Analysis of brain volume in hippocampal sclerotic temporal lobe epilepsy using automatic brain segmentation technology

Introduction

Temporal lobe epilepsy (TLE) is a focal epilepsy characterized by lesions in the temporal lobe structures. It is one of the most common drug-refractory epilepsies in adults (1). Hippocampal sclerosis (HS) is considered the leading cause of TLE. Classic imaging manifestations include reduced hippocampal volume (2) and increased hippocampal signal on T2-weighted imaging (T2WI) or T2-fluid-attenuated inversion recovery (T2FLAIR) (3). Other indirect imaging signs include blurred hippocampal stripes, flattened finger-like processes, enlarged temporal horns of the ipsilateral lateral ventricle, and atrophy in the ipsilateral fornix, mammillary body, and temporal lobe (4) (Figure 1A).

Figure 1 Schematic diagram of brain volume segmentation. (A1-A3) The coronal and axial classic MRI images of the control group, the LTLE-HS group and the RTLE-HS group respectively. The arrows indicate the hardened left seahorse, and the triangle indicates the hardened right seahorse. It can be observed that the volume of the sclerotic hippocampus decreases, the T2FLAIR signal increases, and the temporal angle on the affected side widens. (B1-B3) The segmentation process of T1-MPRAGE images in FreeSurfer and extracting the regions of interest from them. (C1-C3) FreeSurfer’s automatic segmentation of hippocampal subregions. CA, cornu ammonis; GC-DG, granule cell layer of the dentate gyrus; HP-tail, hippocampal tail; LTLE-HS, left-sided hippocampal sclerotic temporal lobe epilepsy; MRI, magnetic resonance imaging; RTLE-HS, right-sided hippocampal sclerotic temporal lobe epilepsy; T1-MPRAGE, T1-weighted magnetization-prepared rapid gradient-echo; T2FLAIR, T2-fluid-attenuated inversion recovery.

Epileptic seizures can cause significant adverse effects, such as loss of consciousness, convulsions, spasms, sleep disorders, and depression, which significantly impact patients’ quality of life (5). Therefore, epilepsy treatment aims to reduce or control seizure frequency and severity to improve the quality of life for patients (6). Studies have shown that surgery for patients with drug-refractory epilepsy can significantly reduce seizure frequency and potentially terminate epileptic seizures (7). The key factor in surgery is accurately locating the epileptogenic focus and determining its scope of involvement (8).

Neuroimaging studies have shown that the white matter affected by epileptic seizures in patients with unilateral hippocampal sclerotic temporal lobe epilepsy (TLE-HS) extends beyond the medial temporal lobe, involving the temporal area, parahippocampal gyrus, amygdala, thalamus, and some contralateral brain regions (9-11). Structural and functional abnormalities are most significant near the sclerotic hippocampus (12). Previously, technical limitations hindered the quantitative analysis of brain regions involved in epileptogenic lesions. Recently, the application of brain segmentation technology has provided a meaningful way to study brain tissue damage in TLE-HS. The FreeSurfer automatic segmentation technique effectively overcomes the shortcomings of manual segmentation, such as strong subjectivity and poor reproducibility (13,14), and it extracts precise volumes of key regions of interest and provides absolute measures of brain structures. Notably, its segmentation results closely align with the gold standard of manual segmentation (15,16).

With the development and application of automatic brain segmentation technology, Beheshti et al. found in morphometric analysis based on whole-brain voxels that the overall temporal lobe white matter volume of patients with TLE-HS changes (17). However, changes in the volume of temporal lobe subregions and contralateral brain regions have not been elucidated. This study uses automatic brain segmentation technology based on surface morphology measurement analysis to analyze the brain volume of TLE-HS patients and explore the clinical application value of this technology in TLE-HS patients. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-723/rc).

