{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,4]],"date-time":"2026-07-04T02:24:43Z","timestamp":1783131883600,"version":"3.54.6"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2022,2,28]],"date-time":"2022-02-28T00:00:00Z","timestamp":1646006400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,2,28]],"date-time":"2022-02-28T00:00:00Z","timestamp":1646006400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001711","name":"Schweizerischer Nationalfonds zur F\u00f6rderung der Wissenschaftlichen Forschung","doi-asserted-by":"publisher","award":["188350"],"award-info":[{"award-number":["188350"]}],"id":[{"id":"10.13039\/501100001711","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100003052","name":"Ministry of Trade, Industry and Energy","doi-asserted-by":"publisher","award":["202011A06"],"award-info":[{"award-number":["202011A06"]}],"id":[{"id":"10.13039\/501100003052","id-type":"DOI","asserted-by":"publisher"}]},{"name":"University of Bern"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur J Nucl Med Mol Imaging"],"published-print":{"date-parts":[[2022,7]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>Alzheimer\u2019s disease (AD) studies revealed that abnormal deposition of tau spreads in a specific spatial pattern, namely Braak stage. However, Braak staging is based on post mortem brains, each of which represents the cross section of the tau trajectory in disease progression, and numerous studies were reported that do not conform to that model. This study thus aimed to identify the tau trajectory and quantify the tau progression in a data-driven approach with the continuous latent space learned by variational autoencoder (VAE).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      A total of 1080 [\n                      <jats:sup>18<\/jats:sup>\n                      F]Flortaucipir brain positron emission tomography (PET) images were collected from the Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI) database. VAE was built to compress the hidden features from tau images in latent space. Hierarchical agglomerative clustering and minimum spanning tree (MST) were applied to organize the features and calibrate them to the tau progression, thus deriving\n                      <jats:italic>pseudo-time<\/jats:italic>\n                      . The image-level tau trajectory was inferred by continuously sampling across the calibrated latent features. We assessed the\n                      <jats:italic>pseudo-time<\/jats:italic>\n                      with regard to tau standardized uptake value ratio (SUVr) in AD-vulnerable regions, amyloid deposit, glucose metabolism, cognitive scores, and clinical diagnosis.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      We identified four clusters that plausibly capture certain stages of AD and organized the clusters in the latent space. The inferred tau trajectory agreed with the Braak staging. According to the derived\n                      <jats:italic>pseudo-time<\/jats:italic>\n                      , tau first deposits in the parahippocampal and amygdala, and then spreads to the fusiform, inferior temporal lobe, and posterior cingulate. Prior to the regional tau deposition, amyloid accumulates first.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The spatiotemporal trajectory of tau progression inferred in this study was consistent with Braak staging. The profile of other biomarkers in disease progression agreed well with previous findings. We addressed that this approach additionally has the potential to quantify tau progression as a continuous variable by taking a whole-brain tau image into account.