{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,26]],"date-time":"2026-10-26T01:04:08Z","timestamp":1792976648256,"version":"4.5.0"},"reference-count":33,"publisher":"Springer Science and Business Media LLC","issue":"3","license":[{"start":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T00:00:00Z","timestamp":1757548800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T00:00:00Z","timestamp":1757548800000},"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":["Eur Radiol"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>\n                      Computed tomography (CT) is widely used for bone health assessment, impacting osteoporosis diagnosis and treatment. However, the influence of intravenous contrast agents on CT-based bone mineral density (BMD) measurements remains debated. This study evaluates the effect of contrast agents on Hounsfield measurements,\n                      <jats:italic>T<\/jats:italic>\n                      -scores, and\n                      <jats:italic>Z<\/jats:italic>\n                      -scores, assessing their impact on diagnostic accuracy to reduce misclassification and optimize CT-based BMD assessment.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>\n                      A retrospective analysis of 597 patients (median age: 66 years, 157 females, 440 males) was performed using dual-energy CT (DECT) scans of the abdomen and chest. All patients underwent non-contrast, arterial, and venous phase CT. Automated segmentation (nnU-Net) delineated L1 and L1\u2013L4 trabecular bone, validated by two radiologists.\n                      <jats:italic>T<\/jats:italic>\n                      -scores were calculated according to DEXA-equivalent guidelines.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Based on non-contrast CT, 35% were diagnosed with osteoporosis, 46% with osteopenia, and 18% had normal bone status. Median\n                      <jats:italic>T<\/jats:italic>\n                      -score was \u22122.0 (L1) and \u22122.1 (L1\u2013L4) (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). Contrast agents significantly altered BMD values, with median changes of 22.9% (arterial) and 20.1% (venous). The most pronounced changes occurred in patients under 50 years (+99% at L1,\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001). In older females, 21% were misclassified as osteopenic instead of osteoporotic (\n                      <jats:italic>p<\/jats:italic>\n                      \u2009&lt;\u20090.001).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Contrast agents significantly affect BMD measurements, leading to diagnostic misclassification. This effect should be considered when using CT for osteoporosis diagnosis and treatment planning.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Key Points<\/jats:title>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Question<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>Standard CT scans with contrast media may distort bone density measurements, potentially leading to misdiagnosis of osteoporosis and inappropriate clinical decisions<\/jats:italic>\n                      .\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Findings<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>Contrast-enhanced CT scans significantly alter T- and Z-scores, leading to diagnostic shifts in over 50% of patients, especially women over 50<\/jats:italic>\n                      .\n                    <\/jats:p>\n                    <jats:p>\n                      <jats:bold>\n                        <jats:italic>Clinical relevance<\/jats:italic>\n                      <\/jats:bold>\n                      <jats:italic>Our findings highlight the risk of osteoporosis misclassification due to contrast agents in CT imaging, underscoring the need for adjusted interpretation protocols to ensure accurate diagnosis and appropriate treatment, particularly in older adults and female patients<\/jats:italic>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Graphical Abstract<\/jats:title>\n                  <\/jats:sec>","DOI":"10.1007\/s00330-025-11988-1","type":"journal-article","created":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T18:28:32Z","timestamp":1757615312000},"page":"2135-2146","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Opportunistic osteoporosis assessment from routine CT\u2014effect of intravenous contrast agents on absolute values, T-scores, and derived classifications in single- and dual-energy CT"],"prefix":"10.1007","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0524-6574","authenticated-orcid":false,"given":"Jennifer","family":"Gotta","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vitali","family":"Koch","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Scherwin","family":"Mahmoudi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon S.","family":"Martin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jan Erik","family":"Scholtz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christian","family":"Booz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katrin","family":"Eichler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon","family":"Bernatz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Philipp","family":"Reschke","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tatjana","family":"Gruber-Rouh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tommaso","family":"D\u2019Angelo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Thomas J.","family":"Vogl","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Leon D.","family":"Gruenewald","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,9,11]]},"reference":[{"key":"11988_CR1","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1007\/s12603-023-1971-4","volume":"27","author":"Z Zhu","year":"2023","unstructured":"Zhu Z, Yu P, Wu Y et al (2023) Sex specific global burden of osteoporosis in 204 countries and territories, from 1990 to 2030: an age-period-cohort modeling study. J Nutr Health Aging 27:767\u2013774. https:\/\/doi.org\/10.1007\/s12603-023-1971-4","journal-title":"J Nutr Health Aging"},{"key":"11988_CR2","doi-asserted-by":"publisher","first-page":"1243","DOI":"10.1093\/gerona\/glt093","volume":"68","author":"JA Cauley","year":"2013","unstructured":"Cauley JA (2013) Public health impact of osteoporosis. J Gerontol A Biol Sci Med Sci 68:1243\u20131251. https:\/\/doi.org\/10.1093\/gerona\/glt093","journal-title":"J Gerontol A Biol Sci Med Sci"},{"key":"11988_CR3","doi-asserted-by":"publisher","first-page":"3023","DOI":"10.1007\/s00198-016-3631-6","volume":"27","author":"RB Hopkins","year":"2016","unstructured":"Hopkins RB, Burke N, Von Keyserlingk C et al (2016) The current economic burden of illness of osteoporosis in Canada. Osteoporos Int 27:3023\u20133032. https:\/\/doi.org\/10.1007\/s00198-016-3631-6","journal-title":"Osteoporos Int"},{"key":"11988_CR4","unstructured":"Osteoporosis Imaging: State of the Art and Advanced Imaging (2024) Radiology. Zugegriffen: 8. Juli 2024. [Online]. Verf\u00fcgbar unter: https:\/\/pubs.rsna.org\/doi\/10.1148\/radiol.12110462"},{"key":"11988_CR5","doi-asserted-by":"publisher","first-page":"254","DOI":"10.1109\/RBME.2018.2852620","volume":"12","author":"AS Areeckal","year":"2019","unstructured":"Areeckal AS, Kocher M, S DS (2019) Current and emerging diagnostic imaging-based techniques for assessment of osteoporosis and fracture risk. IEEE Rev Biomed Eng 12:254\u2013268. https:\/\/doi.org\/10.1109\/RBME.2018.2852620","journal-title":"IEEE Rev Biomed Eng"},{"key":"11988_CR6","doi-asserted-by":"publisher","DOI":"10.1007\/s11657-020-00808-2","volume":"15","author":"CP Wong","year":"2020","unstructured":"Wong CP, Gani LU, Chong LR (2020) Dual-energy X-ray absorptiometry bone densitometry and pitfalls in the assessment of osteoporosis: a primer for the practicing clinician. Arch Osteoporos 15:135. https:\/\/doi.org\/10.1007\/s11657-020-00808-2","journal-title":"Arch Osteoporos"},{"key":"11988_CR7","doi-asserted-by":"publisher","first-page":"980","DOI":"10.1007\/s00259-022-06028-9","volume":"50","author":"JC Dickson","year":"2023","unstructured":"Dickson JC, Armstrong IS, Gabi\u00f1a PM et al (2023) EANM practice guideline for quantitative SPECT-CT. Eur J Nucl Med Mol Imaging 