Trial reportPloS one2018
Tutorial for using SliceOmatic to calculate thigh area and composition from computed tomography images from older adults.
Trial report in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02261961 (Immune Function and Muscle Adaptations to Resistance Exercise in Older Adults), which is not on this map. Cited by 15 papers.
What it found
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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.
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.
Immune Function and Muscle Adaptations to Resistance Exercise in Older Adults
Who cites it
15 citing papers in PubMed, 24 citations in OpenAlex.
- A guide for using NIH Image J for single slice cross-sectional area and composition analysis of the thigh from computed tomography.PloS one · 2019Trial
- Tutorial for using SliceOmatic to calculate thigh area and composition from computed tomography images from older adults.PloS one · 2018Trial
- Comprehensive Study on Quantitative Evaluation of Oral Muscle Tissue in Children With Low Tongue Posture Using Cone Beam Computed Tomography: A Comprehensive Study on Nasal Ventilation Conditions Using Computational Fluid Dynamics.Journal of oral rehabilitation · 2026Article
- Article
- Characterization of body composition dynamics throughout treatment in patients with early-stage breast cancer.NPJ breast cancer · 2026Article
- Effect of Preoperative Sarcopenic Obesity on Outcomes in Patients with Gastric Cancer After Surgery.Cancers · 2026Article
- The Impact of Sarcopenic Obesity on Weight Loss Outcomes and Recurrent Weight Gain Following Laparoscopic Sleeve Gastrectomy.Diabetes, metabolic syndrome and obesity : targets and therapy · 2025Article
- Association of Computed Tomography Scan-Assessed Body Composition with Immune and PI3K/AKT Pathway Proteins in Distinct Breast Cancer Tumor Components.International journal of molecular sciences · 2024Article
- Prognostic value of computed tomography‑derived skeletal muscle index and radiodensity in patients with gastric cancer after curative gastrectomy.Oncology letters · 2024Article
- AI-based fully automatic image analysis: Optimal abdominal and thoracic segmentation volumes for estimating total muscle volume on computed tomography scans.Osteoporosis and sarcopenia · 2024Article
- Effect of Sarcopenic Obesity on Weight Loss Outcomes and Quality of Life after Laparoscopic Sleeve Gastrectomy: A Retrospective Cohort Study.Obesity surgery · 2024Observational
- Metabolic score tool for personalized acute pancreatitis prognosis: A multicenter analysis.Biomolecules & biomedicine · 2024Article
- Altered Plasma Fatty Acid Abundance Is Associated with Cachexia in Treatment-Naïve Pancreatic Cancer.Cells · 2022Article
- Population Pharmacokinetic Analysis from First-in-Human Data for HDAC Inhibitor, REC-2282 (AR-42), in Patients with Solid Tumors and Hematologic Malignancies: A Case Study for Evaluating Flat vs. Body Size Normalized Dosing.European journal of drug metabolism and pharmacokinetics · 2021Article
- Muscle mass, not radiodensity, predicts physical function in cancer patients with or without cachexia.Oncotarget · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 3 institutions in 1 country.
Funding
Abstract
objectiveArea of muscle, fat, and bone is often measured in thigh CT scans when tissue composition is a key outcome. SliceOmatic software is commonly referenced for such analysis but published methods may be insufficient for new users. Thus, a quick start guide to calculating thigh composition using SliceOmatic has been developed.
methodsCT images of the thigh were collected from older (69 ± 4 yrs, N = 24) adults before and after 12-weeks of resistance training. SliceOmatic was used to segment images into seven density regions encompassing fat, muscle, and bone from -190 to +2000 Hounsfield Units [HU]. The relative contributions to thigh area and the effects of tissue density overlap for skin and marrow with muscle and fat were determined.
resultsThe largest contributors to the thigh were normal fat (-190 to -30 HU, 29.1 ± 7.4%) and muscle (35 to 100 HU, 48.9 ± 8.2%) while the smallest were high density (101 to 150 HU, 0.79 ± 0.50%) and very high density muscle (151 to 200 HU, 0.07 ± 0.02%). Training significantly (P<0.05) increased area for muscle in the very low (-29 to -1 HU, 5.5 ± 7.9%), low (0 to 34 HU, 9.6 ± 16.8%), normal (35 to 100 HU, 4.2 ± 7.9%), and high (100 to 150 HU, 70.9 ± 80.6%) density ranges for muscle. Normal fat, very high density muscle and bone did not change (P>0.05). Contributions to area were altered by ~1% or less and the results of training were not affected by accounting for skin and marrow.
conclusionsWhen using SliceOmatic to calculate thigh composition, accounting for skin and marrow may not be necessary. We recommend defining muscle as -29 to +200 HU but that smaller ranges (e.g. low density muscle, 0 to 34 HU) can easily be examined for relationships with the health condition and intervention of interest.
trial registrationClinicaltrials.gov NCT02261961.
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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.