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s00259-021-05662-z","type":"journal-article","created":{"date-parts":[[2022,2,28]],"date-time":"2022-02-28T06:03:13Z","timestamp":1646028193000},"page":"3061-3072","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Image-level trajectory inference of tau pathology using variational autoencoder for Flortaucipir PET"],"prefix":"10.1007","volume":"49","author":[{"given":"Jimin","family":"Hong","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Seung Kwan","family":"Kang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ian","family":"Alberts","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaying","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raphael","family":"Sznitman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jae Sung","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Axel","family":"Rominger","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hongyoon","family":"Choi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8714-3084","authenticated-orcid":false,"given":"Kuangyu","family":"Shi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"the Alzheimer\u2019s Disease Neuroimaging Initiative","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,2,28]]},"reference":[{"key":"5662_CR1","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1007\/s40336-018-0290-y","volume":"6","author":"N Okamura","year":"2018","unstructured":"Okamura N, Harada R, Ishiki A, Kikuchi A, Nakamura T, Kudo Y. The development and validation of tau PET tracers: current status and future directions. Clin Transl Imaging. 2018;6:305\u201316. https:\/\/doi.org\/10.1007\/s40336-018-0290-y.","journal-title":"Clin Transl Imaging"},{"key":"5662_CR2","doi-asserted-by":"publisher","first-page":"e282","DOI":"10.1212\/WNL.0000000000004860","volume":"90","author":"R La Joie","year":"2018","unstructured":"La Joie R, Bejanin A, Fagan AM, Ayakta N, Baker SL, Bourakova V, et al. Associations between [18F]AV1451 tau PET and CSF measures of tau pathology in a clinical sample. Neurology. 2018;90:e282\u201390. https:\/\/doi.org\/10.1212\/WNL.0000000000004860.","journal-title":"Neurology"},{"key":"5662_CR3","doi-asserted-by":"publisher","unstructured":"R LJ, Av V, Sl B. Prospective longitudinal atrophy in Alzheimer\u2019s disease correlates with the intensity and topography of baseline tau-PET. Sci Transl Med. 2020;12. https:\/\/doi.org\/10.1126\/scitranslmed.aau5732.","DOI":"10.1126\/scitranslmed.aau5732."},{"key":"5662_CR4","doi-asserted-by":"publisher","first-page":"1063","DOI":"10.1093\/brain\/awz019","volume":"142","author":"BA Gordon","year":"2019","unstructured":"Gordon BA, Blazey TM, Christensen J, Dincer A, Flores S, Keefe S, et al. Tau PET in autosomal dominant Alzheimer\u2019s disease: relationship with cognition, dementia and other biomarkers. Brain. 2019;142:1063\u201376. https:\/\/doi.org\/10.1093\/brain\/awz019.","journal-title":"Brain"},{"key":"5662_CR5","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1007\/BF00308809","volume":"82","author":"H Braak","year":"1991","unstructured":"Braak H, Braak E. Neuropathological stageing of Alzheimer-related changes. Acta Neuropathol. 1991;82:239\u201359. https:\/\/doi.org\/10.1007\/BF00308809.","journal-title":"Acta Neuropathol"},{"key":"5662_CR6","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1016\/j.jalz.2018.02.018","volume":"14","author":"CR Jack Jr","year":"2018","unstructured":"Jack CR Jr, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, et al. NIA-AA Research Framework: toward a biological definition of Alzheimer\u2019s disease. Alzheimers Dement. 