{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T00:53:40Z","timestamp":1790988820667,"version":"4.1.0"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","license":[{"start":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T00:00:00Z","timestamp":1790899200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T00:00:00Z","timestamp":1790899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Skeletal Radiol"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Bone marrow adipose tissue (BMAT) is a metabolically active fat depot implicated in skeletal aging and systemic metabolism. While\u00a0chemical shift-encoding MRI enables noninvasive quantification of bone marrow fat fraction (BMFF), current knowledge of vertebral BMAT is largely limited to small cohorts or restricted anatomical regions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To characterize the spatial distribution of vertebral bone marrow fat fraction across the spine and determine region-specific associations with age and sex in a population-based cohort.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>\n                      In this retrospective study, MRI data from 82,920 UK Biobank participants recruited between 2006 and 2010 were analyzed. The baseline case subset (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200981,318) had a mean age of 54.8\u2009\u00b1\u20097.6\u00a0years, and 42,113\/81,318 (51.8%) were female. Automated vertebral body segmentation enabled voxel-wise BMFF quantification using Dixon MRI. Vertebra- and region-level BMFF metrics were derived. Associations with age and sex were assessed using region-specific linear regression.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Vertebral BMAT demonstrated a non-linear cranio-caudal pattern. Mean BMFF was\u2009~\u200939% in the cervical,\u2009~\u200955% in the thoracic,\u2009~\u200945% in the lumbar spine, and\u2009~\u200970% in the sacrum. BMAT increased with age in all regions (all\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001; increase per decade: cervical 3.33%, thoracic 3.41%, lumbar 2.95%, sacral 3.83%). Females exhibited higher BMFF than males across all regions (all\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). The overall spatial pattern remained consistent across age groups and sexes.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Vertebral BMAT exhibits a structured, non-linear spatial distribution with region-specific age- and sex-dependent patterns. This population-based atlas provides normative reference data supporting region-specific BMAT assessment in skeletal and metabolic disease.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00256-026-05381-2","type":"journal-article","created":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T07:45:39Z","timestamp":1790927139000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Regional variation in vertebral bone marrow adiposity: a population-based atlas of age- and sex-specific patterns"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-9031-3779","authenticated-orcid":false,"given":"Ulf","family":"Bach","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Uslar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Charlotte","family":"F\u00fcnning","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guney","family":"Tombak","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katharina","family":"Frenes","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joan","family":"Walter","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philipp A.","family":"Gerber","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Felix","family":"Beuschlein","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ender","family":"Konukoglu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas","family":"Frauenfelder","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ertunc","family":"Erdil","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Falko","family":"Ensle","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,10,2]]},"reference":[{"issue":"2","key":"5381_CR1","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1016\/j.cmet.2014.06.003","volume":"20","author":"WP Cawthorn","year":"2014","unstructured":"Cawthorn WP, Scheller EL, Learman BS, et al. Bone marrow adipose tissue is an endocrine organ that contributes to increased circulating adiponectin during caloric restriction. Cell Metab. 