
==== Front
Neuroimage Clin
Neuroimage Clin
NeuroImage : Clinical
2213-1582
Elsevier

S2213-1582(24)00097-4
10.1016/j.nicl.2024.103658
103658
Regular Article
Region-specific MRI predictors of surgical outcome in temporal lobe epilepsy
Fadaie Fatemeh a
Caldairou Benoit a
Gill Ravnoor S. a
Foit Niels A. ab
Hall Jeffery A. c
Bernhardt Boris C. d
Bernasconi Neda a1
Bernasconi Andrea andrea.bernasconi@mcgill.ca
a1⁎
a Neuroimaging of Epilepsy Laboratory, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
b Freiburg Medical Center, Department of Neurosurgery, University of Freiburg, Freiburg, Germany
c Department of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
d Multimodal Imaging and Connectome Analysis Lab, McConnell Brain Imaging Centre, Montreal Neurological Institute and Hospital, McGill University, Montreal, QC, Canada
⁎ Corresponding author at: Montreal Neurological Institute, 3801 University Street, Montreal, Quebec, H3A 2B4, Canada. andrea.bernasconi@mcgill.ca
1 Authors contributed equally.

20 8 2024
2024
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43 1036588 7 2024
18 8 2024
19 8 2024
© 2024 The Authors. Published by Elsevier Inc.
2024

https://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Highlights

• Seizure-free TLE patients have more severe pre-op mesiotemporal atrophy.

• Hippocampal atrophy and its resection extent predict seizure freedom in 89% of cases.

• Post-operative MRI anomalies do not affect surgical outcome.

Objective

In drug-resistant temporal lobe epilepsy (TLE), it is not well-established in how far surgery should target morphological anomalies to achieve seizure freedom. Here, we assessed interactions between structural brain compromise and surgery to identify region-specific predictors of seizure outcome.

Methods

We obtained pre- and post-operative 3D T1-weighted MRI in 55 TLE patients who underwent selective amygdalo-hippocampectomy (SAH) or anterior temporal lobectomy (ATL) and 40 age and sex-matched healthy subjects. We measured surface-based morphological alterations of the mesiotemporal lobe structures (hippocampus, amygdala, entorhinal and piriform cortices), the neocortex and the thalamus on both pre- and post-operative MRI. Using precise co-registration, in each patient we mapped the surgical cavity onto the MRI acquired before surgery, thereby quantifying the amount of pathological tissue resected; these features, together with the preoperative morphometric data, served as input to a supervised classification algorithm for postsurgical outcome prediction.

Results

On pre-operative MRI, patients who became seizure-free (TLE-SF) presented with severe ipsilateral amygdalar and hippocampal atrophy, while not seizure-free patients (TLE-NSF) displayed amygdalar hypertrophy. Stratifying patients based on the surgical approach, post-operative MRI showed similar patterns of mesiotemporal and thalamic changes, but divergent neocortical thinning affecting the parieto-temporo-occipital regions following ATL and the frontal lobes after SAH. Irrespective of the surgical approach, hippocampal atrophy on pre-operative MRI and its extent of resection were the most predictive features of seizure-freedom in 89% of patients (selected 100% across validations).

Significance

Our study indicates a critical role of the extent of resection of MRI-derived hippocampal morphological anomalies on seizure outcome. Precise pre-operative quantification of the mesiotemporal lobe provides non-invasive prognostics for individualized surgery.
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pmc1 Introduction

Drug-resistant temporal lobe epilepsy (TLE) associated with mesiotemporal sclerosis (MTS) is the prototype of surgically remediable focal epilepsy. A commonly used feature of MTS on MRI is hippocampal atrophy, a feature that has streamlined epilepsy surgery. While in most patients, surgery leads to seizure freedom and improved quality of life (Wiebe et al., 2001), about 30 % of carefully selected cases with unilateral electro-clinical and MRI features of MTS continue to have seizures (de Tisi et al., 2011).

