{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,5]],"date-time":"2026-10-05T20:12:39Z","timestamp":1791231159729,"version":"4.1.0"},"reference-count":42,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T00:00:00Z","timestamp":1755475200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T00:00:00Z","timestamp":1755475200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["JP22K07746"],"award-info":[{"award-number":["JP22K07746"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["JP25K02603"],"award-info":[{"award-number":["JP25K02603"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["JP24K18796"],"award-info":[{"award-number":["JP24K18796"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Ishizue provided by Kyoto University Research Administration Center"},{"name":"The Kyoto University Foundation"},{"name":"Kodama Foundation"},{"name":"Sumitomo Pharma Co., Ltd"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Jpn J Radiol"],"published-print":{"date-parts":[[2026,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>To differentiate between Parkinson\u2019s Disease (PD) and healthy controls by using integrated analysis of PD-specific MR findings including deformation of the substantia nigra pars compacta (SNpc), signal loss in neuromelanin (NM) sensitive MRI, and iron deposition in the deep gray matter (DGM) structures.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Materials and methods<\/jats:title>\n                    <jats:p>Patients with PD and healthy controls were recruited between August 2022 and December 2023. All subjects underwent 3\u00a0T MRI including a magnetization transfer contrast (MTC) and a double flip angle multi-echo protocol as part of Strategically Acquired Gradient Echo (STAGE). The data analysis included detecting the presence of Nigrosome-1 (N1) sign in the SNpc, signal intensity and volume of NM content and iron quantification through quantitative susceptibility mapping (QSM) in DGMs. The 3D regions of interest were manually demarcated on QSM maps. Mean susceptibility values from global analysis (whole structure) as well as regional high iron analysis (age-based threshold) were extracted for each individual structure. Univariate and multivariate analyses were performed using these parameters.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Nineteen patients with PD (68.0\u2009\u00b1\u20098.0\u00a0years, 10 males, Hoehn and Yahr scale 1 (n\u2009=\u20091), 2 (n\u2009=\u200913), 3 (n\u2009=\u20094), 4 (n\u2009=\u20091)) and 21 healthy controls (68.3\u2009\u00b1\u20098.6\u00a0years, 12 males) were enrolled. Discriminating PD from controls was successful using each method: N1 sign (P\u2009&lt;\u20090.001), NM volume (P\u2009&lt;\u20090.001), susceptibility values of global analysis (caudate, P\u2009&lt;\u20090.001; putamen, P\u2009&lt;\u20090.001; pulvinar, P\u2009=\u20090.006), regional analysis (putamen, P\u2009&lt;\u20090.001; pulvinar, P\u2009=\u20090.009, thalamus, P\u2009=\u20090.008). Stepwise logistic regression analyses were performed, and the best model was created using N1 sign, NM volume, regional analysis (putamen, red nucleus and thalamus) (area under the curve of 0.99).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Integrated analysis of PD specific MR findings including N1 sign, NM volume, and iron content in the DGM structures robustly discriminates between PD and healthy controls.