Patterns of Sulcal depth and cortical thickness in Parkinson's disease

Impaired topological properties of cortical morphological brain networks correlate with motor symptoms in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is characterized by loss of selectively vulnerable neurons within the basal ganglia circuit and progressive atrophy in subcortical and cortical regions. However, the impact of neurodegenerative pathology on the topological organization of cortical morphological networks has not been explored. The aims of this study were to investigate altered network patterns of covariance in cortical thickness and complexity, and to evaluate how morphological network integrity in PD is related to motor impairment.

METHODS

Individual morphological networks were constructed for 50 PD patients and 46 healthy controls (HCs) by estimating interregional similarity distributions in surface-based indices. We performed graph theoretical analysis and network-based statistics to detect PD-related alterations and further examined the correlation of network metrics with clinical scores. Furthermore, support vector regression based on topological characteristics was applied to predict the severity of motor impairment in PD.

RESULTS

Compared with HCs, PD patients showed lower local efficiency (p = 0.004), normalized characteristic path length (p = 0.022), and clustering coefficient (p = 0.005) for gyrification index-based morphological brain networks. Nodal topological abnormalities were mainly in the frontal, parietal and temporal regions, and impaired morphological connectivity was involved in the sensorimotor and default mode networks. The support vector regression model using network-based features allowed prediction of motor symptom severity with a correlation coefficient of 0.606.

CONCLUSIONS

This study identified a disrupted topological organization of cortical morphological networks that could substantially advance our understanding of the network degeneration mechanism of PD and might offer indicators for monitoring disease progression.

An MRI Study of Morphology, Asymmetry, and Sex Differences of Inferior Precentral Sulcus

Numerous studies utilizing magnetic resonance imaging (MRI) have observed sex and interhemispheric disparities in sulcal morphology, which could potentially underpin certain functional disparities in the human brain. Most of the existing research examines the precentral sulcus comprehensively, with a rare focus on its subsections. To explore the morphology, asymmetry, and sex disparities within the inferior precentral sulcus (IPCS), we acquired 3.0T magnetic resonance images from 92 right-handed Chinese adolescents. Brainvisa was used to reconstruct the IPCS structure and calculate its mean depth (MD). Based on the morphological patterns of IPCS, it was categorized into five distinct types. Additionally, we analyzed four different types of spatial relationships between IPCS and inferior frontal sulcus (IFS). There was a statistically significant sex disparity in the MD of IPCS, primarily observed in the right hemisphere. Females exhibited significantly greater asymmetry in the MD of IPCS compared to males. No statistically significant sex or hemispheric variations were identified in sulcal patterns. Our findings expand the comprehension of inconsistencies in sulcal structure, while also delivering an anatomical foundation for the study of related regions' function.

Surface-based morphometry study of brain in patients with carbon monoxide poisoning

PURPOSE

Although cortical volume abnormalities are frequently detected in patients with carbon monoxide poisoning (COP), particularly delayed neurological sequelae (DNS), the associated changes in cortical thickness and shape patterns remain unknown.

MATERIALS & METHODS

Using surface-based morphometry, we investigated the differences in cortical thickness and shape indices between a COP group (n = 44) vs healthy controls (HCs, n = 36), and between the DNS (n = 21) vs non-DNS (n = 23) subgroups. Additionally, the influence of cortical damage on neurological disorders was explored.

RESULTS

The COP group exhibited significant cortical thinning mainly in the bilateral fronto-parietal lobes (P < 0.05, family-wise error corrected). When cortical thinning in the bilateral parietal lobes, bilateral primary motor areas, left primary sensory areas, and bilateral paracentral lobules was explored in the DNS subgroups compared to the non-DNS subgroup (P < 0.05, FWE corrected), no differences in shape indices between the two subgroups were noted. In the COP group, there were significant positive correlations between the Mini-Mental State Examination (MMSE) score and cortical thickness in the right superior frontal gyrus (SFG) and bilateral rostral middle frontal gyrus (rMFG) (P < 0.05, false discovery rate corrected). There was no any significant correlation between cortical thickness and Neuropsychiatric inventory (NPI), UPDRS III scores (P > 0.05, FDR-corrected).

CONCLUSION

Cortical thickness is a more sensitive index than shape for measuring cortical damage in patients with COP exposure, as cortical thinning in the right SFG and bilateral rMFG is related to cognitive impairment.