50:980\u2013995. https:\/\/doi.org\/10.1007\/s00259-022-06028-9","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"11988_CR8","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1002\/jmri.25647","volume":"46","author":"G Chang","year":"2017","unstructured":"Chang G, Boone S, Martel D et al (2017) MRI assessment of bone structure and microarchitecture. J Magn Reson Imaging 46:323\u2013337. https:\/\/doi.org\/10.1002\/jmri.25647","journal-title":"J Magn Reson Imaging"},{"key":"11988_CR9","first-page":"769","volume":"24","author":"AL Coronha","year":"2011","unstructured":"Coronha AL, Camilo ME, Ravasco P (2011) [The relevance of body composition in cancer patients: What is the evidence?]. Acta Med Port 24:769\u2013778","journal-title":"Acta Med Port"},{"key":"11988_CR10","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1007\/s11154-006-9004-2","volume":"7","author":"G Kazakia","year":"2007","unstructured":"Kazakia G, Majumdar S (2007) New imaging technologies in the diagnosis of osteoporosis. Rev Endocrine Metab Disord 7:67\u201374. https:\/\/doi.org\/10.1007\/s11154-006-9004-2","journal-title":"Rev Endocrine Metab Disord"},{"key":"11988_CR11","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1007\/s11926-020-00892-w","volume":"22","author":"TM Link","year":"2020","unstructured":"Link TM, Kazakia G (2020) Update on imaging-based measurement of bone mineral density and quality. Curr Rheumatol Rep 22:13. https:\/\/doi.org\/10.1007\/s11926-020-00892-w","journal-title":"Curr Rheumatol Rep"},{"key":"11988_CR12","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1002\/jmri.28067","volume":"56","author":"MC Florkow","year":"2022","unstructured":"Florkow MC, Willemsen K, Mascarenhas VV, Oei EHG, van Stralen M, Seevinck PR (2022) Magnetic resonance imaging versus computed tomography for three-dimensional bone imaging of musculoskeletal pathologies: a review. J Magn Reson Imaging 56:11\u201334. https:\/\/doi.org\/10.1002\/jmri.28067","journal-title":"J Magn Reson Imaging"},{"key":"11988_CR13","doi-asserted-by":"publisher","first-page":"1229","DOI":"10.1007\/s00261-020-02755-5","volume":"46","author":"AA Perez","year":"2021","unstructured":"Perez AA, Pickhardt PJ, Elton DC, Sandfort V, Summers RM (2021) Fully automated CT imaging biomarkers of bone, muscle, and fat: correcting for the effect of intravenous contrast. Abdom Radiol (NY) 46:1229\u20131235. https:\/\/doi.org\/10.1007\/s00261-020-02755-5","journal-title":"Abdom Radiol (NY)"},{"key":"11988_CR14","unstructured":"Blankemeier L, Desai A, Chaves JMZ et al (2023) Comp2Comp: open-source body composition assessment on computed tomography. Preprint at https:\/\/arxiv.org\/abs\/2302.06568"},{"key":"11988_CR15","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1097\/RLI.0000000000001040","volume":"59","author":"J Haubold","year":"2024","unstructured":"Haubold J, Baldini G, Parmar V et al (2024) BOA: a CT-based body and organ analysis for radiologists at the point of care. Invest Radiol 59:433\u2013441. https:\/\/doi.org\/10.1097\/RLI.0000000000001040","journal-title":"Invest Radiol"},{"key":"11988_CR16","doi-asserted-by":"publisher","first-page":"203","DOI":"10.1038\/s41592-020-01008-z","volume":"18","author":"F Isensee","year":"2021","unstructured":"Isensee F, Jaeger PF, Kohl SAA, Petersen J, Maier-Hein KH (2021) nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation. Nat Methods 18:203\u2013211. https:\/\/doi.org\/10.1038\/s41592-020-01008-z","journal-title":"Nat Methods"},{"key":"11988_CR17","doi-asserted-by":"publisher","first-page":"e230024","DOI":"10.1148\/ryai.230024","volume":"5","author":"J Wasserthal","year":"2023","unstructured":"Wasserthal J, Breit HC, Meyer MT et al (2023) TotalSegmentator: robust segmentation of 104 anatomic structures in CT images. Radiology 5:e230024. https:\/\/doi.org\/10.1148\/ryai.230024","journal-title":"Radiology"},{"key":"11988_CR18","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.bone.2016.12.016","volume":"104","author":"HP Dimai","year":"2017","unstructured":"Dimai HP (2017) Use of dual-energy X-ray absorptiometry (DXA) for diagnosis and fracture risk assessment; WHO-criteria, T- and Z-score, and reference databases. Bone 