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s11604-025-01858-7","type":"journal-article","created":{"date-parts":[[2025,8,18]],"date-time":"2025-08-18T05:04:19Z","timestamp":1755493459000},"page":"24-34","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Integrated evaluation of Nigrosome 1 sign, neuromelanin-sensitive MR and iron deposition"],"prefix":"10.1007","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1982-3168","authenticated-orcid":false,"given":"Yasutaka","family":"Fushimi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kiarash","family":"Ghassaban","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sean K.","family":"Sethi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Satoshi","family":"Nakajima","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sachi","family":"Okuchi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Akihiko","family":"Sakata","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Takayuki","family":"Yamamoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sayo","family":"Otani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Satoshi","family":"Ikeda","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuta","family":"Terada","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Atsushi","family":"Shima","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nobukatsu","family":"Sawamoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuji","family":"Nakamoto","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,8,18]]},"reference":[{"key":"1858_CR1","doi-asserted-by":"publisher","first-page":"83","DOI":"10.1016\/S0022-510X(97)00100-7","volume":"151","author":"SY Ma","year":"1997","unstructured":"Ma SY, Roytta M, Rinne JO, Collan Y, Rinne UK. Correlation between neuromorphometry in the substantia nigra and clinical features in Parkinson\u2019s disease using disector counts. J Neurol Sci. 1997;151:83\u20137.","journal-title":"J Neurol Sci"},{"key":"1858_CR2","doi-asserted-by":"publisher","first-page":"2419","DOI":"10.1093\/brain\/awt192","volume":"136","author":"JH Kordower","year":"2013","unstructured":"Kordower JH, Olanow CW, Dodiya HB, Chu Y, Beach TG, Adler CH, et al. Disease duration and the integrity of the nigrostriatal system in Parkinson\u2019s disease. Brain. 2013;136:2419\u201331.","journal-title":"Brain"},{"key":"1858_CR3","doi-asserted-by":"publisher","first-page":"803","DOI":"10.1002\/ana.22284","volume":"69","author":"R de la Fuente-Fernandez","year":"2011","unstructured":"de la Fuente-Fernandez R, Schulzer M, Kuramoto L, Cragg J, Ramachandiran N, Au WL, et al. Age-specific progression of nigrostriatal dysfunction in Parkinson\u2019s disease. Ann Neurol. 2011;69:803\u201310.","journal-title":"Ann Neurol"},{"issue":"Pt 5","key":"1858_CR4","doi-asserted-by":"publisher","first-page":"2283","DOI":"10.1093\/brain\/114.5.2283","volume":"114","author":"JM Fearnley","year":"1991","unstructured":"Fearnley JM, Lees AJ. Ageing and Parkinson\u2019s disease: substantia nigra regional selectivity. Brain. 1991;114(Pt 5):2283\u2013301.","journal-title":"Brain"},{"issue":"Pt 8","key":"1858_CR5","doi-asserted-by":"publisher","first-page":"1437","DOI":"10.1093\/brain\/122.8.1437","volume":"122","author":"P Damier","year":"1999","unstructured":"Damier P, Hirsch EC, Agid Y, Graybiel AM. The substantia nigra of the human brain. part II. Patterns of loss of dopamine-containing neurons in Parkinson\u2019s disease. Brain. 1999;122(Pt 8):1437\u201348.","journal-title":"Brain"},{"key":"1858_CR6","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0093814","volume":"9","author":"ST Schwarz","year":"2014","unstructured":"Schwarz ST, Afzal M, Morgan PS, Bajaj N, Gowland PA, Auer DP. The \u201cswallow tail\u201d appearance of the healthy nigrosome: a new accurate test of Parkinson\u2019s disease: a case-control and retrospective cross-sectional MRI study at 3T. PLoS ONE. 2014;9: e93814.","journal-title":"PLoS ONE"},{"key":"1858_CR7","doi-asserted-by":"publisher","first-page":"674","DOI":"10.1148\/radiol.212696","volume":"305","author":"M Brammerloh","year":"2022","unstructured":"Brammerloh M, Kirilina E, Alkemade A, Bazin PL, Jantzen C, Jager C, et al. Swallow tail sign: revisited. Radiology. 