Cortical and subcortical morphological alterations in motor subtypes of Parkinson's disease

Parkinson's disease (PD) can be classified into an akinetic-rigid (AR) and a tremor-dominant (TD) subtype based on predominant motor symptoms. Patients with different motor subtypes often show divergent clinical manifestations; however, the underlying neural mechanisms remain unclear. This study aimed to characterize the cortical and subcortical morphological alterations in motor subtypes of PD. T1-weighted MRI images were obtained for 90 patients with PD (64 with the AR subtype and 26 with the TD subtype) and 56 healthy controls (HCs). Cortical surface area, sulcal depth (measured by Freesurfer's Sulc index), and subcortical volume were computed to identify the cortical and subcortical morphological alterations in the two motor subtypes. Compared with HCs, we found widespread surface area reductions in the AR subtype yet sparse surface area reductions in the TD subtype. We found no significant Sulc change in the AR subtype yet increased Sulc in the right supramarginal gyrus in the TD subtype. The hippocampal volumes in both subtypes were lower than those of HCs. In PD patients, the surface area of left posterior cingulate cortex was positively correlated with Mini-Mental State Examination (MMSE) score, while the Sulc value of right middle frontal gyrus was positively correlated with severity of motor impairments. Additionally, the hippocampal volumes were positively correlated with MMSE and Montreal Cognitive Assessment scores and negatively correlated with severity of motor impairments and Hoehn & Yahr scores. Taken together, these findings may contribute to a better understanding of the neural substrates underlying the distinct symptom profiles in the two PD subtypes.

Early alterations in cortical morphology after neoadjuvant chemotherapy in breast cancer patients: A longitudinal magnetic resonance imaging study

There is growing evidence that chemotherapy may have a significant impact on the brains of breast cancer patients, causing changes in cortical morphology. However, early morphological alterations induced by chemotherapy in breast cancer patients are unclear. To investigate the patterns of those alterations, we compared female breast cancer patients (n = 45) longitudinally before (time point 0, TP0) and after (time point 1, TP1) the first cycle of neoadjuvant chemotherapy, using voxel‐based morphometry (VBM) and surface‐based morphometry (SBM). VBM and SBM alteration data underwent correlation analysis. We also compared cognition‐related neuropsychological tests in the breast cancer patients between TP0 and TP1. Reductions in gray matter volume, cortical thickness, sulcal depth, and gyrification index were found in most brain areas, while increments were found to be mainly concentrated in and around the hippocampus. Reductions of fractal dimension mainly occurred in the limbic and occipital lobes, while increments mainly occurred in the anterior and posterior central gyrus. Significant correlations were found between altered VBM and altered SBM mainly in the bilateral superior frontal gyrus. We found no significant differences in the cognition‐related neuropsychological tests before and after chemotherapy. The altered brain regions are in line with those associated with impaired cognitive domains in previous studies. We conclude that breast cancer patients showed widespread morphological alterations soon after neoadjuvant chemotherapy, despite an absence of cognitive impairments. The affected brain regions may indicate major targets of early brain damage after chemotherapy.

Machine Learning Models for Diagnosis of Parkinson's Disease Using Multiple Structural Magnetic Resonance Imaging Features

Purpose

This study aimed to develop machine learning models for the diagnosis of Parkinson's disease (PD) using multiple structural magnetic resonance imaging (MRI) features and validate their performance.

Methods

Brain structural MRI scans of 60 patients with PD and 56 normal controls (NCs) were enrolled as development dataset and 69 patients with PD and 71 NCs from Parkinson's Progression Markers Initiative (PPMI) dataset as independent test dataset. First, multiple structural MRI features were extracted from cerebellar, subcortical, and cortical regions of the brain. Then, the Pearson's correlation test and least absolute shrinkage and selection operator (LASSO) regression were used to select the most discriminating features. Finally, using logistic regression (LR) classifier with the 5-fold cross-validation scheme in the development dataset, the cerebellar, subcortical, cortical, and a combined model based on all features were constructed separately. The diagnostic performance and clinical net benefit of each model were evaluated with the receiver operating characteristic (ROC) analysis and the decision curve analysis (DCA) in both datasets.

Results

After feature selection, 5 cerebellar (absolute value of left lobule crus II cortical thickness (CT) and right lobule IV volume, relative value of right lobule VIIIA CT and lobule VI/VIIIA gray matter volume), 3 subcortical (asymmetry index of caudate volume, relative value of left caudate volume, and absolute value of right lateral ventricle), and 4 cortical features (local gyrification index of right anterior circular insular sulcus and anterior agranular insula complex, local fractal dimension of right middle insular area, and CT of left supplementary and cingulate eye field) were selected as the most distinguishing features. The area under the curve (AUC) values of the cerebellar, subcortical, cortical, and combined models were 0.679, 0.555, 0.767, and 0.781, respectively, for the development dataset and 0.646, 0.632, 0.690, and 0.756, respectively, for the independent test dataset, respectively. The combined model showed higher performance than the other models (Delong's test, all p-values < 0.05). All models showed good calibration, and the DCA demonstrated that the combined model has a higher net benefit than other models.

Conclusion

The combined model showed favorable diagnostic performance and clinical net benefit and had the potential to be used as a non-invasive method for the diagnosis of PD.