2018;14:535\u201362. https:\/\/doi.org\/10.1016\/j.jalz.2018.02.018.","journal-title":"Alzheimers Dement"},{"key":"5662_CR7","doi-asserted-by":"publisher","first-page":"1411","DOI":"10.2967\/jnumed.120.252254","volume":"61","author":"VS Mattay","year":"2020","unstructured":"Mattay VS, Fotenos AF, Ganley CJ, Marzella L. Brain tau imaging: food and drug administration approval of 18F-flortaucipir injection. J Nucl Med. 2020;61:1411\u20132. https:\/\/doi.org\/10.2967\/jnumed.120.252254.","journal-title":"J Nucl Med"},{"key":"5662_CR8","doi-asserted-by":"publisher","first-page":"247","DOI":"10.1002\/ana.24711","volume":"80","author":"H Cho","year":"2016","unstructured":"Cho H, Choi JY, Hwang MS, Kim YJ, Lee HM, Lee HS, et al. In vivo cortical spreading pattern of tau and amyloid in the Alzheimer disease spectrum. Ann Neurol. 2016;80:247\u201358. https:\/\/doi.org\/10.1002\/ana.24711.","journal-title":"Ann Neurol"},{"key":"5662_CR9","doi-asserted-by":"publisher","first-page":"971","DOI":"10.1016\/j.neuron.2016.01.028","volume":"89","author":"M Sch\u00f6ll","year":"2016","unstructured":"Sch\u00f6ll M, Lockhart SN, Schonhaut DR, O\u2019Neil JP, Janabi M, Ossenkoppele R, et al. PET imaging of tau deposition in the aging human brain. Neuron. 2016;89:971\u201382. https:\/\/doi.org\/10.1016\/j.neuron.2016.01.028.","journal-title":"Neuron"},{"key":"5662_CR10","doi-asserted-by":"publisher","first-page":"1539","DOI":"10.1093\/brain\/aww023","volume":"139","author":"AJ Schwarz","year":"2016","unstructured":"Schwarz AJ, Yu P, Miller BB, Shcherbinin S, Dickson J, Navitsky M, et al. Regional profiles of the candidate tau PET ligand 18F-AV-1451 recapitulate key features of Braak histopathological stages. Brain. 2016;139:1539\u201350. https:\/\/doi.org\/10.1093\/brain\/aww023.","journal-title":"Brain"},{"key":"5662_CR11","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1093\/brain\/awv338","volume":"139","author":"DT Jones","year":"2016","unstructured":"Jones DT, Knopman DS, Gunter JL, Graff-Radford J, Vemuri P, Boeve BF, et al. Cascading network failure across the Alzheimer\u2019s disease spectrum. Brain. 2016;139:547\u201362. https:\/\/doi.org\/10.1093\/brain\/awv338.","journal-title":"Brain"},{"key":"5662_CR12","doi-asserted-by":"publisher","first-page":"1517","DOI":"10.1093\/brain\/awy059","volume":"141","author":"CR Jack Jr","year":"2018","unstructured":"Jack CR Jr, Wiste HJ, Schwarz CG, Lowe VJ, Senjem ML, Vemuri P, et al. Longitudinal tau PET in ageing and Alzheimer\u2019s disease. Brain. 2018;141:1517\u201328. https:\/\/doi.org\/10.1093\/brain\/awy059.","journal-title":"Brain"},{"key":"5662_CR13","doi-asserted-by":"publisher","first-page":"1112","DOI":"10.1038\/s41380-018-0342-8","volume":"24","author":"A Leuzy","year":"2019","unstructured":"Leuzy A, Chiotis K, Lemoine L, Gillberg P-G, Almkvist O, Rodriguez-Vieitez E, et al. Tau PET imaging in neurodegenerative tauopathies\u2014still a challenge. Mol Psychiatry. 2019;24:1112\u201334. https:\/\/doi.org\/10.1038\/s41380-018-0342-8.","journal-title":"Mol Psychiatry"},{"key":"5662_CR14","doi-asserted-by":"publisher","first-page":"755","DOI":"10.1007\/s00401-014-1349-0","volume":"128","author":"JF Crary","year":"2014","unstructured":"Crary JF, Trojanowski JQ, Schneider JA, Abisambra JF, Abner EL, Alafuzoff I, et al. Primary age-related tauopathy (PART): a common pathology associated with human aging. Acta Neuropathol. 