RESUMEN
Introduction: Studies quantifying cortical metrics in brain tumor patients who present with seizures are limited. The current investigation assesses morphometric/volumetric differences across a wide range of anatomical regions, including temporal and extra-temporal, in patients with gliomas and intracranial metastases (IMs) presenting with seizures that could serve as a biomarker in the identification of seizure expression and serve as a neuronal target for mitigation. Methods: In a retrospective design, the MR sequences of ninety-two tumor patients [55% gliomas; 45% IM] and 34 controls were subjected to sophisticated morphometric and volumetric assessments using BrainSuite and MATLAB modules. We examined 103 regions of interests (ROIs) across eight distinct cortical categories of interests (COI) [gray matter, white matter; total volume, CSF; cortical areas: inner, mid, pial; cortical thickness]. The primary endpoint was quantifying and identifying ROIs with significant differences in z-scores based upon the presence of seizures. Feature selection employing neighborhood component analysis (NCA) determined the ROI within each COI having the highest significance/weight in the differentiation of seizure vs. non-seizure patients harboring brain tumor. Results: Overall, the mean age of the cohort was 58.0 ± 12.8 years, and 45% were women. The prevalence of seizures in tumor patients was 28%. Forty-two ROIs across the eight pre-defined COIs had significant differences in z-scores between tumor patients presenting with and without seizures. The NCA feature selection noted the volume of pars-orbitalis and right middle temporal gyrus to have the highest weight in differentiating tumor patients based on seizures for three distinct COIs [GM, total volume, and CSF volume] and white matter, respectively. Left-sided transverse temporal gyrus, left precuneus, left transverse temporal, and left supramarginal gyrus were associated with having the highest weight in the differentiation of seizure vs. non-seizure in tumor patients for morphometrics relating to cortical areas in the pial, inner and mid regions and cortical thickness, respectively. Conclusion: Our study elucidates potential biomarkers for seizure targeting in patients with gliomas and IMs based upon morphometric and volumetric assessments. Amongst the widespread brain regions examined in our cohort, pars orbitalis, supramarginal and temporal gyrus (middle, transverse), and the pre-cuneus contribute a maximal potential for differentiation of seizure patients from non-seizure.
RESUMEN
BACKGROUND: Depression is a common comorbidity of Parkinson's disease (PD); however, the impact of antidepressant status on cortical function in parkinsonian depression is not fully understood. While studies of resting state functional MRI in major depression have shown that antidepressant treatment affects cortical connectivity, data on connectivity and antidepressant status in PD is sparse. OBJECTIVE: We tested the hypothesis that cortico-limbic network (CLN) resting state connectivity is abnormal in antidepressant-treated parkinsonian depression. METHODS: Thirteen antidepressant-treated depressed PD and 47 non-depressed PD participants from the Parkinson's Progression Markers Initiative (PPMI) database were included. Data was collected using 3T Siemens TIM Trio MR scanners and analyzed using SPM and CONN functional connectivity toolbox. Volumetric analysis was also performed using BrainSuite. RESULTS: We found decreased connectivity in the antidepressant-treated depressed PD group when compared to non-depressed PD between the left frontal operculum and bilateral insula, and also reduced connectivity between right orbitofrontal cortex and left temporal fusiform structures. Increased depression scores were associated with decreased insular-frontal opercular connectivity. No ROI volumetric differences were found between groups. CONCLUSION: Given the relationship between depression scores and cortico-limbic connectivity in PD, the abnormal insular-frontal opercular hypoconnectivity in this cohort may be associated with persistent depressive symptoms or antidepressant effects.