{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T06:09:16Z","timestamp":1784268556576,"version":"3.55.0"},"reference-count":36,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T00:00:00Z","timestamp":1783900800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>Objectives: To evaluate the impact of contrast phase, age, and sex on CT-derived body composition metrics\u2014specifically attenuation and volume of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), liver, and skeletal muscle. The potential of the proportion of muscle voxels below 0 Hounsfield units (HU) as a surrogate for fatty infiltration was also explored. Materials and Methods: A retrospective analysis of 866 multiphasic abdominal CT scans (non-enhanced [NE], arterial [ART], portal venous [PV]) from 2012 to 2022 was performed. Segmentation of SAT, VAT, liver, and skeletal muscle was conducted using the AI-based TotalSegmentator. Wilcoxon signed-rank tests and Bland\u2013Altman analysis (mean bias and 95% limits of agreement) were applied to assess contrast-related effects; Spearman\u2019s correlation coefficient was used to assess demographic associations. Results: Significant variation in attenuation and volume of SAT, VAT, and muscle was observed across contrast phases (p &lt; 0.001). SAT attenuation was higher in NE and PV than in ART, while VAT attenuation was highest in PV. SAT volume increased and VAT volume decreased in contrast-enhanced phases. Attenuation and volume showed strong inter-phase correlation (\u03c1 &gt; 0.9). VAT attenuation was significantly higher in females, whereas VAT volume was significantly greater in males. VAT volume negatively correlated with liver attenuation (\u03c1 = \u22120.33). Muscle voxels &lt;0 HU were significantly reduced in contrast-enhanced scans. Conclusions: Contrast phase, age, and sex significantly influence CT-based body composition parameters. These confounding factors should be considered when using quantitative imaging biomarkers in clinical and research settings.<\/jats:p>","DOI":"10.3390\/jimaging12070319","type":"journal-article","created":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T00:55:21Z","timestamp":1783990521000},"page":"319","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Exploring Adipose Tissue Behavior in CT: Impact of Age, Sex, and Contrast Media on Body Composition, Liver and Skeletal Muscle"],"prefix":"10.3390","volume":"12","author":[{"given":"Emil","family":"Matthisson","sequence":"first","affiliation":[{"name":"Faculty of Medicine, University of Basel, Klingelbergstrasse 61, 4057 Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanns-Christian","family":"Breit","sequence":"additional","affiliation":[{"name":"Department of Radiology, University Hospital of Basel, Petersgraben 4, 4031 Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6586-0034","authenticated-orcid":false,"given":"Markus","family":"Obmann","sequence":"additional","affiliation":[{"name":"Department of Radiology, University Hospital of Basel, Petersgraben 4, 4031 Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jakob","family":"Wasserthal","sequence":"additional","affiliation":[{"name":"Department of Radiology, University Hospital of Basel, Petersgraben 4, 4031 Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin","family":"Segeroth","sequence":"additional","affiliation":[{"name":"Department of Radiology, University Hospital of Basel, Petersgraben 4, 4031 Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Boll","sequence":"additional","affiliation":[{"name":"Department of Radiology, University Hospital of Basel, Petersgraben 4, 4031 Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,7,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"902","DOI":"10.4329\/wjr.v8.i12.902","article-title":"Computed tomography and patient risk: Facts, perceptions and uncertainties","volume":"8","author":"Power","year":"2016","journal-title":"World J. Radiol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1007\/s11547-019-01109-6","article-title":"European trends in radiology: Investigating factors affecting the number of examinations and the effective dose","volume":"125","author":"Masjedi","year":"2020","journal-title":"Radiol. Medica"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"e230024","DOI":"10.1148\/ryai.230024","article-title":"TotalSegmentator: Robust Segmentation of 104 Anatomic Structures in CT Images","volume":"5","author":"Wasserthal","year":"2023","journal-title":"Radiol. Artif. Intell."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"110728","DOI":"10.1016\/j.ejrad.2023.110728","article-title":"CNN-based evaluation of bone density improves diagnostic performance to detect osteopenia and osteoporosis in patients with non-contrast chest CT examinations","volume":"161","author":"Breit","year":"2023","journal-title":"Eur. J. Radiol."