Radiomics of Colorectal Liver Metastases: Identification of New Prognostic Biomarkers.

January 13, 2025 updated by: Istituto Clinico Humanitas

Radiomic Features of Tumor and of Liver-Tumor Interface in Patients with Colorectal Liver Metastases. Identification of New Prognostic Biomarkers.

Background: Liver metastases (CLM) affect about half of patients with colorectal cancer and dictate patients' prognosis. Prediction of prognosis is of paramount importance for patients allocation to the most adequate treatment, but available parameters do not adequately fulfil this role. Tumor pathology and molecular data and liver-tumor interface characteristics showed a major prognostic impact, but they are not included in standard prognostic scores and standard imaging modalities are poorly informative about them. Radiomic analyses demonstrated a very good prediction of pathology data and of patients outcome in several tumor, but their application to CLM remains to explore.

Hypothesis The preoperative identification of CLM and liver-tumor interface characteristics would improve prognosis prediction and patients allocation to treatments. As in other tumors, radiomic analyses could allow a major refinement in prediction of pathology data. Radiomic features per se could have a major association with prognosis.

Aims

The study has the following end-points:

  • to assess whether radiomic features of tumor and of liver-tumor interface improve prognosis prediction in CLM patients undergoing liver surgery in comparison with standard prognostic scores.
  • to explore if radiomic features are associated with pathology data.
  • to explore performances of radiomic features in comparison with standard radiologic criteria to assess tumor response to chemotherapy.
  • to merge radiomic and detailed pathology data in a single prognostic score.

Experimental Design The study will combine a retrospective (n=300 patients) and a prospective (n=400) series of patients undergoing liver resection at authors institution. Retrospectively collected patients will represent the training dataset for the prognostic model including standard prognostic factors plus radiomic features, while the first half of the prospective cohort (n=200) will be the validation dataset (minimum follow-up 30 months). For the analysis of association of radiomic features with pathology details and tumor response to chemotherapy, the prospective cohort of patients (n=400, ≈800 CLMs) will be used as training and validation dataset (data about liver-tumor interface cannot be reliably assessed in the retrospective series). Finally, all prospectively collected patients with adequate follow-up will contribute to build a composite prognostic score combining radiomic features and detailed pathology data. Per-patient evaluation will be performed in prognostic analyses; per-lesion evaluation will be performed while evaluating the association between radiomic and pathology data. The LifeX ® software will be used to perform radiomic analyses. The volume of interest (VOI) of the tumor will be tracked. An automatic volume expansion will be applied to the tumor VOI to track the liver-tumor interface (expansion of 5 mm).

Expected Results The present study has the solid expectancy to demonstrate that radiomic features of CLM and of liver-tumor interface have a major prognostic role and a good association with pathology data. We further believe that a prognostic score combining radiomic and pathology data may further optimize prognosis prediction.

Impact On Cancer Our analysis aims to improve CLM prognosis prediction by identifying radiomic features that impact prognosis and predict pathology data, and to propose a combined prognostic model of radiomic and pathology data. These are the basis for a precision medicine based on a preoperative prognostic-driven treatment allocation.

Study Overview

Status

Completed

Conditions

Study Type

Observational

Enrollment (Actual)

400

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • Italy
    • Milan
      • Rozzano, Milan, Italy, 20089
        • Humanitas Research Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

Study Population

Patients who underwent liver resection for colorectal liver metastases at the IRCCS Humanitas Research Centre, Milan, Italy between January 2021 and December 2024.

Description

Inclusion Criteria:

  • Patients undergoing liver surgery for CLM confirmed at final pathology
  • At least 1 CLM with diameter >10 mm
  • Preoperative CT imaging available for radiomic analysis.
  • Age >18 years
  • No other malignancies in the previous 5 years
  • Interval CT-surgery ≤60 days

Exclusion Criteria:

  • Loco-regional treatments of CRLM before liver resection
  • Inadequate portal phase of the CT or high-density material artifacts affecting the analysis
  • Incomplete clinical data

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Prognosis prediction
Time Frame: 2020-2024
To asses if radiomic features of tumor and of liver-tumor interface in patients with CLM improve prediction of prognosis after complete resection in comparison with standard prognostic parameters
2020-2024
Association with pathology data
Time Frame: 2020-2024
To explore if radiomic features of tumor and of liver-tumor interface in patients with CLM are associated with pathology data, including TRG, percentage of viable cells, tumor growth pattern, tumor thickness at the interface, peritumoral micrometastases, and immune infiltrate in the tumor and the peritumoral area, and molecular status. In addition any association among pathology data will be explored
2020-2024
Prognostic score
Time Frame: 2020-2024
To implement radiomic features and detailed pathology data of tumor and of liver-tumor interface in a single prognostic score for patients with CLM
2020-2024

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Comparison with radiological criteria
Time Frame: 2020-2024
To explore performances of radiomic features in comparison with standard radiologic criteria (i.e. RECIST and mRECIST criteria) for prediction of tumor response to chemotherapy
2020-2024

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Istituto Clinico Humanitas

Collaborators

AIRC (Italian Association for Cancer Research)

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

January 1, 2020

Primary Completion (Actual)

December 31, 2024

Study Completion (Actual)

December 31, 2024

Study Registration Dates

First Submitted

January 13, 2025

First Submitted That Met QC Criteria

January 13, 2025

First Posted (Actual)

March 25, 2025

Study Record Updates

Last Update Posted (Actual)

March 25, 2025

Last Update Submitted That Met QC Criteria

January 13, 2025

Last Verified

January 1, 2025

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • AIRC grant #2019-23822

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

product manufactured in and exported from the U.S.

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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