Cortical Mean Curvature Research Articles

Brain structural changes in preschool children with MRI-negative epilepsy.

To investigate abnormalities in cortical and subcortical structures of the brain in preschool children with MRI-negative epilepsy. Cortical thickness, cortical mean curvature, cortical surface area, cortical volume, and volumes of subcortical structures were measured using Freesurfer software in preschool children with epilepsy and age-matched controls. Findings showed cortical thickening in the left fusiform gyrus, left middle temporal gyrus, right suborbital sulcus, and right gyrus rectus, and cortical thinning mainly in the parietal lobe of preschool children with epilepsy compared to controls. The difference in cortical thickness in the left superior parietal lobule remained after correction for multiple comparisons and was negatively correlated with duration of epilepsy. Cortical mean curvature, surface area, and volume were mainly altered in the frontal and temporal lobes. Changes in mean curvature in the right pericallosal sulcus were positively correlated with age at seizure onset, and changes in mean curvature in the left intraparietal sulcus and transverse parietal sulcus were positively correlated with frequency of seizures. There were no significant differences in the volumes of the subcortical structures. Changes in preschool children with epilepsy occur in the cortical rather than subcortical structures of the brain. These findings further our understanding of the effects of epilepsy in preschool children and will inform management of epilepsy in this patient population.

Machine learning classification of schizophrenia patients and healthy controls using diverse neuroanatomical markers and Ensemble methods

Schizophrenia is a major psychiatric disorder that imposes enormous clinical burden on patients and their caregivers. Determining classification biomarkers can complement clinical measures and improve understanding of the neural basis underlying schizophrenia. Using neuroanatomical features, several machine learning based investigations have attempted to classify schizophrenia from healthy controls but the range of neuroanatomical measures employed have been limited in range to date. In this study, we sought to classify schizophrenia and healthy control cohorts using a diverse set of neuroanatomical measures (cortical and subcortical volumes, cortical areas and thickness, cortical mean curvature) and adopted Ensemble methods for better performance. Additionally, we correlated such neuroanatomical features with Quality of Life (QoL) assessment scores within the schizophrenia cohort. With Ensemble methods and diverse neuroanatomical measures, we achieved classification accuracies ranging from 83 to 87%, sensitivities and specificities varying between 90–98% and 65–70% respectively. In addition to lower QoL scores within schizophrenia cohort, significant correlations were found between specific neuroanatomical measures and psychological health, social relationship subscale domains of QoL. Our results suggest the utility of inclusion of subcortical and cortical measures and Ensemble methods to achieve better classification performance and their potential impact of parsing out neurobiological correlates of quality of life in schizophrenia.

Identificacion of MRI-based psychosis subtypes: Replication and refinement

The identification of the cerebral substrates of psychoses such as schizophrenia and bipolar disorder is likely hampered by its biological heterogeneity, which may contribute to the low replication of results in the field. In this study we aimed to replicate in a completely new sample and supplement the results of a previous study with additional data on this topic. In the aforementioned study we identified a schizophrenia cluster characterized by high mean cortical curvature and low cortical thickness, subcortical hypometabolism and progressive negative symptoms. Here, we have used magnetic resonance images from 61 schizophrenia and 28 bipolar patients, as well as 51 healthy controls and a cluster analysis to search for possible subgroups primarily characterized by cerebral structural data. Diffusion tensor imaging (fractional anisotropy, FA), cognition, clinical data and electroencephalographic (EEG) modulation during a P300 task were used to validate the possible clusters. Two clusters of patients were identified. The first cluster (29 schizophrenia and 18 bipolar patients) showed decreased cortical thickness and area values, as well as lower subcortical volumes and higher cortical curvature in some regions, as compared to the second cluster. This first cluster also showed decreased FA in frontal lobe connections and worse cognitive performance. Although this cluster also showed longer illness duration, there were first episode patients in both clusters and treatment doses and types were not different between clusters. Both clusters of patients showed decreased EEG task-related modulation. In conclusion, our data give additional support to a distinct biologically based cluster encompassing schizophrenia and bipolar disorder patients with cortical and subcortical alterations, hampered cortical connectivity and lower cognitive performance.

Homozygous LAMC3 mutation links to structural and functional changes in visual attention networks

The occipital lobe contains a substantial part of the neural machinery involved in visual perception. Mutations in the LAMC3 gene have recently been shown to cause complex bilateral occipital cortical gyration abnormalities. However, to what extent these structural changes impact visual behavior is not known. We recorded responses for two screening test batteries targeting visual function (Leuven - Perceptual Organization Screening Test, Cortical Vision Screening Test) and measured eye fixation performance in a visual attention experiment from a patient with homozygous LAMC3 gene mutation. Using voxel-based morphometry (VBM) we quantitatively assessed the extent of structural changes brought on by the genetic mutation by comparing mean cortical curvature, cortical thickness, and gray matter volume in 34 cortical areas between patient and an age-, sex-, and education-matched control group. Anatomical connectivity between these cortical areas was investigated by a structural covariance analysis. Visual screening-, and behavioral results revealed that the patient's impairments were predominantly in visuo-spatial attention. Consistent with this, VBM and structural connectivity results revealed significant structural changes in cortical regions subserving attentional functions. We conclude that the LAMC3 gene mutation affects cortical areas beyond the occipital lobe and primarily those visual functions that involve heavily distributed networks – such as visuo-spatial attention.