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"761","DOI":"10.2147\/RMHP.S257677","article-title":"Total psoas area index is valuable to assess sarcopenia, sarcopenic overweight\/obesity and predict outcomes in patients undergoing open pancreatoduodenectomy","volume":"13","author":"Xu","year":"2020","journal-title":"Risk Manag. Healthc. Policy"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"175","DOI":"10.1016\/j.radonc.2021.04.019","article-title":"A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy","volume":"160","author":"Chen","year":"2021","journal-title":"Radiother. Oncol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"e230235","DOI":"10.1148\/ryai.230235","article-title":"TotalSegmentator: A Gift to the Biomedical Imaging Community","volume":"5","author":"Sebro","year":"2023","journal-title":"Radiol. Artif. Intell."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"715","DOI":"10.1016\/S2213-8587(19)30084-1","article-title":"Visceral and ectopic fat, atherosclerosis, and cardiometabolic disease: A position statement","volume":"7","author":"Neeland","year":"2019","journal-title":"Lancet Diabetes Endocrinol."},{"key":"ref_9","first-page":"452","article-title":"Abdominal obesity as important component of insulin-resistance syndrome","volume":"9","author":"Despres","year":"1993","journal-title":"Nutrition"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1016\/j.ecl.2020.02.002","article-title":"Visceral Fat: Culprit or Canary?","volume":"49","author":"Jensen","year":"2020","journal-title":"Endocrinol. Metab. Clin. N. Am."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Charette, N., Vandeputte, C., Ameye, L., Bogaert, C.V., Krygier, J., Guiot, T., Deleporte, A., Delaunoit, T., Geboes, K., and Van Laethem, J.L. (2019). Prognostic value of adipose tissue and muscle mass in advanced colorectal cancer: A post hoc analysis of two non-randomized phase II trials. BMC Cancer, 19.","DOI":"10.1186\/s12885-019-5319-8"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"582","DOI":"10.2214\/AJR.20.22874","article-title":"Value-added opportunistic CT: Insights into osteoporosis and sarcopenia","volume":"215","author":"Boutin","year":"2020","journal-title":"Am. J. Roentgenol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1148\/radiol.2019190512","article-title":"Automated Liver Fat Quantification at Nonenhanced Abdominal CT for Population-based Steatosis Assessment","volume":"293","author":"Graffy","year":"2019","journal-title":"Radiology"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"697","DOI":"10.21037\/qims-20-907","article-title":"3D-segmentation and characterization of visceral and abdominal subcutaneous adipose tissue on CT: Influence of contrast medium and contrast phase","volume":"11","author":"Gohmann","year":"2021","journal-title":"Quant. Imaging Med. Surg."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.2169\/internalmedicine.52.0521","article-title":"Lipid Deposition in Various Sites of the Skeletal Muscles and Liver Exhibits a Positive Correlation with Visceral Fat Accumulation in Middle-aged Japanese Men with Metabolic Syndrome","volume":"52","author":"Taira","year":"2013","journal-title":"Intern. Med."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e220574","DOI":"10.1148\/radiol.220574","article-title":"Abdominal CT Body Composition Thresholds Using Automated AI Tools for Predicting 10-year Adverse Outcomes","volume":"306","author":"Lee","year":"2023","journal-title":"Radiology"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"20170968","DOI":"10.1259\/bjr.20170968","article-title":"Fully automated segmentation and quantification of visceral and subcutaneous fat at abdominal CT: Application to a longitudinal adult screening cohort","volume":"91","author":"Lee","year":"2018","journal-title":"Br. J. Radiol."},{"key":"ref_18","unstructured":"(2025, March 20). Nora\u2014The Medical Imaging Platform. Available online: https:\/\/www.nora-imaging.com\/."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1617","DOI":"10.1007\/s10278-024-01265-w","article-title":"Intra-Individual Reproducibility of Automated Abdominal Organ Segmentation\u2014Performance of TotalSegmentator Compared to Human Readers and an Independent nnU-Net Model","volume":"38","author":"Abel","year":"2025","journal-title":"J. Digit Imaging. Inform. Med."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"13419","DOI":"10.1038\/s41598-022-17611-3","article-title":"CT-derived body composition analysis could possibly replace DXA and BIA to monitor NET-patients","volume":"12","author":"Kroll","year":"2022","journal-title":"Sci. Rep."