Methods

Research subjects

The study was approved by the Ethics Review Committee of General Hospital of Ningxia Medical University (2023-01-01) (No. KYLL-2021-0295), and conducted in accordance with the Helsinki Declaration and its subsequent amendments. All included investigators signed informed consent. According to the 2017 diagnostic criteria for TLE established by the International League Against Epilepsy (ILAE), this study enrolled 60 patients with unilateral TLE-HS who underwent magnetic resonance imaging (MRI) scans at General Hospital of Ningxia Medical University due to epileptic symptoms from January 2023 to February 2024. Among them, 34 patients had left-sided TLE-HS (LTLE-HS), and 26 patients had right-sided TLE-HS (RTLE-HS). During the same period, 35 healthy controls matched by gender and age were recruited. Inclusion criteria for the TLE-HS group: (I) clinical diagnosis of epilepsy according to the ILAE diagnostic criteria; (II) symptomatology and electroencephalogram consistent with TLE; (III) positive unilateral HS on cranial MRI; (IV) MRI examinations performed between epileptic seizures; and (V) all participants were right-handed.

Exclusion criteria for the TLE-HS group: (I) other diseases causing epileptic symptoms, such as tumors, trauma, or inflammation; (II) congenital brain malformation; and (III) poor MRI image quality, inability to perform automatic segmentation, or mismatched segmentation.

Inclusion criteria for the control group: (I) no family history of epilepsy or other neurological diseases; (II) no neurological diseases, such as brain tumors, brain trauma, or inflammation; (III) no history of chronic diseases, such as cardiovascular and cerebrovascular diseases or diabetes; (IV) negative results of cranial MRI; (V) age and gender-matched with those of the case group; and (VI) all participants were right-handed.

MRI data acquisition

MRI scanning was performed on all subjects using a GE SIGNA Architect 3.0 T MRI instrument (Beijing, China) with a 48-channel phased array head coil. All subjects underwent scans using the same scanning protocol. The main scanning sequence parameters are shown in Table 1.

Image post-processing

After the T1-weighted magnetization-prepared rapid gradient-echo (T1-MPRAGE) scan, the original image was obtained, and the whole brain was segmented using FreeSurfer software, developed by MIT Health Sciences & Technology and Massachusetts General Hospital. FreeSurfer is an open-source segmentation tool that uses subcortical structural maps to mark brain structures, which are then aligned and fused with magnetic resonance (MR) images to generate gray and white matter segmentation surfaces and gray matter and cerebrospinal fluid segmentation surfaces. The thickness and volume of gray and white matter are calculated based on these surfaces (18,19). FreeSurfer has been proven to be an accurate and reliable tool for measuring the cortical thickness and volume of neuroanatomical structures (20). The whole-brain automatic segmentation was performed using the software FreeSurfer7.3.2 on an Ubuntu20.04 system built on an 8-core HP workstation. After running the software for about 4.5 hours, brain volume segmentation images and whole brain structure volumes were obtained. From the volume values, the white matter volumes of the bilateral temporal lobe subregions (posterior superior temporal gyrus, temporal pole, transverse temporal gyrus, superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus), fusiform gyrus, parahippocampal gyrus, insula, and the volumes of the hippocampus, thalamus, and amygdala were extracted (Figure 1B). Hippocampal subfield segmentation: based on recon-all, the command segmentHA_T1.sh is executed for precise hippocampal subfield segmentation, dividing the bilateral hippocampus into the following subregions (Figure 1C): subiculum (Sub), cornu ammonis (CA)1, CA2/3, CA4, granule cell layer of the dentate gyrus (GC-DG), and hippocampal tail (HP-tail). This study focuses on the relationship between overall hippocampal atrophy and changes in temporal lobe white matter volume, therefore the total hippocampal volume from the template was used for statistical analysis.

