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Multicenter Study
. 2025 May 1;82(5):495-505.
doi: 10.1001/jamaneurol.2025.0112.

Automated Imaging Differentiation for Parkinsonism

David E Vaillancourt  1   2   3   4 Angelos Barmpoutis  5 Samuel S Wu  6 Jesse C DeSimone  1 Marissa Schauder  1 Robin Chen  4 Todd B Parrish  7   8 Wei-En Wang  1 Eric Molho  9 John C Morgan  10 David K Simon  11   12 Burton L Scott  13 Liana S Rosenthal  14 Stephen N Gomperts  11   15 Rizwan S Akhtar  16 David Grimes  17   18 Sol De Jesus  19 Natividad Stover  20 Ece Bayram  21 Adolfo Ramirez-Zamora  2   3 Stefan Prokop  2   22 Ruogu Fang  4   23 John T Slevin  24 Prabesh Kanel  25   26 Nicolaas I Bohnen  25   27 Paul Tuite  28 Stephen Aradi  29 Antonio P Strafella  30   31 Mustafa S Siddiqui  32 Albert A Davis  33 Xuemei Huang  19 Jill L Ostrem  34 Hubert Fernandez  35 Irene Litvan  21 Robert A Hauser  29 Alexander Pantelyat  14 Nikolaus R McFarland  2   3 Tao Xie  36 Michael S Okun  2   3 AIDP Study GroupAlicia Leader  9 Áine Russell  12 Hannah Babcock  12 Karen White-Tong  13 Jun Hua  37   38 Anna E Goodheart  11   15 Erin Colleen Peterec  11   15 Cynthia Poon  16 Max B Galarce  16 Tanya Thompson  18 Autumn M Collier  19 Candace Cromer  20 Natt Putra  21 Reilly Costello  21 Eda Yilmaz  34 Crystal Mercado  36 Tomas Mercado  36 Amanda Fessenden  3 Renee Wagner  24 C Chauncey Spears  27 Jacqueline L Caswell  25 Marina Bryants  28 Kristyn Kuzianik  29 Youshra Ahmed  29 Nathaniel Bendahan  31 Joy O Njoku  32 Amy Stiebel  33 Hengameh Zahed  39 Sarah S Wang  34 Phuong T Hoang  34 Joseph Seemiller  14 Guangwei Du  19
Affiliations
Multicenter Study

Automated Imaging Differentiation for Parkinsonism

David E Vaillancourt et al. JAMA Neurol. .

Abstract

Importance: Magnetic resonance imaging (MRI) paired with appropriate disease-specific machine learning holds promise for the clinical differentiation of Parkinson disease (PD), multiple system atrophy (MSA) parkinsonian variant, and progressive supranuclear palsy (PSP). A prospective study is needed to test whether the approach meets primary end points to be considered in a diagnostic workup.

Objective: To assess the discriminative performance of Automated Imaging Differentiation for Parkinsonism (AIDP) using 3-T diffusion MRI and support vector machine (SVM) learning.

Design, setting, and participants: This was a prospective, multicenter cohort study conducted from July 2021 to January 2024 across 21 Parkinson Study Group sites (US/Canada). Included were patients with PD, MSA, and PSP with established criteria and unanimous agreement in the clinical diagnosis among 3 independent, blinded neurologists who specialize in movement disorders. Patients were assigned to a training set or an independent testing set.

Exposure: MRI.

Main outcomes and measures: Area under the receiver operating characteristic curve (AUROC) in the testing set for primary model end points of PD vs atypical parkinsonism, MSA vs PSP, PD vs MSA, and PD vs PSP. AIDP was also paired with antemortem MRI to test against postmortem neuropathology in a subset of autopsy cases.

Results: A total of 316 patients were screened and 249 patients (mean [SD] age, 67.8 [7.7] years; 155 male [62.2%]) met inclusion criteria. Of these patients, 99 had PD, 53 had MSA, and 97 had PSP. A retrospective cohort of 396 patients (mean [SD] age, 65.8 [8.9] years; 234 male [59.1%]) was also included. Of these patients, 211 had PD, 98 had MSA, and 87 had PSP. Patients were assigned to the training set (78%; 104 prospective, 396 retrospective) or independent testing set, which included 145 (22%; 60 PD, 27 MSA, 58 PSP) prospective patients (mean age, 67.4 [SD 7.7] years; 95 male [65.5%]). The model was robust in differentiating PD vs atypical parkinsonism (AUROC, 0.96; 95% CI, 0.93-0.99; positive predictive value [PPV], 0.91; negative predictive value [NPV], 0.83), MSA vs PSP (AUROC, 0.98; 95% CI, 0.96-1.00; PPV, 0.98; NPV, 0.81), PD vs MSA (AUROC, 0.98; 95% CI, 0.96-1.00; PPV, 0.97; NPV, 0.97), and PD vs PSP (AUROC, 0.98; 95% CI, 0.96-1.00; PPV, 0.92; NPV, 0.98). AIDP predictions were confirmed neuropathologically in 46 of 49 brains (93.9%).