2022;305:674\u20137.","journal-title":"Radiology"},{"key":"1858_CR8","doi-asserted-by":"publisher","first-page":"534","DOI":"10.1212\/WNL.0b013e31829e6fd2","volume":"81","author":"AI Blazejewska","year":"2013","unstructured":"Blazejewska AI, Schwarz ST, Pitiot A, Stephenson MC, Lowe J, Bajaj N, et al. Visualization of nigrosome 1 and its loss in PD: pathoanatomical correlation and in vivo 7 T MRI. Neurology. 2013;81:534\u201340.","journal-title":"Neurology"},{"key":"1858_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2021.118255","volume":"239","author":"M Brammerloh","year":"2021","unstructured":"Brammerloh M, Morawski M, Friedrich I, Reinert T, Lange C, Pelicon P, et al. Measuring the iron content of dopaminergic neurons in substantia nigra with MRI relaxometry. Neuroimage. 2021;239: 118255.","journal-title":"Neuroimage"},{"key":"1858_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.nicl.2019.102103","volume":"25","author":"Z Cheng","year":"2020","unstructured":"Cheng Z, He N, Huang P, Li Y, Tang R, Sethi SK, et al. Imaging the Nigrosome 1 in the substantia nigra using susceptibility weighted imaging and quantitative susceptibility mapping: an application to Parkinson\u2019s disease. NeuroImage Clin. 2020;25: 102103.","journal-title":"NeuroImage Clin"},{"key":"1858_CR11","doi-asserted-by":"publisher","first-page":"1215","DOI":"10.1097\/01.wnr.0000227984.84927.a7","volume":"17","author":"M Sasaki","year":"2006","unstructured":"Sasaki M, Shibata E, Tohyama K, Takahashi J, Otsuka K, Tsuchiya K, et al. Neuromelanin magnetic resonance imaging of locus ceruleus and substantia nigra in Parkinson\u2019s disease. NeuroReport. 2006;17:1215\u20138.","journal-title":"NeuroReport"},{"key":"1858_CR12","doi-asserted-by":"publisher","first-page":"205","DOI":"10.2463\/mrms.7.205","volume":"7","author":"T Nakane","year":"2008","unstructured":"Nakane T, Nihashi T, Kawai H, Naganawa S. Visualization of neuromelanin in the Substantia nigra and locus ceruleus at 1.5T using a 3D-gradient echo sequence with magnetization transfer contrast. Magn Reson Med Sci. 2008;7:205\u201310.","journal-title":"Magn Reson Med Sci"},{"key":"1858_CR13","doi-asserted-by":"publisher","first-page":"719","DOI":"10.1007\/s00234-013-1171-8","volume":"55","author":"K Ogisu","year":"2013","unstructured":"Ogisu K, Kudo K, Sasaki M, Sakushima K, Yabe I, Sasaki H, et al. 3D neuromelanin-sensitive magnetic resonance imaging with semi-automated volume measurement of the substantia nigra pars compacta for diagnosis of Parkinson\u2019s disease. Neuroradiology. 2013;55:719\u201324.","journal-title":"Neuroradiology"},{"key":"1858_CR14","doi-asserted-by":"publisher","first-page":"874","DOI":"10.1002\/mds.28417","volume":"36","author":"S Oshima","year":"2021","unstructured":"Oshima S, Fushimi Y, Okada T, Nakajima S, Yokota Y, Shima A, et al. Neuromelanin-sensitive magnetic resonance imaging using DANTE pulse. Mov Disord. 2021;36:874\u201382.","journal-title":"Mov Disord"},{"key":"1858_CR15","doi-asserted-by":"publisher","first-page":"1216","DOI":"10.1007\/s11604-023-01452-9","volume":"41","author":"S Oshima","year":"2023","unstructured":"Oshima S, Fushimi Y, Miyake KK, Nakajima S, Sakata A, Okuchi S, et al. Denoising approach with deep learning-based reconstruction for neuromelanin-sensitive MRI: image quality and diagnostic performance. Jpn J Radiol. 2023;41:1216\u201325.","journal-title":"Jpn J Radiol"},{"key":"1858_CR16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2020.116935","volume":"218","author":"Y Liu","year":"2020","unstructured":"Liu Y, Li J, He N, Chen Y, Jin Z, Yan F, et al. Optimizing neuromelanin contrast in the substantia nigra and locus coeruleus using a magnetization transfer contrast prepared 3D gradient recalled echo sequence. Neuroimage. 2020;218: 116935.","journal-title":"Neuroimage"},{"key":"1858_CR17","doi-asserted-by":"publisher","first-page":"789","DOI":"10.1148\/radiol.2016160662","volume":"283","author":"ST Schwarz","year":"2017","unstructured":"Schwarz ST, Xing Y, Tomar P, Bajaj N, Auer DP. In vivo assessment of brainstem depigmentation in Parkinson disease: potential as a severity marker for multicenter studies. Radiology. 2017;283:789\u201398.","journal-title":"Radiology"},{"key":"1858_CR18","doi-asserted-by":"publisher","first-page":"1790","DOI":"10.1002\/mrm.26584","volume":"78","author":"P Trujillo","year":"2017","unstructured":"Trujillo P, Summers PE, Ferrari E, Zucca FA, Sturini M, Mainardi LT, et al. Contrast mechanisms associated with neuromelanin-MRI. Magn Reson Med. 2017;78:1790\u2013800.","journal-title":"Magn Reson Med"},{"key":"1858_CR19","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1016\/j.neuroimage.2015.02.045","volume":"112","author":"J Langley","year":"2015","unstructured":"Langley J, Huddleston DE, Chen X, Sedlacik J, Zachariah N, Hu X. A multicontrast approach for comprehensive imaging of substantia nigra. Neuroimage. 2015;112:7\u201313.","journal-title":"Neuroimage"},{"key":"1858_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2019.116457","volume":"208","author":"K Wengler","year":"2020","unstructured":"Wengler K, He X, Abi-Dargham A, Horga G. Reproducibility assessment of neuromelanin-sensitive magnetic resonance imaging protocols for region-of-interest and voxelwise analyses. Neuroimage. 2020;208: 116457.","journal-title":"Neuroimage"},{"key":"1858_CR21","doi-asserted-by":"publisher","first-page":"337","DOI":"10.1093\/brain\/awad300","volume":"147","author":"P Trujillo","year":"2024","unstructured":"Trujillo P, Aumann MA, Claassen DO. Neuromelanin-sensitive MRI as a promising biomarker of catecholamine function. Brain. 2024;147:337\u201351.","journal-title":"Brain"},{"key":"1858_CR22","doi-asserted-by":"publisher","first-page":"e24","DOI":"10.1093\/brain\/awad393","volume":"147","author":"T Watanabe","year":"2024","unstructured":"Watanabe T. Neuromelanin? MRI of catecholaminergic neurons. Brain. 2024;147:e24\u20136.","journal-title":"Brain"},{"key":"1858_CR23","doi-asserted-by":"publisher","first-page":"5108","DOI":"10.1073\/pnas.1807983116","volume":"116","author":"CM Cassidy","year":"2019","unstructured":"Cassidy CM, Zucca FA, Girgis RR, Baker SC, Weinstein JJ, Sharp ME, et al. Neuromelanin-sensitive MRI as a noninvasive proxy measure of dopamine function in the human brain. Proc Natl Acad Sci U S A. 2019;116:5108\u201317.","journal-title":"Proc Natl Acad Sci U S A"},{"key":"1858_CR24","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.parkreldis.2018.07.007","volume":"58","author":"J Wang","year":"2019","unstructured":"Wang J, Huang Z, Li Y, Ye F, Wang C, Zhang Y, et al. Neuromelanin-sensitive MRI of the substantia nigra: an imaging biomarker to differentiate essential tremor from tremor-dominant Parkinson\u2019s disease. Parkinsonism Relat Disord. 2019;58:3\u20138.","journal-title":"Parkinsonism Relat Disord"},{"key":"1858_CR25","doi-asserted-by":"publisher","first-page":"176","DOI":"10.3174\/ajnr.A0770","volume":"29","author":"SL Harder","year":"2008","unstructured":"Harder SL, Hopp KM, Ward H, Neglio H, Gitlin J, Kido D. Mineralization of the deep gray matter with age: a retrospective review with susceptibility-weighted MR imaging. AJNR Am J Neuroradiol. 2008;29:176\u201383.","journal-title":"AJNR Am J Neuroradiol"},{"key":"1858_CR26","doi-asserted-by":"publisher","first-page":"59","DOI":"10.1002\/jmri.25130","volume":"44","author":"M Liu","year":"2016","unstructured":"Liu M, Liu S, Ghassaban K, Zheng W, Dicicco D, Miao Y, et al. Assessing global and regional iron content in deep gray matter as a function of age using susceptibility mapping. J Magn Reson Imaging. 