<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>9(19)</volume><submitter>Haueise T</submitter><pubmed_abstract>This research addresses the assessment of adipose tissue (AT) and spatial distribution of visceral (VAT) and subcutaneous fat (SAT) in the trunk from standardized magnetic resonance imaging at 3 T, thereby demonstrating the feasibility of deep learning (DL)-based image segmentation in a large population-based cohort in Germany (five sites). Volume and distribution of AT play an essential role in the pathogenesis of insulin resistance, a risk factor of developing metabolic/cardiovascular diseases. Cross-validated training of the DL-segmentation model led to a mean Dice similarity coefficient of >0.94, corresponding to a mean absolute volume deviation of about 22 ml. SAT is significantly increased in women compared to men, whereas VAT is increased in males. Spatial distribution shows age- an</pubmed_abstract><journal>Science advances</journal><pagination>eadd0433</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC10181183</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>Analysis of volume and topography of adipose tissue in the trunk: Results of MRI of 11,141 participants in the German National Cohort.</pubmed_title><pmcid>PMC10181183</pmcid><pubmed_authors>Machann J</pubmed_authors><pubmed_authors>Peters A</pubmed_authors><pubmed_authors>Norajitra T</pubmed_authors><pubmed_authors>Jockel KH</pubmed_authors><pubmed_authors>Gobel-Gueniot K</pubmed_authors><pubmed_authors>Volzke H</pubmed_authors><pubmed_authors>Stefan N</pubmed_authors><pubmed_authors>Haueise T</pubmed_authors><pubmed_authors>Schick F</pubmed_authors><pubmed_authors>Hosten N</pubmed_authors><pubmed_authors>Willich SN</pubmed_authors><pubmed_authors>Schlett CL</pubmed_authors><pubmed_authors>Umutlu L</pubmed_authors><pubmed_authors>Kroncke T</pubmed_authors><pubmed_authors>Weiss JB</pubmed_authors><pubmed_authors>Kauczor HU</pubmed_authors><pubmed_authors>Bamberg F</pubmed_authors><pubmed_authors>Maier-Hein KH</pubmed_authors><pubmed_authors>Rospleszcz S</pubmed_authors><pubmed_authors>Krist L</pubmed_authors><pubmed_authors>Nonnenmacher T</pubmed_authors><pubmed_authors>Pischon T</pubmed_authors><pubmed_authors>Nattenmuller J</pubmed_authors><pubmed_authors>Niendorf T</pubmed_authors></additional><is_claimable>false</is_claimable><name>Analysis of volume and topography of adipose tissue in the trunk: Results of MRI of 11,141 participants in the German National Cohort.</name><description>This research addresses the assessment of adipose tissue (AT) and spatial distribution of visceral (VAT) and subcutaneous fat (SAT) in the trunk from standardized magnetic resonance imaging at 3 T, thereby demonstrating the feasibility of deep learning (DL)-based image segmentation in a large population-based cohort in Germany (five sites). Volume and distribution of AT play an essential role in the pathogenesis of insulin resistance, a risk factor of developing metabolic/cardiovascular diseases. Cross-validated training of the DL-segmentation model led to a mean Dice similarity coefficient of >0.94, corresponding to a mean absolute volume deviation of about 22 ml. SAT is significantly increased in women compared to men, whereas VAT is increased in males. Spatial distribution shows age- an</description><dates><release>2023-01-01T00:00:00Z</release><publication>2023 May</publication><modification>2025-04-21T22:44:14.392Z</modification><creation>2025-04-05T18:50:46.051Z</creation></dates><accession>S-EPMC10181183</accession><cross_references><pubmed>37172093</pubmed><doi>10.1126/sciadv.add0433</doi></cross_references></HashMap>