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Colorectal Liver MetastasesNCT07830576

Multimodal Survival Prediction Model for Colorectal Liver Metastases Post-Operation

An observational study of Colorectal Liver Metastases and Colorectal Neoplasms, run by Anhui Provincial Hospital at 1 site in China.

Recruiting

Looking for participants now. Contact the study team or a site below to ask about taking part.

Sites and contacts
Official record

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Trial summary

The purpose of this study is to construct and validate a multimodal survival prediction model by integrating 3D radiomics features derived from preoperative magnetic resonance imaging (MRI) with systemic clinical baseline indicators for patients with colorectal liver metastases (CRLM) after surgery. Read more about this study

Who is it for?
Ages 18 to 80 years
What is being tested?
Multimodal Predictive Evaluation
Type of treatment
Surgery or procedure
How many people
205 participants
Where
1 siteChina
Study dates
1 Feb 2017to Sep 2026
Phase
Observational

Key requirements

Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.

  • Ages 18 to 80 years
  • All sexes
  • No healthy volunteers
  • Adult, Older adult

Study population: The study population consists of adult patients diagnosed with colorectal liver metastases who underwent surgical resection across multiple participating clinical centers, featuring high-quality preoperative liver MRI scans and complete clinical follow-up histories.

Who may be able to join

  • Age >= 18 years old. Confirmed diagnosis of colorectal cancer with liver metastases (CRLM). Underwent surgical resection for colorectal liver metastases. Preoperative liver magnetic resonance imaging (MRI) was performed with high-quality images available for 3D radiomics feature extraction.
  • Complete baseline clinical, laboratory, and post-operative follow-up survival data.

Who cannot join

  • Patients who received local ablation only (such as radiofrequency ablation) without surgical resection.
  • Preoperative MRI images with severe artifacts or poor quality that prevent high-throughput radiomics analysis.
  • Concurrent history of other primary malignant neoplasms. Missing key clinical variables or lost to follow-up immediately after surgical intervention.

Trial locations and contacts

1 site in 1 country. Contact the study team or a site near you to ask about taking part.

China1 site, 1 recruiting
  • The First Affiliated Hospital of University of Science and Technology of China

    Hefei, Anhui, 230001

    can zhang, 15755077865, 15755077865@163.com

    Recruiting

Other trials in China

About this study

Official title: Construction of a Post-operative Multimodal Survival Prediction Model for Patients With Colorectal Liver Metastases: A Study Based on the Fusion of a Multicenter Cohort and High-dimensional Radiomics

The purpose of this study is to construct and validate a multimodal survival prediction model by integrating 3D radiomics features derived from preoperative magnetic resonance imaging (MRI) with systemic clinical baseline indicators for patients with colorectal liver metastases (CRLM) after surgery. By combining micro-level radiomics signatures reflecting tumor micro-heterogeneity with macro-level clinical parameters (such as liver function and tumor biomarkers), the study aims to accurately evaluate individual post-operative prognostic risks. This quantitative tool will provide reliable decision support for clinicians to customize post-operative follow-up and personalized adjuvant treatment strategies.

Read the detailed description

This study is based on a strictly screened multicenter cohort of patients with colorectal liver metastases who underwent surgical intervention. First, high-throughput quantitative features are automatically extracted from the 3D regions of interest (ROIs) segmented based on pre-operative magnetic resonance imaging (MRI). Advanced machine learning dimensionality reduction algorithms are subsequently applied to eliminate redundant variables and select core imaging signatures that deeply reflect tumor micro-heterogeneity, microvascular proliferation, and invasive status. On this basis, these micro-level radiomics features are fused with macro-level clinical parameters, including liver function indexes and tumor load markers. Multivariable survival analysis models are performed to identify independent prognostic factors, which are further used to develop a visual and intuitive predictive nomogram tool. Finally, time-dependent evaluation metrics and an external validation cohort will be utilized to systematically test the dynamic predictive performance and cross-platform generalizability of the model. This multimodal dual-track data paradigm aims to achieve a non-invasive and efficient "digital optical biopsy" approach for prognostic evaluation.

Being tested
Multimodal Predictive Evaluation
Keywords
Colorectal Liver Metastases, Radiomics, Magnetic Resonance Imaging, Nomogram, Prognosis
Medical subject headings
Colorectal Neoplasms, Liver Neoplasms

What participants receive

What participants receive. In a randomised study each person is assigned to one group by chance.

  • Multimodal Predictive EvaluationProcedure or surgery

    Observational and non-invasive assessment based on preoperative MRI-derived 3D modeling and three-dimensional lesion reconstruction, combined with clinical parameters, to build a survival prediction model. No experimental intervention is assigned.

Study groups in NCT07830576
Study groupRoleWhat they receive
CRLM Surgical CohortA multicenter cohort consisting of patients with colorectal liver metastases who underwent surgical resection. Preoperative magnetic resonance imaging (MRI) is utilized for 3D modeling and three-dimensional reconstruction of the liver and lesions, from which key spatial/morphological features and systemic clinical parameters are analyzed to predict post-operative recurrence-free survival.
Receives: Procedure: Multimodal Predictive Evaluation

What is being measured

The primary outcome is the main question the study is designed to answer.

  1. Recurrence-Free Survival (RFS)

    Recurrence-free survival (RFS) is defined as the time from the date of surgical resection to the date of first tumor recurrence (local, regional, or distant) or death from any cause, whichever occurs first.

    Measured: Up to 5 years post-surgery

Timeline

From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.

  1. First posted21 Sep 2026
  2. Study start1 Feb 2017
  3. Primary completionSep 2026 (estimated)
  4. Study completionSep 2026 (estimated)

Resources

More details

For doctors and researchers: how the study is designed, who runs it, and its registry IDs.

Study design
Study type
Observational
Observational model
Cohort
Time perspective
Retrospective
Enrolment
205 participants (estimated)
IDs, dates and publications
ClinicalTrials.gov ID
NCT07830576
Sponsor's protocol ID
2026KY-249
Other IDs
2025AHGXZK10006
Status last verified
Sep 2026
First submitted
31 Jul 2026
Last updated
21 Sep 2026
Results posted
No
Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
Individual data sharing
No: To protect participant privacy and comply with institutional data governance policies, individual participant data from this retrospective study will not be publicly shared.

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