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Movement Disorders Resulting From Bilateral Basal Ganglia Lesions in End-Stage Kidney Disease: A Systematic Review
Kah Hui Yap, Nurul Husna Baharudin, Abdul Halim Abdul Gafor, Rabani Remli, Shen-Yang Lim, Wan Asyraf Wan Zaidi, Shahrul Azmin, Shahizon Azura Mohamed Mukari, Raihanah Abdul Khalid, Norlinah Mohamed Ibrahim
J Mov Disord. 2022;15(3):258-263.   Published online May 26, 2022
DOI: https://doi.org/10.14802/jmd.21185
  • 3,352 View
  • 118 Download
AbstractAbstract PDFSupplementary Material
Objective
The basal ganglia (BG) are susceptible to fluctuations in blood urea levels, sometimes resulting in movement disorders. We described patients with end-stage kidney disease (ESKD) presenting with movement disorders associated with bilateral BG lesions on imaging.
Methods
We report four patients and systematically reviewed all published cases of ESKD presenting with movement disorders and bilateral BG lesions (EBSCOhost and Ovid).
Results
Of the 72 patients identified, 55 (76.4%) were on regular dialysis. Parkinsonism was the most common movement disorder (n = 39; 54.2%), followed by chorea (n = 24; 33.3%). Diabetes mellitus (n = 51; 70.8%) and hypertension (n = 16; 22.2%) were the most common risk factors. Forty-three (59.7%) were of Asian ethnicity. Complete clinical resolution was reported in 17 (30.9%) patients, while 38 (69.1%) had incomplete clinical resolution with relapse. Complete radiological resolution occurred in 14 (34.1%) patients.
Conclusion
Movement disorders associated with BG lesions should be recognized as a rare and potentially reversible metabolic movement disorder in patients with ESKD.
Original Articles
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Automated Brainstem Segmentation Detects Differential Involvement in Atypical Parkinsonian Syndromes
Martina Bocchetta, Juan Eugenio Iglesias, Viorica Chelban, Edwin Jabbari, Ruth Lamb, Lucy L. Russell, Caroline V. Greaves, Mollie Neason, David M. Cash, David L. Thomas, Jason D. Warren, John Woodside, Henry Houlden, Huw R. Morris, Jonathan D. Rohrer
J Mov Disord. 2020;13(1):39-46.   Published online September 26, 2019
DOI: https://doi.org/10.14802/jmd.19030
  • 8,243 View
  • 248 Download
  • 15 Web of Science
  • 15 Crossref
AbstractAbstract PDFSupplementary Material
Objective
Brainstem segmentation has been useful in identifying potential imaging biomarkers for diagnosis and progression in atypical parkinsonian syndromes (APS). However, the majority of work has been performed using manual segmentation, which is time consuming for large cohorts.
Methods
We investigated brainstem involvement in APS using an automated method. We measured the volume of the medulla, pons, superior cerebellar peduncle (SCP) and midbrain from T1-weighted MRIs in 67 patients and 42 controls. Diagnoses were corticobasal syndrome (CBS, n = 14), multiple system atrophy (MSA, n = 16: 8 with parkinsonian syndrome, MSA-P; 8 with cerebellar syndrome, MSA-C), progressive supranuclear palsy with a Richardson’s syndrome (PSP-RS, n = 12), variant PSP (n = 18), and APS not otherwise specified (APS-NOS, n = 7).
Results
All brainstem regions were smaller in MSA-C (19–42% volume difference, p < 0.0005) and in both PSP groups (18–33%, p < 0.0005) than in controls. MSA-P showed lower volumes in all regions except the SCP (15–26%, p < 0.0005). The most affected region in MSA-C and MSA-P was the pons (42% and 26%, respectively), while the most affected regions in both the PSP-RS and variant PSP groups were the SCP (33% and 23%, respectively) and midbrain (26% and 24%, respectively). The brainstem was less affected in CBS, but nonetheless, the pons (14%, p < 0.0005), midbrain (14%, p < 0.0005) and medulla (10%, p = 0.001) were significantly smaller in CBS than in controls. The brainstem was unaffected in APS-NOS.
