{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T13:05:04Z","timestamp":1779800704500,"version":"3.53.1"},"reference-count":38,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T00:00:00Z","timestamp":1768435200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T00:00:00Z","timestamp":1768435200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62376150"],"award-info":[{"award-number":["62376150"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Innovation 2030 - Major Projects","award":["2022ZD021606"],"award-info":[{"award-number":["2022ZD021606"]}]},{"name":"Digital Medical Research Institute Research Funding-Shanghai University","award":["SHU-UM-JBGS-2025-8"],"award-info":[{"award-number":["SHU-UM-JBGS-2025-8"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur Radiol"],"DOI":"10.1007\/s00330-025-12261-1","type":"journal-article","created":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T13:04:30Z","timestamp":1768482270000},"page":"4759-4773","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Stratifying amyloid burden in early Alzheimer\u2019s disease using cascaded attention-guided vision transformer using [\u00b9\u2078F]Florbetapir PET"],"prefix":"10.1007","volume":"36","author":[{"given":"Chenhan","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huiwei","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fangyang","family":"Jiao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fei","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chenyang","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianwei","family":"Men","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zizhao","family":"Ju","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huamei","family":"Lin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunhao","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaying","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cheng","family":"Yue","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuoyan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Min","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yihui","family":"Guan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xin","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuantao","family":"Zuo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4948-3683","authenticated-orcid":false,"given":"Jiehui","family":"Jiang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,1,15]]},"reference":[{"key":"12261_CR1","doi-asserted-by":"publisher","first-page":"1577","DOI":"10.1016\/S0140-6736(20)32205-4","volume":"397","author":"P Scheltens","year":"2021","unstructured":"Scheltens P, De Strooper B, Kivipelto M et al (2021) Alzheimer\u2019s disease. Lancet 397:1577\u20131590","journal-title":"Lancet"},{"key":"12261_CR2","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/S1474-4422(09)70299-6","volume":"9","author":"CR Jack","year":"2010","unstructured":"Jack CR, Knopman DS, Jagust WJ et al (2010) Hypothetical model of dynamic biomarkers of the Alzheimer\u2019s pathological cascade. Lancet Neurol 9:119\u2013128","journal-title":"Lancet Neurol"},{"key":"12261_CR3","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1001\/jama.2010.2008","volume":"305","author":"CM Clark","year":"2011","unstructured":"Clark CM, Schneider JA, Bedell BJ et al (2011) Use of florbetapir-PET for imaging \u03b2-amyloid pathology. JAMA 305:275\u2013283","journal-title":"JAMA"},{"key":"12261_CR4","doi-asserted-by":"publisher","first-page":"2126","DOI":"10.1093\/brain\/aws125","volume":"135","author":"N Villain","year":"2012","unstructured":"Villain N, Ch\u00e9telat G, Grassiot B et al (2012) Regional dynamics of amyloid-\u03b2 deposition in healthy elderly, mild cognitive impairment and Alzheimer\u2019s disease: a voxelwise PiB\u2013PET longitudinal study. Brain 135:2126\u20132139","journal-title":"Brain"},{"key":"12261_CR5","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1007\/s12149-014-0924-8","volume":"29","author":"C Hosokawa","year":"2015","unstructured":"Hosokawa C, Ishii K, Hyodo T et al (2015) Investigation of 11C-PiB equivocal PET findings. Ann Nucl Med 29:164\u2013169","journal-title":"Ann Nucl Med"},{"key":"12261_CR6","doi-asserted-by":"publisher","first-page":"1459","DOI":"10.1007\/s00259-015-3067-9","volume":"42","author":"P Payoux","year":"2015","unstructured":"Payoux P, Delrieu J, Gallini A et al (2015) Cognitive and functional patterns of nondemented subjects with equivocal visual amyloid PET findings. Eur J Nucl Med Mol Imaging 