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Validation of Soma Software for Body Composition Analysis

This study is testing a new computer program called Soma Body-Composition Segmentation Software. Soma is designed to automatically measure body composition (like muscle and fat) from CT scans. The goal is to see if Soma's measurements match what expert radiologists would find. Researchers will use 200 de-identified (anonymous) CT scans from existing public databases. The study aims to confirm that Soma can accurately analyze body composition in a diverse group of people, which could help doctors better assess conditions like sarcopenia (muscle loss), obesity, and other health risks. This is an observational study, meaning no new treatments are given; it's focused on evaluating the software.

Study design
This is an observational study evaluating a software program using 200 de-identified CT scans. The scans are selected to represent different body mass index (BMI) levels, ages, sexes, and clinical situations.
What's involved
Not specified in the trial record.
Compensation
Not stated in the trial record.
Follow-up
Not specified.

AI-generated from the public study record. Only the study team can confirm whether you're eligible — confirm details with them before making decisions.

NCT07600866

Validation of a Body-Composition Segmentation Software on a Diverse Public CT Scan Cohort

Not Yet Recruiting
Not specifiedAges 18+Observational
Nucleo Research, Inc.
~200 participants
Updated 2026-05-22 on ClinicalTrials.gov
What's tested:Soma Body-Composition Segmentation Software

At a glance

Recruiting sites
0 of 1 listed site is recruiting right now
RecruitingSuspended, closed, or not yet open
What they're measuring
Dice Similarity Coefficient (DSC) of Soma Segmentation Versus Multi-Rater Radiologist Reference Standard
Measured over Single time point: completion of standalone Soma inference and consolidated multi-rater annotation on all 200 study scans, anticipated within two weeks of study start.

Conditions

Sarcopenia
Body Composition
Obesity

Explore related trials

ObesitySarcopenia

Where it's being run

1 sites across 1 states
California1

Study leadership

  • Luca Pegolotti · PRINCIPAL_INVESTIGATOR · Nucleo Research, Inc.

Who to contact

Angelica Iacovelli
[email protected]
302-855-3039
Email the study team

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Do you actually qualify for this trial?

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Eligibility criteria

Inclusion

Subjects above 16 years or older at the time the source imaging was acquired.
De-identified abdominal computed tomography (CT) scan available from one of the six predefined publicly available datasets (autoPET, AMOS, MSD Pancreas, CT-ORG, ENHANCE.PET, or RATIC).
Scan covers the third lumbar vertebra (L3) with a contiguous axial slice suitable for L3-level body-composition analysis.
Demographic metadata required for stratified sampling (age, sex; BMI where available; clinical context as encoded in source dataset) is present.

Exclusion

Subject under 16 years of age at the time the source imaging was acquired.
Scan does not include the L3 vertebra or has severe motion artifact, truncation, or metallic artifact precluding analysis at the L3 level.
Duplicate or near-duplicate scans of the same subject already included in the cohort.
Missing demographic metadata required for at least one stratification axis.

What this trial measures

  • Dice Similarity Coefficient (DSC) of Soma Segmentation Versus Multi-Rater Radiologist Reference StandardSingle time point: completion of standalone Soma inference and consolidated multi-rater annotation on all 200 study scans, anticipated within two weeks of study start.

    Mean Dice Similarity Coefficient (DSC) between Soma-generated segmentation masks and the consensus reference from three board-certified radiologists, computed per tissue class (skeletal muscle, subcutaneous adipose tissue, visceral adipose tissue, intramuscular adipose tissue) on all annotated axial slices (every fifth slice across the full scan depth). Predefined performance thresholds: mean DSC greater than or equal to 0.90 for skeletal muscle, subcutaneous adipose, and visceral adipose tissues; mean DSC greater than or equal to 0.85 for intramuscular adipose tissue. Thresholds must be met both in aggregate and within every demographic and clinical subgroup with at least 20 scans (BMI category, age band, sex, body region, clinical context). Reported with 95% bias-corrected and accelerated (BCa) bootstrap confidence intervals.