{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T19:09:53Z","timestamp":1792782593889,"version":"4.5.0"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T00:00:00Z","timestamp":1787097600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T00:00:00Z","timestamp":1787097600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"Universit\u00e4tsmedizin Rostock","id":[{"id":"https:\/\/ror.org\/04dm1cm79","id-type":"ROR","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neuroradiology"],"published-print":{"date-parts":[[2026,9]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>A standardized, population-based three-dimensional (3D) computer-aided design (CAD) model of the intracranial arterial system was developed from time-of-flight magnetic resonance angiography (TOF-MRA) data of the Study of Health in Pomerania (SHIP) cohort, tailored for realistic simulation and experimental neurovascular applications.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      An averaged intracranial TOF-MRA dataset generated from 4308 individual whole-body MRI examinations of the SHIP cohort was used as the anatomical basis. Intracranial arteries were segmented using\n                      <jats:italic>3D Slicer<\/jats:italic>\n                      with Frangi-based vessel enhancement, semi-automatic region-growing, and manual refinement to obtain continuous vascular masks. Centerlines were extracted with\n                      <jats:italic>VMTK (Vascular Modelling Toolkit)<\/jats:italic>\n                      , and vessel radii were computed via distance mapping. The resulting centerline and radius data were imported into a CAD environment (\n                      <jats:italic>Creo Parametric<\/jats:italic>\n                      ) to reconstruct smooth vessel centerlines, generate circular cross-sections, and create a lofted three-dimensional lumen model, which was converted into a hollow geometry with a uniform wall thickness and exported as an STL file for 3D printing.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The proposed workflow yielded a geometrically consistent, hollow 3D model of the central intracranial arteries, representing a population-averaged arterial anatomy with smooth vessel courses, gradual diameter transitions, and a closed, continuous wall. The CAD model could be successfully manufactured as a physical 3D-printed phantom and provides a stable, reproducible test environment for digital and in vitro investigations of neurovascular interventions under standardized anatomical conditions.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Population-based TOF-MRA data can be transformed into a technically robust and anatomically meaningful intracranial reference model suitable for CAD-based simulation and additive manufacturing. The resulting 3D CAD geometry serves as a reusable reference for comparative studies, methodological validation, early-stage device development, and training in endovascular neurosurgery, without aiming to replace patient-specific models.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00234-026-04147-w","type":"journal-article","created":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T09:19:44Z","timestamp":1787131184000},"page":"2683-2696","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Development of a standardized intracranial vessel model from 3D time-of-flight magnetic resonance angiography data of the SHIP cohort"],"prefix":"10.1007","volume":"68","author":[{"given":"Antonia","family":"Dalmer","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stefan","family":"Siewert","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dominique","family":"Passler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hagen","family":"Paetow","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christoph","family":"Brandt-Wunderlich","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Cantr\u00e9","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ebba","family":"Beller","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S\u00f6nke","family":"Langner","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Klaus-Peter","family":"Schmitz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marc-Andr\u00e9","family":"Weber","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Felix","family":"Streckenbach","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,8,19]]},"reference":[{"key":"4147_CR1","doi-asserted-by":"publisher","first-page":"e56","DOI":"10.1161\/CIR.0000000000000659","volume":"139","author":"EJ Benjamin","year":"2019","unstructured":"Benjamin EJ, Muntner P, Alonso A et al (2019) Heart Disease and Stroke Statistics-2019 Update: A Report From the American Heart Association. Circulation 139:e56\u2013e528. https:\/\/doi.org\/10.1161\/CIR.0000000000000659","journal-title":"Circulation"},{"key":"4147_CR2","doi-asserted-by":"publisher","first-page":"e282","DOI":"10.1161\/STR.0000000000000407","volume":"53","author":"SM Greenberg","year":"2022","unstructured":"Greenberg SM, Ziai WC, Cordonnier C et al (2022) 2022 Guideline for the Management of Patients With Spontaneous Intracerebral Hemorrhage: A Guideline From the American Heart Association\/American Stroke Association. Stroke 53:e282\u2013e361. https:\/\/doi.org\/10.1161\/STR.0000000000000407","journal-title":"Stroke"},{"key":"4147_CR3","doi-asserted-by":"publisher","first-page":"e46","DOI":"10.1161\/STR.0000000000000158","volume":"49","author":"WJ Powers","year":"2018","unstructured":"Powers WJ, Rabinstein AA, Ackerson T et al (2018) 2018 Guidelines for the Early Management of Patients With Acute Ischemic Stroke: A Guideline for Healthcare Professionals From the American Heart Association\/American Stroke Association. Stroke 49:e46\u2013e110. https:\/\/doi.org\/10.1161\/STR.0000000000000158","journal-title":"Stroke"},{"key":"4147_CR4","doi-asserted-by":"publisher","first-page":"e314","DOI":"10.1161\/STR.0000000000000436","volume":"54","author":"BL Hoh","year":"2023","unstructured":"Hoh BL, Ko NU, Amin-Hanjani S et al (2023) 2023 Guideline for the Management of Patients With Aneurysmal Subarachnoid Hemorrhage: A Guideline From the American Heart Association\/American Stroke Association. Stroke 54:e314\u2013e370. https:\/\/doi.org\/10.1161\/STR.0000000000000436","journal-title":"Stroke"},{"key":"4147_CR5","doi-asserted-by":"publisher","DOI":"10.3390\/healthcare10112132","author":"F Streckenbach","year":"2022","unstructured":"Streckenbach F, Leifert G, Beyer T et al (2022) Application of a deep learning approach to analyze large-scale MRI data of the spine. Healthcare (Basel). https:\/\/doi.org\/10.3390\/healthcare10112132","journal-title":"Healthcare (Basel)"},{"key":"4147_CR6","doi-asserted-by":"publisher","first-page":"e372","DOI":"10.1093\/ije\/dyac034","volume":"51","author":"H V\u00f6lzke","year":"2022","unstructured":"V\u00f6lzke H, Sch\u00f6ssow J, Schmidt CO et al (2022) Cohort profile update: the Study of Health in Pomerania (SHIP). Int J Epidemiol 51:e372\u2013e383. https:\/\/doi.org\/10.1093\/ije\/dyac034","journal-title":"Int J Epidemiol"},{"key":"4147_CR7","doi-asserted-by":"publisher","DOI":"10.3390\/healthcare10010033","author":"N Hosten","year":"2021","unstructured":"Hosten N, B\u00fclow R, V\u00f6lzke H et al (2021) SHIP-MR and radiology: 12 years of whole-body magnetic resonance imaging in a single center. Healthcare. https:\/\/doi.org\/10.3390\/healthcare10010033","journal-title":"Healthcare"},{"key":"4147_CR8","doi-asserted-by":"publisher","first-page":"S283","DOI":"10.1016\/j.jacr.2021.08.012","volume":"18","author":"LN Ledbetter","year":"2021","unstructured":"Ledbetter LN, Burns J, Shih RY et al (2021) ACR Appropriateness Criteria\u00ae Cerebrovascular Diseases-Aneurysm, Vascular Malformation, and Subarachnoid Hemorrhage. J Am Coll Radiol 18:S283\u2013S304. https:\/\/doi.org\/10.1016\/j.jacr.2021.08.012","journal-title":"J Am Coll Radiol"},{"key":"4147_CR9","doi-asserted-by":"publisher","DOI":"10.7554\/eLife.71186","author":"S Bollmann","year":"2022","unstructured":"Bollmann S, Mattern H, Bernier M et al (2022) Imaging of the pial arterial vasculature of the human brain in vivo using high-resolution 7T time-of-flight