2014;128:755\u201366. https:\/\/doi.org\/10.1007\/s00401-014-1349-0.","journal-title":"Acta Neuropathol"},{"key":"5662_CR15","doi-asserted-by":"publisher","first-page":"1551","DOI":"10.1093\/brain\/aww027","volume":"139","author":"R Ossenkoppele","year":"2016","unstructured":"Ossenkoppele R, Schonhaut DR, Sch\u00f6ll M, Lockhart SN, Ayakta N, Baker SL, et al. Tau PET patterns mirror clinical and neuroanatomical variability in Alzheimer\u2019s disease. Brain. 2016;139:1551\u201367. https:\/\/doi.org\/10.1093\/brain\/aww027.","journal-title":"Brain"},{"key":"5662_CR16","doi-asserted-by":"publisher","first-page":"2286","DOI":"10.1093\/brain\/awx171","volume":"140","author":"M Sch\u00f6ll","year":"2017","unstructured":"Sch\u00f6ll M, Ossenkoppele R, Strandberg O, Palmqvist S, Swedish BioFINDER study, J\u00f6gi J, et al. Distinct 18F-AV-1451 tau PET retention patterns in early- and late-onset Alzheimer\u2019s disease. Brain. 2017;140:2286\u201394. https:\/\/doi.org\/10.1093\/brain\/awx171.","journal-title":"Brain."},{"key":"5662_CR17","doi-asserted-by":"publisher","first-page":"2732","DOI":"10.1093\/brain\/awv191","volume":"138","author":"R Ossenkoppele","year":"2015","unstructured":"Ossenkoppele R, Pijnenburg YAL, Perry DC, Cohn-Sheehy BI, Scheltens NME, Vogel JW, et al. The behavioural\/dysexecutive variant of Alzheimer\u2019s disease: clinical, neuroimaging and pathological features. Brain. 2015;138:2732\u201349. https:\/\/doi.org\/10.1093\/brain\/awv191.","journal-title":"Brain"},{"key":"5662_CR18","doi-asserted-by":"publisher","first-page":"1006","DOI":"10.1212\/WNL.0b013e31821103e6","volume":"76","author":"ML Gorno-Tempini","year":"2011","unstructured":"Gorno-Tempini ML, Hillis AE, Weintraub S, Kertesz A, Mendez M, Cappa SF, et al. Classification of primary progressive aphasia and its variants. Neurology. 2011;76:1006\u201314. https:\/\/doi.org\/10.1212\/WNL.0b013e31821103e6.","journal-title":"Neurology"},{"key":"5662_CR19","doi-asserted-by":"publisher","first-page":"870","DOI":"10.1016\/j.jalz.2017.01.014","volume":"13","author":"SJ Crutch","year":"2017","unstructured":"Crutch SJ, Schott JM, Rabinovici GD, Murray M, Snowden JS, van der Flier WM, et al. Consensus classification of posterior cortical atrophy. Alzheimers Dement. 2017;13:870\u201384. https:\/\/doi.org\/10.1016\/j.jalz.2017.01.014.","journal-title":"Alzheimers Dement"},{"key":"5662_CR20","doi-asserted-by":"publisher","first-page":"871","DOI":"10.1038\/s41591-021-01309-6","volume":"27","author":"JW Vogel","year":"2021","unstructured":"Vogel JW, Young AL, Oxtoby NP, Smith R, Ossenkoppele R, Strandberg OT, et al. Four distinct trajectories of tau deposition identified in Alzheimer\u2019s disease. Nat Med. 2021;27:871\u201381. https:\/\/doi.org\/10.1038\/s41591-021-01309-6.","journal-title":"Nat Med"},{"key":"5662_CR21","doi-asserted-by":"publisher","first-page":"448","DOI":"10.1016\/j.neuroimage.2017.05.058","volume":"157","author":"A Maass","year":"2017","unstructured":"Maass A, Landau S, Baker SL, Horng A, Lockhart SN, La Joie R, et al. Comparison of multiple tau-PET measures as biomarkers in aging and Alzheimer\u2019s disease. Neuroimage. 2017;157:448\u201363. https:\/\/doi.org\/10.1016\/j.neuroimage.2017.05.058.","journal-title":"Neuroimage"},{"key":"5662_CR22","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1016\/j.neuroimage.2017.07.050","volume":"161","author":"S Mishra","year":"2017","unstructured":"Mishra S, Gordon BA, Su Y, Christensen J, Friedrichsen K, Jackson K, et al. AV-1451 PET imaging of tau pathology in preclinical Alzheimer disease: defining a summary measure. Neuroimage. 