Heterotopia in Individuals with 22q11.2 Deletion Syndrome.

BACKGROUND AND PURPOSE: MR imaging studies and neuropathologic findings in individuals with 22q11.2 deletion syndrome show anomalous early brain development. We aimed to retrospectively evaluate cerebral abnormalities, focusing on gray matter heterotopia, and to correlate these with subjects' neuropsychiatric impairments. MATERIALS AND METHODS: Three raters assessed gray matter heterotopia and other morphologic brain abnormalities on 3D T1WI and T2*WI in 75 individuals with 22q11.2 deletion syndrome (27 females, 15.5 [SD, 7.4] years of age) and 53 controls (24 females, 12.6 [SD, 4.7] years of age). We examined the association among the groups' most frequent morphologic findings, general cognitive performance, and comorbid neuropsychiatric conditions. RESULTS: Heterotopia in the white matter were the most frequent finding in individuals with 22q11.2 deletion syndrome (n = 29; controls, n = 0; between-group difference, P < .001), followed by cavum septi pellucidi and/or vergae (n = 20; controls, n = 0; P < .001), periventricular cysts (n = 10; controls, n = 0; P = .007), periventricular nodular heterotopia (n = 10; controls, n = 0; P = .007), and polymicrogyria (n = 3; controls, n = 0; P = .3). However, individuals with these morphologic brain abnormalities did not differ significantly from those without them in terms of general cognitive functioning and psychiatric comorbidities. CONCLUSIONS: Taken together, our findings, periventricular nodular heterotopia or heterotopia in the white matter (possibly related to interrupted Arc cells migration), persistent cavum septi pellucidi and/or vergae, and formation of periventricular cysts, give clues to the brain development disorder induced by the 22q11.2 deletion syndrome. There was no evidence that these morphologic findings were associated with differences in psychiatric or cognitive presentation of the 22q11.2 deletion syndrome.

Volumetry of Mesiotemporal Structures Reflects Serostatus in Patients with Limbic Encephalitis.

BACKGROUND AND PURPOSE: Limbic encephalitis is an autoimmune disease. A variety of autoantibodies have been associated with different subtypes of limbic encephalitis, whereas its MR imaging signature is uniformly characterized by mesiotemporal abnormalities across subtypes. Here, we hypothesized that patients with limbic encephalitis would show subtype-specific mesiotemporal structural correlates, which could be classified by supervised machine learning on an individual level. MATERIALS AND METHODS: T1WI MPRAGE scans from 46 patients with antibodies against glutamic acid decarboxylase and 34 patients with antibodies against the voltage-gated potassium channel complex (including 10 patients with leucine-rich glioma-inactivated 1 autoantibodies) and 48 healthy controls were retrospectively ascertained. Parcellation of the amygdala, hippocampus, and hippocampal subfields was performed using FreeSurfer. Volumes were extracted and compared between groups using unpaired, 2-tailed t tests. The volumes of hippocampal subfields were analyzed using a multivariate linear model and a binary decision tree classifier. RESULTS: Temporomesial volume alterations were most pronounced in an early stage and in the affected hemispheric side of patients. Statistical analysis revealed antibody-specific hippocampal fingerprints with a higher volume of CA1 in patients with glutamic acid decarboxylase-associated limbic encephalitis (P = .02), compared with controls, whereas CA1 did not differ from that in controls in patients with voltage-gated potassium channel complex autoantibodies. The classifier could successfully distinguish between patients with autoantibodies against leucine-rich glioma-inactivated 1 and glutamic acid decarboxylase with a specificity of 87% and a sensitivity of 80%. CONCLUSIONS: Our results suggest stage-, side- and antibody-specific structural correlates of limbic encephalitis; thus, they create a perspective toward an MR imaging-based diagnosis.