42:1459\u20131468","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"12261_CR7","doi-asserted-by":"publisher","first-page":"1622","DOI":"10.1212\/01.wnl.0000295996.54210.69","volume":"69","author":"JL Cummings","year":"2007","unstructured":"Cummings JL, Doody R, Clark C (2007) Disease-modifying therapies for Alzheimer disease: challenges to early intervention. Neurology 69:1622\u20131634","journal-title":"Neurology"},{"key":"12261_CR8","doi-asserted-by":"publisher","first-page":"567","DOI":"10.2967\/jnumed.114.148981","volume":"56","author":"SM Landau","year":"2015","unstructured":"Landau SM, Fero A, Baker SL et al (2015) Measurement of longitudinal \u03b2-amyloid change with 18F-florbetapir PET and standardized uptake value ratios. J Nucl Med 56:567\u2013574","journal-title":"J Nucl Med"},{"key":"12261_CR9","doi-asserted-by":"publisher","first-page":"1183","DOI":"10.1001\/jamaneurol.2015.1633","volume":"72","author":"S Schreiber","year":"2015","unstructured":"Schreiber S, Landau SM, Fero A et al (2015) Comparison of visual and quantitative florbetapir F 18 positron emission tomography analysis in predicting mild cognitive impairment outcomes. JAMA Neurol 72:1183\u20131190","journal-title":"JAMA Neurol"},{"key":"12261_CR10","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1007\/s00259-020-05006-3","volume":"48","author":"BM de Vries","year":"2021","unstructured":"de Vries BM, Golla SS, Ebenau J et al (2021) Classification of negative and positive 18F-florbetapir brain PET studies in subjective cognitive decline patients using a convolutional neural network. Eur J Nucl Med Mol Imaging 48:721\u2013728","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"12261_CR11","doi-asserted-by":"publisher","first-page":"659","DOI":"10.2967\/jnumed.122.264414","volume":"64","author":"SK Kang","year":"2023","unstructured":"Kang SK, Kim D, Shin SA et al (2023) Fast and accurate amyloid brain PET quantification without MRI using deep neural networks. J Nucl Med 64:659\u2013666","journal-title":"J Nucl Med"},{"key":"12261_CR12","doi-asserted-by":"publisher","first-page":"3453","DOI":"10.3390\/app13063453","volume":"13","author":"H Shin","year":"2023","unstructured":"Shin H, Jeon S, Seol Y, Kim S, Kang, D (2023) Vision transformer approach for classification of Alzheimer\u2019s disease using 18F-Florbetaben brain images. Appl Sci 13:3453","journal-title":"Appl Sci"},{"key":"12261_CR13","doi-asserted-by":"publisher","first-page":"1384","DOI":"10.3390\/diagnostics11081384","volume":"11","author":"Y Dai","year":"2021","unstructured":"Dai Y, Gao Y, Liu F (2021) Transmed: transformers advance multi-modal medical image classification. Diagnostics 11:1384","journal-title":"Diagnostics"},{"key":"12261_CR14","doi-asserted-by":"publisher","first-page":"201","DOI":"10.1212\/WNL.0b013e3181cb3e25","volume":"74","author":"RC Petersen","year":"2010","unstructured":"Petersen RC, Aisen PS, Beckett LA et al (2010) Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI) clinical characterization. Neurology 74:201\u2013209","journal-title":"Neurology"},{"key":"12261_CR15","doi-asserted-by":"publisher","first-page":"375","DOI":"10.1007\/s43657-022-00068-9","volume":"3","author":"M Tian","year":"2023","unstructured":"Tian M, Zuo C, Civelek AC et al (2023) International nuclear medicine consensus on the clinical use of amyloid positron emission tomography in Alzheimer\u2019s disease. Phenomics 3:375\u2013389","journal-title":"Phenomics"},{"key":"12261_CR16","doi-asserted-by":"publisher","first-page":"332","DOI":"10.1007\/s00259-019-04595-y","volume":"47","author":"HJ Son","year":"2020","unstructured":"Son HJ, Oh JS, Oh M et al (2020) The clinical feasibility of deep learning-based classification of amyloid PET images in visually equivocal cases. Eur J Nucl Med Mol Imaging 47:332\u2013341","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"12261_CR17","doi-asserted-by":"publisher","first-page":"1398","DOI":"10.1007\/s00259-014-2753-3","volume":"41","author":"S Landau","year":"2014","unstructured":"Landau S, Thomas B, Thurfjell L et al (2014) Amyloid PET imaging in Alzheimer\u2019s disease: a comparison of three radiotracers. Eur J Nucl Med Mol Imaging 41:1398\u20131407","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"12261_CR18","doi-asserted-by":"publisher","first-page":"378","DOI":"10.2967\/jnumed.111.090340","volume":"53","author":"AD Joshi","year":"2012","unstructured":"Joshi AD, Pontecorvo MJ, Clark CM et al (2012) Performance characteristics of amyloid PET with florbetapir F 18 in patients with Alzheimer\u2019s disease and cognitively normal subjects. J Nucl Med 53:378\u2013384","journal-title":"J