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American Academy of Neurology (AAN), Neurology, 9(96), p. e1319-e1333, 2020

DOI: 10.1212/wnl.0000000000011237

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Basal Ganglia Dysmorphism in Patients With Aicardi Syndrome

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Data provided by SHERPA/RoMEO

Abstract

ObjectiveAiming to detect associations between neuroradiologic and EEG evaluations and long-term clinical outcome in order to detect possible prognostic factors, a detailed clinical and neuroimaging characterization of 67 cases of Aicardi syndrome (AIC), collected through a multicenter collaboration, was performed.MethodsOnly patients who satisfied Sutton diagnostic criteria were included. Clinical outcome was assessed using gross motor function, manual ability, and eating and drinking ability classification systems. Brain imaging studies and statistical analysis were reviewed.ResultsPatients presented early-onset epilepsy, which evolved into drug-resistant seizures. AIC has a variable clinical course, leading to permanent disability in most cases; nevertheless, some cases presented residual motor abilities. Chorioretinal lacunae were present in 86.56% of our patients. Statistical analysis revealed correlations between MRI, EEG at onset, and clinical outcome. On brain imaging, 100% of the patients displayed corpus callosum malformations, 98% cortical dysplasia and nodular heterotopias, and 96.36% intracranial cysts (with similar rates of 2b and 2d). As well as demonstrating that posterior fossa abnormalities (found in 63.63% of cases) should also be considered a common feature in AIC, our study highlighted the presence (in 76.36%) of basal ganglia dysmorphisms (never previously reported).ConclusionThe AIC neuroradiologic phenotype consists of a complex brain malformation whose presence should be considered central to the diagnosis. Basal ganglia dysmorphisms are frequently associated. Our work underlines the importance of MRI and EEG, both for correct diagnosis and as a factor for predicting long-term outcome.Classification of EvidenceThis study provides Class II evidence that for patients with AIC, specific MRI abnormalities and EEG at onset are associated with clinical outcomes.