Pre-operative MRI predictors of surgical outcome are critical for patient counseling. Several studies have emphasized that extent of resection of mesiotemporal lobe (MTL) structures is decisive (Bernhardt et al., 2015b, Radhakrishnan et al., 1998, Schramm, 2008, Sheikh et al., 2019), with some advocating the removal of the hippocampus and entorhinal cortex (Arruda et al., 1996, Bonilha et al., 2007), while others stressing the resection of the piriform cortex (Borger et al., 2021, Galovic et al., 2019). Previous studies, however, did not account for structural alterations that are differentially distributed within and across these structures, which may differ from patient to patient (Bernasconi et al., 2003, Bernhardt et al., 2015b); in other words, it is not established in how far surgery should target abnormal areas to achieve seizure freedom. Moreover, contributions of contralateral MTL or thalamic pathology have not been taken into consideration, despite work suggesting their potential role in broader pathological networks (He et al., 2017, Pereira et al., 2014).

Here, we assessed interactions between structural brain compromise and surgery to identify region-specific predictors of seizure outcome. Specifically, we measured morphological alterations of the MTL, the neocortex and the thalamus on both pre- and postoperative MRI. Using non-linear co-registration, in each TLE patient we mapped the surgical cavity onto the MRI acquired before surgery, thereby quantifying the amount of pathological tissue resected across the MTL and the temporal neocortex; these features, together with the preoperative morphometric data, served as input to a supervised classification algorithm for outcome prediction in single patients.

2 Material and methods

2.1 Subjects

We studied 55 consecutive patients with unilateral drug-resistant TLE (29 females, mean ± SD age = 37 ± 10 years, range = 17–61 years) evaluated and operated at the Montreal Neurological Hospital, and who agreed to undergo a research-dedicated MRI pre-operatively and at least three months after surgery. TLE diagnosis and lateralization of the seizure focus into left TLE (LTLE; n = 31) and right TLE (RTLE; n = 24) were determined by a comprehensive evaluation including detailed history, neurological examination, review of medical records, video-EEG recordings, neuropsychology, and clinical MRI. In nine patients, where the seizure onset was not localized, lateralization was established through stereoencephalography. No patient had a mass lesion (e.g., malformations of cortical development, tumor, vascular malformations) or a history of traumatic brain injury or encephalitis.

All surgeries were performed by a single neurosurgeon. Based on the presence or absence of hippocampal atrophy on clinical neuroradiological assessment, selective amygdalohippocampectomy (SAH; n = 35, 21 females, mean age = 36.1 ± 11.2 years, range = 17–61 years) or anterior temporal lobe resection (Olivier, 1988) (ATL; n = 20, 8 females, mean age = 38.2 ± 8.6 years, range = 26–50 years) was carried out. Demographic and clinical data of these patients are presented in Table 1. The mean interval between pre- and postoperative MRI was not different for the two procedures (SAH: 5.7 ± 3.2 months, range = 3–15 months; ATL: 5.6 ± 3.5 months, range = 3–13 months; t=0.11, p = 0.9). Based on the histological analysis of the resected specimen (Blumcke et al., 2013), there was a trend for a higher proportion of hippocampal cell loss and gliosis versus isolated gliosis in SAH compared to ATL (n = 29/6 vs. 11/9; χ2 = 3.67, p = 0.06). Mean follow-up time was similar between the two procedures (SAH: 89 ± 28 months, range: 30–132 months; ATL: 85 ± 33, range: 24–132; t=0.21, p = 0.8). While the proportion of Engel-I outcome was higher in SAH as compared to ATL, the difference did not reach significance (SAH: 26/35 = 74 %; ATL: 10/20 = 50 %; χ2 = 2.33, p = 0.1). When dichotomizing patients based on post-surgical seizure outcome (Supplementary Table), a higher proportion of HS was seen in TLE-SF than TLE-NSF, while TLE-NSF presented with a higher proportion of isolated gliosis. The control group consisted of 40 age- and sex-matched healthy individuals (21 females, mean age = 34.9 ± 12 years, range = 22–66 years).Table 1 Demographic and clinical information based on surgical procedure.

