherapy response in colorectal cancer (CRC) is improved by combining CT radiomics and serum CEA levels. This integrated model helps identify poor responders for timely treatment adjustments.

Area of Science:

Oncology
Radiology
Biomarkers

Background:

Response to neoadjuvant chemoradiotherapy (NACRT) in locally advanced colorectal cancer (CRC) is variable.
Accurate prediction of treatment response is essential for optimizing patient management and avoiding ineffective therapies.

Purpose of the Study:

To develop and validate an integrated predictive model for therapeutic response in CRC patients undergoing NACRT.
The model combines radiomics from non-contrast CT scans with serum biomarkers.

Main Methods:

Retrospective analysis of 92 patients with stages II-III CRC treated with NACRT.
Extraction of radiomic features from pre-treatment planning CT images.
Development of a radiomics score (Rad-score) using LASSO logistic regression and integration with serum carcinoembryonic antigen (CEA) levels into a nomogram.

Keywords:

CT‐based radiomics carcinoembryonic antigen colorectal cancer neoadjuvant chemoradiotherapy pathological complete response

Related Experiment Videos

Last Updated: May 27, 2026

Detection of a Circulating MicroRNA Custom Panel in Patients with Metastatic Colorectal Cancer

Detection of a Circulating MicroRNA Custom Panel in Patients with Metastatic Colorectal Cancer

Published on: March 14, 2019

Main Results:

The CT-based radiomics signature demonstrated strong predictive performance for pathological complete response (pCR) (AUC: 0.854 in derivation, 0.818 in validation).
Multivariate analysis identified Rad-score and low pretreatment serum CEA as independent predictors of pCR.
The integrated nomogram showed excellent calibration in both derivation and validation cohorts.

Conclusions:

A combined model integrating CT-based radiomics and pretreatment serum CEA offers a robust and efficient tool for predicting NACRT response in CRC.
This approach can aid in identifying patients who may not benefit from standard NACRT, guiding treatment modifications.