G Nicoletti1, M E Caligiuri2, A Cherubini2, M Morelli3, F Novellino2, G Arabia3, M Salsone2, A Quattrone2,3. 1. From the Institute of Bioimaging and Molecular Physiology (G.N., M.E.C., A.C., F.N., M.S., A.Q.), National Research Council, Catanzaro, Italy g.nicoletti@unicz.it. 2. From the Institute of Bioimaging and Molecular Physiology (G.N., M.E.C., A.C., F.N., M.S., A.Q.), National Research Council, Catanzaro, Italy. 3. Institute of Neurology (M.M., G.A., A.Q.), University "Magna Graecia", Catanzaro, Italy.
Abstract
BACKGROUND AND PURPOSE: The superior cerebellar peduncle is damaged in progressive supranuclear palsy. However, alterations differ between progressive supranuclear palsy with Richardson syndrome and progressive supranuclear palsy-parkinsonism. In this study, we propose an automated tool for superior cerebellar peduncle integrity assessment and test its performance in patients with progressive supranuclear palsy with Richardson syndrome, progressive supranuclear palsy-parkinsonism, Parkinson disease, and healthy controls. MATERIALS AND METHODS: Structural and diffusion MRI was performed in 21 patients with progressive supranuclear palsy with Richardson syndrome, 9 with progressive supranuclear palsy-parkinsonism, 20 with Parkinson disease, and 30 healthy subjects. In a fully automated pipeline, the left and right superior cerebellar peduncles were first identified on MR imaging by using a tractography-based atlas of white matter tracts; subsequently, volume, mean diffusivity, and fractional anisotropy were extracted from superior cerebellar peduncles. These measures were compared across groups, and their discriminative power in differentiating patients was evaluated in a linear discriminant analysis. RESULTS: Compared with those with Parkinson disease and controls, patients with progressive supranuclear palsy with Richardson syndrome showed alterations of all superior cerebellar peduncle metrics (decreased volume and fractional anisotropy, increased mean diffusivity). Patients with progressive supranuclear palsy-parkinsonism had smaller volumes than those with Parkinson disease and controls and lower fractional anisotropy than those with Parkinson disease. Patients with progressive supranuclear palsy with Richardson syndrome had significantly altered fractional anisotropy and mean diffusivity in the left superior cerebellar peduncle compared with those with progressive supranuclear palsy-parkinsonism. Discriminant analysis with the sole use of significant variables separated progressive supranuclear palsy-parkinsonism from progressive supranuclear palsy with Richardson syndrome with 70% accuracy and progressive supranuclear palsy-parkinsonism from Parkinson disease with 74% accuracy. CONCLUSIONS: We demonstrate the feasibility of an automated approach for extracting multimodal MR imaging metrics from the superior cerebellar peduncle in healthy subjects and patients with parkinsonian. We provide evidence that structural and diffusion measures of the superior cerebellar peduncle might be valuable for computer-aided diagnosis of progressive supranuclear palsy subtypes and for differentiating patients with progressive supranuclear palsy-parkinsonism from with those with Parkinson disease.
