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Automated Brainstem Segmentation Detects Differential Involvement in Atypical Parkinsonian Syndromes

Bocchetta, M; Iglesias, JE; Chelban, V; Jabbari, E; Lamb, R; Russell, LL; Greaves, CV; ... Rohrer, JD; + view all (2019) Automated Brainstem Segmentation Detects Differential Involvement in Atypical Parkinsonian Syndromes. Journal of Movement Disorders 10.14802/jmd.19030. (In press). Green open access

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Abstract

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.

Type: Article
Title: Automated Brainstem Segmentation Detects Differential Involvement in Atypical Parkinsonian Syndromes
Location: Korea (South)
Open access status: An open access version is available from UCL Discovery
DOI: 10.14802/jmd.19030
Publisher version: http://dx.doi.org/10.14802/jmd.19030
Language: English
Additional information: © This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/ licenses/by-nc/4.0).
Keywords: Brainstem, Magnetic resonance imaging, Parkinsonian syndromes
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Brain Repair and Rehabilitation
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Movement Neurosciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Department of Neuromuscular Diseases
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neurodegenerative Diseases
URI: https://discovery.ucl.ac.uk/id/eprint/10082627
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