OBJECTIVE: To apply a machine learning analysis to clinical and presynaptic dopaminergic imaging data of patients with rapid eye movement (REM) sleep behavior disorder (RBD) to predict the development of Parkinson disease (PD) and dementia with Lewy bodies (DLB). METHODS: In this multicenter study of the International RBD study group, 173 patients (mean age 70.5 ± 6.3 years, 70.5% males) with polysomnography-confirmed RBD who eventually phenoconverted to overt alpha-synucleinopathy (RBD due to synucleinopathy) were enrolled, and underwent baseline presynaptic dopaminergic imaging and clinical assessment, including motor, cognitive, olfaction, and constipation evaluation. For comparison, 232 RBD non-phenoconvertor patients (67.6 ± 7.1 years, 78.4% males) and 160 controls (68.2 ± 7.2 years, 53.1% males) were enrolled. Imaging and clinical features were analyzed by machine learning to determine predictors of phenoconversion. RESULTS: Machine learning analysis showed that clinical data alone poorly predicted phenoconversion. Presynaptic dopaminergic imaging significantly improved the prediction, especially in combination with clinical data, with 77% sensitivity and 85% specificity in differentiating RBD due to synucleinopathy from non phenoconverted RBD patients, and 85% sensitivity and 86% specificity in discriminating PD-converters from DLB-converters. Quantification of presynaptic dopaminergic imaging showed that an empirical z-score cutoff of -1.0 at the most affected hemisphere putamen characterized RBD due to synucleinopathy patients, while a cutoff of -1.0 at the most affected hemisphere putamen/caudate ratio characterized PD-converters. INTERPRETATION: Clinical data alone poorly predicted phenoconversion in RBD due to synucleinopathy patients. Conversely, presynaptic dopaminergic imaging allows a good prediction of forthcoming phenoconversion diagnosis. This finding may be used in designing future disease-modifying trials. ANN NEUROL 2024;95:1178-1192.

Center of Sleep Medicine Dokkyo Medical University Hospital Tochigi Japan

Clinic of Sleep and Chronomedicine St Hedwig Hospital Berlin Germany

Department of Biomedical Metabolic and Neural Sciences University of Modena and Reggio Emilia Modena Italy

Department of Biomedicine and Prevention University of Rome Tor Vergata Rome Italy

Department of Brain and Behavioral Sciences University of Pavia Pavia Italy

Department of Business and Management LUISS University Rome Italy

Department of Environment and Health Istituto Superiore di Sanità Rome Italy

Department of Neurology and Center of Clinical Neuroscience 1st Faculty of Medicine Charles University and General University Hospital Prague Czech Republic

Department of Neurology Dokkyo Medical University Saitama Medical Center Saitama Japan

Department of Neurology Mayo Clinic Rochester Minnesota USA

Department of Neurology P J Safarik University Kosice Slovak Republic

Department of Neurology University Hospital of L Pasteur Kosice Slovak Republic

Department of Neuroscience University of Genoa Genoa Italy

Department of Neurosciences Biomedicine and Movement Sciences University of Verona Verona Italy

Department of Radiology Mayo Clinic Rochester Minnesota USA

Department of Systems Medicine University of Rome Tor Vergata Rome Italy

Division of Neurology Nuffield Department of Clinical Neurosciences Oxford University Oxford UK

EuroMov Digital Health in Motion Univ Montpellier IMT Mines Ales Montpellier France

Institute of Cognitive Sciences and Technologies Consiglio Nazionale delle Ricerche Rome Italy

Institute of Nuclear Medicine 1st Faculty of Medicine Charles University and General University Hospital Prague Czech Republic

Institute of Physiology Sleep Research and Clinical Chronobiology Charité Universitätsmedizin Berlin Berlin Germany

IRCCS Istituto delle Scienze Neurologiche di Bologna Bologna Italy

IRCCS Neuromed Pozzilli Italy

IRCCS Ospedale Policlinico San Martino Genoa Italy

Neurology Service Sleep Disorder Centre Hospital Clínic Barcelona Universitat de Barcelona IDIBAPS CIBERNED CB06 05 0018 ISCIII Barcelona Spain

