{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,16]],"date-time":"2026-10-16T17:40:55Z","timestamp":1792172455420,"version":"4.4.0"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T00:00:00Z","timestamp":1737331200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T00:00:00Z","timestamp":1737331200000},"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":["82394434, 82272039, and 82021002, 8197164"],"award-info":[{"award-number":["82394434, 82272039, and 82021002, 8197164"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82394432"],"award-info":[{"award-number":["82394432"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"STI2030-Major Projects","award":["2022ZD0211600"],"award-info":[{"award-number":["2022ZD0211600"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Eur J Nucl Med Mol Imaging"],"published-print":{"date-parts":[[2025,3]]},"DOI":"10.1007\/s00259-025-07096-3","type":"journal-article","created":{"date-parts":[[2025,1,20]],"date-time":"2025-01-20T02:51:56Z","timestamp":1737341516000},"page":"1566-1575","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Cross-modality PET image synthesis for Parkinson\u2019s Disease diagnosis: a leap from [18F]FDG to [11C]CFT"],"prefix":"10.1007","volume":"52","author":[{"given":"Zhenrong","family":"Shen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haolin","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiaying","family":"Lu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingjie","family":"Ge","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Honglin","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ping","family":"Wu","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":"Yuhua","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yunhao","family":"Yang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fengtao","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yihui","family":"Guan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaicong","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qian","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8856-7217","authenticated-orcid":false,"given":"Chuantao","family":"Zuo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,1,20]]},"reference":[{"key":"7096_CR1","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1016\/s0140-6736(23)01478-2","volume":"403","author":"HR Morris","year":"2024","unstructured":"Morris HR, Spillantini MG, Sue CM, Williams-Gray CH. The pathogenesis of Parkinson\u2019s disease. Lancet. 2024;403:293\u2013304. https:\/\/doi.org\/10.1016\/s0140-6736(23)01478-2.","journal-title":"Lancet"},{"key":"7096_CR2","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1038\/s41583-021-00542-9","volume":"23","author":"J Blesa","year":"2022","unstructured":"Blesa J, Foffani G, Dehay B, Bezard E, Obeso JA. Motor and non-motor circuit disturbances in early Parkinson disease: which happens first? Nat Rev Neurosci. 2022;23:115\u201328. https:\/\/doi.org\/10.1038\/s41583-021-00542-9.","journal-title":"Nat Rev Neurosci"},{"key":"7096_CR3","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1038\/s41582-021-00486-9","volume":"17","author":"D Berg","year":"2021","unstructured":"Berg D, Borghammer P, Fereshtehnejad SM, Heinzel S, Horsager J, Schaeffer E, et al. Prodromal Parkinson disease subtypes - key to understanding heterogeneity. Nat Rev Neurol. 2021;17:349\u201361. https:\/\/doi.org\/10.1038\/s41582-021-00486-9.","journal-title":"Nat Rev Neurol"},{"key":"7096_CR4","doi-asserted-by":"publisher","first-page":"385","DOI":"10.1016\/s1474-4422(21)00030-2","volume":"20","author":"E Tolosa","year":"2021","unstructured":"Tolosa E, Garrido A, Scholz SW, Poewe W. Challenges in the diagnosis of Parkinson\u2019s disease. Lancet Neurol. 