angiography. Elife. https:\/\/doi.org\/10.7554\/eLife.71186","journal-title":"Elife"},{"key":"4147_CR10","doi-asserted-by":"publisher","DOI":"10.1186\/s41747-024-00463-z","volume":"8","author":"M Cosottini","year":"2024","unstructured":"Cosottini M, Calzoni T, Lazzarotti GA et al (2024) Time-of-flight MRA of intracranial vessels at 7 T. Eur Radiol Exp 8:68. https:\/\/doi.org\/10.1186\/s41747-024-00463-z","journal-title":"Eur Radiol Exp"},{"key":"4147_CR11","doi-asserted-by":"publisher","first-page":"432","DOI":"10.1002\/mrm.29647","volume":"90","author":"Y Ji","year":"2023","unstructured":"Ji Y, Wu W, de Buck MHS et al (2023) Highly accelerated intracranial time-of-flight magnetic resonance angiography using wave-encoding. Magn Reson Med 90:432\u2013443. https:\/\/doi.org\/10.1002\/mrm.29647","journal-title":"Magn Reson Med"},{"key":"4147_CR12","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1016\/S1064-9689(21)00251-8","volume":"3","author":"GA Laub","year":"1995","unstructured":"Laub GA (1995) Time-of-flight method of MR angiography. Magn Reson Imaging Clin N Am 3:391\u2013398. https:\/\/doi.org\/10.1016\/S1064-9689(21)00251-8","journal-title":"Magn Reson Imaging Clin N Am"},{"key":"4147_CR13","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1016\/j.mri.2019.08.014","volume":"63","author":"CR Meixner","year":"2019","unstructured":"Meixner CR, Liebig P, Speier P et al (2019) High resolution time-of-flight MR-angiography at 7 T exploiting VERSE saturation, compressed sensing and segmentation. Magn Reson Imaging 63:193\u2013204. https:\/\/doi.org\/10.1016\/j.mri.2019.08.014","journal-title":"Magn Reson Imaging"},{"key":"4147_CR14","doi-asserted-by":"publisher","first-page":"167","DOI":"10.1109\/TNB.2023.3298444","volume":"23","author":"SC Pal","year":"2024","unstructured":"Pal SC, Toumpanakis D, Wikstrom J et al (2024) Multi-Level Residual Dual Attention Network for Major Cerebral Arteries Segmentation in MRA Toward Diagnosis of Cerebrovascular Disorders. IEEE Trans Nanobiosci 23:167\u2013175. https:\/\/doi.org\/10.1109\/TNB.2023.3298444","journal-title":"IEEE Trans Nanobiosci"},{"key":"4147_CR15","doi-asserted-by":"crossref","unstructured":"Pal SC, Banerjee S, Toumpanakis D et al (eds) (2022) Segmentation of Major Cerebral Vessel from MRA images and Evaluation using U-Net Family: 2022 IEEE 6th International Conference on Condition Assessment Techniques in Electrical Systems (CATCON). IEEE","DOI":"10.1109\/CATCON56237.2022.10077711"},{"key":"4147_CR16","doi-asserted-by":"publisher","first-page":"890","DOI":"10.1148\/radiology.190.3.8115646","volume":"190","author":"D Atkinson","year":"1994","unstructured":"Atkinson D, Brant-Zawadzki M, Gillan G et al (1994) Improved MR angiography: magnetization transfer suppression with variable flip angle excitation and increased resolution. Radiology 190:890\u2013894. https:\/\/doi.org\/10.1148\/radiology.190.3.8115646","journal-title":"Radiology"},{"key":"4147_CR17","doi-asserted-by":"publisher","first-page":"1323","DOI":"10.1016\/j.mri.2012.05.001","volume":"30","author":"A Fedorov","year":"2012","unstructured":"Fedorov A, Beichel R, Kalpathy-Cramer J et al (2012) 3D Slicer as an image computing platform for the Quantitative Imaging Network. Magn Reson Imaging 30:1323\u20131341. https:\/\/doi.org\/10.1016\/j.mri.2012.05.001","journal-title":"Magn Reson Imaging"},{"key":"4147_CR18","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2020.592352","volume":"14","author":"G Tetteh","year":"2020","unstructured":"Tetteh G, Efremov V, Forkert ND et al (2020) DeepVesselNet: vessel segmentation, centerline prediction, and bifurcation detection in 3-D angiographic volumes. Front Neurosci 14:592352. https:\/\/doi.org\/10.3389\/fnins.2020.592352","journal-title":"Front Neurosci"},{"key":"4147_CR19","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1016\/j.media.2004.11.009","volume":"10","author":"MS Hassouna","year":"2006","unstructured":"Hassouna MS, Farag AA, Hushek S et al (2006) Cerebrovascular segmentation from TOF using stochastic models. Med Image Anal 10:2\u201318. https:\/\/doi.org\/10.1016\/j.media.2004.11.009","journal-title":"Med Image