2014;20(2):368\u201375. https:\/\/doi.org\/10.1016\/j.cmet.2014.06.003.","journal-title":"Cell Metab"},{"key":"5381_CR2","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/j.csbj.2023.12.029","volume":"24","author":"DM Morris","year":"2024","unstructured":"Morris DM, Wang C, Papanastasiou G, et al. A novel deep learning method for large-scale analysis of bone marrow adiposity using UK Biobank Dixon MRI data. Comput Struct Biotechnol J. 2024;24:89\u2013104. https:\/\/doi.org\/10.1016\/j.csbj.2023.12.029.","journal-title":"Comput Struct Biotechnol J"},{"issue":"1","key":"5381_CR3","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-16878-2","volume":"11","author":"KJ Suchacki","year":"2020","unstructured":"Suchacki KJ, Tavares AAS, Mattiucci D, et al. Bone marrow adipose tissue is a unique adipose subtype with distinct roles in glucose homeostasis. Nat Commun. 2020;11(1):3097. https:\/\/doi.org\/10.1038\/s41467-020-16878-2.","journal-title":"Nat Commun"},{"issue":"3","key":"5381_CR4","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1023\/a:1011513223894","volume":"2","author":"J Justesen","year":"2001","unstructured":"Justesen J, Stenderup K, Ebbesen EN, et al. Adipocyte tissue volume in bone marrow is increased with aging and in patients with osteoporosis. Biogerontology. 2001;2(3):165\u201371. https:\/\/doi.org\/10.1023\/a:1011513223894.","journal-title":"Biogerontology"},{"key":"5381_CR5","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2022.981487","volume":"13","author":"D Ali","year":"2022","unstructured":"Ali D, Tencerova M, Figeac F, et al. The pathophysiology of osteoporosis in obesity and type 2 diabetes in aging women and men: the mechanisms and roles of increased bone marrow adiposity. Front Endocrinol (Lausanne). 2022;13:981487. https:\/\/doi.org\/10.3389\/fendo.2022.981487.","journal-title":"Front Endocrinol (Lausanne)"},{"key":"5381_CR6","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2022.853765","volume":"13","author":"N Aaron","year":"2022","unstructured":"Aaron N, Costa S, Rosen CJ, et al. The implications of bone marrow adipose tissue on inflammaging. Front Endocrinol (Lausanne). 2022;13:853765. https:\/\/doi.org\/10.3389\/fendo.2022.853765.","journal-title":"Front Endocrinol (Lausanne)"},{"issue":"6","key":"5381_CR7","doi-asserted-by":"publisher","first-page":"401","DOI":"10.1016\/j.tem.2022.03.003","volume":"33","author":"G Pach\u00f3n-Pe\u00f1a","year":"2022","unstructured":"Pach\u00f3n-Pe\u00f1a G, Bredella MA. Bone marrow adipose tissue in metabolic health. Trends Endocrinol Metab. 2022;33(6):401\u20138. https:\/\/doi.org\/10.1016\/j.tem.2022.03.003.","journal-title":"Trends Endocrinol Metab"},{"issue":"10","key":"5381_CR8","doi-asserted-by":"publisher","first-page":"1499","DOI":"10.1007\/s00256-015-2200-y","volume":"44","author":"Y Yang","year":"2015","unstructured":"Yang Y, Luo X, Yan F, et al. Effect of zoledronic acid on vertebral marrow adiposity in postmenopausal osteoporosis assessed by MR spectroscopy. Skeletal Radiol. 2015;44(10):1499\u2013505. https:\/\/doi.org\/10.1007\/s00256-015-2200-y.","journal-title":"Skeletal Radiol"},{"issue":"1","key":"5381_CR9","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1007\/s40610-018-0087-9","volume":"4","author":"CS Craft","year":"2018","unstructured":"Craft CS, Li Z, MacDougald OA, et al. Molecular differences between subtypes of bone marrow adipocytes. Curr Mol Biol Rep. 2018;4(1):16\u201323.","journal-title":"Curr Mol Biol Rep"},{"key":"5381_CR10","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms8808","volume":"6","author":"EL Scheller","year":"2015","unstructured":"Scheller EL, Doucette CR, Learman BS, et al. Region-specific variation in the properties of skeletal adipocytes reveals regulated and constitutive marrow adipose tissues. Nat Commun. 2015;6:7808. https:\/\/doi.org\/10.1038\/ncomms8808.","journal-title":"Nat Commun"},{"issue":"1","key":"5381_CR11","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1111\/nyas.12327","volume":"1311","author":"EL Scheller","year":"2014","unstructured":"Scheller EL, Rosen CJ. What\u2019s the matter with MAT? Marrow adipose tissue, metabolism, and skeletal health. Ann N Y Acad Sci. 2014;1311(1):14\u201330. https:\/\/doi.org\/10.1111\/nyas.12327.","journal-title":"Ann N Y Acad Sci"},{"issue":"3","key":"5381_CR12","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1080\/21623945.2016.1149269","volume":"5","author":"EL Scheller","year":"2016","unstructured":"Scheller EL, Burr AA, MacDougald OA, et al. Inside out: bone marrow adipose tissue as a source of circulating adiponectin. Adipocyte. 