Conclusions and relevance: This prospective multicenter cohort study of AIDP met its primary end points. Results suggest using AIDP in the diagnostic workup for common parkinsonian syndromes.

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Conflict of interest statement

Conflict of Interest Disclosures: Dr Vaillancourt reported receiving nonfinancial support from Automated Imaging Diagnostics, grants from the National Institutes of Health (NIH), nonfinancial support from Department of Defense, personal fees from Neuroimaging Solutions making MRI-compatible sensors outside the submitted work, and having a patent (11439341) licensed. Dr Barmpoutis reported receiving grants from the NIH and being cofounder and shareholder of Neuropacs Corp outside the submitted work. Dr Wu reported receiving grants from NIH during the conduct of the study. Dr Molho reported receiving grants from Parkinson Study Group paid to Albany Medical Center during the conduct of the study. Dr Morgan reported receiving grants from University of Florida, Cerevance, Cerevel, Intracellular Therapeutics, UCB, Neuraly, and Georgia Memory Net program and consultant/speaker fees from Amneal, Eli Lilly, Eisai, and Kyowa Kirin outside the submitted work. Dr Simon reported serving as an unpaid advisor for Neuropacs and Bial; receiving consultant fees from Fortis Medical Devices, and Mission Therapeutics, and advisory board fees/grants from Weston Brain Institute. Dr Rosenthal reported receiving grants from the National Institute of Neurological Disorders and Stroke (NINDS), Pfizer, EIP Pharma, Functional Neuromdulation, and Biohaven Pharmaceuticals; personal fees and nonfinancial support from Biohaven Pharmaceuticals; and personal fees from UCB Pharmaceuticals, Bial Pharmaceuticals, Reata Pharmaceuticals, and Biogen Pharmaceuticals outside the submitted work. Dr Gomperts reported receiving grants from NIH; personal fees from Acadia, CervoMed, Clearview, Guidepoint Global, WaveBreak, and REACH Market Research and nonfinancial support from Hillhurst outside the submitted work. Dr Grimes reported receiving grants from NIH during the conduct of the study. Dr De Jesus reported receiving grants from Penn State during the conduct of the study. Dr Stover reported receiving grants from University of South Florida during the conduct of the study and working at the University of Alabama at Birmingham, from which she receives salary compensation for clinical treatment to patients as well as doing clinical trials. Dr Bayram reported receiving grants from NIH during the conduct of the study. Dr Kanel reported receiving grants from NIH during the conduct of the study. Dr Bohnen reported receiving grants from NIH, VA, Parkinson’s Foundation, and Farmer Family Foundation and serving as owner of Tulip M3D, an academic start-up, outside the submitted work. Dr Tuite reported receiving grants from University of Minnesota during the conduct of the study. Dr Aradi reported receiving grants from University of Florida, Sage Therapeutics, Hoffmann-La Roche, Prilenia Therapeutics, Huntington Study Group, and Novartis Pharmaceuticals outside the submitted work. Dr Strafella reported receiving grants from University of Florida, Subaward from NIH grant to University of Florida during the conduct of the study. Dr Siddiqui reported receiving grants from University of Florida during the conduct of the study. Dr Davis reported receiving grants from NIH. Dr Huang reported receiving grants from NIH during the conduct of the study. Dr Ostrem reported receiving grants from University of California at San Francisco, Neuroderm, Medtronic, Boston Scientific, Merz, Amneal, Clearpoint, AbbVie, Supernus, Acadia, Parkinsons Foundation and committee member/chair fees from Aspen Neuroscience and Acura X outside the submitted work. Dr Du reported receiving grants from University of Florida during the conduct of the study and having a patent for MRI T1W and T2W combined features for detecting neurodegeneration issued. Dr Fernandez reported receiving grants from Parkinson’s Foundation, Michael J. Fox Foundation, Biogen, and Roche; personal fees from Parkinson Study Group, Neurocrine, AbbVie, and Amneal; and serving as editor in chief receiving a stipend from Elsevier outside the submitted work. Dr Litvan reported receiving grants from Michael J. Fox Foundation, Parkinson’s Foundation, Lewy Body Association, CurePSP, Roche, AbbVie, Lundbeck, EIP-Pharma, Alterity, Novartis, and UCB outside the submitted work. Dr Hauser reported serving on the steering committee for NIH and receiving grants from Global Kinetics, Kyowa, Neuroderm Ltd, Pharma2B, Vivify Biotech, AbbVie, Sage Therapeutics, Ovid Therapeutics, Amneal, Agex Therapeutics, Avanex, BlueRock Therapeutics, MDCE Suzhou, MedRhythms, PD Neurotechnology, RegenXBio, Tremor Research Support Group, Tris Pharma, UCB, Cerevel, Acorda Therapeutics, Jazz Therapeutics, Neurocrine Biosciences, Inhikibase, Supernu, Scion Neurostim, Sunovian, Tolmar, Revance, Merz, Canfield Scientific, Biogen, Forsee Pharmaceuticals, KeifeRx, Mitsubishi Tanabe, Intrance, Zambon, Truebinding, Serina Therapeutics, Nano PharmaSolutions, HanAll BioPharma, AEON Biopharma Inc, Alexza Pharmaceuticals, Annovis Bio Inc, Bukwang Pharmaceuticals, Cavion, Cerevance Beta Inc, Enterin, F. Hoffman-La Roche Ltd, Genentech Inc, MJFF, Neuraly, Sage Therapeutics, Sanofi US Services Inc, UCB Biopharma SRL, National Parkinson Foundation, and Michael J. Fox Foundation outside the submitted work. Dr McFarland reported receiving travels support from NIH during the conduct of the study. Dr Okun reported receiving grants from NIH, Michael J. Fox Foundation, Parkinson’s Foundation, the Parkinson Alliance, the Smallwood Foundation, UF Foundation and Tourette Association of America; serving as medical advisor the Parkinson’s Foundation and multiple principal investigator of the NIH Training Grant; receiving royalties for publications with Hachette Book Group, Demos, Manson, Amazon, Smashwords, Books4Patients, Perseus, Robert Rose, Oxford and Cambridge (movement disorders books); serving as associate editor for New England Journal of Medicine Journal Watch Neurology and JAMA Neurology; participating in CME and educational activities (past 12-24 months) on movement disorders sponsored by WebMD/Medscape, RMEI Medical Education, American Academy of Neurology, Movement Disorders Society, Mediflix, and by Vanderbilt University. The institution and not Dr. Okun receives grants from industry. Research projects at the University of Florida receive device and drug donations. No other disclosures were reported.

