Computer Assisted Early Detection of Liver Metastases From fMRI Maps

Metastatic Colorectal Cancer Clinical Trial

Official title:

Computer Assisted Early Detection of Liver Metastases From fMRI Maps

Clinical Trial Details — Status: Not yet recruiting

Administrative data

• NCT number: NCT00435097
• Other study ID #: colmri-HMO-CTIL
• Status: Not yet recruiting
• Phase: N/A
• First received: February 13, 2007
• Last updated: February 13, 2007

Study information

• Verified date: February 2007
• Source: Hadassah Medical Organization
• Contact: Ayala Hubert, MD
• Email: ayalah[@]hadassah.org.il
• Is FDA regulated: No
• Health authority: Israel: Israeli Health Ministry Pharmaceutical Administration
• Study type: Observational

Clinical Trial Summary

The purpose of this protocol is to develop a detailed MRI technique and haemodynamic maps enabling early detection of colorectal metastases in the liver.

Description:

In this research, we propose to develop methods and protocols for imaging-based, non-invasive early detection and diagnosis of colon cancer metastases. Colon cancer is the third most common cancer worldwide. While it is amenable to surgery if detected early, advanced carcinomas are usually lethal, with liver metastases being the most common cause of death. Early and accurate detection of these lesions is recognized as having the potential of improving survival rates and reducing treatment morbidity. Current diagnostic imaging offers improved discrimination and sensitivity that can be used for earlier detection of smaller lesions conducive to curative therapy.

In previous research, we demonstrated the feasibility of fMRI based on hypercapnia and hyperoxia for monitoring changes in liver perfusion and hemodynamics without contrast agent administration. The isolation and analysis of areas with significant hemodynamical changes in images acquired at early phase of tumor development has proven to be a difficult, time consuming, and potentially unreliable task. Our goal is thus two-fold: 1. use image processing and machine learning tools on a training set of hemodynamical maps obtained from well validated tumors to automate the process and improve its discrimination and sensitivity characteristics, and; 2. implement our method in patients with colorectal liver metastases. The method can help general radiologists with no image processing training to highlight undetectable tumors from background noise and increase diagnosis specificity and sensitivity.

Recruitment information / eligibility

• Status: Not yet recruiting
• Enrollment: 0
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: Both
• Age group: 20 Years and older

Eligibility

Inclusion Criteria:

• Control group of healthy volunteers

• Study group: Patients with colon cancer stage III or IV with high suspicion of liver metastases: raising CEA, suspected lesion in the liver by CT or PET.

Exclusion Criteria:

• Contraindication to perform MRI.

Study Design

Observational Model: Defined Population, Primary Purpose: Screening, Time Perspective: Longitudinal

Related Conditions & MeSH terms

• Colorectal Neoplasms
• Metastatic Colorectal Cancer

Locations

Country	Name	City	State
Israel	Hadassah Medical Organization	Jerusalem
Israel	Hebrew University	Jerusalem

Sponsors (1)

Lead Sponsor	Collaborator
Hadassah Medical Organization

Country where clinical trial is conducted

Israel,