A pioneering FreeSurfer volumetric study of a series of patients with mesial temporal lobe epilepsy and hippocampal sclerosis with comorbid depression

Bibliometric analysis of research in epilepsy and comorbid depression from 2014 to 2023

BACKGROUND

Epilepsy and depression have complicated bidirectional relationships. Our study aimed to explore the field of epilepsy comorbid with depression in a bibliometric perspective from 2014-2023.

AIM

To improve our understanding of epilepsy and depression by evaluating the relationship between epilepsy and depression, bibliometric analyses were performed.

METHODS

Epilepsy and depression-related publications from the last decade were retrieved from the Web of Science Core Collection. We conducted bibliometric and visual analysis using VOSviewer and CiteSpace, examining authorships, countries, institutions, journals of publication, co-citations of references, connections between keywords, clusters of keywords, and keywords with citation bursts.

RESULTS

Over the past ten years, we collected 1045 research papers focusing on the field of epilepsy and comorbid depression. Publications on epilepsy and depression have shown a general upward trend over time, though with some fluctuations. The United States, with 287 articles, and the University of Melbourne, contributing 34 articles, were the top countries and institutions, respectively. In addition, in the field of epilepsy and depression, Professor Lee, who has published 30 articles, was the most contributing author. The hot topics pay attention to the quality of life in patients with epilepsy and depression.

CONCLUSION

We reported that quality of life and stigma in patients with epilepsy comorbid with depression are possible future hot topics and directions in the field of epilepsy and depression research.

Cortical thickness and grey-matter volume anomaly detection in individual MRI scans: Comparison of two methods

Over the past decades, morphometric analysis of brain MRI has contributed substantially to the understanding of healthy brain structure, development and aging as well as to improved characterisation of disease related pathologies. Certified commercial tools based on normative modeling of these metrics are meanwhile available for diagnostic purposes, but they are cost intensive and their clinical evaluation is still in its infancy. Here we have compared the performance of "ScanOMetrics", an open-source research-level tool for detection of statistical anomalies in individual MRI scans, depending on whether it is operated on the output of FreeSurfer or of the deep learning based brain morphometry tool DL + DiReCT. When applied to the public OASIS3 dataset, containing patients with Alzheimer's disease (AD) and healthy controls (HC), cortical thickness anomalies in patient scans were mainly detected in regions that are known as predilection areas of cortical atrophy in AD, regardless of the software used for extraction of the metrics. By contrast, anomaly detections in HCs were up to twenty-fold reduced and spatially unspecific using both DL + DiReCT and FreeSurfer. Progression of the atrophy pattern with clinical dementia rating (CDR) was clearly observable with both methods. DL + DiReCT provided results in less than 25 min, more than 15 times faster than FreeSurfer. This difference in computation time might be relevant when considering application of this or similar methodology as diagnostic decision support for neuroradiologists.

[Structural brain changes in patients with temporal lobe epilepsy and comorbid depression]

OBJECTIVE

To assess the morphological features of the brain structures in patients with temporal lobe epilepsy and comorbid depression.

MATERIAL AND METHODS

From 1 January 2017 to 31 December 2020, we studied 80 patients with temporal lobe epilepsy (aged 18-60 years, 38 of whom had comorbid depression) and 48 healthy subjects of comparable age. Magnetic resonance imaging (MRI) of the brain was performed using the epilepsy protocol in a scanner with a magnetic field strength of 1.5 T. Focal temporal lobe epilepsy was diagnosed by neurologists (epileptologists) specialising in epilepsy according to the International League Against Epilepsy (ILAE) classification of epilepsy. Psychiatrists assessed the presence and severity of depressive disorders by clinical interview and by participants' scores on the Beck Depression Inventory (BDI-II). MRI data were processed using FreeSurfer 6.0 software to determine volumes of subcortical structures and thicknesses of cortical structures. At the group level, analysis of covariance with Holm-Bonferroni correction was used as the statistical method.

RESULTS

Morphometric analysis revealed a significant decrease in the volume of the thalamus bilaterally and the brain stem and an increase in the volume of the choroid plexus in the left hemisphere, as well as a significant decrease in the thickness of the entorhinal cortex, temporal pole and isthmus of the cingulate gyrus in the left hemisphere and middle temporal gyrus and inferior temporal gyrus in the right hemisphere in patients with epilepsy compared to healthy controls. No association was found between the presence of depression and significant structural changes on MRI.

CONCLUSION

The data obtained suggest an effect of temporal lobe epilepsy, but not comorbid depression, on the morphology of brain structures.

Epilepsy in Pediatric Patients—Evaluation of Brain Structures’ Volume Using VolBrain Software

Epilepsy is one of the most frequent serious brain disorders. Approximately 30,000 of the 150,000 children and adolescents who experience unprovoked seizures are diagnosed with epilepsy each year. Magnetic resonance imaging is the method of choice in diagnosing and monitoring patients with this condition. However, one very effective tool using MR images is volBrain software, which automatically generates information about the volume of brain structures. A total of 57 consecutive patients (study group) suffering from epilepsy and 34 healthy patients (control group) who underwent MR examination qualified for the study. Images were then evaluated by volBrain. Results showed atrophy of the brain and particular structures—GM, cerebrum, cerebellum, brainstem, putamen, thalamus, hippocampus and nucleus accumbens volume. Moreover, the statistically significant difference in the volume between the study and the control group was found for brain, lateral ventricle and putamen. A volumetric analysis of the CNS in children with epilepsy confirms a decrease in the volume of brain tissue. A volumetric assessment of brain structures based on MR data has the potential to be a useful diagnostic tool in children with epilepsy and can be implemented in clinical work; however, further studies are necessary to enhance the effectiveness of this software.

Subcortical Volume Changes in Early Menopausal Women and Correlation With Neuropsychological Tests

Background: The aging process and declining estradiol levels are two important factors that cause structural brain alterations. Many prior studies have investigated these two elements and revealed controversial results in menopausal women. Here, a cross-sectional study was designed to individually evaluate estradiol-related structural changes in the brain. Methods: A total of 45 early menopausal women and 54 age-matched premenopausal controls were enrolled and subjected to magnetic resonance imaging (MRI) scans, blood biochemistry tests, and neuropsychological tests. MRI structural images were analyzed using FreeSurfer to detect changes in subcortical and cortical volumes as well as cortical thickness. Finally, structural brain data as well as clinical and neuropsychological data were used for Pearson's correlation analyses to individually determine estradiol-related structural and functional changes in the brains of early menopausal women. Results: Compared with the premenopausal controls, the early menopausal women showed significant subcortical volumetric loss in the left amygdala and right amygdala, higher serum follicle-stimulating hormone (FSH) levels, more recognizable climacteric and depressive symptoms, decreased quality of sleep, and decreased working memory and executive functions. Simultaneously, FSH levels were related to lower working memory accuracy and longer working memory reaction time. Decreased subcortical volume in the bilateral amygdala was also related to lower working memory accuracy and longer executive reaction time in early menopausal women. Conclusion: The data suggest that estradiol deficiency in early menopausal women can lead to subcortical volume and functional brain changes, which may contribute to further understanding the neurobiological role of declined estradiol levels in early menopausal women.