Nucl Med"},{"key":"12261_CR19","doi-asserted-by":"publisher","first-page":"e053480","DOI":"10.1002\/alz.053480","volume":"17","author":"G Quattrini","year":"2021","unstructured":"Quattrini G, Ferrari C, Pievani M et al (2021) Data-driven cut-off values for 18-F-AV-45 tau PET staging in AD. Alzheimers Dement 17:e053480","journal-title":"Alzheimers Dement"},{"key":"12261_CR20","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J (2016) Identity mappings in deep residual networks. In: Proceedings of the European conference on computer vision. pp 630\u2013645","DOI":"10.1007\/978-3-319-46493-0_38"},{"key":"12261_CR21","doi-asserted-by":"crossref","unstructured":"Liu Z, Lin Y, Cao Y et al (2021) Swin transformer: hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE\/CVF international conference on computer vision. pp 10012\u201310022","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"12261_CR22","doi-asserted-by":"crossref","unstructured":"Jang J, Hwang D (2022) M3T: three-dimensional medical image classifier using multi-plane and multi-slice transformer. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition. pp 20718\u201320729","DOI":"10.1109\/CVPR52688.2022.02006"},{"key":"12261_CR23","doi-asserted-by":"crossref","unstructured":"Yuan L, Chen Y, Wang T et al (2021) Tokens-to-token vit: training vision transformers from scratch on imagenet. In: Proceedings of the IEEE\/CVF international conference on computer vision. pp 558\u2013567","DOI":"10.1109\/ICCV48922.2021.00060"},{"key":"12261_CR24","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.jalz.2014.07.003","volume":"11","author":"WE Klunk","year":"2015","unstructured":"Klunk WE, Koeppe RA, Price JC et al (2015) The Centiloid Project: standardizing quantitative amyloid plaque estimation by PET. Alzheimers Dement 11:1\u201315","journal-title":"Alzheimers Dement"},{"key":"12261_CR25","doi-asserted-by":"publisher","first-page":"980","DOI":"10.3174\/ajnr.A6573","volume":"41","author":"F Reith","year":"2020","unstructured":"Reith F, Koran M, Davidzon G et al (2020) Application of deep learning to predict standardized uptake value ratio and amyloid status on 18F-florbetapir PET using ADNI data. AJNR Am J Neuroradiol 41:980\u2013986","journal-title":"AJNR Am J Neuroradiol"},{"key":"12261_CR26","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.231442","volume":"311","author":"S Fan","year":"2024","unstructured":"Fan S, Ponisio MR, Xiao P et al (2024) AmyloidPETNet: classification of amyloid positivity in brain PET imaging using end-to-end deep learning. Radiology 311:e231442","journal-title":"Radiology"},{"key":"12261_CR27","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.bbr.2018.02.017","volume":"344","author":"H Choi","year":"2018","unstructured":"Choi H, Jin KH (2018) Predicting cognitive decline with deep learning of brain metabolism and amyloid imaging. Behav Brain Res 344:103\u2013109","journal-title":"Behav Brain Res"},{"key":"12261_CR28","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.neurobiolaging.2017.06.027","volume":"59","author":"S Mathotaarachchi","year":"2017","unstructured":"Mathotaarachchi S, Pascoal TA, Shin M et al (2017) Identifying incipient dementia individuals using machine learning and amyloid imaging. Neurobiol Aging 59:80\u201390","journal-title":"Neurobiol Aging"},{"key":"12261_CR29","doi-asserted-by":"publisher","first-page":"2397","DOI":"10.1002\/alz.12886","volume":"19","author":"LE Collij","year":"2023","unstructured":"Collij LE, Salvad\u00f3 G, De Wilde A et al (2023) Quantification of [18F] florbetaben amyloid-PET imaging in a mixed memory clinic population: the ABIDE project. Alzheimers Dement 19:2397\u20132407","journal-title":"Alzheimers Dement"},{"key":"12261_CR30","doi-asserted-by":"publisher","first-page":"1636","DOI":"10.1097\/PAS.0000000000001151","volume":"42","author":"DF Steiner","year":"2018","unstructured":"Steiner DF, MacDonald R, Liu Y et al (2018) Impact of deep learning assistance on the histopathologic review of lymph nodes for metastatic breast cancer. Am J Surg Pathol 42:1636\u20131646","journal-title":"Am J Surg Pathol"},{"key":"12261_CR31","doi-asserted-by":"publisher","first-page":"1229","DOI":"10.1038\/s41591-020-0942-0","volume":"26","author":"P Tschandl","year":"2020","unstructured":"Tschandl P, Rinner C, Apalla Z et al (2020) Human-computer collaboration for skin cancer recognition. Nat Med 26:1229\u20131234","journal-title":"Nat Med"},{"key":"12261_CR32","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1038\/s41586-019-1799-6","volume":"577","author":"SM