Statistical analysis

Statistical analysis was performed using SPSS 26.0 software. The Kruskal-Wallis test and χ² test were used to analyze age and gender differences between the control, LTLE-HS, and RTLE-HS groups. The paired t-test (for normal distribution data) or two-related sample Wilcoxon test (for non-normal distribution data) was used to compare brain volume differences between the left and right sides of the control group. The independent sample t-test (for normal distribution data) or two-sample Mann-Whitney U test (for non-normal distribution data) was used to compare brain volume differences between the control group, the LTLE-HS group, and the RTLE-HS group. To control the risk of the first type of error caused by multiple comparisons, for the inter-group comparisons between a and b, and a and c, the Bonferroni method was adopted for multiple correction. The white matter volume of patients with TLE-HS was further correlated with the course, frequency, and duration of disease. Absolute value of correlation coefficient (|r|) ≥0.8 was defined as highly correlated, 0.5≤ |r| <0.8 was moderately correlated, 0.3≤ |r| <0.5 was low correlation, and 0< |r| <0.3 was weakly correlated.

Results

Demographic data

This study included 60 patients with unilateral TLE-HS, comprising 29 males and 31 females. Among them, 34 patients had LTLE-HS, aged 15–55 years (mean 31.68±10.76 years), and 26 patients had RTLE-HS, aged 15–56 years (mean 35.38±13.58 years). Additionally, there were 35 healthy controls, including 19 females and 16 males, with a mean age of 35.86±12.37 years. There were no statistically significant differences in gender or age among the three groups (P>0.05) (Table 2).

Differences in brain volume between the left and right sides of the control group

The brain volumes of the left and right sides of the control group followed a normal distribution. Paired t-test results indicated significant differences in the white matter volume of the left and right temporal regions (transverse temporal gyrus, superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus, and parahippocampal gyrus) and the volumes of the amygdala and hippocampus: transverse temporal gyrus: t=8.034, P<0.001; superior temporal gyrus: t=11.855, P<0.001; middle temporal gyrus: t=−9.655, P<0.001; inferior temporal gyrus: t=3.940, P<0.001; parahippocampal gyrus: t=−2.625, P=0.013; hippocampus: t=−6.227, P<0.001; amygdala: t=−5.119, P<0.001.

The transverse temporal gyrus, superior temporal gyrus, and inferior temporal gyrus were left-dominant, while the middle temporal gyrus, parahippocampal gyrus, hippocampus, and amygdala were right-dominant. No significant differences were found in the volumes of the posterior superior temporal gyrus, temporal pole, fusiform gyrus, insula, and thalamus (all P>0.05). The results remained consistent after standardization (standard volume value = absolute volume/total brain volume × 100%).

Differences in brain volume of the affected side of the LTLE-HS group, RTLE-HS group, and the control group

Significant differences were observed in the volumes of the temporal white matter (middle temporal gyrus, inferior temporal gyrus, fusiform gyrus, parahippocampal gyrus), hippocampus, and thalamus between the left side of the control group and the affected side of the LTLE-HS group: middle temporal gyrus: t=2.762, P=0.007; inferior temporal gyrus: t=3.995, P<0.001; fusiform gyrus: t=3.393, P=0.001; parahippocampal gyrus: t=4.851, P<0.001; hippocampus: t=6.058, P<0.001; thalamus: t=3.927, P<0.001. No significant differences were found in the volumes of the posterior superior temporal gyrus, temporal pole, transverse temporal gyrus, superior temporal gyrus, insula, and amygdala (P>0.05).

For the RTLE-HS group compared to the control group, significant differences were found in the white matter volume, hippocampus, and thalamus volumes in the right temporal region (middle temporal gyrus, and parahippocampal gyrus): middle temporal gyrus: t=2.784, P=0.008; parahippocampal gyrus: t=4.833, P<0.001; hippocampus: t=7.130, P<0.001; thalamus: t=3.003, P=0.004. No significant differences were found in the volumes of the posterior superior temporal gyrus, temporal pole, transverse temporal gyrus, superior temporal gyrus, inferior temporal gyrus, amygdala, and insula (all P>0.05) (Table 3, Figure 2A).