2017;161:171\u20138. https:\/\/doi.org\/10.1016\/j.neuroimage.2017.07.050.","journal-title":"Neuroimage"},{"key":"5662_CR23","doi-asserted-by":"publisher","first-page":"1070","DOI":"10.1001\/jamaneurol.2016.2078","volume":"73","author":"L Wang","year":"2016","unstructured":"Wang L, Benzinger TL, Su Y, Christensen J, Friedrichsen K, Aldea P, et al. Evaluation of tau imaging in staging Alzheimer disease and revealing interactions between \u03b2-amyloid and tauopathy. JAMA Neurol. 2016;73:1070. https:\/\/doi.org\/10.1001\/jamaneurol.2016.2078.","journal-title":"JAMA Neurol"},{"key":"5662_CR24","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1016\/j.jalz.2016.08.005","volume":"13","author":"CR Jack Jr","year":"2017","unstructured":"Jack CR Jr, Wiste HJ, Weigand SD, Therneau TM, Lowe VJ, Knopman DS, et al. Defining imaging biomarker cut points for brain aging and Alzheimer\u2019s disease. Alzheimers Dement. 2017;13:205\u201316. https:\/\/doi.org\/10.1016\/j.jalz.2016.08.005.","journal-title":"Alzheimers Dement"},{"key":"5662_CR25","doi-asserted-by":"publisher","first-page":"1539","DOI":"10.1093\/brain\/aww023","volume":"139","author":"AJ Schwarz","year":"2016","unstructured":"Schwarz AJ, Yu P, Miller BB, Shcherbinin S, Dickson J, Navitsky M, et al. Regional profiles of the candidate tau PET ligand 18 F-AV-1451 recapitulate key features of Braak histopathological stages. Brain. 2016;139:1539\u201350. https:\/\/doi.org\/10.1093\/brain\/aww023.","journal-title":"Brain"},{"key":"5662_CR26","doi-asserted-by":"publisher","first-page":"483","DOI":"10.1038\/s41398-021-01602-5","volume":"11","author":"S-D Chen","year":"2021","unstructured":"Chen S-D, Lu J-Y, Li H-Q, Yang Y-X, Jiang J-H, Cui M, et al. Staging tau pathology with tau PET in Alzheimer\u2019s disease: a longitudinal study. Transl Psychiatry. 2021;11:483. https:\/\/doi.org\/10.1038\/s41398-021-01602-5.","journal-title":"Transl Psychiatry"},{"key":"5662_CR27","unstructured":"Kingma DP, Welling M. Auto-encoding variational Bayes. arXiv. 2013. https:\/\/arxiv.org\/abs\/1312.6114. Accessed 20 Dec 2013."},{"key":"5662_CR28","doi-asserted-by":"publisher","first-page":"826","DOI":"10.1002\/ana.23908","volume":"74","author":"SM Landau","year":"2013","unstructured":"Landau SM, Lu M, Joshi AD, Pontecorvo M, Mintun MA, Trojanowski JQ, et al. Comparing positron emission tomography imaging and cerebrospinal fluid measurements of \u03b2-amyloid: CSF and amyloid PET imaging. Ann Neurol. 2013;74:826\u201336. https:\/\/doi.org\/10.1002\/ana.23908.","journal-title":"Ann Neurol"},{"key":"5662_CR29","doi-asserted-by":"publisher","first-page":"1207","DOI":"10.1016\/j.neurobiolaging.2009.07.002","volume":"32","author":"SM Landau","year":"2011","unstructured":"Landau SM, Harvey D, Madison CM, Koeppe RA, Reiman EM, Foster NL, et al. Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI. Neurobiol Aging. 2011;32:1207\u201318. https:\/\/doi.org\/10.1016\/j.neurobiolaging.2009.07.002.","journal-title":"Neurobiol Aging"},{"key":"5662_CR30","doi-asserted-by":"publisher","first-page":"1321","DOI":"10.1093\/brain\/aww041","volume":"139","author":"M Sarazin","year":"2016","unstructured":"Sarazin M, Lagarde J, Bottlaender M. Distinct tau PET imaging patterns in typical and atypical Alzheimer\u2019s disease. Brain. 2016;139:1321\u20134. https:\/\/doi.org\/10.1093\/brain\/aww041.","journal-title":"Brain"},{"key":"5662_CR31","doi-asserted-by":"publisher","first-page":"427","DOI":"10.1001\/jamaneurol.2016.5755","volume":"74","author":"C Xia","year":"2017","unstructured":"Xia C, Makaretz SJ, Caso C, McGinnis S, Gomperts SN, Sepulcre J, et al. Association of in vivo [18F]AV-1451 tau PET imaging results with cortical atrophy and symptoms in typical and atypical Alzheimer disease. JAMA Neurol. 