Conclusion
Automated methods can accurately quantify the involvement of brainstem structures in APS. This will be important in future trials with large patient numbers where manual segmentation is unfeasible.

Citations

Citations to this article as recorded by  
  • Loss of brainstem white matter predicts onset and motor neuron symptoms in C9orf72 expansion carriers: a GENFI study
    Agnès Pérez-Millan, Sergi Borrego-Écija, John C. van Swieten, Lize Jiskoot, Fermin Moreno, Robert Laforce, Caroline Graff, Mario Masellis, Maria Carmela Tartaglia, James B. Rowe, Barbara Borroni, Elizabeth Finger, Matthis Synofzik, Daniela Galimberti, Rik
    Journal of Neurology.2023; 270(3): 1573.     CrossRef
  • Comparative validation of AI and non-AI methods in MRI volumetry to diagnose Parkinsonian syndromes
    Joomee Song, Juyoung Hahm, Jisoo Lee, Chae Yeon Lim, Myung Jin Chung, Jinyoung Youn, Jin Whan Cho, Jong Hyeon Ahn, Kyungsu Kim
    Scientific Reports.2023;[Epub]     CrossRef
  • Identification of the pathogenesis features of various phenotypes of multiple sclerosis based on the study of the morphological functional connectivity of subcortical gray matter structures
    A. G. Trufanov, A. Y. Polushin, E. A. Gorbunova, M. V. Lukin
    Russian Journal for Personalized Medicine.2023; 3(1): 27.     CrossRef
  • Structural MRI predicts clinical progression in presymptomatic genetic frontotemporal dementia: findings from the GENetic Frontotemporal dementia Initiative cohort
    Martina Bocchetta, Emily G Todd, Arabella Bouzigues, David M Cash, Jennifer M Nicholas, Rhian S Convery, Lucy L Russell, David L Thomas, Ian B Malone, Juan Eugenio Iglesias, John C van Swieten, Lize C Jiskoot, Harro Seelaar, Barbara Borroni, Daniela Galim
    Brain Communications.2023;[Epub]     CrossRef
  • Quantitative MRI protocol and decision model for a ‘one stop shop’ early-stage Parkinsonism diagnosis: Study design
    Samy Abo Seada, Anke W. van der Eerden, Agnita J.W. Boon, Juan A. Hernandez-Tamames
    NeuroImage: Clinical.2023; 39: 103506.     CrossRef
  • Neuroimaging correlates of brain injury in Wilson’s disease: a multimodal, whole-brain MRI study
    Samuel Shribman, Martina Bocchetta, Carole H Sudre, Julio Acosta-Cabronero, Maggie Burrows, Paul Cook, David L Thomas, Godfrey T Gillett, Emmanuel A Tsochatzis, Oliver Bandmann, Jonathan D Rohrer, Thomas T Warner
    Brain.2022; 145(1): 263.     CrossRef
  • Nuclear imaging in Parkinson's disease: The past, the present, and the future
    Haim Golan, Olga Volkov, Eli Shalom
    Journal of the Neurological Sciences.2022; 436: 120220.     CrossRef
  • Criteria-unfulfilled multiple system atrophy at an initial stage exhibits laterality of middle cerebellar peduncles
    Minori Furuta, Masayuki Sato, Setsuki Tsukagoshi, Yoshito Tsushima, Yoshio Ikeda
    Journal of the Neurological Sciences.2022; 438: 120281.     CrossRef
  • A data-driven model of brain volume changes in progressive supranuclear palsy
    W. J. Scotton, M. Bocchetta, E. Todd, D. M. Cash, N. Oxtoby, L. VandeVrede, H. Heuer, D. C. Alexander, J. B. Rowe, H. R. Morris, A. Boxer, J. D. Rohrer, P. A. Wijeratne
    Brain Communications.2022;[Epub]     CrossRef
  • Neuroimaging Correlates of Cognitive Deficits in Wilson's Disease
    Samuel Shribman, Maggie Burrows, Rhian Convery, Martina Bocchetta, Carole H. Sudre, Julio Acosta‐Cabronero, David L. Thomas, Godfrey T. Gillett, Emmanuel A. Tsochatzis, Oliver Bandmann, Jonathan D. Rohrer, Thomas T. Warner