Figures

Figure 1.
Figure 1.. Enrollment and Allocation of Patients for Machine Learning
Enrollment and allocation of patients to the training and testing sets for the primary end point model. Patients from the prospective cohort were assigned to training and testing sets using stratified sampling. Patients from the retrospective cohort were used to reinforce the training set and were not used in the independent testing of the model. MSA indicates multiple system atrophy parkinsonian variant; PD, Parkinson disease; PSP, progressive supranuclear palsy.
Figure 2.
Figure 2.. Automated Imaging Differentiation for Parkinsonism (AIDP) for Disease-Specific Classification of Parkinsonism
A, Region of interest (ROI) analysis and feature extraction. Free-water (FW) and FW-corrected fractional anisotropy (FAt) values were calculated from 132 total brain ROIs. B, Support vector machine (SVM) learning. FW and FAt from brain ROIs, age, and sex composed a feature vector for the SVM input. The feature vector was split into a training set and independent testing set. Five-fold cross-validation (CV) was used during training to achieve the best possible discrimination between the positive and negative classes. The area under the receiver operating characteristic curve (AUROC) was obtained in the testing set for each primary end point (Parkinson disease [PD] vs atypical parkinsonism [AP], multiple system atrophy [MSA] parkinsonian variant vs progressive supranuclear palsy [PSP], PD vs MSA, and PD vs PSP). C, Patient predictions with AIDP. Three exemplar participant-level FW maps are shown for PD, MSA, and PSP testing cases. Higher FW levels are shown in blue/white colors. The corresponding disease-specific probability estimates and final AIDP diagnostic predictions are shown. M1 indicates primary motor cortex; SMA, supplementary motor area.
Figure 3.
Figure 3.. Automated Imaging Differentiation for Parkinsonism (AIDP) Primary End Point Model and Verification Run Performance
A, Area under the receiver operating characteristic curve (AUROC) for the primary model end points of Parkinson disease (PD) vs atypical parkinsonism (AP), multiple system atrophy parkinsonian variant (MSA) vs progressive supranuclear palsy (PSP), PD vs MSA, and PD vs PSP. The AUROC and 95% CI calculated using the DeLong method are reported for each end point. B, AUROC for 49 model verification runs for each primary end point. The average AUROC across all runs and the 95% CI on the mean are reported.

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