Figure 2 Comparison of regional volumes of different ROIs in left hemisphere (A) and right hemisphere (B) among. *, indicated the significant differences in white matter volume between the control group and the case group (*, P<0.05; **, P<0.01; ***, P<0.001; ns, not significant, P>0.05), which were calculated using the independent sample t-test. HC, healthy control; LTLE-HS, left-sided hippocampal sclerotic temporal lobe epilepsy; ROI, region of interest; RTLE-HS, right-sided hippocampal sclerotic temporal lobe epilepsy.

Differences in brain volume of the contralateral parts of the LTLE-HS group, RTLE-HS group, and the control group

Significant differences were observed in the volumes of the posterior superior temporal gyrus, middle temporal gyrus, parahippocampal gyrus, and thalamus between the right side of the control group and the contralateral side of the LTLE-HS group: middle temporal gyrus: t=2.481, P=0.016; parahippocampal gyrus: t=3.715, P<0.001; thalamus: t=3.224, P=0.002. No significant differences were found in the volumes of the temporal pole, transverse temporal gyrus, superior temporal gyrus, inferior temporal gyrus, fusiform gyrus, hippocampus, insula, and amygdala (all P>0.05).

In the RTLE-HS group, there was a statistically significant difference in the amygdala volume between the contralateral and corresponding sides in the control group (t=−4.421, P<0.001). However, there were no statistically significant differences in the volumes of the posterior superior temporal gyrus, temporal pole, transverse temporal gyrus, superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus, fusiform gyrus, parahippocampal gyrus, hippocampus, thalamus, and insula (all P>0.05) (Table 3, Figure 2B).

Correlation analysis

In LTLE-HS, the volumes of the temporal superior gyrus, hippocampus, parahippocampal gyrus, amygdala, thalamus, contralateral parahippocampal gyrus, transverse temporal gyrus, temporal superior gyrus and amygdala on the affected side were negatively correlated with the course of the disease at a low level, and the volume of the fusiform gyrus on the affected side was negatively correlated with the course of the disease at a moderate level. In RTLE-HS, the temporal superior gyrus on the affected side was negatively correlated with the course of the disease at a low level (Table 4).

Discussion

This study employed FreeSurfer, a software for surface morphology measurement and analysis, to conduct whole-brain automatic segmentation and investigate changes in brain volume between LTLE-HS and RTLE-HS. Building on previous research, our findings further confirm that the extent of brain damage varies between LTLE-HS and RTLE-HS, providing critical imaging evidence for preoperative evaluation, surgical planning, and prognosis in TLE-HS patients.

Analysis of left and right brain volumes in the healthy control group

Our results indicate significant differences in the volumes of the left and right transverse temporal gyrus, superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus, hippocampus, parahippocampal gyrus, and amygdala in the control group. Conversely, no significant differences were found in the volumes of the posterior superior temporal gyrus, temporal pole, fusiform gyrus, insula, and thalamus. Previous studies, such as those by Liang et al., have shown that structural and functional asymmetry in the cerebral hemispheres is common in healthy individuals, with asymmetry patterns influenced by handedness, gender, and age (21). All 38 healthy controls in this study were right-handed, with no statistical differences in gender and age. Yet, differences were observed in the volume of the bilateral temporal region, parahippocampal gyrus, and amygdala. The consistency of the results after volume standardization with previous studies supports the conclusion that asymmetry in brain volume is present in detailed temporal lobe subregions, hippocampus, and amygdala.

Analysis of brain volume changes in the affected side of LTLE-HS and RTLE-HS compared to the control group

Extensive white matter damage in both cerebral hemispheres of the TLE-HS group has been reported, with more severe damage observed in the dominant hemisphere where the epileptogenic focus is located (22). After excluding factors such as frequency of onset and course of disease, our results showed that for the affected side of TLE-HS, the white matter volume of the subregion closer to the hardened hippocampus decreased significantly. Atrophy is most pronounced in the parahippocampal gyrus, fusiform gyrus, and inferior temporal gyrus adjacent to the sclerotic hippocampus. Additionally, extratemporal brain tissue located distant from the sclerotic hippocampus and white matter in contralateral brain regions are also affected to some extent. Furthermore, this study found that brain tissue atrophy in LTLE-HS was more pronounced than in RTLE-HS, which aligns with previous research findings (23-25).

