Trial Outcomes & Findings for Toward an Automated Method of Abdominal Fat Segmentation of MR Images (NCT NCT01228968)

Results Overview

This is the measurement of Abdominal Visceral Fat in cubic centimeters as determined with a new automated segmentation program.

Recruitment status

COMPLETED

Target enrollment

9 participants

Primary outcome timeframe

five minutes

Results posted on

2018-07-11

Participant Flow

we recruited subjects currently enrolled in related studies.

Participant milestones

Participant milestones
Measure	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.
Overall Study STARTED	9
Overall Study COMPLETED	9
Overall Study NOT COMPLETED	0

Reasons for withdrawal

Withdrawal data not reported

Baseline Characteristics

Toward an Automated Method of Abdominal Fat Segmentation of MR Images

Baseline characteristics by cohort

Baseline characteristics by cohort
Measure	Volunteers n=9 Participants 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.
Age, Categorical <=18 years	0 Participants n=5 Participants
Age, Categorical Between 18 and 65 years	9 Participants n=5 Participants
Age, Categorical >=65 years	0 Participants n=5 Participants
Age, Continuous	39.8 years STANDARD_DEVIATION 9.3 • n=5 Participants
Sex: Female, Male Female	8 Participants n=5 Participants
Sex: Female, Male Male	1 Participants n=5 Participants
Region of Enrollment United States	9 participants n=5 Participants

PRIMARY outcome

Timeframe: five minutes

This is the measurement of Abdominal Visceral Fat in cubic centimeters as determined with a new automated segmentation program.

Outcome measures

Outcome measures
Measure	Volunteers n=9 Participants 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.
Visceral Fat Volume With Automated Analysis	994 cubic centimeters Standard Deviation 618

PRIMARY outcome

Timeframe: five minutes

This is the measure of visceral fat found with our older manual segmentation method

Outcome measures

Outcome measures
Measure	Volunteers n=9 Participants 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.
Visceral Fat Volume With Manual Segmentation	1175 cm3 Standard Deviation 636

SECONDARY outcome

Timeframe: five minutes

This is the volume of Abdominal Subcutaneous Fat in cubic centimeters as determined with new automated anatomical segmentation software.

Outcome measures

Outcome measures
Measure	Volunteers n=9 Participants 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.
Subcutaneous Fat Volume With Automated Analysis	2506 cubic centimeters Standard Deviation 887

SECONDARY outcome

Timeframe: five minutes

This is the volume of Abdominal Subcutaneous Fat in cubic centimeters as determined with the older manual segmentation technique.

Outcome measures

Outcome measures
Measure	Volunteers n=9 Participants 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.
Subcutaneous Fat Volume With Manual Segmentation	2910 cubic centimeters Standard Deviation 964

Adverse Events

Volunteers

Serious events: 0 serious events

Other events: 0 other events

Deaths: 0 deaths

Serious adverse events

Adverse event data not reported

Other adverse events

Adverse event data not reported

Additional Information

Gary Skolnick

Washington University School of Medicine

Phone: 3143625292

Email: [email protected]

Results disclosure agreements

Principal investigator is a sponsor employee
Publication restrictions are in place