2017;74:427\u201336. https:\/\/doi.org\/10.1001\/jamaneurol.2016.5755.","journal-title":"JAMA Neurol"},{"key":"5662_CR32","doi-asserted-by":"publisher","first-page":"119","DOI":"10.1016\/S1474-4422(09)70299-6","volume":"9","author":"CR Jack Jr","year":"2010","unstructured":"Jack CR Jr, Knopman DS, Jagust WJ, Shaw LM, Aisen PS, Weiner MW, et al. Hypothetical model of dynamic biomarkers of the Alzheimer\u2019s pathological cascade. Lancet Neurol. 2010;9:119\u201328. https:\/\/doi.org\/10.1016\/S1474-4422(09)70299-6.","journal-title":"Lancet Neurol"},{"key":"5662_CR33","doi-asserted-by":"publisher","first-page":"951","DOI":"10.1016\/S1474-4422(20)30314-8","volume":"19","author":"G Ch\u00e9telat","year":"2020","unstructured":"Ch\u00e9telat G, Arbizu J, Barthel H, Garibotto V, Law I, Morbelli S, et al. Amyloid-PET and 18F-FDG-PET in the diagnostic investigation of Alzheimer\u2019s disease and other dementias. Lancet Neurol. 2020;19:951\u201362. https:\/\/doi.org\/10.1016\/S1474-4422(20)30314-8.","journal-title":"Lancet Neurol"},{"key":"5662_CR34","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1186\/s13195-020-00702-6","volume":"12","author":"A Rubinski","year":"2020","unstructured":"Rubinski A, Franzmeier N, Neitzel J, Ewers M, the Alzheimer\u2019s Disease Neuroimaging Initiative (ADNI). FDG-PET hypermetabolism is associated with higher tau-PET in mild cognitive impairment at low amyloid-PET levels. Alz Res Therapy. 2020;12:133. https:\/\/doi.org\/10.1186\/s13195-020-00702-6.","journal-title":"Alz Res Therapy."},{"key":"5662_CR35","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1186\/s40478-018-0535-z","volume":"6","author":"MC Wren","year":"2018","unstructured":"Wren MC, Lashley T, \u00c5rstad E, Sander K. Large inter- and intra-case variability of first generation tau PET ligand binding in neurodegenerative dementias. Acta Neuropathol Commun. 2018;6:34. https:\/\/doi.org\/10.1186\/s40478-018-0535-z.","journal-title":"Acta Neuropathol Commun."},{"key":"5662_CR36","doi-asserted-by":"publisher","first-page":"3477","DOI":"10.1093\/brain\/awaa276","volume":"143","author":"DN Soleimani-Meigooni","year":"2020","unstructured":"Soleimani-Meigooni DN, Iaccarino L, La Joie R, Baker S, Bourakova V, Boxer AL, et al. 18F-flortaucipir PET to autopsy comparisons in Alzheimer\u2019s disease and other neurodegenerative diseases. Brain. 2020;143:3477\u201394. https:\/\/doi.org\/10.1093\/brain\/awaa276.","journal-title":"Brain"},{"key":"5662_CR37","doi-asserted-by":"publisher","first-page":"486","DOI":"10.3389\/fneur.2019.00486","volume":"10","author":"Q Zhao","year":"2019","unstructured":"Zhao Q, Liu M, Ha L, Zhou Y, Alzheimer\u2019s Disease Neuroimaging Initiative. Quantitative 18F-AV1451 brain tau PET imaging in cognitively normal older adults, mild cognitive impairment, and Alzheimer\u2019s disease patients. Front Neurol. 2019;10:486. https:\/\/doi.org\/10.3389\/fneur.2019.00486.","journal-title":"Front Neurol."},{"key":"5662_CR38","doi-asserted-by":"publisher","first-page":"963","DOI":"10.1007\/s11307-017-1080-z","volume":"19","author":"SSV Golla","year":"2017","unstructured":"Golla SSV, Timmers T, Ossenkoppele R, Groot C, Verfaillie S, Scheltens P, et al. Quantification of tau load using [18F]AV1451 PET. Mol Imaging Biol. 2017;19:963\u201371. https:\/\/doi.org\/10.1007\/s11307-017-1080-z.","journal-title":"Mol Imaging Biol"},{"key":"5662_CR39","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1177\/0271678X18820765","volume":"40","author":"SS Golla","year":"2020","unstructured":"Golla SS, Wolters EE, Timmers T, Ossenkoppele R, van der Weijden CW, Scheltens P, et al. Parametric methods for [18 F]flortaucipir PET. J Cereb Blood Flow Metab. 