Nuclear Medicine Service Hospital Clínic Barcelona Biomedical Research Networking Centre of Bioengineering Biomaterials and Nanomedicine ISCIII Barcelona Spain

Nuclear Medicine Unit Department of Medical Science and Public Health University of Cagliari Cagliari Italy

Nuclear Medicine Unit Department of Medical Sciences University of Turin Turin Italy

Nuclear Medicine Unit ICS Maugeri SpA SB IRCCS Pavia Italy

Nuclear Medicine Unit University Hospital of Montpellier Montpellier France

Sleep and Neurology Department Beau Soleil Clinic Montpellier France

Sleep Disorder Center Department of Public Health and Clinical and Molecular Medicine University of Cagliari Cagliari Italy

Sleep Medicine and Epilepsy Unit IRCCS Mondino Foundation Pavia Italy

Sleep Medicine Center Neurology Unit University Hospital of Rome Tor Vergata Rome Italy

Zobrazit více v PubMed

Postuma RB, Iranzo A, Hu M, et al. Risk and predictors of dementia and parkinsonism in idiopathic REM sleep behaviour disorder: a multicentre study. Brain. 2019. Mar 1;142(3):744–59. PubMed PMC

Doppler K, Antelmi E, Kuzkina A, et al. Consistent skin α-synuclein positivity in REM sleep behavior disorder - A two center two-to-four-year follow-up study. Parkinsonism Relat Disord. 2021. May;86:108–13. PubMed

Iranzo A, Fairfoul G, Ayudhaya ACN, et al. Detection of α-synuclein in CSF by RT-QuIC in patients with isolated rapid-eye-movement sleep behaviour disorder: a longitudinal observational study. Lancet Neurol. 2021. Mar;20(3):203–12. PubMed

Galbiati A, Verga L, Giora E, Zucconi M, Ferini-Strambi L. The risk of neurodegeneration in REM sleep behavior disorder: A systematic review and meta-analysis of longitudinal studies. Sleep Med Rev. 2019. Feb;43:37–46. PubMed

Hoglinger GU, Adler CH, Berg D, et al. A biological classification of Parkinson’s disease: the SynNeurGe research diagnostic criteria. Lancet Neurol. 2024. Feb;23(2):191–204. PubMed

Simuni T, Chahine LM, Poston K, et al. A biological definition of neuronal alpha-synuclein disease: towards an integrated staging system for research. Lancet Neurol. 2024. Feb;23(2):178–90. PubMed

Lang AE, Siderowf AD, Macklin EA, et al. Trial of Cinpanemab in Early Parkinson’s Disease. N Engl J Med. 2022. Aug 4;387(5):408–20. PubMed

Pagano G, Taylor KI, Anzures-Cabrera J, et al. Trial of Prasinezumab in Early-Stage Parkinson’s Disease. N Engl J Med. 2022. Aug 4;387(5):421–32. PubMed

Arnaldi D, Fama F, Girtler N, et al. Rapid eye movement sleep behavior disorder: A proof-of-concept neuroprotection study for prodromal synucleinopathies. Eur J Neurol. 2021. Apr;28(4):1210–7. PubMed

Miglis MG, Adler CH, Antelmi E, et al. Biomarkers of conversion to α-synucleinopathy in isolated rapid-eye-movement sleep behaviour disorder. Lancet Neurol. 2021. Aug;20(8):671–84. PubMed PMC

Iranzo A, Santamaria J, Valldeoriola F, et al. Dopamine transporter imaging deficit predicts early transition to synucleinopathy in idiopathic REM sleep behavior disorder. Ann Neurol. 2017. Aug 22;82(3):419–28. PubMed

Arnaldi D, Chincarini A, Hu MT, et al. Dopaminergic imaging and clinical predictors for phenoconversion of REM sleep behaviour disorder. Brain. 2021. Feb 12;144(1):278–87. PubMed PMC

AASM. International Classification of Sleep Disorders, 3rd ed. Darien, IL: American Academy of Sleep Medicine; 2014.