	Controls
(n = 40)	SAH
(n = 35)	ATL
(n = 20)	significance	
Age	35 ± 12	36 ± 11	38 ± 9	t=-0.97, p = 0.33	
Female	21	21	8	χ2 = 2.04, p = 0.36	
TLE (L/R)	−	19/16	12/8	χ2 = 0.16, p = 0.68	
Disease onset (yrs)	−	14 ± 10	15 ± 9	t = 0.69, p = 0.49	
FC	−	51 %	15 %	χ2 = 7.15, p = 0.007	
HS/G	−	29/6	11/9	χ2 = 3.67, p = 0.06	
SEEG	−	11 %	25 %	χ2 = 1.71, p = 0.19	
GTC	−	45 %	40 %	χ2 = 0.16, p = 0.68	
Engel 1	−	74 %	50 %	χ2 = 2.33, p = 0.1	
Follow-up (yrs)	−	7 ± 2.3	7 ± 2.7	t=0.21, p = 0.82	
Age, disease onset and follow up are represented in mean ± standard deviation years; SAH: selective amygdalohippocampectmy; ATL: anterior temporal lobectomy; FC=febrile convulsions; L/R=Left/Right; HS/G=hippocampal sclerosis/isolated gliosis; SEEG=stereoelectroencephalography; GTC=generalized tonic-clonic seizure.

2.2 Pre-operative morphometry

All pre- and post-operative images were acquired on the same scanner using a 3D T1-weighted fast field echo sequence (repetition time = 18 ms; echo time = 10 ms; flip angle = 30°; matrix = 256 × 256; field of view = 256 mm; isotropic voxel size of 1 mm3). Images underwent automated correction for intensity non-uniformity and intensity standardization (Sled et al., 1998). The pre-operative MRI of each patient and the MRI of each healthy control was linearly registered to the MNI152 template (Collins et al., 1994). Surface-based analysis of cortical thickness was performed as in our previous work (Bernhardt et al., 2010, Lee et al., 2022). An expert rater (NB), unaware of the subjects’ category (patient, control), segmented manually the mesiotemporal lobe (MTL) structures, namely the hippocampus (HP), amygdala (AM), entorhinal cortex (EC), and piriform cortex (PRC) on the pre-operative MRI of patients and controls according to previously published protocols (Bernasconi et al., 2003, Pereira et al., 2005). We have previously shown excellent intra- and inter-rater reliability in the measurement of the HP, AM and EC (Bernasconi et al., 1999); intra- and inter-observer reliability for the PRC is reported in the Supplementary material. The thalamus (THA) was automatically segmented using FSL (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki). To compute volume change, after converting MTL and THA labels to surface meshes, we quantified expansion or shrinkage based on the Jacobian determinants of the surface displacement vectors using a previously published method (Kim et al., 2008).

