Clinical trial NCT00435097: Computer Assisted Early Detection of Liver Metastases From fMRI Maps
Official title: Computer Assisted Early Detection of Liver Metastases From fMRI Maps
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Metastatic Colorectal Cancer
Keywords: colon cancer
metastatic colorectal cancer
MRI
Magnetic resonance imaging
Early cancer detection
medical image processing
machine learning
disease modeling
Colon Cancer Stage III
Lead sponsor: Hadassah Medical Organization
Sponsor class: OTHER
First posted: 2007-02-14
Sex: ALL
Minimum age (years): 20
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: DEFINED_POPULATION
Time perspective: PROSPECTIVE

Brief 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.

Detailed 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.

Eligibility criteria: 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.

Primary outcomes:
Secondary outcomes:
Other outcomes:
Locations:
city: Jerusalem
country: Israel
facility: Hadassah Medical Organization
city: Jerusalem
country: Israel
facility: Hebrew University
Study officials:
affiliation: Hadassah Medical Organization
name: Ayala Hubert, MD
role: PRINCIPAL_INVESTIGATOR
affiliation: Hadassah Medical Organization
name: Abramovitch Rinat, PhD
role: PRINCIPAL_INVESTIGATOR
affiliation: Hebrew University, Jerusalem
name: Joskowicz Leo, PhD
role: PRINCIPAL_INVESTIGATOR
References: