[¹⁸F]FDG-PET zur Differenzialdiagnostik und Prognostik der neurodegenerativen Parkinson-Syndrome: Update 2022

Zusammenfassung

Die Positronenemissionstomografie (PET) mit [¹⁸F]Fluordesoxyglukose ([¹⁸F]FDG) ist eine etablierte bildgebende Methode zur Diagnostik der neurodegenerativen Parkinson-Syndrome. In der vorliegenden Arbeit geben wir nach einer Einführung in den klinisch-neurologischen Kontext eine aktualisierte Übersicht über die mittlerweile sehr umfangreiche Evidenz (u.a. basierend auf post mortem Studien und aktuellen Metaanalysen), dass die [¹⁸F]FDG-PET erkrankungsspezifische Muster des zerebralen Glukosestoffwechsels bei den einzelnen Parkinson-Syndromen abbilden und damit einen über die klinische Diagnose hinausgehenden differenzialdiagnostischen Beitrag liefern kann. Dies betrifft sowohl die Abgrenzung des idiopathischen Parkinson-Syndroms (IPS) von den atypischen Parkinson-Syndromen (APS), als auch die Trennung der APS untereinander. Ferner fassen wir die aktuelle Studienlage zur Wertigkeit der [¹⁸F]FDG-PET zur Prognose der Entwicklung einer Demenz beim IPS zusammen. Hierbei gehen wir jeweils auch auf den Beitrag konkurrierender bildgebender Verfahren ein. Abschließend diskutieren wir jüngste technische Entwicklungen und die Kosteneffektivität der [¹⁸F]FDG-PET am Beispiel der Abklärung zur Tiefen-Hirnstimulation.

Abstract

Positron emission tomography (PET) with [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG) is an established imaging method for the diagnosis of neurodegenerative Parkinsonian syndromes. After an introduction of the clinical-neurological context, the present review gives an updated overview of current extensive evidence (among others based on post mortem studies and metaanalyses) that [¹⁸F]FDG-PET can depict disease-specific patterns of cerebral glucose metabolism in Parkinsonian syndromes and, thus, contribute to their differential diagnosis beyond clinical ratings. This does not only entail the distinction between Parkinson’s disease (PD) and atypical Parkinsonian Syndromes (APS) but also the differentiation among the APS. In addition, we summarize current studies addressing the value of [¹⁸F]FDG-PET for predicting the development of dementia in PD. We also report the merits of competing imaging methods. Finally, we discuss recent methodological developments and the cost effectiveness of [¹⁸F]FDG-PET with exemplary reference to the screening for deep brain stimulation.

Schlüsselwörter

Parkinson-Syndrom - PD - MSA - PSP - CBD - PET - zerebraler Glukosemetabolismus

Keywords

Parkinsonian syndrome - PD - MSA - PSP - CBD - PET - cerebral glucose metabolism

Publication History

Article published online:
02 December 2022

• Literatur

• 1 Meyer P, Hellwig S, Amtage F. Differenzialdiagnostik des neurodegenerativen Parkinson-Syndroms mit nuklearmedizinischen Verfahren. Der Nuklearmediziner 2012; 35: 109-123
• 2 Meyer PT, Frings L, Hellwig S. Nuklearmedizinische Differenzialdiagnostik der Parkinson-Syndrome: Update 2016. Der Nuklearmediziner 2016; 39: 245-258
• 3 Lippa CF, Duda JE, Grossman M. et al. DLB and PDD boundary issues: diagnosis, treatment, molecular pathology, and biomarkers. Neurology 2007; 68: 812-9 DOI: 10.1212/01.wnl.0000256715.13907.d3. (PMID: 17353469)
• 4 Hellwig S, Frings L, Amtage F. et al. 18F-FDG PET Is an Early Predictor of Overall Survival in Suspected Atypical Parkinsonism. J Nucl Med 2015; 56: 1541-6 DOI: 10.2967/jnumed.115.159822. (PMID: 26229141)
• 5 Dams J, Siebert U, Bornschein B. et al. Cost-effectiveness of deep brain stimulation in patients with Parkinson's disease. Movement Disorders 2013; 28: 763-771 DOI: 10.1002/mds.25407. (PMID: 23576266)
• 6 Walter E, Odin P. Cost-effectiveness of continuous subcutaneous apomorphine in the treatment of Parkinson’s disease in the UK and Germany. Journal of Medical Economics 2015; 18: 155-165 DOI: 10.3111/13696998.2015.1074079. (PMID: 26212480)
• 7 Meissner WG, Laurencin C, Tranchant C. et al. Outcome of deep brain stimulation in slowly progressive multiple system atrophy: A clinico-pathological series and review of the literature. Parkinsonism & Related Disorders 2016; 24: 69-75 DOI: 10.1016/j.parkreldis.2016.01.005. (PMID: 26778473)
• 8 Scelzo E, Lozano AM, Hamani C. et al. Peduncolopontine nucleus stimulation in progressive supranuclear palsy: a randomised trial. Journal of Neurology, Neurosurgery & Psychiatry 2017; 88: 613-616 DOI: 10.1136/jnnp-2016-315192. (PMID: 28214797)
• 9 Rizzo G, Copetti M, Arcuti S. et al. Accuracy of clinical diagnosis of Parkinson disease. Neurology 2016; 86: 566-576 DOI: 10.1212/WNL.0000000000002876. (PMID: 27402941)
• 10 Ling H, O'Sullivan SS, Holton JL. et al. Does corticobasal degeneration exist? A clinicopathological re-evaluation. Brain 2010; 133: 2045-57 DOI: 10.1093/brain/awq123. (PMID: 20584946)
• 11 Aarsland D, Kurz MW. The epidemiology of dementia associated with Parkinson disease. Journal of the Neurological Sciences 2010; 289: 18-22 DOI: 10.1016/j.jns.2009.08.034. (PMID: 19733364)
• 12 Buter TC, Van Den Hout A, Matthews FE. et al. Dementia and survival in Parkinson disease: A 12-year population study. Neurology 2008; 70: 1017-1022 DOI: 10.1212/01.wnl.0000306632.43729.24. (PMID: 18362281)
• 13 Reid WGJ, Hely MA, Morris JGL. et al. Dementia in Parkinson's disease: a 20-year neuropsychological study (Sydney Multicentre Study). Journal of Neurology, Neurosurgery & Psychiatry 2011; 82: 1033-1037
• 14 Emre M, Aarsland D, Brown R. et al. Clinical diagnostic criteria for dementia associated with Parkinson's disease. Movement Disorders 2007; 22: 1689-1707 DOI: 10.1002/mds.21507. (PMID: 17542011)
• 15 Litvan I, Goldman JG, Troster AI. et al. Diagnostic criteria for mild cognitive impairment in Parkinson's disease: Movement Disorder Society Task Force guidelines. Mov Disord 2012; 27: 349-56 DOI: 10.1002/mds.24893. (PMID: 22275317)
• 16 Hoogland J, Boel JA, Bie RMA. et al. Risk of Parkinson's disease dementia related to level I MDS PD-MCI. Movement Disorders 2019; 34: 430-435 DOI: 10.1002/mds.27617. (PMID: 30653248)
• 17 Janvin CC, Larsen JP, Aarsland D. et al. Subtypes of mild cognitive impairment in parkinson's disease: Progression to dementia. Movement Disorders 2006; 21: 1343-1349 DOI: 10.1002/mds.20974. (PMID: 16721732)
• 18 Pedersen KF, Larsen JP, Tysnes O-B. et al. Natural course of mild cognitive impairment in Parkinson disease. Neurology 2017; 88: 767-774 DOI: 10.1212/WNL.0000000000003634. (PMID: 28108638)
• 19 Petersen RC. Mild Cognitive Impairment. CONTINUUM: Lifelong Learning in Neurology 2016; 22: 404-418 DOI: 10.1212/WNL.0000000000200387. (PMID: 35314499)
• 20 Lawson RA, Yarnall AJ, Duncan GW. et al. Stability of mild cognitive impairment in newly diagnosed Parkinson's disease. Journal of Neurology, Neurosurgery & Psychiatry 2017; 88: 648-652 DOI: 10.1136/jnnp-2016-315099. (PMID: 28250029)
• 21 Borson S, Frank L, Bayley PJ. et al. Improving dementia care: The role of screening and detection of cognitive impairment. Alzheimer's & Dementia 2013; 9: 151-159 DOI: 10.1016/j.jalz.2012.08.008. (PMID: 23375564)
• 22 Lawson RA, Yarnall AJ, Duncan GW. et al. Cognitive decline and quality of life in incident Parkinson's disease: The role of attention. Parkinsonism & Related Disorders 2016; 27: 47-53 DOI: 10.1016/j.parkreldis.2016.04.009. (PMID: 27094482)
• 23 Grill WM. Safety considerations for deep brain stimulation: review and analysis. Expert Review of Medical Devices 2005; 2: 409-420 DOI: 10.1586/17434440.2.4.409. (PMID: 16293080)
• 24 Gilman S, Wenning GK, Low PA. et al. Second consensus statement on the diagnosis of multiple system atrophy. Neurology 2008; 71: 670-676 DOI: 10.1212/01.wnl.0000324625.00404.15. (PMID: 18725592)
• 25 Hoglinger GU, Respondek G, Stamelou M. et al. Clinical diagnosis of progressive supranuclear palsy: The movement disorder society criteria. Mov Disord 2017; 32: 853-864 DOI: 10.1002/mds.26987. (PMID: 28467028)
• 26 Scheffels JF, Fröhlich L, Kalbe E. et al. Concordance of Mini-Mental State Examination, Montreal Cognitive Assessment and Parkinson Neuropsychometric Dementia Assessment in the classification of cognitive performance in Parkinson's disease. J Neurol Sci 2020; 412: 116735 DOI: 10.1016/j.jns.2020.116735. (PMID: 32087430)
• 27 Nobili F, Arbizu J, Bouwman F. et al. European Association of Nuclear Medicine and European Academy of Neurology recommendations for the use of brain [18]F-fluorodeoxyglucose positron emission tomography in neurodegenerative cognitive impairment and dementia. European Journal of Neurology 2018; 25: 1201-1217 DOI: 10.1111/ene.13728. (PMID: 29932266)
• 28 Meyer PT, Frings L, Rucker G. et al. (18)F-FDG PET in Parkinsonism: Differential Diagnosis and Evaluation of Cognitive Impairment. J Nucl Med 2017; 58: 1888-1898 DOI: 10.2967/jnumed.116.186403. (PMID: 28912150)
• 29 Tang CC, Poston KL, Eckert T. et al. Differential diagnosis of parkinsonism: a metabolic imaging study using pattern analysis. The Lancet Neurology 2010; 9: 149-158 DOI: 10.1016/S1474-4422(10)70002-8. (PMID: 20061183)
• 30 Zalewski N, Botha H, Whitwell JL. et al. FDG-PET in pathologically confirmed spontaneous 4R-tauopathy variants. Journal of Neurology 2014; 261: 710-716 DOI: 10.1007/s00415-014-7256-4. (PMID: 24492888)
• 31 Sha SJ, Ghosh PM, Lee SE. et al. Predicting amyloid status in corticobasal syndrome using modified clinical criteria, magnetic resonance imaging and fluorodeoxyglucose positron emission tomography. Alzheimer's Research & Therapy 2015; 7: 8 DOI: 10.1007/978-1-4939-9488-5_14. (PMID: 31127555)
• 32 Niethammer M, Tang CC, Feigin A. et al. A disease-specific metabolic brain network associated with corticobasal degeneration. Brain 2014; 137: 3036-46 DOI: 10.1093/brain/awu256. (PMID: 25208922)
• 33 Schindlbeck KA, Gupta DK, Tang CC. et al. Neuropathological correlation supports automated image-based differential diagnosis in parkinsonism. European Journal of Nuclear Medicine and Molecular Imaging 2021; 48: 3522-3529 DOI: 10.1007/s00259-021-05302-6. (PMID: 33839891)
• 34 Wadia PM, Lang AE. The many faces of corticobasal degeneration. Parkinsonism Relat Disord 2007; 13: S336-S340 DOI: 10.1016/S1353-8020(08)70027-0. (PMID: 18267261)
• 35 Pardini M, Huey ED, Spina S. et al. FDG-PET patterns associated with underlying pathology in corticobasal syndrome. Neurology 2019; 92: e1121-e1135 DOI: 10.1212/WNL.0000000000007038. (PMID: 30700592)
• 36 Parmera JB, Coutinho AM, Aranha MR. et al. FDG-PET Patterns Predict Amyloid Deposition and Clinical Profile in Corticobasal Syndrome. Movement Disorders 2021; 36: 651-661 DOI: 10.1002/mds.28373. (PMID: 33206389)
• 37 Gu SC, Ye Q, Yuan CX. Metabolic pattern analysis of 18F-FDG PET as a marker for Parkinson's disease: a systematic review and meta-analysis. Rev Neurosci 2019; DOI: 10.1515/revneuro-2018-0061. (PMID: 31050657)
• 38 Papathoma P-E, Markaki I, Tang C. et al. A replication study, systematic review and meta-analysis of automated image-based diagnosis in parkinsonism. Scientific Reports 2022; 12 DOI: 10.1038/s41598-022-06663-0. (PMID: 35177751)
• 39 Vlaar AM, van Kroonenburgh MJ, Kessels AG. et al. Meta-analysis of the literature on diagnostic accuracy of SPECT in parkinsonian syndromes. BMC Neurol 2007; 7: 27 DOI: 10.1186/1471-2377-7-27. (PMID: 17764571)
• 40 Hellwig S, Amtage F, Kreft A. et al. [(1)(8)F]FDG-PET is superior to [(1)(2)(3)I]IBZM-SPECT for the differential diagnosis of parkinsonism. Neurology 2012; 79: 1314-1322 DOI: 10.1212/WNL.0b013e31826c1b0a. (PMID: 22914831)
• 41 Braune S. The role of cardiac metaiodobenzylguanidine uptake in the differential diagnosis of parkinsonian syndromes. Clin Auton Res 2001; 11: 351-355 DOI: 10.1007/BF02292766. (PMID: 11794715)
• 42 Treglia G, Stefanelli A, Cason E. et al. Diagnostic performance of iodine-123-metaiodobenzylguanidine scintigraphy in differential diagnosis between Parkinson's disease and multiple-system atrophy: A systematic review and a meta-analysis. Clinical Neurology and Neurosurgery 2011; 113: 823-829
• 43 Orimo S, Suzuki M, Inaba A. et al. 123I-MIBG myocardial scintigraphy for differentiating Parkinson's disease from other neurodegenerative parkinsonism: a systematic review and meta-analysis. Parkinsonism Relat Disord 2012; 18: 494-500 DOI: 10.1016/j.parkreldis.2012.01.009. (PMID: 22321865)
• 44 Brumberg J, Schröter N, Blazhenets G. et al. Differential diagnosis of parkinsonism: a head-to-head comparison of FDG PET and MIBG scintigraphy. npj Parkinson's Disease 2020; 6 DOI: 10.1038/s41531-020-00141-y. (PMID: 33311476)
• 45 Zhang K, Liang Z, Wang C. et al. Diagnostic validity of magnetic resonance parkinsonism index in differentiating patients with progressive supranuclear palsy from patients with Parkinson's disease. Parkinsonism Relat Disord 2019; 66: 176-181 DOI: 10.1016/j.parkreldis.2019.08.007. (PMID: 31420309)
• 46 Kim S, Suh CH, Shim WH. et al. Diagnostic Performance of the Magnetic Resonance Parkinsonism Index in Differentiating Progressive Supranuclear Palsy from Parkinson’s Disease: An Updated Systematic Review and Meta-Analysis. Diagnostics 2021; 12: 12 DOI: 10.3390/diagnostics12010012. (PMID: 35054178)
• 47 Bajaj S, Krismer F, Palma J-A. et al. Diffusion-weighted MRI distinguishes Parkinson disease from the parkinsonian variant of multiple system atrophy: A systematic review and meta-analysis. PLOS ONE 2017; 12: e0189897 DOI: 10.1371/journal.pone.0189897. (PMID: 29287113)
• 48 Lim SJ, Suh CH, Shim WH. et al. Diagnostic performance of T2* gradient echo, susceptibility-weighted imaging, and quantitative susceptibility mapping for patients with multiple system atrophy–parkinsonian type: a systematic review and meta-analysis. European Radiology 2022; 32: 308-318 DOI: 10.1007/s00330-021-08174-4. (PMID: 34272590)
• 49 Baudrexel S, Seifried C, Penndorf B. et al. The value of putaminal diffusion imaging versus 18-fluorodeoxyglucose positron emission tomography for the differential diagnosis of the Parkinson variant of multiple system atrophy. Mov Disord 2014; 29: 380-387 DOI: 10.1002/mds.25749. (PMID: 24243813)
• 50 Kwon KY, Choi CG, Kim JS. et al. Diagnostic value of brain MRI and 18F-FDG PET in the differentiation of Parkinsonian-type multiple system atrophy from Parkinson's disease. Eur J Neurol 2008; 15: 1043-1049 DOI: 10.1111/j.1468-1331.2008.02235.x. (PMID: 18717730)
• 51 Kwon K-Y, Choi CG, Kim JS. et al. Comparison of brain MRI and 18F-FDG PET in the differential diagnosis of multiple system atrophy from Parkinson's disease. Movement Disorders 2007; 22: 2352-2358 DOI: 10.1002/mds.21714. (PMID: 17894342)
• 52 Vlaar AM, Bouwmans A, Mess WH. et al. Transcranial duplex in the differential diagnosis of parkinsonian syndromes: a systematic review. J Neurol 2009; 256: 530-538 DOI: 10.1007/s00415-009-0143-8. (PMID: 19224315)
• 53 Richter D, Katsanos AH, Schroeder C. et al. Lentiform Nucleus Hyperechogenicity in Parkinsonian Syndromes: A Systematic Review and Meta-Analysis with Consideration of Molecular Pathology. Cells 2019; 9: 2 DOI: 10.3390/cells9010002. (PMID: 31861253)
• 54 Cong S, Xiang C, Wang H. et al. Diagnostic utility of fluid biomarkers in multiple system atrophy: a systematic review and meta-analysis. Journal of Neurology 2021; 268: 2703-2712 DOI: 10.1007/s00415-020-09781-9. (PMID: 32162061)
• 55 Tonges L, Buhmann C, Klebe S. et al. Blood-based biomarker in Parkinson's disease: potential for future applications in clinical research and practice. J Neural Transm (Vienna) 2022; DOI: 10.1007/s00702-022-02498-1. (PMID: 35428925)
• 56 Lee W. Conventional Magnetic Resonance Imaging in the Diagnosis of Parkinsonian Disorders: A Meta-Analysis. Movement Disorders Clinical Practice 2021; 8: 217-223 DOI: 10.1002/mdc3.13070. (PMID: 33553491)
• 57 Heim B, Krismer F, Seppi K. Differentiating PSP from MSA using MR planimetric measurements: a systematic review and meta-analysis. Journal of Neural Transmission 2021; 128: 1497-1505 DOI: 10.1007/s00702-021-02362-8. (PMID: 34105000)
• 58 Garcia-Garcia D, Clavero P, Gasca Salas C. et al. Posterior parietooccipital hypometabolism may differentiate mild cognitive impairment from dementia in Parkinson’s disease. European Journal of Nuclear Medicine and Molecular Imaging 2012; 39: 1767-1777 DOI: 10.1007/s00259-012-2198-5. (PMID: 22872307)
• 59 Meyer PT, Frings L, Hellwig S. Update on SPECT and PET in parkinsonism - part 2: biomarker imaging of cognitive impairment in Lewy-body diseases. Curr Opin Neurol 2014; 27: 398-404 DOI: 10.1097/WCO.0000000000000107. (PMID: 24978635)
• 60 Firbank MJ, Yarnall AJ, Lawson RA. et al. Cerebral glucose metabolism and cognition in newly diagnosed Parkinson's disease: ICICLE-PD study. Journal of Neurology, Neurosurgery & Psychiatry 2017; 88: 310-316
• 61 Gonzalez-Redondo R, Garcia-Garcia D, Clavero P. et al. Grey matter hypometabolism and atrophy in Parkinson's disease with cognitive impairment: a two-step process. Brain 2014; 137: 2356-2367 DOI: 10.1093/brain/awu159. (PMID: 24951642)
• 62 Bohnen NI, Koeppe RA, Minoshima S. et al. Cerebral glucose metabolic features of Parkinson disease and incident dementia: longitudinal study. J Nucl Med 2011; 52: 848-855 DOI: 10.2967/jnumed.111.089946. (PMID: 21571793)
• 63 Baba T, Kikuchi A, Hirayama K. et al. Severe olfactory dysfunction is a prodromal symptom of dementia associated with Parkinson's disease: a 3 year longitudinal study. Brain 2012; 135: 161-169 DOI: 10.1093/brain/awr321. (PMID: 22287381)
• 64 Baba T, Hosokai Y, Nishio Y. et al. Longitudinal study of cognitive and cerebral metabolic changes in Parkinson's disease. J Neurol Sci 2017; 372: 288-293 DOI: 10.1016/j.jns.2016.11.068. (PMID: 28017230)
• 65 Tard C, Demailly F, Delval A. et al. Hypometabolism in Posterior and Temporal Areas of the Brain is Associated with Cognitive Decline in Parkinson's Disease. J Parkinsons Dis 2015; 5: 569-74 DOI: 10.3233/JPD-150583. (PMID: 26406137)
• 66 Gasca-Salas C, Clavero P, García-García D. et al. Significance of visual hallucinations and cerebral hypometabolism in the risk of dementia in Parkinson's disease patients with mild cognitive impairment. Human Brain Mapping 2016; 37: 968-977 DOI: 10.1002/hbm.23080. (PMID: 26663702)
• 67 Pilotto A, Premi E, Paola Caminiti S. et al. Single-subject SPM FDG-PET patterns predict risk of dementia progression in Parkinson disease. Neurology 2018; 90: e1029-e1037 DOI: 10.1212/WNL.0000000000005161. (PMID: 29453242)
• 68 Arslan DB, Gurvit H, Genc O. et al. The cerebral blood flow deficits in Parkinson’s disease with mild cognitive impairment using arterial spin labeling MRI. Journal of Neural Transmission 2020; 127: 1285-1294 DOI: 10.1007/s00702-020-02227-6. (PMID: 32632889)
• 69 Shibata H, Uchida Y, Inui S. et al. Machine learning trained with quantitative susceptibility mapping to detect mild cognitive impairment in Parkinson's disease. Parkinsonism & Related Disorders 2022; 94: 104-110 DOI: 10.1016/j.parkreldis.2021.12.004. (PMID: 34906915)
• 70 Buchert R, Krüger J, Gessert N. et al. Deep Learning in SPECT und PET des Gehirns. Der Nuklearmediziner 2019; 42: 118-132
• 71 Wu P, Zhao Y, Wu J. et al. Differential diagnosis of parkinsonism based on deep metabolic imaging indices. Journal of Nuclear Medicine 2022; DOI: 10.2967/jnumed.121.263029. (PMID: 35241481)
• 72 Hu X, Sun X, Hu F. et al. Multivariate radiomics models based on 18F-FDG hybrid PET/MRI for distinguishing between Parkinson’s disease and multiple system atrophy. European Journal of Nuclear Medicine and Molecular Imaging 2021; 48: 3469-3481 DOI: 10.1007/s00259-021-05325-z. (PMID: 33829415)
• 73 Oh M, Lee N, Kim C. et al. Diagnostic accuracy of dual-phase 18F-FP-CIT PET imaging for detection and differential diagnosis of Parkinsonism. Scientific Reports 2021; 11 DOI: 10.1038/s41598-021-94040-8. (PMID: 34294739)
• 74 Peng S, Tang C, Schindlbeck K. et al. Dynamic ¹⁸F-FPCIT PET: Quantification of Parkinson Disease Metabolic Networks and Nigrostriatal Dopaminergic Dysfunction in a Single Imaging Session. Journal of Nuclear Medicine 2021; 62: 1775-1782
• 75 Speck I, Arndt S, Thurow J. et al. 18F-FDG PET Imaging of the Inferior Colliculus in Asymmetric Hearing Loss. Journal of Nuclear Medicine 2020; 61: 418-422 DOI: 10.2967/jnumed.119.231407. (PMID: 31481576)
• 76 Ozden C, Frings L, Apostolova I. et al. FDG Uptake in the Basal Forebrain as Measured by Digital High-Resolution PET Is a Promising Marker of Basal Forebrain Degeneration in the Lewy Body Disease Spectrum: A Pilot Study. Clin Nucl Med 2020; 45: 261-266 DOI: 10.1097/RLU.0000000000002960. (PMID: 32108697)
• 77 Schröter N, Blazhenets G, Frings L. et al. Nigral glucose metabolism as a diagnostic marker of neurodegenerative parkinsonian syndromes. npj Parkinson‘s Disease, in press..