McKinney","year":"2020","unstructured":"McKinney SM, Sieniek M, Godbole V et al (2020) International evaluation of an AI system for breast cancer screening. Nature 577:89\u201394","journal-title":"Nature"},{"key":"12261_CR33","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-017-01150-x","volume":"8","author":"S Palmqvist","year":"2017","unstructured":"Palmqvist S, Sch\u00f6ll M, Strandberg O et al (2017) Earliest accumulation of \u03b2-amyloid occurs within the default-mode network and concurrently affects brain connectivity. Nat Commun 8:1214","journal-title":"Nat Commun"},{"key":"12261_CR34","doi-asserted-by":"publisher","first-page":"1791","DOI":"10.1212\/WNL.58.12.1791","volume":"58","author":"DR Thal","year":"2002","unstructured":"Thal DR, Rub U, Orantes M et al (2002) Phases of A\u03b2-deposition in the human brain and its relevance for the development of AD. Neurology 58:1791\u20131800","journal-title":"Neurology"},{"key":"12261_CR35","doi-asserted-by":"publisher","first-page":"e111","DOI":"10.1016\/j.jalz.2013.05.1769","volume":"9","author":"MW Weiner","year":"2013","unstructured":"Weiner MW, Veitch DP, Aisen PS et al (2013) The Alzheimer\u2019s Disease Neuroimaging Initiative: a review of papers published since its inception. Alzheimers Dement 9:e111\u2013e194","journal-title":"Alzheimers Dement"},{"key":"12261_CR36","doi-asserted-by":"publisher","first-page":"2475","DOI":"10.1093\/brain\/awy150","volume":"141","author":"M Bilgel","year":"2018","unstructured":"Bilgel M, An Y, Helphrey J et al (2018) Effects of amyloid pathology and neurodegeneration on cognitive change in cognitively normal adults. Brain 141:2475\u20132485","journal-title":"Brain"},{"key":"12261_CR37","doi-asserted-by":"publisher","first-page":"1939","DOI":"10.1001\/jama.2015.4669","volume":"313","author":"R Ossenkoppele","year":"2015","unstructured":"Ossenkoppele R, Jansen WJ, Rabinovici GD et al (2015) Prevalence of amyloid PET positivity in dementia syndromes: a meta-analysis. JAMA 313:1939\u20131950","journal-title":"JAMA"},{"key":"12261_CR38","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1016\/j.jalz.2019.01.010","volume":"15","author":"Alzheimer\u2019s Association","year":"2019","unstructured":"Alzheimer\u2019s Association (2019) 2019 Alzheimer\u2019s disease facts and figures. Alzheimers Dement 15:321\u2013387","journal-title":"Alzheimers Dement"}],"container-title":["European Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-025-12261-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00330-025-12261-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00330-025-12261-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T12:26:04Z","timestamp":1779798364000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00330-025-12261-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,15]]},"references-count":38,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2026,6]]}},"alternative-id":["12261"],"URL":"https:\/\/doi.org\/10.1007\/s00330-025-12261-1","relation":{},"ISSN":["1432-1084"],"issn-type":[{"value":"1432-1084","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,15]]},"assertion":[{"value":"27 August 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 November 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 December 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 January 2026","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 Jiehui Jiang.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Guarantor"}},{"value":"C.Y. and W.J. are affiliated with Shanghai Rebound Data System Co. Ltd. The remaining authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article.","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":"Written informed consent was obtained from all subjects (patients) in this study.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}},{"value":"Institutional Review Board approval was obtained. This study received ethical approval from both the Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI) institutional review boards and the Institutional Review Board of Huashan Hospital (HIRB, No. 2018-363). All procedures were conducted in accordance with the Declaration of Helsinki.","order":6,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"Some study subjects or cohorts have been previously reported in the ADNI database, which is publicly available and has been used in prior studies.","order":7,"name":"Ethics","group":{"name":"EthicsHeading","label":"Study subjects or cohorts overlap"}},{"order":8,"name":"Ethics","group":{"name":"EthicsHeading","label":"Methodology"}}]}}