Postuma RB, Berg D, Stern M, et al. MDS clinical diagnostic criteria for Parkinson’s disease. Mov Disord. 2015. Oct;30(12):1591–601. PubMed

American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. 5th ed. Washington, DC2013.

Gilman S, Wenning GK, Low PA, et al. Second consensus statement on the diagnosis of multiple system atrophy. Neurology. 2008. Aug 26;71(9):670–6. PubMed PMC

McKeith IG, Boeve BF, Dickson DW, et al. Diagnosis and management of dementia with Lewy bodies: Fourth consensus report of the DLB Consortium. Neurology. 2017. Jul 4;89(1):88–100. PubMed PMC

Darcourt J, Booij J, Tatsch K, et al. EANM procedure guidelines for brain neurotransmission SPECT using (123)I-labelled dopamine transporter ligands, version 2. Eur J Nucl Med Mol Imaging. 2010. Feb;37(2):443–50. PubMed

Morbelli S, Esposito G, Arbizu J, et al. EANM practice guideline/SNMMI procedure standard for dopaminergic imaging in Parkinsonian syndromes 1.0. Eur J Nucl Med Mol Imaging. 2020. Jul;47(8):1885–912. PubMed PMC

Neill M, Fisher JM, Brand C, et al. Practical Application of DaTQUANT with Optimal Threshold for Diagnostic Accuracy of Dopamine Transporter SPECT. Tomography (Ann Arbor, Mich). 2021. Dec 18;7(4):980–9. PubMed PMC

Maltais DD, Jordan LG, 3rd, Min HK, et al. Confirmation of (123)I-FP-CIT-SPECT (ioflupane) quantification methods in dementia with Lewy body and other neurodegenerative disorders. Journal of nuclear medicine : official publication, Society of Nuclear Medicine. 2020. Mar 20. PubMed PMC

Lanfranchi F, Arnaldi D, Miceli A, et al. Different z-score cut-offs for striatal binding ratio (SBR) of DaT SPECT are needed to support the diagnosis of Parkinson’s Disease (PD) and dementia with Lewy bodies (DLB). Eur J Nucl Med Mol Imaging. 2022. Dec 6. PubMed

Goetz CG, Fahn S, Martinez-Martin P, et al. Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS): Process, format, and clinimetric testing plan. Mov Disord. 2007. Jan;22(1):41–7. PubMed

Hentz JG, Mehta SH, Shill HA, Driver-Dunckley E, Beach TG, Adler CH. Simplified conversion method for unified Parkinson’s disease rating scale motor examinations. Mov Disord. 2015;30(14):1967–70. PubMed PMC

Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of psychiatric research. 1975. Nov;12(3):189–98. PubMed

Nasreddine ZS, Phillips NA, Bedirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005. Apr;53(4):695–9. PubMed

van Steenoven I, Aarsland D, Hurtig H, et al. Conversion between mini-mental state examination, montreal cognitive assessment, and dementia rating scale-2 scores in Parkinson’s disease. Mov Disord. 2014. Dec;29(14):1809–15. PubMed PMC

Visser M, Marinus J, Stiggelbout AM, Van Hilten JJ. Assessment of autonomic dysfunction in Parkinson’s disease: the SCOPA-AUT. Mov Disord. 2004. Nov;19(11):1306–12. PubMed

Szewczyk-Krolikowski K, Tomlinson P, Nithi K, et al. The influence of age and gender on motor and non-motor features of early Parkinson’s disease: initial findings from the Oxford Parkinson Disease Center (OPDC) discovery cohort. Parkinsonism Relat Disord. 2014. Jan;20(1):99–105. PubMed

Palsson OS, Whitehead WE, van Tilburg MA, et al. Rome IV Diagnostic Questionnaires and Tables for Investigators and Clinicians. Gastroenterology. 2016. Feb 13. PubMed

Doty RL, Shaman P, Dann M. Development of the University of Pennsylvania Smell Identification Test: a standardized microencapsulated test of olfactory function. Physiol Behav. 1984. Mar;32(3):489–502. PubMed