2.3 Pre-to-post operative morphometry

Fig. 1 illustrates the procedure to compute pre- to post-operative morphological changes of the MTL and the neocortex. For each patient, the post-operative MRI was linearly registered to the pre-operative MRI in native space. We then linearly mapped the post-operative MRI to the MNI152 template by concatenating the transformation matrix of pre- to post-operative registration with the one resulting from the registration of the pre-operative MRI to the MNI152 template; this procedure guaranteed an optimal alignment of post- to pre-operative images in a common space. After manually delineating the surgical cavity on the post-operative MRI in native space, we used the previously obtained concatenated transformation to linearly register the resulting label to the MNI152 template. To further refine the co-registration of the post- to the pre-operative MRI, we used a multiscale non-linear deformation technique (Collins et al., 1995) that performs iterative global-to-local warping, thereby minimizing image dissimilarity. Furthermore, we excluded the surgical cavity via cost function masking in order to minimize its impact on the registration procedure (Brett et al., 2001); in other words, the cavity was not included when calculating image dissimilarity. Using the inverse of the resulting transform, we warped the cavity to the pre-operative MRI and intersected it with GM and WM surfaces as well as the HP, AM, EC and PRC surfaces, thereby delineating the resection area. The accuracy of each step was verified in all individuals.Fig. 1 MRI pre-processing. A) Mapping surgical cavity to pre-operative MRI. 1. For each individual, post- and pre-operative T1-weighted images underwent automated correction for intensity non-uniformity and intensity standardization. 2. The post-operative MRI was first linearly registered to the pre-operative MRI in native space and then linearly mapped to the MNI152 template. 3. The surgical cavity was manually delineated, non-linearly registered to the pre-operative MRI and intersected with the mesiotemporal labels. B) Computation of resected anomaly. After converting the preoperative mesiotemporal labels to surface meshes, point-wise volume changes were calculated and thresholded at a z-score ≥ 1.5 with respect to healthy controls. In parallel, the resection cavity was overlaid on the mesiotemporal surfaces. The percent resected anomaly was computed as the ratio between the resected anomaly area and the total anomaly area.

2.4 Statistical analysis

Analyses were conducted using SurfStat (https://www.math.mcgill.ca/keith/surfstat/) for MATLAB (The Mathworks, Natick, MA, R2021b). Prior to all analyses, patients’ left and right hemispheric data were sorted relative to the epileptogenic focus (i.e., into ipsi- and contralateral). To minimize confounds related to interhemispheric asymmetries, prior to sorting, we normalized measures at a given vertex using a z-transformation with respect to the corresponding distribution in healthy controls.

On pre-operative MRI, vertex-wise two-tailed Student’s t-tests compared MTL and THA volume, as well as neocortical thickness between patients and controls. In clusters of significant findings, linear models assessed differences between seizure-free (TLE-SF, Engel I) vs. not seizure-free patients (TLE-NSF, Engel II-IV), and SAH vs. ATL. For significant findings, we calculated the Cohen’s d effect size.

Linear mixed-effects models assessed effects of surgery on post-operative morphometry of the MTL structures, the THA, and the neocortex. This framework flexibly analyses within-subjects repeated measurements with irregular intervals. We tested the main effects of SAH and ATL separately, with subjects as random effect and differences between scan dates as fixed effect. For neocortical analysis, we further corrected for fixed effects of volume of resection and pre-operative cortical thickness. In clusters of significant findings, linear models assessed differences between TLE-SF and TLE-NSF.

To assess the relationship between extent of resection and seizure outcome, for each patient, we determined the percent of resected morphological alterations within each MTL structure and the neocortex, calculated as the ratio between the area of anomaly within the surgical cavity and the total area of the pre-operative alteration (defined as ≥ |1.5 SD| beyond the mean of healthy controls). Linear models assessed group-level relations between the resected alteration and seizure outcome comparing TLE-SF and TLE-NSF cohorts; analyses were repeated controlling for type of surgery, whole-brain cortical thickness, volume of the contralateral MTL structures, as well as ipsilateral and contralateral THA volumes. For individualized predictions, we trained a linear discriminant analysis (LDA) classifier (Liu et al., 2009) using the extent of resected alteration together with pre-operative morphology of ipsi- and contralateral MTL structures, THA and the neocortex (z-normalized with respect to healthy controls). These features were separately calculated for each surgical group within clusters of differences, then averaged and mapped back to each patient’s MRI. Performance evaluation was based on a 5-fold cross-validation with 50 iterations. Our primary performance validation metric was accuracy, which reflects the ratio of number of correct predictions (TLE-SF, TLE-NSF) to the total number of input samples. Moreover, we calculated a confusion matrix to highlight cases in which our predictive model succeeded or failed.

Surface-based findings were corrected using random field theory for non-isotropic images, controlling for family-wise error PFWE<0.05. Cluster-wise results were corrected at a false discovery rate PFDR<0.05 (Benjamini and Hochberg, 1995).