This study also revealed that the range of white matter affected by LTLE-HS and RTLE-HS was inconsistent, with more subregions exhibiting significant white matter volume reduction in the temporal lobe of LTLE-HS compared to RTLE-HS. Patients with LTLE-HS showed significant volume reduction in the middle temporal gyrus, inferior temporal gyrus, fusiform gyrus, hippocampus, parahippocampal gyrus, and thalamus, while the volume reduction in RTLE-HS was concentrated in the middle temporal gyrus, hippocampus, parahippocampal gyrus, and thalamus. Literature reports suggest that the lateralization effect of the disease may be influenced by physiological networks, with different connections between the dominant and non-dominant hemispheres potentially playing a role (26). Epileptic seizures originating from the dominant hemisphere may cause more extensive excitotoxic damage, resulting in more severe brain tissue damage in the dominant hemisphere where the epileptogenic focus is located. Given that all subjects in this study were right-handed, with the left hemisphere being dominant in most cases, the more extensive white matter damage observed in LTLE-HS compared to RTLE-HS may be attributed to differences in the connectivity between left and right dominant hemisphere structures (27,28).

Analysis of brain volume changes in the contralateral parts of the LTLE-HS group, RTLE-HS group, and control group

Research has shown that alterations in the functional connectivity between medial temporal lobe structures in TLE-HS patients may lead to disruption of white matter fiber structures projecting within and outside the temporal lobe, affecting connections to the contralateral hemisphere to varying extents (29). Our study revealed that the volumes of the contralateral middle temporal gyrus, parahippocampal gyrus, and thalamus in the LTLE-HS group were significantly reduced compared to the control group, with the parahippocampal gyrus and thalamus exhibiting particularly pronounced reductions. In contrast, aside from the amygdala, no significant changes were observed in the contralateral brain volume of the RTLE-HS group. Zanao et al. identified through their study of white matter fiber bundle structural changes in TLE-HS that LTLE-HS affects bilateral brain volumes more extensively. In contrast, RTLE-HS primarily impacts the affected side, with less pronounced effects on the contralateral hemisphere, a finding confirmed post-surgically (30,31).

Our study further substantiates that compared to RTLE-HS, LTLE-HS exhibits significantly reduced contralateral brain volumes, indicating more severe and extensive white matter damage in the contralateral hemisphere. This asymmetrical white matter damage in LTLE-HS and RTLE-HS may stem from uneven innervation of fiber bundles in the left and right cerebral hemispheres (32). When the epileptogenic focus is in the left hemisphere, excitotoxic damage from seizures may more readily affect the contralateral side. This disparity in white matter damage severity between LTLE-HS and RTLE-HS could also be attributed to differing physiological network connections between dominant and non-dominant hemispheres (24). Other studies suggest that varying maturation rates between hemispheres may additionally explain this asymmetric change, highlighting developmental nervous system factors in the pathogenesis of TLE (33).

Furthermore, our study noted an increase in contralateral amygdala volume in both LTLE-HS and RTLE-HS, with RTLE-HS showing a more noticeable increase. The amygdala, as a crucial component of the subcortical region, exhibits a slight increase in volume despite the atrophy of other subcortical structures, particularly the bilateral thalamus. Previous studies have reported similar findings, with more focus on the swelling of the amygdala in TLE patients without HS. Such results can be interpreted as epileptic seizures damage the hippocampus and amygdala, leading to hippocampal neuronal loss and glial cell proliferation, though sparing amygdala neurons. Processes such as excitotoxic injury and neuroinflammation may increase amygdala volume, potentially reflecting differential stress protein expressions between the hippocampus and amygdala (34). The significance of the pathway between the amygdala and the anterior cingulate cortex is particularly relevant to anxiety disorders. Although psychiatric aspects were not assessed in this study, our findings may be correlated with the psychiatric characteristics observed in TLE-HS patients with amygdala enlargement. In this investigation, the thalamus exhibited bilateral significant damage in LTLE-HS, although the degree of damage was slightly less severe compared to that of the hippocampus. This can be explained as bilateral atrophy caused by Papez loop injury (35). Contrary to previous research, the contralateral thalamus in RTLE-HS did not demonstrate significant differences, which may be due to the smaller sample size of RTLE-HS patients, leading to discrepancies in the results.