2016;5(3):251\u201369. https:\/\/doi.org\/10.1080\/21623945.2016.1149269.","journal-title":"Adipocyte"},{"issue":"2","key":"5381_CR13","doi-asserted-by":"publisher","first-page":"390","DOI":"10.1002\/jmri.26233","volume":"49","author":"Y Zhao","year":"2019","unstructured":"Zhao Y, Huang M, Ding J, et al. Prediction of abnormal bone density and osteoporosis from lumbar spine MR using modified dixon quant in 257 subjects with quantitative computed tomography as reference. J Magn Reson Imaging. 2019;49(2):390\u20139. https:\/\/doi.org\/10.1002\/jmri.26233.","journal-title":"J Magn Reson Imaging"},{"key":"5381_CR14","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2022.1046547","volume":"13","author":"Y Leonhardt","year":"2022","unstructured":"Leonhardt Y, Ketschau J, Ruschke S, et al. Associations of incidental vertebral fractures and longitudinal changes of MR-based proton density fat fraction and T2* measurements of vertebral bone marrow. Front Endocrinol (Lausanne). 2022;13:1046547. https:\/\/doi.org\/10.3389\/fendo.2022.1046547.","journal-title":"Front Endocrinol (Lausanne)"},{"issue":"1","key":"5381_CR15","doi-asserted-by":"publisher","DOI":"10.1186\/s12891-019-2916-2","volume":"20","author":"M Dieckmeyer","year":"2019","unstructured":"Dieckmeyer M, Ruschke S, Rohrmeier A, et al. Vertebral bone marrow fat fraction changes in postmenopausal women with breast cancer receiving combined aromatase inhibitor and bisphosphonate therapy. BMC Musculoskelet Disord. 2019;20(1):515. https:\/\/doi.org\/10.1186\/s12891-019-2916-2.","journal-title":"BMC Musculoskelet Disord"},{"issue":"3","key":"5381_CR16","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1016\/j.bone.2008.11.003","volume":"44","author":"GM Blake","year":"2009","unstructured":"Blake GM, Griffith JF, Yeung DK, et al. Effect of increasing vertebral marrow fat content on BMD measurement, T-score status and fracture risk prediction by DXA. Bone. 2009;44(3):495\u2013501. https:\/\/doi.org\/10.1016\/j.bone.2008.11.003.","journal-title":"Bone"},{"key":"5381_CR17","doi-asserted-by":"publisher","first-page":"299","DOI":"10.1016\/j.bone.2017.02.001","volume":"97","author":"Y Sheu","year":"2017","unstructured":"Sheu Y, Amati F, Schwartz AV, et al. Vertebral bone marrow fat, bone mineral density and diabetes: the osteoporotic fractures in men (MrOS) study. Bone. 2017;97:299\u2013305. https:\/\/doi.org\/10.1016\/j.bone.2017.02.001.","journal-title":"Bone"},{"issue":"8","key":"5381_CR18","doi-asserted-by":"publisher","first-page":"729","DOI":"10.1007\/s00256-010-0936-y","volume":"39","author":"MA Bredella","year":"2010","unstructured":"Bredella MA. Perspective: the bone-fat connection. Skeletal Radiol. 2010;39(8):729\u201331. https:\/\/doi.org\/10.1007\/s00256-010-0936-y.","journal-title":"Skeletal Radiol"},{"issue":"4","key":"5381_CR19","doi-asserted-by":"publisher","DOI":"10.1002\/osp4.70088","volume":"11","author":"JR Parkinson","year":"2025","unstructured":"Parkinson JR, Thanaj M, Basty N, et al. Fat fraction and iron concentration in lumbar vertebral bone marrow in the UK Biobank. Obes Sci Pract. 2025;11(4):e70088. https:\/\/doi.org\/10.1002\/osp4.70088.","journal-title":"Obes Sci Pract"},{"issue":"2","key":"5381_CR20","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1007\/s00198-021-06147-3","volume":"33","author":"FT Gassert","year":"2022","unstructured":"Gassert FT, Kufner A, Gassert FG, et al. MR-based proton density fat fraction (PDFF) of the vertebral bone marrow differentiates between patients with and without osteoporotic vertebral fractures. Osteoporos Int. 2022;33(2):487\u201396. https:\/\/doi.org\/10.1007\/s00198-021-06147-3.","journal-title":"Osteoporos Int"},{"issue":"4","key":"5381_CR21","doi-asserted-by":"publisher","first-page":"1018","DOI":"10.1002\/jmri.24854","volume":"42","author":"T Baum","year":"2015","unstructured":"Baum T, Yap SP, Dieckmeyer M, et al. Assessment of whole spine vertebral bone marrow fat using chemical shift-encoding based water-fat MRI. J Magn Reson Imaging. 2015;42(4):1018\u201323. https:\/\/doi.org\/10.1002\/jmri.24854.","journal-title":"J Magn Reson Imaging"},{"issue":"4","key":"5381_CR22","doi-asserted-by":"publisher","first-page":"2548","DOI":"10.1007\/s00330-025-12035-9","volume":"36","author":"R Graf","year":"2026","unstructured":"Graf R, Platzek P, Riedel EO, et al. VIBESegmentator: full body MRI segmentation for the NAKO and UK Biobank. Eur Radiol. 