Toward an Automated Method of Abdominal Fat Segmentation of MR Images

NCT ID: NCT01228968

Last Updated: 2018-07-11

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 9 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2010-10-31
• Study Completion Date: 2011-02-28

Brief Summary

Subjects will undergo a brief magnetic resonance (MRI) scan. The resulting images will be used to compare two abdominal fat segmentation techniques. The first technique is already validated and in use. The second technique was recently developed and has not been validated. The hypothesis is that the second technique will be the faster and more reliable of the two.

Conditions

Obesity

Study Design

• Observational Model Type: CASE_ONLY
• Study Time Perspective: CROSS_SECTIONAL

Study Groups

Volunteers

Volunteers will have a range of body mass index from 19 - 45 kilogram per square meter. In order to fit in the magnetic resonance scanner subjects must weigh less than 300 pounds.

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

• ambulatory
• cognitively sound

Exclusion Criteria

• body mass index less than 18 or greater than 45 kilograms per square meter

• Minimum Eligible Age: 18 Years
• Maximum Eligible Age: 70 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Washington University School of Medicine

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Samuel Klein, M.D.

Role: PRINCIPAL_INVESTIGATOR

Washington University School of Medicine

Locations

Washington University School of Medicine

St Louis, Missouri, United States

Countries

United States

Other Identifiers

MRImethods060229

Identifier Type: -

Identifier Source: org_study_id