Clinical application value of automatic brain segmentation technology for brain volume analysis

Surgery has become pivotal in treating refractory epilepsy, including excision surgery like anterior temporal lobectomy or selective amygdala-hippocampal structure resection for mesial TLE (36). Our study included four unilateral TLE-HS patients who underwent surgical treatment, with three having LTLE-HS and one RTLE-HS. Before surgery, we conducted volumetric analyses of temporal white matter, insula, thalamus, and amygdala in these patients. Results indicated bilateral brain volume reductions in LTLE-HS patients, while RTLE-HS patients primarily exhibited volume changes on the affected side. Post-surgery follow-up showed three patients remained seizure-free nearly 2 years post-operatively, and one patient was seizure-free for almost a year, underscoring surgery’s critical role in treatment (37). Automatic brain segmentation technology facilitates the accurate localization of epileptogenic foci and their affected areas, pivotal for preoperative evaluations, surgical approach selection, and prognosis assessment. Furthermore, our study corroborates that LTLE-HS and RTLE-HS present differing patterns of brain tissue damage, potentially contributing to distinct functional impairments like language deficits in LTLE-HS versus visual impairments in RTLE-HS (38). This technology aids in identifying the lateralization of epileptogenic foci and assessing the extent of white matter damage in LTLE-HS and RTLE-HS. Based on the results of quantitative analysis, individualized surgical approaches will be formulated. During surgical resection, it is imperative to preserve more functional white matter adjacent to the focal lesions in order to enhance prognosis and mitigate potential complications (39-41).

Correlation analysis

In this study, we observed a negative correlation between white matter volume in the subregions of the temporal lobe and disease duration in patients with TLE-HS. This correlation was particularly pronounced in patients with LTLE-HS, where white matter volume across multiple subregions diminished as disease duration increased. This phenomenon highlights the progressive degenerative characteristics of the temporal-limbic system throughout the chronic course of epilepsy, indicating that disease duration may serve as a significant driving factor for white matter degeneration. Previous studies assessing the impact of TLE on brain structure have demonstrated that longer disease duration correlates with greater impairment of white matter integrity. Potential underlying mechanisms include recurrent seizures that lead to axonal loss, reduced membrane density, and increased extracellular volume, all of which collectively contribute to the overall decline in white matter integrity (42). The detrimental effects of chronic epileptic activity on brain structure are particularly evident in regions critical for cognitive functions, such as memory and language, where a reduction in structural volume may lead to corresponding cognitive impairments (43,44). The observed negative correlation between white matter volume and disease duration represents a significant finding, highlighting the necessity for continuous monitoring of brain structural changes in patients with TLE-HS. This suggests that an extended disease duration may contribute to cognitive decline. Future research should adopt multimodal approaches to further investigate the relationship between cognitive function and white matter integrity. Furthermore, this study indicates that there is no significant association between seizure frequency and duration with various testing parameters, suggesting that these factors may not significantly influence the progression of TLE.

A comparative analysis of this study with previous studies

Voxel-based morphometry (VBM) and FreeSurfer are two widely utilized methods for extracting information about brain anatomical structures. However, VBM has limitations in terms of anatomical specificity, as its results are derived from voxel clusters, making it difficult to accurately localize specific anatomical structures. In contrast, FreeSurfer is generally considered more accurate and reliable for the segmentation of subcortical nuclei, particularly the hippocampus, closely approximating the gold standard of manual segmentation. Additionally, FreeSurfer can precisely model cortical geometry, a feat that VBM struggles to achieve.