    Movement Disorders.2022; 37(8): 1728.     CrossRef
  • Corticobasal syndrome and Parkinson’s disease at the beginning: asymmetrical patterns of MRI and Blink Reflex for early diagnosis
    Giulia Donzuso, Giorgia Sciacca, Antonina Luca, Calogero E. Cicero, Giovanni Mostile, Alessandra Nicoletti, Mario Zappia
    Journal of Neural Transmission.2022; 129(12): 1427.     CrossRef
  • Eye movements and association with regional brain atrophy in clinical subtypes of progressive supranuclear palsy
    Ji-Hyun Choi, Heejung Kim, Jung Hwan Shin, Jee-Young Lee, Han-Joon Kim, Jong-Min Kim, Beomseok Jeon
    Journal of Neurology.2021; 268(3): 967.     CrossRef
  • Artificial intelligence applied to neuroimaging data in Parkinsonian syndromes: Actuality and expectations
    Annalisa Vitale, Rossella Villa, Lorenzo Ugga, Valeria Romeo, Arnaldo Stanzione, Renato Cuocolo
    Mathematical Biosciences and Engineering.2021; 18(2): 1753.     CrossRef
  • Differential early subcortical involvement in genetic FTD within the GENFI cohort
    Martina Bocchetta, Emily G. Todd, Georgia Peakman, David M. Cash, Rhian S. Convery, Lucy L. Russell, David L. Thomas, Juan Eugenio Iglesias, John C. van Swieten, Lize C. Jiskoot, Harro Seelaar, Barbara Borroni, Daniela Galimberti, Raquel Sanchez-Valle, Ro
    NeuroImage: Clinical.2021; 30: 102646.     CrossRef
  • Quantitative MRI markers in Parkinson's disease and parkinsonian syndromes
    Germain Arribarat, Patrice Péran
    Current Opinion in Neurology.2020; 33(2): 222.     CrossRef
Article image
Increased Signal in the Superior Cerebellar Peduncle of Patients with Progressive Supranuclear Palsy
Hiroshi Kataoka, Yukako Nishimori, Takao Kiriyama, Hitoki Nanaura, Tesseki Izumi, Nobuyuki Eura, Naoki Iwasa, Kazuma Sugie
J Mov Disord. 2019;12(3):166-171.   Published online August 9, 2019
DOI: https://doi.org/10.14802/jmd.19002
  • 9,076 View
  • 223 Download
  • 2 Web of Science
  • 2 Crossref
AbstractAbstract PDF
Objective
The provisional diagnosis of progressive supranuclear palsy (PSP) depends on a combination of typical clinical features and specific MRI findings, such as atrophy of the tegmentum in the midbrain. Atrophy of the superior cerebellar peduncle (SCP) distinguishes PSP from other types of parkinsonism. Histological factors affect the conventional fluid-attenuated inversion recovery (FLAIR) signals, such as the extent of neuronal loss and gliosis.
Methods
We investigated patients with PSP to verify the percentage of patients with various PSP phenotypes presenting a high signal intensity in the SCP. Three interviewers, who were not informed about the clinical data, visually inspected the presence or absence of a high signal intensity in the SCP on the FLAIR images. We measured the pixel value in the SCP of each patient. Clinical characteristics were evaluated using the Mann-Whitney test, followed by the χ2 test.
Results
Ten of the 51 patients with PSP showed a high signal intensity in the SCP on FLAIR MRI. Higher pixel values were observed within the SCP of patients with a high signal intensity in the SCP than in patients without a high signal intensity (p < 0.001). The sensitivity and specificity of the high signal intensity in the SCP of patients with PSP was 19.6% and 100%, respectively. This finding was more frequently observed in patients with PSP with Richardson’s syndrome (PSP-RS) (25.7%) than other phenotypes (6.2%).