Hummel T, Sekinger B, Wolf SR, Pauli E, Kobal G. ‘Sniffin’ sticks’: olfactory performance assessed by the combined testing of odor identification, odor discrimination and olfactory threshold. Chem Senses. 1997;22(1):39–52. PubMed

Kobayashi M, Saito S, Kobayakawa T, Deguchi Y, Costanzo RM. Cross-cultural comparison of data using the odor stick identification test for Japanese (OSIT-J). Chem Senses. 2006. May;31(4):335–42. PubMed

Fisher RA. The Use of Multiple Measurements in Taxonomic Problems. Annals of Eugenics. 1936;7:179–88.

Bishop CM. Pattern recognition and machine learning. New York: Springer; 2006.

Breiman L. Classification and Regression Trees (1st ed.): Routledge; 1984.

Cortes C, Vapnik V. Support-vector networks. Machine learning. 1995;20:273–97.

Cover T, Hart P. Nearest neighbor pattern classification. IEEE transactions on information theory. 1967;13(1):21–7.

Lachenbruch PA. McNemar Test. Wiley StatsRef: Statistics Reference Online.

Diaz-Galvan P, Miyagawa T, Przybelski SA, et al. Brain glucose metabolism and nigrostriatal degeneration in isolated rapid eye movement sleep behaviour disorder. Brain Commun. 2023;5(1):fcad021. PubMed PMC

Herz DM, Meder D, Camilleri JA, Eickhoff SB, Siebner HR. Brain Motor Network Changes in Parkinson’s Disease: Evidence from Meta-Analytic Modeling. Mov Disord. 2021. May;36(5):1180–90. PubMed PMC

Ikeda K, Ebina J, Kawabe K, Iwasaki Y. Dopamine Transporter Imaging in Parkinson Disease: Progressive Changes and Therapeutic Modification after Anti-parkinsonian Medications. Intern Med. 2019;58(12):1665–72. PubMed PMC

Iranzo A, Valldeoriola F, Lomena F, et al. Serial dopamine transporter imaging of nigrostriatal function in patients with idiopathic rapid-eye-movement sleep behaviour disorder: a prospective study. Lancet Neurol. 2011. Sep;10(9):797–805. PubMed

Nobili F, Campus C, Arnaldi D, et al. Cognitive-nigrostriatal relationships in de novo, drug-naive Parkinson’s disease patients: a [I-123]FP-CIT SPECT study. Mov Disord. 2010. Jan 15;25(1):35–43. PubMed

Arnaldi D, De Carli F, Picco A, et al. Nigro-caudate dopaminergic deafferentation: a marker of REM sleep behavior disorder? Neurobiol Aging. 2015. Sep;36(12):3300–5. PubMed

Walker Z, Costa DC, Walker RW, et al. Striatal dopamine transporter in dementia with Lewy bodies and Parkinson disease: a comparison. Neurology. 2004. May 11;62(9):1568–72. PubMed

Booij J, Dubroff J, Pryma D, et al. Diagnostic Performance of the Visual Reading of (123)I-Ioflupane SPECT Images With or Without Quantification in Patients With Movement Disorders or Dementia. Journal of nuclear medicine : official publication, Society of Nuclear Medicine. 2017. Nov;58(11):1821–6. PubMed

Zhang H, Iranzo A, Hogl B, et al. Risk Factors for Phenoconversion in Rapid Eye Movement Sleep Behavior Disorder. Ann Neurol. 2022. Mar;91(3):404–16. PubMed

Litvan I, Goldman JG, Troester AI, et al. Diagnostic criteria for mild cognitive impairment in Parkinson’s disease: Movement Disorder Society Task Force guidelines. Mov Disord. 2012. Mar;27(3):349–56. PubMed PMC

McCleery J, Morgan S, Bradley KM, Noel-Storr AH, Ansorge O, Hyde C. Dopamine transporter imaging for the diagnosis of dementia with Lewy bodies. The Cochrane database of systematic reviews. 2015. Jan 30;1(1):Cd010633. PubMed PMC