3 Results

3.1 Pre-operative morphometry

Compared to controls (Fig. 2A), with the exception of AM which was atrophic ipsilateral to the seizure focus (PFWE<0.0001, Cohen’s d = 0.63), all other MTL structures as well as the THA showed bilateral asymmetric atrophy (PFWE<0.0001) with larger effects ipsilaterally, particularly for HP (ipsilateral/contralateral d = 0.90/0.52). Cortex-wide mapping revealed bilateral symmetric fronto-temporal atrophy (PFWE<0.0001, d = 0.57/0.55), mostly in dorsolateral prefrontal and central areas.Fig. 2 Pre-operative morphometry. A) Group analyses show regions of mesiotemporal, thalamic and neocortical atrophy in TLE patients compared to controls. Findings are adjusted for multiple comparisons using random field theory for non-isotropic images and thresholded at P<0.05. Significant clusters are shown in solid colors and outlined in black; trends are shown in semitransparent. B) Bar plots illustrate comparisons between seizure-free (TLE-SF, in blue) vs. not seizure-free (TLE-NSF, in red) patients and healthy controls in clusters of findings. For the neocortex, brain surfaces above the bar plots show clusters of atrophy. Symbols indicate group differences after correcting for multiple comparisons at PFDR<0.05. Abbreviations: HP=hippocampus, EC=entorhinal cortex, AM=amygdala, PRC=piriform cortex, THA=thalamus. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Stratifying patients based on outcome (Fig. 2B), TLE-SF displayed greater ipsilateral HP (PFDR<0.05, d = -1.33) and AM (PFDR<0.05, d = -0.68) atrophy; conversely, TLE-NSF patients had AM (PFDR<0.05, d = -0.67) hypertrophy. While both cohorts had similar degrees of bilateral THA and fronto-central thinning (PFDR<0.05), in TLE-NSF additional bitemporal atrophy extended into parietal and insular cortices, more so contralaterally (PFDR<0.05). Analyzing patients based on the type of surgery (Supplementary Figure 1), the SAH cohort showed greater ipsilateral HP atrophy compared to the ATL cohort (PFDR<0.05; d = -0.92), while the latter showed greater THA atrophy bilaterally (ipsilateral/contralateral: PFDR<0.05, d = 0.81/0.93).

3.2 Pre- to post-operative comparisons

Irrespective of the type of surgery (Fig. 3A and 3B), comparing contralateral pre- to post-operative MTL morphometry revealed HP (SAH/ATL: PFWE<0.002/PFWE<0.01, d = 0.75/0.94) and AM (PFWE<0.0001, d = 0.71/0.97) atrophy, as well as areas of hypertrophy within the EC (PFWE<0.008/ PFWE<0.01, d = 0.61/0.93) and PRC (p<0.05/ PFWE<0.0001, d = 1.04). Both surgery types also led to an accentuation of THA atrophy, mainly ipsilaterally (PFWE<0.0001, SAH/ATL d = 1.37/0.97), and extensive bilateral neocortical limbic atrophy (encompassing the posterior parahippocampus, fusiform, cingulate, and orbitofrontal cortices; PFWE<0.0001, d = 0.93, d = 0.67). In addition, the SAH procedure was followed by atrophy across the ipsilateral temporo-parieto-occipital and ventrolateral frontal cortices (PFWE<0.0001, d = 0.97), and ATL by bilateral fronto-polar atrophy (PFWE<0.0001, d = 1.24).Fig. 3 Pre- to post-operative morphometry. A-B) Group comparisons between selective amygdalohippocampectomy (SAH) and anterior temporal lobectomy (ATL) cohorts and healthy controls. C) Direct contrasts between the two surgical approaches. Findings have been adjusted for multiple comparisons using random field theory for nonisotropic images and thresholded at P<0.05. Significant clusters are shown in solid colors and outlined in black; trends are shown in semitransparent.