2016;44:59\u201371.","journal-title":"J Magn Reson Imaging"},{"key":"1858_CR27","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2020.607705","volume":"14","author":"Y Li","year":"2020","unstructured":"Li Y, Sethi SK, Zhang C, Miao Y, Yerramsetty KK, Palutla VK, et al. Iron Content in deep gray matter as a function of age using quantitative susceptibility mapping: a multicenter study. Front Neurosci. 2020;14: 607705.","journal-title":"Front Neurosci"},{"key":"1858_CR28","doi-asserted-by":"publisher","first-page":"106","DOI":"10.3389\/fnagi.2019.00106","volume":"11","author":"K Ghassaban","year":"2019","unstructured":"Ghassaban K, He N, Sethi SK, Huang P, Chen S, Yan F, et al. Regional high iron in the Substantia nigra differentiates Parkinson\u2019s disease patients from healthy controls. Front Aging Neurosci. 2019;11:106.","journal-title":"Front Aging Neurosci"},{"key":"1858_CR29","doi-asserted-by":"publisher","first-page":"1287917","DOI":"10.3389\/fnagi.2023.1287917","volume":"15","author":"S Hartono","year":"2023","unstructured":"Hartono S, Chen RC, Welton T, Tan AS, Lee W, Teh PY, et al. Quantitative iron-neuromelanin MRI associates with motor severity in Parkinson\u2019s disease and matches radiological disease classification. Front Aging Neurosci. 2023;15:1287917.","journal-title":"Front Aging Neurosci"},{"key":"1858_CR30","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2021.117810","volume":"230","author":"N He","year":"2021","unstructured":"He N, Ghassaban K, Huang P, Jokar M, Wang Y, Cheng Z, et al. Imaging iron and neuromelanin simultaneously using a single 3D gradient echo magnetization transfer sequence: combining neuromelanin, iron and the nigrosome-1 sign as complementary imaging biomarkers in early stage Parkinson\u2019s disease. Neuroimage. 2021;230: 117810.","journal-title":"Neuroimage"},{"key":"1858_CR31","doi-asserted-by":"publisher","first-page":"2129","DOI":"10.1002\/mds.22340","volume":"23","author":"CG Goetz","year":"2008","unstructured":"Goetz CG, Tilley BC, Shaftman SR, Stebbins GT, Fahn S, Martinez-Martin P, et al. Movement disorder society-sponsored revision of the Unified Parkinson\u2019s Disease Rating Scale (MDS-UPDRS): scale presentation and clinimetric testing results. Mov Disord. 2008;23:2129\u201370.","journal-title":"Mov Disord"},{"key":"1858_CR32","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.mri.2019.09.006","volume":"65","author":"EM Haacke","year":"2020","unstructured":"Haacke EM, Chen Y, Utriainen D, Wu B, Wang Y, Xia S, et al. STrategically acquired gradient echo (STAGE) imaging, part III: technical advances and clinical applications of a rapid multi-contrast multi-parametric brain imaging method. Magn Reson Imaging. 2020;65:15\u201326.","journal-title":"Magn Reson Imaging"},{"key":"1858_CR33","doi-asserted-by":"publisher","first-page":"698","DOI":"10.1002\/jmri.24413","volume":"40","author":"S Liu","year":"2014","unstructured":"Liu S, Mok K, Neelavalli J, Cheng YC, Tang J, Ye Y, et al. Improved MR venography using quantitative susceptibility-weighted imaging. J Magn Reson Imaging. 2014;40:698\u2013708.","journal-title":"J Magn Reson Imaging"},{"key":"1858_CR34","unstructured":"Team RC. R: A language and environment for statistical computing. 2024."},{"issue":"Pt 8","key":"1858_CR35","doi-asserted-by":"publisher","first-page":"1421","DOI":"10.1093\/brain\/122.8.1421","volume":"122","author":"P Damier","year":"1999","unstructured":"Damier P, Hirsch EC, Agid Y, Graybiel AM. The substantia nigra of the human brain. I. Nigrosomes and the nigral matrix, a compartmental organization based on calbindin D(28K) immunohistochemistry. Brain. 1999;122(Pt 8):1421\u201336.","journal-title":"Brain"},{"key":"1858_CR36","doi-asserted-by":"publisher","first-page":"1387","DOI":"10.1007\/s00234-019-02279-w","volume":"61","author":"A Le Berre","year":"2019","unstructured":"Le Berre A, Kamagata K, Otsuka Y, Andica C, Hatano T, Saccenti L, et al. Convolutional neural network-based segmentation can help in assessing the substantia nigra in neuromelanin MRI. Neuroradiology. 