Anal"},{"key":"4147_CR20","doi-asserted-by":"publisher","DOI":"10.1177\/16878132231181552","author":"HK Abdul-Ameer","year":"2023","unstructured":"Abdul-Ameer HK (2023) 3D-shape formation of blood vessels based on computer aided design system. Adv Mech Eng. https:\/\/doi.org\/10.1177\/16878132231181552","journal-title":"Adv Mech Eng"},{"key":"4147_CR21","doi-asserted-by":"publisher","DOI":"10.1088\/1758-5082\/1\/3\/035002","author":"WL Mondy","year":"2009","unstructured":"Mondy WL, Cameron D, Timmermans J-P et al (2009) Computer-aided design of microvasculature systems for use in vascular scaffold production. Biofabrication. https:\/\/doi.org\/10.1088\/1758-5082\/1\/3\/035002","journal-title":"Biofabrication"},{"key":"4147_CR22","doi-asserted-by":"publisher","first-page":"294","DOI":"10.1093\/ije\/dyp394","volume":"40","author":"H V\u00f6lzke","year":"2011","unstructured":"V\u00f6lzke H, Alte D, Schmidt CO et al (2011) Cohort profile: the study of health in Pomerania. Int J Epidemiol 40:294\u2013307. https:\/\/doi.org\/10.1093\/ije\/dyp394","journal-title":"Int J Epidemiol"},{"key":"4147_CR23","doi-asserted-by":"publisher","first-page":"70","DOI":"10.1007\/s00117-020-00739-6","volume":"60","author":"D Cantr\u00e9","year":"2020","unstructured":"Cantr\u00e9 D, Langner S, Kaule S et al (2020) Dreidimensionale Bildgebung und 3D-Druck zur plastischen Vorbereitung medizinischer Eingriffe (Three-dimensional imaging and three-dimensional printing for plastic preparation of medical interventions). Radiologe 60:70\u201379. https:\/\/doi.org\/10.1007\/s00117-020-00739-6","journal-title":"Radiologe"},{"key":"4147_CR24","doi-asserted-by":"publisher","first-page":"714","DOI":"10.1055\/a-2211-2983","volume":"196","author":"H Paetow","year":"2024","unstructured":"Paetow H, Streckenbach F, Brandt-Wunderlich C et al (2024) Entwicklung eines bioresorbierbaren, selbstexpandierenden Mikrostents f\u00fcr interventionelle Anwendungen \u2013 ein innovativer Ansatz f\u00fcr stentgest\u00fctztes Coiling (Development of a bioresorbable self-expanding microstent for interventional applications - an innovative approach for stent-assisted coiling). Rofo 196:714\u2013725. https:\/\/doi.org\/10.1055\/a-2211-2983","journal-title":"Rofo"},{"key":"4147_CR25","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1007\/s12021-016-9320-y","volume":"15","author":"T Dun\u00e5s","year":"2017","unstructured":"Dun\u00e5s T, W\u00e5hlin A, Ambarki K et al (2017) A Stereotactic Probabilistic Atlas for the Major Cerebral Arteries. Neuroinformatics 15:101\u2013110. https:\/\/doi.org\/10.1007\/s12021-016-9320-y","journal-title":"Neuroinformatics"},{"key":"4147_CR26","doi-asserted-by":"publisher","first-page":"1805","DOI":"10.1161\/STROKEAHA.106.477000","volume":"38","author":"TG Phan","year":"2007","unstructured":"Phan TG, Fong AC, Donnan G et al (2007) Digital map of posterior cerebral artery infarcts associated with posterior cerebral artery trunk and branch occlusion. Stroke 38:1805\u20131811. https:\/\/doi.org\/10.1161\/STROKEAHA.106.477000","journal-title":"Stroke"},{"key":"4147_CR27","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1007\/s42113-019-00062-x","volume":"2","author":"RA Poldrack","year":"2019","unstructured":"Poldrack RA, Feingold F, Frank MJ et al (2019) The importance of standards for sharing of computational models and data. Comput Brain Behav 2:229\u2013232. https:\/\/doi.org\/10.1007\/s42113-019-00062-x","journal-title":"Comput Brain Behav"},{"key":"4147_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.jacadv.2024.100893","volume":"3","author":"D Chetan","year":"2024","unstructured":"Chetan D, Valverde I, Yoo S-J (2024) 3D printed models in cardiology training. JACC Adv 3:100893. https:\/\/doi.org\/10.1016\/j.jacadv.2024.100893","journal-title":"JACC Adv"},{"key":"4147_CR29","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1016\/j.repc.2023.11.006","volume":"43","author":"C Sequeira","year":"2024","unstructured":"Sequeira C, Oliveira-Santos M, Borges Rosa J et al (2024) Three-dimensional simulation for interventional cardiology procedures: face and content validity. Rev Port Cardiol 