Direct contrast between the two procedures (Fig. 3C) confirmed greater ipsilateral temporo-occipital and bilateral parietal atrophy following SAH (ipsi PFWE<0.03/contra PFWE<0.0001, d = 0.48/0.53), and greater bilateral frontal atrophy after ATL (PFWE<0.0001/ PFWE<0.005, d = 0.50/0.46). On the other hand, there were no group differences for the MTL structures and the THA. Finally, no differences were observed when stratifying patients based on seizure outcome.

3.3 Relationship between resection of morphological anomalies and seizure outcome

Patients who underwent SAH had a larger resection of the HP (SAH/ATL: 60 % vs. 37 %, PFDR<0.01), while the ATL cohort had a larger resection of EC (ATL/SAH: 81 % vs. 65 %, PFDR<0.01) and temporal neocortex (23 % vs. 9 %, PFDR<0.01; Fig. 4A). Conversely, cohorts did not differ with respect to resected alterations of the AM (SAH/ATL: 60 % vs. 58 %) and PRC (28 % vs. 24 %). Compared to TLE-NSF, TLE-SF patients underwent a larger resection of HP (61 % vs. 39 %, d = 0.93, PFDR<0.001) and EC (75 % vs. 63 %, d = 0.93, PFDR<0.001) anomalies, whereas there were no differences for the AM (61 % vs. 55 %), PRC (30 % vs. 22 %), and temporal neocortex (15 % for both groups; Fig. 4B). Results remained unchanged when controlling for type of surgery, overall cortical thickness, volume of THA and contralateral MTL structures.Fig. 4 Relationship between resection of morphological anomalies and seizure outcome. A) The probability of a vertex being surgically resected is superimposed on surface templates (range, 20–100 %) for selective amygdalohippocampectomy (SAH) and anterior temporal lobectomy (ATL). For each surgical cohort, smaller maps below each respective surface template show group differences between patients and controls. B) Boxplots display the percentage of resected pathology for the mesiotemporal structures and neocortex for seizure-free (TLE-SF) vs. not seizure-free (TLE-NSF) patients. ✦ indicates significant group difference after correcting for multiple comparisons at PFDR<0.05.

The LDA classifier applied to pre-operative morphometric features and resected alterations correctly predicted surgical outcome in 78 % of patients (95 % confidence interval = 72 %-84 %), with a discriminative power of 0.89 for seizure freedom and 0.58 for seizure relapse (Table 2). The most predictive features were the extent of resected HP morphological anomalies (selected 100 % across the 5-fold iterations), pre-operative HP (ipsilateral/contralateral: 99 %/100 %) and AM atrophy (ipsilateral: 61 %), AM hypertrophy (50 %/89 %), as well as the extent of resection of EC anomalies (35 %).Table 2 Confusion matrix.

	TLE-SF (predicted)	TLE-NSF (predicted)	
TLE-SF (actual; N=36)	0.89 %	0.11 %	
TLE-NSF (actual; N=19)	0.42 %	0.58 %	
The matrix displays the median performance for the classifier. Diagonal/non-diagonal cells show correct/incorrect predictions.

4 Discussion

To identify region-specific predictors of seizure outcome, we assessed interactions between whole-brain morphological compromise and surgery using precise co-registration between pre- and post-operative MRI. Advancing previous knowledge based on studies exclusively relating outcome to the extent of resection, we assessed the impact of markers of pathology at the site of surgery. Our results show that resection of MTL morphological anomalies, particularly those within the hippocampus, leads to seizure freedom. This finding was further supported by a supervised classifier for which the extent of resected hippocampal anomalies, together with pre-operative atrophy, were the most predictive features. Notably, these findings were independent of the type of surgery; in other words, surgical outcome was not dependent on resection size, but rather on the removal of the pathological tissue, with an average of at least 60 % for the hippocampus. Thus, our results suggest that precise MRI-based quantification of MTL morphology is an essential diagnostic and prognostic tool.