104:39\u201343. https:\/\/doi.org\/10.1016\/j.bone.2016.12.016","journal-title":"Bone"},{"key":"11988_CR19","doi-asserted-by":"publisher","first-page":"2023","DOI":"10.1007\/s00198-017-4009-0","volume":"28","author":"JA Kanis","year":"2017","unstructured":"Kanis JA, Cooper C, Rizzoli R et al (2017) Identification and management of patients at increased risk of osteoporotic fracture: outcomes of an ESCEO expert consensus meeting. Osteoporos Int 28:2023\u20132034. https:\/\/doi.org\/10.1007\/s00198-017-4009-0","journal-title":"Osteoporos Int"},{"key":"11988_CR20","doi-asserted-by":"publisher","first-page":"20180726","DOI":"10.1259\/bjr.20180726","volume":"92","author":"PJ Pickhardt","year":"2019","unstructured":"Pickhardt PJ, Lee SJ, Liu J et al (2019) Population-based opportunistic osteoporosis screening: Validation of a fully automated CT tool for assessing longitudinal BMD changes. Br J Radiol 92:20180726. https:\/\/doi.org\/10.1259\/bjr.20180726","journal-title":"Br J Radiol"},{"key":"11988_CR21","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.nut.2017.12.016","volume":"53","author":"F Morsbach","year":"2018","unstructured":"Morsbach F, Zhang YH, Nowik P et al (2018) Influence of tube potential on CT body composition analysis. Nutrition 53:9\u201313. https:\/\/doi.org\/10.1016\/j.nut.2017.12.016","journal-title":"Nutrition"},{"key":"11988_CR22","doi-asserted-by":"publisher","first-page":"687","DOI":"10.1007\/s00256-022-04222-2","volume":"52","author":"Z Kutle\u0161a","year":"2023","unstructured":"Kutle\u0161a Z, Jerkovi\u0107 K, Ordulj I, Budimir Mr\u0161i\u0107 D (2023) The effect of contrast media on CT measures of bone mineral density: a systematic review. Skeletal Radiol 52:687\u2013694. https:\/\/doi.org\/10.1007\/s00256-022-04222-2","journal-title":"Skeletal Radiol"},{"key":"11988_CR23","doi-asserted-by":"publisher","first-page":"101441","DOI":"10.1016\/j.jocd.2023.101441","volume":"27","author":"A Cheneymann","year":"2024","unstructured":"Cheneymann A, Therkildsen J, Winther S et al (2024) Bone mineral density derived from cardiac CT scans: using contrast enhanced scans for opportunistic screening. J Clin Densitom 27:101441. https:\/\/doi.org\/10.1016\/j.jocd.2023.101441","journal-title":"J Clin Densitom"},{"key":"11988_CR24","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-024-79985-w","volume":"14","author":"TR Ahn","year":"2024","unstructured":"Ahn TR, Lee JH, Lee J (2024) Effect of contrast media on CT bone density assessment: comparative analysis of low-dose chest CT and abdominopelvic CT. Sci Rep 14:28378. https:\/\/doi.org\/10.1038\/s41598-024-79985-w","journal-title":"Sci Rep"},{"key":"11988_CR25","doi-asserted-by":"publisher","DOI":"10.1186\/s41747-021-00259-5","volume":"6","author":"M Woisetschl\u00e4ger","year":"2022","unstructured":"Woisetschl\u00e4ger M, Klintstr\u00f6m E, Sp\u00e5ngeus A (2022) The impact of imaging time and contrast agent dose on screening for osteoporosis with contrast-enhanced CT. Eur Radiol Exp 6:8. https:\/\/doi.org\/10.1186\/s41747-021-00259-5","journal-title":"Eur Radiol Exp"},{"key":"11988_CR26","doi-asserted-by":"publisher","first-page":"880","DOI":"10.1016\/j.acra.2021.06.010","volume":"29","author":"V Koch","year":"2022","unstructured":"Koch V, Albrecht MH, Gruenewald LD et al (2022) Impact of intravenously injected contrast agent on bone mineral density measurement in dual-source dual-energy CT. Acad Radiol 29:880\u2013887. https:\/\/doi.org\/10.1016\/j.acra.2021.06.010","journal-title":"Acad Radiol"},{"key":"11988_CR27","doi-asserted-by":"publisher","first-page":"3147","DOI":"10.1007\/s00330-020-07319-1","volume":"31","author":"F Roski","year":"2021","unstructured":"Roski F, Hammel J, Mei K et al (2021) Opportunistic osteoporosis screening: contrast-enhanced dual-layer spectral CT provides accurate measurements of vertebral bone mineral density. Eur Radiol 31:3147\u20133155. https:\/\/doi.org\/10.1007\/s00330-020-07319-1","journal-title":"Eur Radiol"},{"key":"11988_CR28","doi-asserted-by":"publisher","first-page":"694","DOI":"10.2214\/AJR.15.15128","volume":"206","author":"TJ Ziemlewicz","year":"2016","unstructured":"Ziemlewicz TJ, Maciejewski A, Binkley N, Brett AD, Brown