1.Thinning of the Corpus Callosum and Cerebellar Atrophy is Correlated with Phenotypic Severity in a Family with Spastic Paraplegia Type 11.
Sanjeev RAJAKULENDRAN ; Coro PAISAN-RUIZ ; Henry HOULDEN
Journal of Clinical Neurology 2011;7(2):102-104
BACKGROUND: Mutations in the spatacsin gene are associated with spastic paraplegia type 11 (SPG11), which is the most-common cause of autosomal recessive hereditary spastic paraplegia. Although SPG11 has diverse phenotypes, thinning of the corpus callosum is an important feature. CASE REPORT: Clinical, genetic, and radiological evaluations were undertaken in a large family from Gujarat in North India with hereditary spastic paraplegia, whose affected members presented with varying degrees of spasticity, ataxia, and cognitive impairment. The clinical severity and the degree of corpus callosum and cerebellar atrophy varied among the four affected individuals in the family. Genetic testing of the affected members revealed recessive mutations in the spatacsin gene, consistent with a diagnosis of SPG11. CONCLUSIONS: We believe that the extent of corpus callosum thinning and cerebellar atrophy is correlated with disease severity in affected patients. The addition of extrapyramidal features in the most-affected members suggests that SPG11 exhibits considerable phenotypic heterogeneity.
Ataxia
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Atrophy
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Corpus Callosum
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Genetic Testing
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Humans
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India
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Muscle Spasticity
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Paraplegia
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Phenotype
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Population Characteristics
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Spastic Paraplegia, Hereditary
2.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
Journal of Movement Disorders 2020;13(1):39-46
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.