2026;36(4):2548\u201362. https:\/\/doi.org\/10.1007\/s00330-025-12035-9.","journal-title":"Eur Radiol"},{"issue":"2","key":"5381_CR23","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.241613","volume":"314","author":"T Akinci D'Antonoli","year":"2025","unstructured":"Akinci D\u2019Antonoli T, Berger LK, Indrakanti AK, et al. Totalsegmentator MRI: robust sequence-independent segmentation of multiple anatomic structures in MRI. Radiology. 2025;314(2):e241613. https:\/\/doi.org\/10.1148\/radiol.241613.","journal-title":"Radiology"},{"key":"5381_CR24","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2018.00141","volume":"9","author":"T Baum","year":"2018","unstructured":"Baum T, Rohrmeier A, Syv\u00e4ri J, et al. Anatomical variation of age-related changes in vertebral bone marrow composition using chemical shift encoding-based water-fat magnetic resonance imaging. Front Endocrinol (Lausanne). 2018;9:141. https:\/\/doi.org\/10.3389\/fendo.2018.00141.","journal-title":"Front Endocrinol (Lausanne)"},{"issue":"2","key":"5381_CR25","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1002\/jmri.25769","volume":"47","author":"DC Karampinos","year":"2018","unstructured":"Karampinos DC, Ruschke S, Dieckmeyer M, et al. Quantitative MRI and spectroscopy of bone marrow. J Magn Reson Imaging. 2018;47(2):332\u201353. https:\/\/doi.org\/10.1002\/jmri.25769.","journal-title":"J Magn Reson Imaging"},{"key":"5381_CR26","doi-asserted-by":"publisher","DOI":"10.3389\/fendo.2020.00065","volume":"11","author":"J Tratwal","year":"2020","unstructured":"Tratwal J, Labella R, Bravenboer N, et al. Reporting guidelines, review of methodological standards, and challenges toward harmonization in bone marrow adiposity research. Report of the Methodologies Working Group of the International Bone Marrow Adiposity Society. Front Endocrinol (Lausanne). 2020;11:65. https:\/\/doi.org\/10.3389\/fendo.2020.00065.","journal-title":"Front Endocrinol (Lausanne)"},{"issue":"5","key":"5381_CR27","doi-asserted-by":"publisher","first-page":"492","DOI":"10.5152\/dir.2020.19401","volume":"26","author":"XJ Pei","year":"2020","unstructured":"Pei XJ, Lian YF, Yan YC, et al. Fat fraction quantification of lumbar spine: comparison of T1-weighted two-point Dixon and single-voxel magnetic resonance spectroscopy in diagnosis of multiple myeloma. Diagn Interv Radiol. 2020;26(5):492\u20137. https:\/\/doi.org\/10.5152\/dir.2020.19401.","journal-title":"Diagn Interv Radiol"},{"key":"5381_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejrad.2024.111359","volume":"172","author":"T Haueise","year":"2024","unstructured":"Haueise T, Schick F, Stefan N, et al. Comparison of the accuracy of commercial two-point and multi-echo Dixon MRI for quantification of fat in liver, paravertebral muscles, and vertebral bone marrow. Eur J Radiol. 2024;172:111359. https:\/\/doi.org\/10.1016\/j.ejrad.2024.111359.","journal-title":"Eur J Radiol"}],"container-title":["Skeletal Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00256-026-05381-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00256-026-05381-2","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00256-026-05381-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,3]],"date-time":"2026-10-03T00:02:31Z","timestamp":1790985751000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00256-026-05381-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,2]]},"references-count":28,"alternative-id":["5381"],"URL":"https:\/\/doi.org\/10.1007\/s00256-026-05381-2","relation":{},"ISSN":["0364-2348","1432-2161"],"issn-type":[{"value":"0364-2348","type":"print"},{"value":"1432-2161","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,2]]},"assertion":[{"value":"18 May 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 September 2026","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 September 2026","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 October 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"This research has been conducted using the UK Biobank Resource under application number 140043. Ethical approvals to conduct the study were obtained by UK Biobank, and the participants provided informed consent.","order":1,"name":"Ethics","label":"Ethical approval","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","label":"Conflict of interest","group":{"name":"EthicsHeading","label":"Declarations"}}]}}