2021;20:385\u201397. https:\/\/doi.org\/10.1016\/s1474-4422(21)00030-2.","journal-title":"Lancet Neurol"},{"key":"7096_CR5","doi-asserted-by":"publisher","first-page":"716","DOI":"10.1007\/s00415-008-0782-1","volume":"255","author":"B Post","year":"2008","unstructured":"Post B, Speelman JD, de Haan RJ. Clinical heterogeneity in newly diagnosed Parkinson\u2019s disease. J Neurol. 2008;255:716\u201322. https:\/\/doi.org\/10.1007\/s00415-008-0782-1.","journal-title":"J Neurol"},{"key":"7096_CR6","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1016\/s0140-6736(23)01429-0","volume":"403","author":"T Foltynie","year":"2024","unstructured":"Foltynie T, Bruno V, Fox S, K\u00fchn AA, Lindop F, Lees AJ. Medical, surgical, and physical treatments for Parkinson\u2019s disease. Lancet. 2024;403:305\u201324. https:\/\/doi.org\/10.1016\/s0140-6736(23)01429-0.","journal-title":"Lancet"},{"key":"7096_CR7","doi-asserted-by":"publisher","first-page":"181","DOI":"10.1002\/mds.26907","volume":"32","author":"AP Strafella","year":"2017","unstructured":"Strafella AP, Bohnen NI, Perlmutter JS, Eidelberg D, Pavese N, Van Eimeren T, et al. Molecular imaging to track Parkinson\u2019s disease and atypical parkinsonisms: new imaging frontiers. Mov Disord. 2017;32:181\u201392. https:\/\/doi.org\/10.1002\/mds.26907.","journal-title":"Mov Disord"},{"key":"7096_CR8","doi-asserted-by":"publisher","first-page":"708","DOI":"10.1038\/nrneurol.2014.205","volume":"10","author":"M Politis","year":"2014","unstructured":"Politis M. Neuroimaging in Parkinson disease: from research setting to clinical practice. Nat Rev Neurol. 2014;10:708\u201322. https:\/\/doi.org\/10.1038\/nrneurol.2014.205.","journal-title":"Nat Rev Neurol"},{"key":"7096_CR9","doi-asserted-by":"publisher","first-page":"1262","DOI":"10.1001\/jamaneurol.2021.1312","volume":"78","author":"T Mitchell","year":"2021","unstructured":"Mitchell T, Leh\u00e9ricy S, Chiu SY, Strafella AP, Stoessl AJ, Vaillancourt DE. Emerging neuroimaging biomarkers across Disease Stage in Parkinson Disease: a review. JAMA Neurol. 2021;78:1262\u201372. https:\/\/doi.org\/10.1001\/jamaneurol.2021.1312.","journal-title":"JAMA Neurol"},{"key":"7096_CR10","doi-asserted-by":"publisher","first-page":"660","DOI":"10.1111\/jnc.15516","volume":"159","author":"NSR Bidesi","year":"2021","unstructured":"Bidesi NSR, Vang Andersen I, Windhorst AD, Shalgunov V, Herth MM. The role of neuroimaging in Parkinson\u2019s disease. J Neurochem. 2021;159:660\u201389. https:\/\/doi.org\/10.1111\/jnc.15516.","journal-title":"J Neurochem"},{"key":"7096_CR11","doi-asserted-by":"publisher","first-page":"1229","DOI":"10.1002\/mds.21505","volume":"22","author":"C Scherfler","year":"2007","unstructured":"Scherfler C, Schwarz J, Antonini A, Grosset D, Valldeoriola F, Marek K, et al. Role of DAT-SPECT in the diagnostic work up of parkinsonism. Mov Disord. 2007;22:1229\u201338. https:\/\/doi.org\/10.1002\/mds.21505.","journal-title":"Mov Disord"},{"key":"7096_CR12","doi-asserted-by":"publisher","first-page":"1591","DOI":"10.1002\/mds.26424","volume":"30","author":"RB Postuma","year":"2015","unstructured":"Postuma RB, Berg D, Stern M, Poewe W, Olanow CW, Oertel W, et al. MDS clinical diagnostic criteria for Parkinson\u2019s disease. Mov Disord. 