2020;40:365\u201373. https:\/\/doi.org\/10.1177\/0271678X18820765.","journal-title":"J Cereb Blood Flow Metab"},{"key":"5662_CR40","unstructured":"Zhao S, Song J, Ermon S. Towards deeper understanding of variational autoencoding models. arXiv. 2017. http:\/\/arxiv.org\/abs\/1702.08658. Accessed 28 Feb 2017."},{"key":"5662_CR41","doi-asserted-by":"publisher","first-page":"129","DOI":"10.1016\/j.ijpsycho.2014.04.001","volume":"92","author":"CJ Stam","year":"2014","unstructured":"Stam CJ, Tewarie P, Van Dellen E, van Straaten ECW, Hillebrand A, Van Mieghem P. The trees and the forest: characterization of complex brain networks with minimum spanning trees. Int J Psychophysiol. 2014;92:129\u201338. https:\/\/doi.org\/10.1016\/j.ijpsycho.2014.04.001.","journal-title":"Int J Psychophysiol"},{"key":"5662_CR42","doi-asserted-by":"publisher","first-page":"308","DOI":"10.1016\/j.neuroimage.2013.10.022","volume":"88","author":"P Tewarie","year":"2014","unstructured":"Tewarie P, Hillebrand A, Schoonheim MM, van Dijk BW, Geurts JJG, Barkhof F, et al. Functional brain network analysis using minimum spanning trees in Multiple Sclerosis: an MEG source-space study. Neuroimage. 2014;88:308\u201318. https:\/\/doi.org\/10.1016\/j.neuroimage.2013.10.022.","journal-title":"Neuroimage"},{"key":"5662_CR43","doi-asserted-by":"publisher","unstructured":"Iturria-Medina Y, Khan AF, Adewale Q, Shirazi AH, Alzheimer\u2019s Disease Neuroimaging Initiative. Blood and brain gene expression trajectories mirror neuropathology and clinical deterioration in neurodegeneration. Brain. 2020;143:661\u201373. https:\/\/doi.org\/10.1093\/brain\/awz400","DOI":"10.1093\/brain\/awz400"}],"container-title":["European Journal of Nuclear Medicine and Molecular Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00259-021-05662-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00259-021-05662-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00259-021-05662-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,2]],"date-time":"2022-07-02T01:06:57Z","timestamp":1656724017000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00259-021-05662-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,28]]},"references-count":43,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2022,7]]}},"alternative-id":["5662"],"URL":"https:\/\/doi.org\/10.1007\/s00259-021-05662-z","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-880967\/v1","asserted-by":"object"}]},"ISSN":["1619-7070","1619-7089"],"issn-type":[{"value":"1619-7070","type":"print"},{"value":"1619-7089","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,28]]},"assertion":[{"value":"5 September 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 December 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 February 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"KS receives research grants from Novartis and Siemens Healthineers, and sponsorships from Novartis, Siemens Healthineers, Hermes Medical Solution, DosiSoft, Varian, THQ Medical Products, QDose, PMOD, Boston Scientific, SIRTEX, MIM Software, and the ICPO Foundation. HC is a cofounder and CTO of Portrai Inc. and a scientific advisory board member for AItheNutriGene.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}