Biological and cognitive correlates of cortical curvature in schizophrenia

Mean cortical curvature may relate to cortico-cortical connections integrity. We explored the association between prefrontal (PFC) cortical curvature and fractional anisotropy (FA) values for tracts connecting PFC and relevant cortical regions. In schizophrenia Anatomical and diffusion magnetic resonance images were obtained from 34 patients (16 of them first-episodes) and 32 healthy controls. We calculated curvature at rostral lateral prefrontal (RLPF) and superior medial prefrontal (SMPF) areas and mean FA for the tracts respectively connecting RLPF and SMPF areas with anterior caudal cingulate (ACC), superior temporal gyrus (STG) and superior parietal SP regions. Cognitive and clinical data were collected, including baseline symptoms, Clinical Global Impression change scores from baseline to follow-up, illness duration and treatment dosage. Patients showed significantly lower FA values in the tracts linking right RLPF-ACC, right SMPF-SPG and bilaterally PFC-STG. FA values in short-range cortico-cortical connections (linking PFC and ACC) were inversely associated with PFC curvature. In patients, cognitive performance was negatively associated with PFC curvature. Larger curvature values were associated to lack of clinical improvement at follow-up. We conclude that cortical curvature is influenced by integrity in short-range cortico-cortical connections and relates to cognition and clinical outcome in schizophrenia patients.

Mean cortical curvature reflects cytoarchitecture restructuring in mild traumatic brain injury.

In the United States alone, the number of persons living with the enduring consequences of traumatic brain injuries is estimated to be between 3.2 and 5 million. This number does not include individuals serving in the United States military or seeking care at Veterans Affairs hospitals. The importance of understanding the neurobiological consequences of mild traumatic brain injury (mTBI) has increased with the return of veterans from conflicts overseas, many of who have suffered this type of brain injury. However, identifying the neuroanatomical regions most affected by mTBI continues to prove challenging. The aim of this study was to assess the use of mean cortical curvature as a potential indicator of progressive tissue loss in a cross-sectional sample of 54 veterans with mTBI compared to 31 controls evaluated with MRI. It was hypothesized that mean cortical curvature would be increased in veterans with mTBI, relative to controls, due in part to cortical restructuring related to tissue volume loss. Mean cortical curvature was assessed in 60 bilateral regions (31 sulcal, 29 gyral). Of the 120 regions investigated, nearly 50% demonstrated significantly increased mean cortical curvature in mTBI relative to controls with 25% remaining significant following multiple comparison correction (all, pFDR < .05). These differences were most prominent in deep gray matter regions of the cortex. Additionally, significant relationships were found between mean cortical curvature and gray and white matter volumes (all, p < .05). These findings suggest potentially unique patterns of atrophy by region and indicate that changes in brain microstructure due to mTBI are sensitive to measures of mean curvature.

Increased temporolimbic cortical folding complexity in temporal lobe epilepsy

Converging evidence suggests that abnormalities of brain development may play a role in the pathogenesis of temporal lobe epilepsy (TLE). As sulco-gyral patterns are thought to be a footprint of cortical development, we set out to quantitatively map folding complexity across the neocortex in TLE. Additionally, we tested whether there was a relationship between cortical complexity and features of hippocampal maldevelopment, commonly referred to as malrotation. To quantify folding complexity, we obtained whole-brain surface-based measures of absolute mean cortical curvature from MRI scans acquired in 43 drug-resistant patients with TLE with unilateral hippocampal atrophy, and 40 age- and sex-matched healthy controls. In patients, we correlated changes in cortical curvature with 3-dimensional measures of hippocampal positioning. We found increased folding complexity in the temporolimbic cortices encompassing parahippocampal, temporopolar, insular, and fronto-opercular regions. Increased complexity was observed ipsilateral to the seizure focus in patients with left TLE (LTLE), whereas these changes were bilateral in patients with right TLE (RTLE). In both TLE groups, increased temporolimbic complexity was associated with increased hippocampal malrotation. We found tendencies for increased complexity in bilateral posterior temporal cortices in LTLE and contralateral parahippocampal cortices in RTLE to be predictive of unfavorable seizure outcome after surgery. The anatomic distribution of increased cortical complexity overlapping with limbic seizure networks in TLE and its association with hippocampal maldevelopment further imply that neurodevelopmental factors may play a role in the epileptogenic process of TLE.