2015;30:1591\u2013601. https:\/\/doi.org\/10.1002\/mds.26424.","journal-title":"Mov Disord"},{"key":"7096_CR13","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1002\/mdc3.13354","volume":"9","author":"C Peralta","year":"2022","unstructured":"Peralta C, Strafella AP, van Eimeren T, Ceravolo R, Seppi K, Kaasinen V, et al. Pragmatic Approach on Neuroimaging techniques for the Differential diagnosis of Parkinsonisms. Mov Disord Clin Pract. 2022;9:6\u201319. https:\/\/doi.org\/10.1002\/mdc3.13354.","journal-title":"Mov Disord Clin Pract"},{"key":"7096_CR14","doi-asserted-by":"publisher","first-page":"1885","DOI":"10.1007\/s00259-020-04817-8","volume":"47","author":"S Morbelli","year":"2020","unstructured":"Morbelli S, Esposito G, Arbizu J, Barthel H, Boellaard R, Bohnen NI, et al. EANM practice guideline\/SNMMI procedure standard for dopaminergic imaging in parkinsonian syndromes 1.0. Eur J Nucl Med Mol Imaging. 2020;47:1885\u2013912. https:\/\/doi.org\/10.1007\/s00259-020-04817-8.","journal-title":"Eur J Nucl Med Mol Imaging"},{"key":"7096_CR15","doi-asserted-by":"publisher","first-page":"1601","DOI":"10.1002\/mds.27362","volume":"33","author":"RB Postuma","year":"2018","unstructured":"Postuma RB, Poewe W, Litvan I, Lewis S, Lang AE, Halliday G, et al. Validation of the MDS clinical diagnostic criteria for Parkinson\u2019s disease. Mov Disord. 2018;33:1601\u20138. https:\/\/doi.org\/10.1002\/mds.27362.","journal-title":"Mov Disord"},{"key":"7096_CR16","first-page":"1","volume":"56","author":"G Xie","year":"2023","unstructured":"Xie G, Huang Y, Wang J, Lyu J, Zheng F, Zheng Y, et al. Cross-modality neuroimage synthesis: a survey. ACM-CSUR. 2023;56:1\u201328.","journal-title":"ACM-CSUR"},{"key":"7096_CR17","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1016\/j.engappai.2018.11.013","volume":"78","author":"A Ben-Cohen","year":"2019","unstructured":"Ben-Cohen A, Klang E, Raskin SP, Soffer S, Ben-Haim S, Konen E, et al. Cross-modality synthesis from CT to PET using FCN and GAN networks for improved automated lesion detection. Eng Appl Artif Intell. 2019;78:186\u201394. https:\/\/doi.org\/10.1016\/j.engappai.2018.11.013.","journal-title":"Eng Appl Artif Intell"},{"key":"7096_CR18","doi-asserted-by":"crossref","unstructured":"Zhang J, Cui Z, Jiang C, Zhang J, Gao F, Shen D. Mapping in cycles: Dual-domain pet-ct synthesis framework with cycle-consistent constraints. International Conference on Medical Image Computing and Computer-Assisted Intervention. 2022:758\u2013\u200967.","DOI":"10.1007\/978-3-031-16446-0_72"},{"key":"7096_CR19","doi-asserted-by":"crossref","unstructured":"Bi L, Kim J, Kumar A, Feng D, Fulham M. Synthesis of positron emission tomography (PET) images via multi-channel generative adversarial networks (GANs). Molecular Imaging, Reconstruction and Analysis of Moving Body Organs, and Stroke Imaging and Treatment: Fifth International Workshop, CMMI 2017, Second International Workshop, RAMBO 2017, and First International Workshop, SWITCH 2017, Held in Conjunction with MICCAI 2017, Qu\u00c9Bec City, QC, Canada, September 14, 2017, Proceedings 5. 2017:43\u201351.","DOI":"10.1007\/978-3-319-67564-0_5"},{"key":"7096_CR20","doi-asserted-by":"publisher","first-page":"2965","DOI":"10.1109\/TMI.2020.2983085","volume":"39","author":"Y Pan","year":"2020","unstructured":"Pan Y, Liu M, Lian C, Xia Y, Shen D. Spatially-constrained fisher representation for brain disease identification with incomplete multi-modal neuroimages. IEEE Trans Med Imaging. 2020;39:2965\u201375.","journal-title":"IEEE Trans Med Imaging"},{"key":"7096_CR21","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1109\/TMI.2021.3107013","volume":"41","author":"S Hu","year":"2021","unstructured":"Hu S, Lei B, Wang S, Wang Y, Feng Z, Shen Y. Bidirectional mapping generative adversarial networks for brain MR to PET synthesis. IEEE Trans Med Imaging. 