Conclusion
The high signal intensity in the SCP on FLAIR MRI might be an effective diagnostic tool for PSP-RS.

Citations

Citations to this article as recorded by  
  • Diffusion tractography of superior cerebellar peduncle and dentatorubrothalamic tracts in two autopsy confirmed progressive supranuclear palsy variants: Richardson syndrome and the speech-language variant
    Rodolfo G. Gatto, Peter R. Martin, Farwa Ali, Heather M. Clark, Joseph R. Duffy, Rene L. Utianski, Hugo Botha, Mary M. Machulda, Dennis W. Dickson, Keith A. Josephs, Jennifer L. Whitwell
    NeuroImage: Clinical.2022; 35: 103030.     CrossRef
  • The Role of Magnetic Resonance Imaging for the Diagnosis of Atypical Parkinsonism
    Lydia Chougar, Nadya Pyatigorskaya, Bertrand Degos, David Grabli, Stéphane Lehéricy
    Frontiers in Neurology.2020;[Epub]     CrossRef
The ‘Hot Cross Bun’ Sign Is Not Always Multiple System Atrophy: Etiologies of 11 Cases
Christopher Way, David Pettersson, Amie Hiller
J Mov Disord. 2019;12(1):27-30.   Published online December 19, 2018
DOI: https://doi.org/10.14802/jmd.18031
  • 9,612 View
  • 326 Download
  • 21 Web of Science
  • 24 Crossref
AbstractAbstract PDF
Objective
To clarify the specificity of the ‘hot cross bun’ sign (HCBS) for multiple system atrophy (MSA) in adult cerebellar ataxia or parkinsonism.
Methods
The radiologic information systems at an academic center and affiliated veterans’ hospital were queried using the keywords ‘hot cross bun,’ ‘pontocerebellar,’ ‘cruciate,’ ‘cruciform,’ ‘MSA,’ ‘multiple system atrophy,’ and ‘multisystem atrophy.’ Scans were reviewed by a neurologist and neuroradiologist to identify the HCBS. Subjects with the HCBS were reviewed by 2 neurologists to identify the most likely etiology of the patient’s neurologic symptoms.
Results
Eleven cases were identified. Etiologies included MSA (4 probable, 2 possible), hereditary cerebellar ataxia (3/11), probable dementia with Lewy bodies (1/11), and uncertain despite autopsy (1/11).
Conclusion
MSA was the most common etiology. However, 5 of the 11 patients did not have MSA. The most common alternate etiology was an undefined hereditary cerebellar ataxia (3/11).

Citations

Citations to this article as recorded by  
  • Progressive supranuclear palsy: A case report and brief review of the literature
    Vivek Batheja, Morgan Fish, Aneri B. Balar, Jeffery P. Hogg, Dhairya A. Lakhani, Musharaf Khan
    Radiology Case Reports.2024; 19(1): 250.     CrossRef
  • A case of bilateral middle cerebellar peduncle infarction with hot cross bun sign
    Daisuke Kuzume, Yuko Morimoto, Satoshi Tsutsumi, Masahiro Yamasaki, Naohisa Hosomi
    Rinsho Shinkeigaku.2024; 64(3): 190.     CrossRef
  • Immune‐mediated spastic ataxia masquerading as clinically probable multisystem atrophy in an elderly woman
    Rithvik Ramesh, Anuhya Chadalawada, Pedapati Radhakrishna, Lakshmi Narasimhan Ranganathan, Philo Hazeena, Sundar Shanmugam, Deepa Avadhani
    Clinical and Experimental Neuroimmunology.2024; 15(3): 146.     CrossRef
  • Food for Thought: A Review of Neuroradiographic Signs Inspired by Food
    C.T. Zoppo, T. Taros, J. Singh, A.S. Puri, A.L. Kuhn
    Neurographics.2024; 14(1): 29.     CrossRef
  • A Cysteinyl-tRNA Synthetase Mutation Causes Novel Autosomal-Dominant Inheritance of a Parkinsonism/Spinocerebellar-Ataxia Complex
    Han-Kui Liu, Hong-Lin Hao, Hui You, Feng Feng, Xiu-Hong Qi, Xiao-Yan Huang, Bo Hou, Chang-Geng Tian, Han Wang, Huan-Ming Yang, Jian Wang, Rui Wu, Hui Fang, Jiang-Ning Zhou, Jian-Guo Zhang, Zhen-Xin Zhang
