Toward an Automated Method of Abdominal Fat Segmentation of MR Images

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.

Study Overview

• Status: Completed
• Conditions: Obesity

• Study Type: Observational
• Enrollment (Actual): 9

Contacts and Locations

Study Locations

• United States
  • Missouri
    • Saint Louis, Missouri, United States, 63110
      • Washington University School of Medicine

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years to 70 years (Adult, Older Adult)
• Accepts Healthy Volunteers: Yes
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Subjects will have a wide range of body mass index and other physical characteristics.

Description

Inclusion Criteria:

• ambulatory
• cognitively sound

Exclusion Criteria:

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

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort
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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Visceral Fat Volume With Automated Analysis	This is the measurement of Abdominal Visceral Fat in cubic centimeters as determined with a new automated segmentation program.	five minutes
Visceral Fat Volume With Manual Segmentation	This is the measure of visceral fat found with our older manual segmentation method	five minutes

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Subcutaneous Fat Volume With Automated Analysis	This is the volume of Abdominal Subcutaneous Fat in cubic centimeters as determined with new automated anatomical segmentation software.	five minutes
Subcutaneous Fat Volume With Manual Segmentation	This is the volume of Abdominal Subcutaneous Fat in cubic centimeters as determined with the older manual segmentation technique.	five minutes

Collaborators and Investigators

• Sponsor: Washington University School of Medicine
• Investigators: Principal Investigator: Samuel Klein, M.D., Washington University School of Medicine

Study record dates

Study Major Dates

• Study Start: October 1, 2010
• Primary Completion (Actual): February 1, 2011
• Study Completion (Actual): February 1, 2011

Study Registration Dates

• First Submitted: October 25, 2010
• First Submitted That Met QC Criteria: October 26, 2010
• First Posted (Estimate): October 27, 2010

Study Record Updates

• Last Update Posted (Actual): July 11, 2018
• Last Update Submitted That Met QC Criteria: June 13, 2018
• Last Verified: June 1, 2018

More Information

Terms related to this study

• Keywords: obesity
• Additional Relevant MeSH Terms: Overnutrition; Nutrition Disorders; Overweight; Body Weight; Obesity
• Other Study ID Numbers: MRImethods060229