2021;41:145\u201357.","journal-title":"IEEE Trans Med Imaging"},{"key":"7096_CR22","doi-asserted-by":"crossref","unstructured":"Pan Y, Liu M, Lian C, Zhou T, Xia Y, Shen D. Synthesizing missing PET from MRI with cycle-consistent generative adversarial networks for Alzheimer\u2019s disease diagnosis. Medical Image Computing and Computer Assisted Intervention\u2013MICCAI. 2018: 21st International Conference, Granada, Spain, September 16\u201320, 2018, Proceedings, Part III 11. 2018:455\u2013\u200963.","DOI":"10.1007\/978-3-030-00931-1_52"},{"key":"7096_CR23","doi-asserted-by":"publisher","first-page":"980","DOI":"10.1093\/brain\/awad346","volume":"147","author":"J Lee","year":"2024","unstructured":"Lee J, Burkett BJ, Min HK, Senjem ML, Dicks E, Corriveau-Lecavalier N, et al. Synthesizing images of tau pathology from cross-modal neuroimaging using deep learning. Brain. 2024;147:980\u201395. https:\/\/doi.org\/10.1093\/brain\/awad346.","journal-title":"Brain"},{"key":"7096_CR24","doi-asserted-by":"publisher","first-page":"552","DOI":"10.1177\/0271678x19828916","volume":"40","author":"Z Huang","year":"2020","unstructured":"Huang Z, Jiang C, Li L, Xu Q, Ge J, Li M, et al. Correlations between dopaminergic dysfunction and abnormal metabolic network activity in REM sleep behavior disorder. J Cereb Blood Flow Metab. 2020;40:552\u201362. https:\/\/doi.org\/10.1177\/0271678x19828916.","journal-title":"J Cereb Blood Flow Metab"},{"key":"7096_CR25","doi-asserted-by":"publisher","first-page":"622","DOI":"10.1016\/j.parkreldis.2013.02.013","volume":"19","author":"P Wu","year":"2013","unstructured":"Wu P, Wang J, Peng S, Ma Y, Zhang H, Guan Y, et al. Metabolic brain network in the Chinese patients with Parkinson\u2019s disease based on 18F-FDG PET imaging. Parkinsonism Relat Disord. 2013;19:622\u20137. https:\/\/doi.org\/10.1016\/j.parkreldis.2013.02.013.","journal-title":"Parkinsonism Relat Disord"},{"key":"7096_CR26","doi-asserted-by":"publisher","first-page":"1741","DOI":"10.2967\/jnumed.121.263029","volume":"63","author":"P Wu","year":"2022","unstructured":"Wu P, Zhao Y, Wu J, Brendel M, Lu J, Ge J, et al. Differential diagnosis of parkinsonism based on deep metabolic imaging indices. J Nucl Med. 2022;63:1741\u20137. https:\/\/doi.org\/10.2967\/jnumed.121.263029.","journal-title":"J Nucl Med"},{"key":"7096_CR27","first-page":"234","volume":"18","author":"O Ronneberger","year":"2015","unstructured":"Ronneberger O, Fischer P, Brox T. U-net: Convolutional networks for biomedical image segmentation. Med Image Comput computer-assisted intervention\u2013MICCAI 2015: 18th Int Conf Munich Ger Oct 5\u20139 2015 Proc part III. 2015;18:234\u201341.","journal-title":"Med Image Comput computer-assisted intervention\u2013MICCAI 2015: 18th Int Conf Munich Ger Oct 5\u20139 2015 Proc part III"},{"key":"7096_CR28","doi-asserted-by":"crossref","unstructured":"Zhu J-Y, Park T, Isola P, Efros AA. Unpaired image-to-image translation using cycle-consistent adversarial networks. Proceedings of the IEEE international conference on computer vision. 2017:2223-32.","DOI":"10.1109\/ICCV.2017.244"},{"key":"7096_CR29","unstructured":"Miyato T, Koyama M. cGANs with projection discriminator. arXiv preprint arXiv:180205637. 2018."},{"key":"7096_CR30","doi-asserted-by":"crossref","unstructured":"He K, Zhang X, Ren S, Sun J. Deep residual learning for image recognition. Proceedings of the IEEE conference on computer vision and pattern recognition. 