Dataset Information

Automated Brainstem Segmentation Detects Differential Involvement in Atypical Parkinsonian Syndromes.

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.

SUBMITTER: Bocchetta M

PROVIDER: S-EPMC6987532 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Publications

Automated Brainstem Segmentation Detects Differential Involvement in Atypical Parkinsonian Syndromes.

Bocchetta Martina M Iglesias Juan Eugenio JE Chelban Viorica V Jabbari Edwin E Lamb Ruth R Russell Lucy L LL Greaves Caroline V CV Neason Mollie M Cash David M DM Thomas David L DL Warren Jason D JD Woodside John J Houlden Henry H Morris Huw R HR Rohrer Jonathan D JD

Journal of movement disorders 20190926 1

<h4>Objective</h4>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.<h4>Methods</h4>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 ...[more]

PMID: 31552724

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Project description:Parkinson's disease (PD) and atypical Parkinsonian syndromes are progressive heterogeneous neurodegenerative diseases that share clinical characteristic of parkinsonism as a common feature, but are considered distinct clinicopathological disorders. Based on the predominant protein aggregates observed within the brain, these disorders are categorized as, (1) α-synucleinopathies, which include PD and other Lewy body spectrum disorders as well as multiple system atrophy, and (2) tauopathies, which comprise progressive supranuclear palsy and corticobasal degeneration. Although, great strides have been made in neurodegenerative disease research since the first medical description of PD in 1817 by James Parkinson, these disorders remain a major diagnostic and treatment challenge. A valid diagnosis at early disease stages is of paramount importance, as it can help accommodate differential prognostic and disease management approaches, enable the elucidation of reliable clinicopathological relationships ideally at prodromal stages, as well as facilitate the evaluation of novel therapeutics in clinical trials. However, the pursuit for early diagnosis in PD and atypical Parkinsonian syndromes is hindered by substantial clinical and pathological heterogeneity, which can influence disease presentation and progression. Therefore, reliable neuroimaging biomarkers are required in order to enhance diagnostic certainty and ensure more informed diagnostic decisions. In this article, an updated presentation of well-established and emerging neuroimaging biomarkers are reviewed from the following modalities: (1) structural magnetic resonance imaging (MRI), (2) diffusion-weighted and diffusion tensor MRI, (3) resting-state and task-based functional MRI, (4) proton magnetic resonance spectroscopy, (5) transcranial B-mode sonography for measuring substantia nigra and lentiform nucleus echogenicity, (6) single photon emission computed tomography for assessing the dopaminergic system and cerebral perfusion, and (7) positron emission tomography for quantifying nigrostriatal functions, glucose metabolism, amyloid, tau and α-synuclein molecular imaging, as well as neuroinflammation. Multiple biomarkers obtained from different neuroimaging modalities can provide distinct yet corroborative information on the underlying neurodegenerative processes. This integrative "multimodal approach" may prove superior to single modality-based methods. Indeed, owing to the international, multi-centered, collaborative research initiatives as well as refinements in neuroimaging technology that are currently underway, the upcoming decades will mark a pivotal and exciting era of further advancements in this field of neuroscience.

Dataset Information

Automated Brainstem Segmentation Detects Differential Involvement in Atypical Parkinsonian Syndromes.

Objective

Methods

Results

Conclusion

Publications

Automated Brainstem Segmentation Detects Differential Involvement in Atypical Parkinsonian Syndromes.

Similar Datasets

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