JK, Pickhardt PJ (2016) Direct comparison of unenhanced and contrast-enhanced CT for opportunistic proximal femur bone mineral density measurement: implications for osteoporosis screening. AJR Am J Roentgenol 206:694\u2013698. https:\/\/doi.org\/10.2214\/AJR.15.15128","journal-title":"AJR Am J Roentgenol"},{"key":"11988_CR29","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1007\/s00198-015-3224-9","volume":"27","author":"PJ Pickhardt","year":"2016","unstructured":"Pickhardt PJ, Lauder T, Pooler BD et al (2016) Effect of IV contrast on lumbar trabecular attenuation at routine abdominal CT: correlation with DXA and implications for opportunistic osteoporosis screening. Osteoporos Int 27:147\u2013152. https:\/\/doi.org\/10.1007\/s00198-015-3224-9","journal-title":"Osteoporos Int"},{"key":"11988_CR30","doi-asserted-by":"publisher","first-page":"2455","DOI":"10.1007\/s00330-017-5191-3","volume":"28","author":"G Fuchs","year":"2018","unstructured":"Fuchs G, Chretien YR, Mario J et al (2018) Quantifying the effect of slice thickness, intravenous contrast and tube current on muscle segmentation: Implications for body composition analysis. Eur Radiol 28:2455\u20132463. https:\/\/doi.org\/10.1007\/s00330-017-5191-3","journal-title":"Eur Radiol"},{"key":"11988_CR31","unstructured":"Krestan, C & Gruber M (2013) Quantitative Computertomographie (QCT). J f\u00fcr Miner Muskuloskelettale Erkrank. https:\/\/www.semanticscholar.org\/paper\/Quantitative-Computertomographie-(QCT)-Qct-Krestan\/6c837acba41376acf142b828b5017096dfa5dc8d"},{"key":"11988_CR32","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1007\/s00198-004-1779-y","volume":"16","author":"KG Faulkner","year":"2005","unstructured":"Faulkner KG (2005) The tale of the T-score: review and perspective. Osteoporos Int 16:347\u2013352. https:\/\/doi.org\/10.1007\/s00198-004-1779-y","journal-title":"Osteoporos Int"},{"key":"11988_CR33","doi-asserted-by":"publisher","first-page":"1539","DOI":"10.1007\/s00198-008-0820-y","volume":"20","author":"BC Khoo","year":"2009","unstructured":"Khoo BC, Brown K, Cann C et al (2009) Comparison of QCT-derived and DXA-derived areal bone mineral density and T scores. Osteoporos Int 20:1539\u20131545. https:\/\/doi.org\/10.1007\/s00198-008-0820-y","journal-title":"Osteoporos Int"}],"container-title":["European Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-025-11988-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00330-025-11988-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-025-11988-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T13:20:56Z","timestamp":1772716856000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00330-025-11988-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,11]]},"references-count":33,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2026,3]]}},"alternative-id":["11988"],"URL":"https:\/\/doi.org\/10.1007\/s00330-025-11988-1","relation":{},"ISSN":["1432-1084"],"issn-type":[{"value":"1432-1084","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,11]]},"assertion":[{"value":"6 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 July 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 August 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 September 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"The scientific guarantor of this publication is the head of the department, Professor Thomas J. Vogl.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Guarantor"}},{"value":"C.B. received speaking fees from Siemens Healthineers. V.K. received travel support from Siemens Healthineers.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"No complex statistical methods were necessary for this paper.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Statistics and biometry"}},{"value":"Retrospective study design.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Institutional Review Board approval was obtained.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"No study subjects or cohorts have been previously reported.","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Study subjects or cohorts overlap"}},{"order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}