2016:770-8.","DOI":"10.1109\/CVPR.2016.90"},{"key":"7096_CR31","unstructured":"Loshchilov I, Hutter F. SGDR: Stochastic Gradient Descent with Warm Restarts; 2016."},{"key":"7096_CR32","unstructured":"Paszke A, Gross S, Massa F, Lerer A, Bradbury J, Chanan G et al. Pytorch: an imperative style, high-performance deep learning library. Adv Neural Inf Process Syst. 2019;32."},{"key":"7096_CR33","doi-asserted-by":"publisher","first-page":"796","DOI":"10.1016\/s1474-4422(06)70549-x","volume":"5","author":"R Djaldetti","year":"2006","unstructured":"Djaldetti R, Ziv I, Melamed E. The mystery of motor asymmetry in Parkinson\u2019s disease. Lancet Neurol. 2006;5:796\u2013802. https:\/\/doi.org\/10.1016\/s1474-4422(06)70549-x.","journal-title":"Lancet Neurol"},{"key":"7096_CR34","doi-asserted-by":"publisher","first-page":"S32","DOI":"10.1212\/WNL.0b013e318198e0e9","volume":"72","author":"J Brotchie","year":"2009","unstructured":"Brotchie J, Fitzer-Attas C. Mechanisms compensating for dopamine loss in early Parkinson disease. Neurology. 2009;72:S32\u20138. https:\/\/doi.org\/10.1212\/WNL.0b013e318198e0e9.","journal-title":"Neurology"},{"key":"7096_CR35","doi-asserted-by":"publisher","first-page":"562","DOI":"10.1097\/rlu.0000000000002148","volume":"43","author":"FT Liu","year":"2018","unstructured":"Liu FT, Ge JJ, Wu JJ, Wu P, Ma Y, Zuo CT, et al. Clinical, dopaminergic, and metabolic correlations in Parkinson Disease: a dual-Tracer PET Study. Clin Nucl Med. 2018;43:562\u201371. https:\/\/doi.org\/10.1097\/rlu.0000000000002148.","journal-title":"Clin Nucl Med"},{"key":"7096_CR36","doi-asserted-by":"publisher","first-page":"629","DOI":"10.1016\/s1474-4422(18)30169-8","volume":"17","author":"KA Schindlbeck","year":"2018","unstructured":"Schindlbeck KA, Eidelberg D. Network imaging biomarkers: insights and clinical applications in Parkinson\u2019s disease. Lancet Neurol. 2018;17:629\u201340. https:\/\/doi.org\/10.1016\/s1474-4422(18)30169-8.","journal-title":"Lancet Neurol"},{"key":"7096_CR37","doi-asserted-by":"publisher","first-page":"3290","DOI":"10.1093\/brain\/awr233","volume":"134","author":"R Nandhagopal","year":"2011","unstructured":"Nandhagopal R, Kuramoto L, Schulzer M, Mak E, Cragg J, McKenzie J, et al. Longitudinal evolution of compensatory changes in striatal dopamine processing in Parkinson\u2019s disease. Brain. 2011;134:3290\u20138. https:\/\/doi.org\/10.1093\/brain\/awr233.","journal-title":"Brain"},{"key":"7096_CR38","doi-asserted-by":"publisher","first-page":"407","DOI":"10.1016\/s1474-4422(23)00109-6","volume":"22","author":"A Siderowf","year":"2023","unstructured":"Siderowf A, Concha-Marambio L, Lafontant DE, Farris CM, Ma Y, Urenia PA, et al. Assessment of heterogeneity among participants in the Parkinson\u2019s progression markers Initiative cohort using \u03b1-synuclein seed amplification: a cross-sectional study. Lancet Neurol. 2023;22:407\u201317. https:\/\/doi.org\/10.1016\/s1474-4422(23)00109-6.","journal-title":"Lancet Neurol"},{"key":"7096_CR39","doi-asserted-by":"publisher","unstructured":"Li W, Lao-Kaim NP, Roussakis AA, Mart\u00edn-Bastida A, Valle-Guzman N, Paul G et al. (11) C-PE2I and (18) F-Dopa PET for assessing progression rate in Parkinson\u2019s: A longitudinal study. Mov Disord. 2018;33:117\u2013\u200927. https:\/\/doi.org\/10.1002\/mds.27183","DOI":"10.1002\/mds.27183"},{"key":"7096_CR40","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1007\/s00415-006-0322-9","volume":"254","author":"J Wang","year":"2007","unstructured":"Wang J, Zuo CT, Jiang YP, Guan YH, Chen ZP, Xiang JD, et al. 18F-FP-CIT PET imaging and SPM analysis of dopamine transporters in Parkinson\u2019s disease in various Hoehn & Yahr stages. J Neurol. 