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1007\/s13244-015-0414-0","article-title":"Imaging body composition in cancer patients: Visceral obesity, sarcopenia and sarcopenic obesity may impact on clinical outcome","volume":"6","author":"Yip","year":"2015","journal-title":"Insights Imaging"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"839","DOI":"10.2337\/diabetes.48.4.839","article-title":"Effects of weight loss on regional fat distribution and insulin sensitivity in obesity","volume":"48","author":"Goodpaster","year":"1999","journal-title":"Diabetes"},{"key":"ref_23","first-page":"203","article-title":"Adipose tissue distribution and plasma lipoprotein levels in obese women. Importance of intra-abdominal fat","volume":"9","author":"Despres","year":"1989","journal-title":"Arterioscler. Off. J. Am. Heart Assoc. Inc."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"826","DOI":"10.2337\/diab.41.7.826","article-title":"Visceral Obesity in Men: Associations With Glucose Tolerance, Plasma Insulin, and Lipoprotein Levels","volume":"41","author":"Pouliot","year":"1992","journal-title":"Diabetes"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1229","DOI":"10.1007\/s00261-020-02755-5","article-title":"Fully automated CT imaging biomarkers of bone, muscle, and fat: Correcting for the effect of intravenous contrast","volume":"46","author":"Perez","year":"2021","journal-title":"Abdom. Radiol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"763","DOI":"10.1038\/sj.ijo.0803474","article-title":"Visceral adipose tissue: Relationships between single slice areas at different locations and obesity-related health risks","volume":"31","author":"Shen","year":"2007","journal-title":"Int. J. Obes."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"679","DOI":"10.2337\/diacare.29.03.06.dc05-1500","article-title":"Does Measurement Site for Visceral and Abdominal Subcutaneous Adipose Tissue Alter Associations With the Metabolic Syndrome?","volume":"29","author":"Kuk","year":"2006","journal-title":"Diabetes Care"},{"key":"ref_28","first-page":"24","article-title":"Agreement between software programmes of body composition analyses on abdominal computed tomography scans of obese adults","volume":"64","author":"Barbalho","year":"2020","journal-title":"Arch. Endocrinol. Metab."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1450","DOI":"10.21037\/qims-21-619","article-title":"Body composition assessment: Comparison of quantitative values between magnetic resonance imaging and computed tomography","volume":"12","author":"Zaffina","year":"2022","journal-title":"Quant. Imaging Med. Surg."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2333","DOI":"10.1152\/japplphysiol.00744.2004","article-title":"Total body skeletal muscle and adipose tissue volumes: Estimation from a single abdominal cross-sectional image","volume":"97","author":"Shen","year":"2004","journal-title":"J. Appl. Physiol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2374","DOI":"10.1038\/s41598-022-06232-5","article-title":"Healthy US population reference values for CT visceral fat measurements and the impact of IV contrast, HU range, and spinal levels","volume":"12","author":"Derstine","year":"2022","journal-title":"Sci. Rep."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.nut.2018.08.001","article-title":"Body composition evaluation with computed tomography: Contrast media and slice thickness cause methodological errors","volume":"59","author":"Morsbach","year":"2019","journal-title":"Nutrition"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"108918","DOI":"10.1016\/j.ejrad.2020.108918","article-title":"Validation of a fully automated liver segmentation algorithm using multi-scale deep reinforcement learning and comparison versus manual segmentation","volume":"126","author":"Winkel","year":"2020","journal-title":"Eur. J. Radiol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"900","DOI":"10.1111\/j.1440-1746.2007.05212.x","article-title":"Visceral adipose tissue area is an independent risk factor for hepatic steatosis","volume":"23","author":"Park","year":"2008","journal-title":"J. Gastroenterol. Hepatol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1038\/ncpgasthep0186","article-title":"Mechanisms of Disease: Adipocytokines and visceral adipose tissue\u2014Emerging role in nonalcoholic fatty liver disease","volume":"2","year":"2005","journal-title":"Nat. Clin. Pract. Gastroenterol. Hepatol."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.nut.2017.02.011","article-title":"Body composition measurement using computed tomography: Does the phase of the scan matter?","volume":"41","author":"Rollins","year":"2017","journal-title":"Nutrition"}],"container-title":["Journal of Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2313-433X\/12\/7\/319\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T05:41:42Z","timestamp":1784266902000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2313-433X\/12\/7\/319"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,13]]},"references-count":36,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2026,7]]}},"alternative-id":["jimaging12070319"],"URL":"https:\/\/doi.org\/10.3390\/jimaging12070319","relation":{},"ISSN":["2313-433X"],"issn-type":[{"value":"2313-433X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,13]]}}}