    Neuroscience Bulletin.2024; 40(10): 1489.     CrossRef
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    Salvatore Ssemmanda
    BMC Neurology.2024;[Epub]     CrossRef
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    Ryan Johnson, John Lausch, Dakota Degenstein, Boris Reznikov
    Clinical Imaging.2024; 114: 110251.     CrossRef
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    Xiaoli Chen, Li Feng, Jing Li, Hong Jiang
    Neurodegenerative Disease Management.2024; 14(3-4): 69.     CrossRef
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    Sanskriti Sasikumar, Antonio P. Strafella
    Seminars in Neurology.2023; 43(01): 095.     CrossRef
  • Anti‐kelchlike protein 11 antibody‐associated encephalitis: Two case reports and review of the literature
    Alejandro León Betancourt, Anina Schwarzwald, Alban Millonig, Michael Oberholzer, Lidia Sabater, Helly Hammer, Nicole Kamber, Lara Diem, Andrew Chan, Robert Hoepner, Anke Salmen, Christoph Friedli
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    Linh Tran, Tuba Ahmad, Anniken Haslund, Phuoc Ngoc Thi Nguyen
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    Fatma Zehra Calikusu, Sema Akkus, Esra Kochan Kizilkilic, Burc Cagri Poyraz, Ali Tarik Altunç, Gunes Kiziltan, Aysegul Gunduz
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    Brain Imaging and Behavior.2022; 16(3): 1196.     CrossRef
  • The “Black Straight-Line Sign” in the Putamen in Diffusion-Weighted Imaging: A Potential Diagnostic MRI Marker for Multiple System Atrophy
    Yiming Zheng, Xiwen Wang, Huajian Zhao, Yanyan Jiang, Ying Zhu, Jing Chen, Wei Sun, Zhaoxia Wang, Yunchuang Sun
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    Hung-Chieh Chen, Li-Hua Lee, Jiing-Feng Lirng, Bing-wen Soong
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    Ansuya Kasavelu Naidoo, Cait‐Lynn Deanne Wells, Yashvir Rugbeer, Neil Naidoo
    Movement Disorders Clinical Practice.2022; 9(8): 1105.     CrossRef
  • Magnetic resonance imaging abnormalities as a marker of multiple system atrophy in isolated rapid eye movement sleep behavior disorder
    Amaia Muñoz-Lopetegi, Joan Berenguer, Alex Iranzo, Monica Serradell, Teresa Pujol, Carles Gaig, Esteban Muñoz, Eduard Tolosa, Joan Santamaría
    Sleep.2021;[Epub]     CrossRef
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    Margiben Tusharbhai Bhatt, R. Sunil
    Indian Journal of Respiratory Care.2021; 10(1): 148.     CrossRef
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    Inna Page, Frank Gaillard
    Practical Neurology.2020; 20(6): 463.     CrossRef
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    Shuzhen Zhu, Hualing Li, Bin Deng, Jialing Zheng, Zifeng Huang, Zihan Chang, Yanjun Huang, Zhibo Wen, Yanran Liang, Mengjue Yu, Ling-Ling Chan, Eng-King Tan, Qing Wang
    Frontiers in Aging Neuroscience.2020;[Epub]     CrossRef
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    M. Portet, M. Filyridou, D. C. Howlett
    Journal of Neurology.2019; 266(10): 2573.     CrossRef
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    Paul Greene
    CONTINUUM: Lifelong Learning in Neurology.2019; 25(4): 919.     CrossRef
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    Minkyeong Kim, Jong Hyeon Ahn, Yoonsu Cho, Ji Sun Kim, Jinyoung Youn, Jin Whan Cho
    Scientific Reports.2019;[Epub]     CrossRef

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