# Development and Validation of Prognostic Radiomic Markers of Response and Recurrence for Patients with Colorectal Liver Metastases

> **NIH NIH R01** · SLOAN-KETTERING INST CAN RESEARCH · 2022 · $683,138

## Abstract

SUMMARY
Colorectal cancer is the second leading cause of cancer-related mortality in the United States. More than 50%
of patients with colorectal cancer will develop liver metastases in their lifetime with a dismal <10% surviving
past three years. A major therapeutic problem in this disease is that no markers prognostic of hepatic
recurrence or predictive of response prior to treatment are known. The goal of this research is to fill this gap by
providing non-invasive and objective prognostic quantitative imaging markers for personalized treatment of
colorectal liver metastases (CRLM). Our single-institution data support that quantitative imaging features
extracted from routine CT scans predict volumetric response to systemic and regional chemotherapy and
identify patients at high risk of hepatic recurrence and poor survival. Progress in developing these novel
markers is limited by a lack of optimization, standardization, and validation, all critical barriers to clinical use.
The objectives of this application are to develop and validate robust imaging features by standardizing image
acquisition, to improve automated tools for clinical trial use, and to validate the predictive power of imaging
features with external data. We have partnered with University of Texas MD Anderson Cancer Center,
Rensselaer Polytechnic Institute, and GE Research, facilitating the widespread integration of the proposed
technology into medical centers worldwide. Our central hypothesis is that quantitative CT-based imaging
features provide novel and robust indices for predicting response, hepatic recurrence, and survival in CRLM
patients. Specifically, we will (1) validate predictive and prognostic imaging features with external data, (2)
prospectively assess repeatability and reproducibility of contrast-enhanced CT imaging features, and (3)
develop an integrated rawdiomics pipeline by fully utilizing sinogram data. We have assembled a critical mass
of experts in surgery, medical oncology, pathology, radiology, biostatistics, and image analysis. Combined with
the largest clinical experience in CRLM in the western world, this application is a unique and unrivaled
opportunity to define radiomics of CRLM. Integration into existing clinical workflows means that small medical
centers without highly specialized radiology groups would benefit from predictive algorithms developed at two
high-volume centers via a low-cost software update. Successful completion of our aims will provide validated
prognostic imaging markers with a pathway to routine clinical use, which are of paramount importance to
improving patient survival of this deadly disease.

## Key facts

- **NIH application ID:** 10472602
- **Project number:** 5R01CA233888-04
- **Recipient organization:** SLOAN-KETTERING INST CAN RESEARCH
- **Principal Investigator:** Yun Shin Chun
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $683,138
- **Award type:** 5
- **Project period:** 2019-03-01 → 2024-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10472602

## Citation

> US National Institutes of Health, RePORTER application 10472602, Development and Validation of Prognostic Radiomic Markers of Response and Recurrence for Patients with Colorectal Liver Metastases (5R01CA233888-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10472602. Licensed CC0.

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