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N/A N=9

Toward an Automated Method of Abdominal Fat Segmentation of MR Images

Obesity

Enrolled (actual)
9
Serious AEs
0.0%
Results posted
May 2011
Primary outcome: Primary: Visceral Fat Volume With Automated Analysis — 994 cubic centimeters

Study Design & Population

Study type
Observational
Phase
N/A
Interventions
Age
Adult, Older Adult · 18+ yrs
Sex
All
Sponsor
Washington University School of Medicine
Primary completion
Feb 2011

Outcome Measures

OutcomeResultp-value
PRIMARY
Visceral Fat Volume With Automated Analysis
994
PRIMARY
Visceral Fat Volume With Manual Segmentation
1175
SECONDARY
Subcutaneous Fat Volume With Automated Analysis
2506
SECONDARY
Subcutaneous Fat Volume With Manual Segmentation
2910

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.

Eligibility Criteria

Inclusion Criteria

  • ambulatory
  • cognitively sound

Exclusion Criteria

  • body mass index less than 18 or greater than 45 kilograms per square meter
View full record on ClinicalTrials.gov →

Data sourced from ClinicalTrials.gov (NCT01228968). Outcome figures and adverse-event rates are extracted automatically from the registry's posted results and are provided for clinician reference, not as a substitute for the primary publication.

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