2007;254:185\u201390. https:\/\/doi.org\/10.1007\/s00415-006-0322-9.","journal-title":"J Neurol"},{"key":"7096_CR41","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1016\/j.smrv.2018.04.001","volume":"41","author":"M Bauckneht","year":"2018","unstructured":"Bauckneht M, Chincarini A, De Carli F, Terzaghi M, Morbelli S, Nobili F, et al. Presynaptic dopaminergic neuroimaging in REM sleep behavior disorder: a systematic review and meta-analysis. Sleep Med Rev. 2018;41:266\u201374. https:\/\/doi.org\/10.1016\/j.smrv.2018.04.001.","journal-title":"Sleep Med Rev"},{"key":"7096_CR42","doi-asserted-by":"publisher","first-page":"1981","DOI":"10.1056\/NEJMra2301725","volume":"388","author":"P Rajpurkar","year":"2023","unstructured":"Rajpurkar P, Lungren MP. The current and future state of AI interpretation of medical images. N Engl J Med. 2023;388:1981\u201390. https:\/\/doi.org\/10.1056\/NEJMra2301725.","journal-title":"N Engl J Med"},{"key":"7096_CR43","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1038\/s41591-021-01614-0","volume":"28","author":"P Rajpurkar","year":"2022","unstructured":"Rajpurkar P, Chen E, Banerjee O, Topol EJ. AI in health and medicine. Nat Med. 2022;28:31\u20138. https:\/\/doi.org\/10.1038\/s41591-021-01614-0.","journal-title":"Nat Med"},{"key":"7096_CR44","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1038\/s41746-024-01012-z","volume":"7","author":"J Wang","year":"2024","unstructured":"Wang J, Xue L, Jiang J, Liu F, Wu P, Lu J, et al. Diagnostic performance of artificial intelligence-assisted PET imaging for Parkinson\u2019s disease: a systematic review and meta-analysis. NPJ Digit Med. 2024;7:17. https:\/\/doi.org\/10.1038\/s41746-024-01012-z.","journal-title":"NPJ Digit Med"},{"key":"7096_CR45","doi-asserted-by":"publisher","first-page":"1482","DOI":"10.1002\/mds.27094","volume":"32","author":"SK Meles","year":"2017","unstructured":"Meles SK, Vadasz D, Renken RJ, Sittig-Wiegand E, Mayer G, Depboylu C, et al. FDG PET, dopamine transporter SPECT, and olfaction: combining biomarkers in REM sleep behavior disorder. Mov Disord. 2017;32:1482\u20136. https:\/\/doi.org\/10.1002\/mds.27094.","journal-title":"Mov Disord"}],"container-title":["European Journal of Nuclear Medicine and Molecular Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00259-025-07096-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00259-025-07096-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00259-025-07096-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,2,19]],"date-time":"2025-02-19T10:55:12Z","timestamp":1739962512000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00259-025-07096-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,20]]},"references-count":45,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,3]]}},"alternative-id":["7096"],"URL":"https:\/\/doi.org\/10.1007\/s00259-025-07096-3","relation":{},"ISSN":["1619-7070","1619-7089"],"issn-type":[{"value":"1619-7070","type":"print"},{"value":"1619-7089","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,20]]},"assertion":[{"value":"7 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 January 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 January 2025","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 to publish"}},{"value":"The authors declare that they have no conflict of interest.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}