Evidence map›Paper›PMID 42894755›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2025

Body composition analysis: Single slice vs. volumetric measures.

Mostafa Alnoury, Jayaram K Udupa, Yubing Tong, Tiange Liu, Yusuf Akhtar, Drew A Torigian

Abstract read
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Mostafa AlnouryMedical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, United States.
Jayaram K UdupaMedical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, United States.
Yubing TongMedical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, United States.
Tiange LiuSchool of Intelligence Science and Technology, University of Science and Technology Beijing, 100083, Beijing, China.
Yusuf AkhtarMedical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, United States.
Drew A TorigianMedical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA, 19104, United States.

Funding

Models and methods for automatically measuring disease body-wide and staging disease via FDG-PET/CT in LymphomaR01CA255748 · NCI · UNIVERSITY OF PENNSYLVANIA · PI SCHUSTER, STEPHEN J, TORIGIAN, DREW · 2021 to 2024
$2.3M
NCI NIH HHS R01 CA255748
6 · The paper itself

Abstract

Body composition analysis (BCA) is useful for evaluating nutritional status, general health, and predicting patient outcomes. Computed tomography (CT)-based BCA has become increasingly popular, with research often focusing on single-transaxial-slice measurements at the L3 vertebral level to estimate volumetric tissue properties. This method assumes the same tissue distribution in all transaxial slices across the body, potentially leading to inaccuracies in clinical assessments. This retrospective study investigates the reliability of single-slice BCA compared to volumetric measurements across the torso in a cohort of 237 adults. Using the GA-Net architecture for automatic tissue segmentation, we analyzed tissue distribution at 25 craniocaudal levels. Our results reveal significant variability in tissue distribution, with cross-sectional areas at L3 poorly correlating with 3D tissue volumes. For instance, we observed a visceral adipose tissue (VAT) volume difference of over 2,900 cm

Indexed as

Body Composition Analysis (BCA)Skeletal Muscle Tissue (SMT)Subcutaneous Adipose Tissue (SAT)Visceral Adipose Tissue (VAT)Volumetric Analysis

Identifiers

PMID42894755
PMCPMC13676770

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.