2019;61:1387\u201395.","journal-title":"Neuroradiology"},{"key":"1858_CR37","doi-asserted-by":"publisher","first-page":"945","DOI":"10.1002\/mds.26201","volume":"30","author":"G Castellanos","year":"2015","unstructured":"Castellanos G, Fernandez-Seara MA, Lorenzo-Betancor O, Ortega-Cubero S, Puigvert M, Uranga J, et al. Automated neuromelanin imaging as a diagnostic biomarker for Parkinson\u2019s disease. Mov Disord. 2015;30:945\u201352.","journal-title":"Mov Disord"},{"key":"1858_CR38","doi-asserted-by":"publisher","first-page":"23","DOI":"10.1186\/s12868-019-0505-9","volume":"20","author":"Q Chen","year":"2019","unstructured":"Chen Q, Chen Y, Zhang Y, Wang F, Yu H, Zhang C, et al. Iron deposition in Parkinson\u2019s disease by quantitative susceptibility mapping. BMC Neurosci. 2019;20:23.","journal-title":"BMC Neurosci"},{"key":"1858_CR39","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2021.618435","volume":"15","author":"P Ravanfar","year":"2021","unstructured":"Ravanfar P, Loi SM, Syeda WT, Van Rheenen TE, Bush AI, Desmond P, et al. Systematic review: quantitative susceptibility mapping (QSM) of brain iron profile in neurodegenerative diseases. Front Neurosci. 2021;15: 618435.","journal-title":"Front Neurosci"},{"key":"1858_CR40","doi-asserted-by":"publisher","first-page":"4407","DOI":"10.1002\/hbm.22928","volume":"36","author":"N He","year":"2015","unstructured":"He N, Ling H, Ding B, Huang J, Zhang Y, Zhang Z, et al. Region-specific disturbed iron distribution in early idiopathic Parkinson\u2019s disease measured by quantitative susceptibility mapping. Hum Brain Mapp. 2015;36:4407\u201320.","journal-title":"Hum Brain Mapp"},{"key":"1858_CR41","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1016\/j.nicl.2018.07.028","volume":"20","author":"DTH Li","year":"2018","unstructured":"Li DTH, Hui ES, Chan Q, Yao N, Chua SE, McAlonan GM, et al. Quantitative susceptibility mapping as an indicator of subcortical and limbic iron abnormality in Parkinson\u2019s disease with dementia. NeuroImage Clin. 2018;20:365\u201373.","journal-title":"NeuroImage Clin"},{"key":"1858_CR42","first-page":"379","volume":"43","author":"A Sakurama","year":"2025","unstructured":"Sakurama A, Fushimi Y, Nakajima S, Sakata A, Okuchi S, Yamamoto T, et al. Comparison study of quantitative susceptibility mapping with GRAPPA and wave-CAIPI: reproducibility, consistency, and microbleeds detection. Jpn J Radiol. 2025;43:379\u201388.","journal-title":"Jpn J Radiol"}],"container-title":["Japanese Journal of Radiology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11604-025-01858-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11604-025-01858-7","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11604-025-01858-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,5]],"date-time":"2026-01-05T07:02:21Z","timestamp":1767596541000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11604-025-01858-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,18]]},"references-count":42,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["1858"],"URL":"https:\/\/doi.org\/10.1007\/s11604-025-01858-7","relation":{},"ISSN":["1867-1071","1867-108X"],"issn-type":[{"value":"1867-1071","type":"print"},{"value":"1867-108X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,18]]},"assertion":[{"value":"8 April 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 August 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 August 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":"Kiarash Ghassaban and Sean K. Sethi are employees of SpinTech MRI, United States.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}