Zheng et al. utilized the VBM technique to identify a reduction in gray matter in the hippocampus, parahippocampal gyrus, and thalamus of patients with TLE-HS (45). However, due to the inherent limitations of the VBM technique, it was not possible to report significant gray matter volume (GMV) changes specifically or commonly between LTLE-HS and RTLE-HS patients. Mugikura et al. further employed the VBM technique to conduct a more detailed study on the asymmetric alterations and common changing regions in LTLE-HS and RTLE-HS (46); however, they did not elucidate the correlation between the disease’s course, frequency of onset, duration, and GMV changes. The current study utilized FreeSurfer technology for more precise and detailed segmentation, revealing significant atrophy in the hippocampus and thalamus on the affected side in patients with TLE-HS, which aligns with previous VBM research findings. Additionally, this study found that the white matter volume in the temporal lobe of LTLE-HS patients was more extensively affected bilaterally in the temporal regions compared to RTLE-HS, with LTLE-HS exhibiting a broader range of involvement. The common area of damage in both conditions was located near the sclerotic hippocampus on the affected side. The white matter volume changes demonstrated in this study provide strong evidence that TLE-HS patients may exhibit different structural patterns of white matter abnormalities based on previous research, thereby enhancing our understanding of TLE pathology. The study conducted by Mugikura et al. revealed an increase in GMV in the contralateral hippocampus and associated regions in patients with RTLE-HS. Furthermore, the volume of the contralateral amygdala in RTLE-HS patients was significantly enlarged. There was also a slight trend towards increased white matter volume in the temporal region; however, this increase did not achieve statistical significance. These findings imply that persistent abnormal discharges in focal epilepsy may lead to extensive damage to the white matter in affected patients, potentially linked to compensatory mechanisms within neural networks.

Park et al. found that lateralization asymmetry in TLE-HS is primarily concentrated in the ipsilateral limbic cortex and hippocampus, while the subcortical and non-limbic cortices exhibit more bilateral progressive damage, potentially related to seizure frequency (47). In this study, the thalamus also exhibited significant bilateral damage in LTLE-HS, although the extent of damage was slightly less severe than that observed in the hippocampus. Contrary to previous research findings, our study did not reveal significant differences in the contralateral thalamus in RTLE-HS. This may be attributed to the limited number of RTLE-HS patient cases included, which could lead to variations in the results. Additionally, we observed that, unlike prior research findings, the white matter volume in the temporal lobe subregions of TLE-HS patients did not exhibit a significant correlation with seizure frequency or duration but was negatively correlated with the disease course. This suggests that the atrophy pattern associated with TLE in extensive, bilateral white matter regions demonstrates a distinct dynamic development trend.

Conclusions

In conclusion, our study utilizing automatic brain segmentation technology to analyze TLE-HS patients’ brain volumes revealed varying degrees of bilateral brain volume alterations, the impact of TLE-HS on brain volume varies according to the location of the epileptogenic focus. LTLE-HS typically involves bilateral white matter changes over a relatively extensive range, whereas RTLE-HS is primarily confined to the affected hemisphere, with the contralateral side exhibiting less involvement. This underscores the technology’s crucial role in preoperative evaluations, surgical planning, and prognostic assessments in epilepsy patients. With four cases pathologically confirmed as HS in this study, future research should include more pathological samples to validate these findings further.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-723/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-723/dss

Funding: This study was supported by the Ningxia Natural Science Foundation Project (No. 2023AAC03611) and the Ningxia Hui Autonomous Region Science and Technology Benefit the People Special Project (No. 2022CMG03051).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-723/coif). Y.H.X. is from GE HealthCare MR Research, Beijing, China. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Ethics Review Committee of the General Hospital of Ningxia Medical University (2023-01-01) (No. KYLL-2021-0295). All participants provided informed consent.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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