43:389\u2013396. https:\/\/doi.org\/10.1016\/j.repc.2023.11.006","journal-title":"Rev Port Cardiol"},{"key":"4147_CR30","doi-asserted-by":"publisher","DOI":"10.1186\/s12938-022-01041-3","volume":"21","author":"M Chen","year":"2022","unstructured":"Chen M, Geng C, Wang D et al (2022) A coarse-to-fine cascade deep learning neural network for segmenting cerebral aneurysms in time-of-flight magnetic resonance angiography. Biomed Eng Online 21:71. https:\/\/doi.org\/10.1186\/s12938-022-01041-3","journal-title":"Biomed Eng Online"},{"key":"4147_CR31","doi-asserted-by":"publisher","DOI":"10.1049\/ipr2.70199","author":"SC Pal","year":"2025","unstructured":"Pal SC, Ahuja CK, Toumpanakis D et al (2025) Computer-aided volumetric quantification of pre\u2010 and post\u2010treatment intracranial aneurysms in MRA. IET Image Process. https:\/\/doi.org\/10.1049\/ipr2.70199","journal-title":"IET Image Process"},{"key":"4147_CR32","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2026.101012","volume":"62","author":"A Kanadath","year":"2026","unstructured":"Kanadath A, Ahmad J, Malik K et al (2026) A review of deep learning-based intracranial aneurysm diagnosis: methods, datasets, challenges, and emerging trends. Comput Sci Rev 62:101012. https:\/\/doi.org\/10.1016\/j.cosrev.2026.101012","journal-title":"Comput Sci Rev"},{"key":"4147_CR33","doi-asserted-by":"crossref","unstructured":"Pal SC, Toumpanakis D, Wikstr\u00f6m J et al (eds) (2024) Automated Segmentation of Post-Treatment Intracranial Aneurysms from MRA Images: A U-Net based Approach: 2024 IEEE 21st India Council International Conference (INDICON). IEEE","DOI":"10.1109\/INDICON63790.2024.10958485"},{"key":"4147_CR34","doi-asserted-by":"crossref","unstructured":"Pal SC, Toumpanakis D, Wikstr\u00f6m J et al (2025) Context-Aware Preprocessing Method for Reduction of Volume of Interest Towards Quantification of Pre and Post-treatment Intracranial Aneurysms in MRA. In: Palaiahnakote S, Schuckers S, Ogier J-M. (eds) Pattern Recognition. ICPR 2024 International Workshops and Challenges, vol 15618. Springer Nature Switzerland, Cham, pp 233\u2013242","DOI":"10.1007\/978-3-031-88220-3_17"},{"key":"4147_CR35","doi-asserted-by":"publisher","DOI":"10.1007\/s13721-025-00551-z","author":"SC Pal","year":"2025","unstructured":"Pal SC, Ahuja CK, Toumpanakis D et al (2025) Computationally efficient dilated residual networks for segmentation of major cerebral vessels in MRA. Netw Model Anal Health Inform Bioinforma. https:\/\/doi.org\/10.1007\/s13721-025-00551-z","journal-title":"Netw Model Anal Health Inform Bioinforma"},{"key":"4147_CR36","doi-asserted-by":"publisher","DOI":"10.1161\/SVIN.123.001177","volume":"4","author":"M Mirza","year":"2024","unstructured":"Mirza M, Kummer K, Touchette J et al (2024) Variability in intracranial vessel diameters and considerations for neurovascular models: a systematic review and meta-analysis. Stroke Vasc Interv Neurol 4:e001177. https:\/\/doi.org\/10.1161\/SVIN.123.001177","journal-title":"Stroke Vasc Interv Neurol"}],"container-title":["Neuroradiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00234-026-04147-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00234-026-04147-w","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00234-026-04147-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T05:54:21Z","timestamp":1792389261000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00234-026-04147-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,19]]},"references-count":36,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2026,9]]}},"alternative-id":["4147"],"URL":"https:\/\/doi.org\/10.1007\/s00234-026-04147-w","relation":{},"ISSN":["0028-3940","1432-1920"],"issn-type":[{"value":"0028-3940","type":"print"},{"value":"1432-1920","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,19]]},"assertion":[{"value":"19 April 2026","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 August 2026","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 August 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","label":"Competing interests","group":{"name":"EthicsHeading","label":"Declarations"}}]}}