BACKGROUND AND PURPOSE: The superior cerebellar peduncle is damaged in progressive supranuclear palsy. However, alterations differ between progressive supranuclear palsy with Richardson syndrome and progressive supranuclear palsy-parkinsonism. In this study, we propose an automated tool for superior cerebellar peduncle integrity assessment and test its performance in patients with progressive supranuclear palsy with Richardson syndrome, progressive supranuclear palsy-parkinsonism, Parkinson disease, and healthy controls. MATERIALS AND METHODS: Structural and diffusion MRI was performed in 21 patients with progressive supranuclear palsy with Richardson syndrome, 9 with progressive supranuclear palsy-parkinsonism, 20 with Parkinson disease, and 30 healthy subjects. In a fully automated pipeline, the left and right superior cerebellar peduncles were first identified on MR imaging by using a tractography-based atlas of white matter tracts; subsequently, volume, mean diffusivity, and fractional anisotropy were extracted from superior cerebellar peduncles. These measures were compared across groups, and their discriminative power in differentiating patients was evaluated in a linear discriminant analysis. RESULTS: Compared with those with Parkinson disease and controls, patients with progressive supranuclear palsy with Richardson syndrome showed alterations of all superior cerebellar peduncle metrics (decreased volume and fractional anisotropy, increased mean diffusivity). Patients with progressive supranuclear palsy-parkinsonism had smaller volumes than those with Parkinson disease and controls and lower fractional anisotropy than those with Parkinson disease. Patients with progressive supranuclear palsy with Richardson syndrome had significantly altered fractional anisotropy and mean diffusivity in the left superior cerebellar peduncle compared with those with progressive supranuclear palsy-parkinsonism. Discriminant analysis with the sole use of significant variables separated progressive supranuclear palsy-parkinsonism from progressive supranuclear palsy with Richardson syndrome with 70% accuracy and progressive supranuclear palsy-parkinsonism from Parkinson disease with 74% accuracy. CONCLUSIONS: We demonstrate the feasibility of an automated approach for extracting multimodal MR imaging metrics from the superior cerebellar peduncle in healthy subjects and patients with parkinsonian. We provide evidence that structural and diffusion measures of the superior cerebellar peduncle might be valuable for computer-aided diagnosis of progressive supranuclear palsy subtypes and for differentiating patients with progressive supranuclear palsy-parkinsonism from with those with Parkinson disease.
Authors: Stephen M Smith; Yongyue Zhang; Mark Jenkinson; Jacqueline Chen; P M Matthews; Antonio Federico; Nicola De Stefano Journal: Neuroimage Date: 2002-09 Impact factor: 6.556
Authors: Jennifer L Whitwell; Ankit V Master; Ramesh Avula; Kejal Kantarci; Scott D Eggers; Heidi A Edmonson; Clifford R Jack; Keith A Josephs Journal: Arch Neurol Date: 2011-06
Authors: I Litvan; Y Agid; D Calne; G Campbell; B Dubois; R C Duvoisin; C G Goetz; L I Golbe; J Grafman; J H Growdon; M Hallett; J Jankovic; N P Quinn; E Tolosa; D S Zee Journal: Neurology Date: 1996-07 Impact factor: 9.910
Authors: J J Hauw; S E Daniel; D Dickson; D S Horoupian; K Jellinger; P L Lantos; A McKee; M Tabaton; I Litvan Journal: Neurology Date: 1994-11 Impact factor: 9.910
Authors: Adam M Staffaroni; Fanny M Elahi; Dana McDermott; Kacey Marton; Elissaios Karageorgiou; Simone Sacco; Matteo Paoletti; Eduardo Caverzasi; Christopher P Hess; Howard J Rosen; Michael D Geschwind Journal: Semin Neurol Date: 2017-12-05 Impact factor: 3.420
Authors: Salvatore Nigro; Angelo Antonini; David E Vaillancourt; Klaus Seppi; Roberto Ceravolo; Antonio P Strafella; Antonio Augimeri; Andrea Quattrone; Maurizio Morelli; Luca Weis; Eleonora Fiorenzato; Roberta Biundo; Roxana G Burciu; Florian Krismer; Nikolaus R McFarland; Christoph Mueller; Elke R Gizewski; Mirco Cosottini; Eleonora Del Prete; Sonia Mazzucchi; Aldo Quattrone Journal: Mov Disord Date: 2020-02-24 Impact factor: 10.338
Authors: Lorenzo Ugga; Renato Cuocolo; Sirio Cocozza; Giuseppe Pontillo; Andrea Elefante; Mario Quarantelli; Caterina Vicidomini; Maria Francesca De Pandis; Giovanna De Michele; Alessandra D'Amico; Oreste de Divitiis; Arturo Brunetti Journal: Neuroradiology Date: 2020-07-24 Impact factor: 2.804