Beside the importance of resecting MTL morphological anomalies, whole-brain pre-operative analysis revealed a regionally divergent impact on outcome. Specifically, TLE-SF patients displayed more severe ipsilateral hippocampal atrophy, while TLE-NSF had more severe bilateral insular and temporal neocortical atrophy. These results expand previous knowledge suggesting that a widespread epileptogenic extending beyond temporal cortices leads to poor surgical outcome (Bernhardt et al., 2015a, Garcia et al., 2017). Regarding the amygdala, while ipsilateral atrophy related to seizure freedom, hypertrophy had a negative impact. Of note, amygdalar enlargement has been previously related to gliotic processes (Bower et al., 2003, Hoffman et al., 2017), which may cause synaptic alterations and abnormal neuronal activity, leading to hyperexcitability and spontaneous seizures, thereby contributing to a more complex seizure network (Bernhardt et al., 2015b).

Previous data have suggested a favorable seizure outcome when the piriform cortex is resected (Borger et al., 2021, Galovic et al., 2019), an association not evident from our findings. While its dense connectivity with the amygdala, entorhinal and orbitofrontal cortices may position this structure as a pivotal node for seizure propagation (Galovic et al., 2019, Vaughan and Jackson, 2014), given the proximity to perforating branches of the anterior choroidal artery, surgical removal remains challenging, particularly of its fronto-basal portion (Delev et al., 2022). Discrepancy between studies may stem from methodological approaches. Firstly, instead of examining effects of the overall extent of resection, our study focused on the ablation of the pathological tissue at the site of surgery. Secondly, our MRI segmentation protocol included only the temporal portion of the piriform cortex since its frontal portion is not easily identifiable even on histology (Pereira et al., 2005); notably, while the latter constitutes about 20 % of the entire structure, difficulties in delineating it on MRI is likely to impact measurement reliability (Gloor and Guberman, 1997). Thirdly, surface-based statistical paradigms are more sensitive in detecting localized morphological changes not evident in measurement of total volume (Kim et al., 2008). From a clinical perspective, our cohorts including patients undergoing two different surgical approaches, with very long post-operative follow-up, adds further validity to our findings.

In relation to post-operative changes, while some studies have shown reversal of pre-operative functional and metabolic disruptions (Lantz et al., 2006, Spanaki et al., 2000), structural changes have been much less studied, with inconsistent results. Some identified no post-operative atrophy (Galovic et al., 2020), or a relative increase of WM and GM concentrations (Yasuda et al., 2010). Others reported volume reduction of contralateral MTL structures (Elliott et al., 2016), widespread cortical thinning extending into temporo-occipital regions (Arnold et al., 2023), as well as decreased fractional anisotropy of WM tracts linking MTL structures to other brain areas (Schoene-Bake et al., 2009). Capitalizing on two cohorts undergoing different surgical approaches, we also evaluated effects of temporal lobe surgery on whole-brain morphology. Our findings point to distinct patterns of post-operative neocortical changes influenced by the type of surgical approaches. Importantly, however, and in keeping with previous reports, neither the cortical nor MTL alterations were related to seizure outcome (Arnold et al., 2023, Li et al., 2021, Yasuda et al., 2010). While the ATL cohort showed post-operative atrophy in frontal cortices, in the SAH group atrophic changes affected mostly the posterior regions. Post-operative atrophy has been mostly attributed to Wallerian degeneration and loss of functional connections (Arnold et al., 2023, Galovic et al., 2020, Yasuda et al., 2010). Another possible reason may be the underlying pathologic mechanisms causing progressive brain atrophy and dysfunction (Li et al., 2021) possibly in combination with long-term use of anti-seizure drugs, even in the absence of seizures (Alvim et al., 2016, Pardoe et al., 2013). Contrary to differential patterns of neocortical atrophy, we observed similar patterns of MTL and thalamic changes, namely contralateral atrophy of the hippocampus and amygdala, hypertrophy within the entorhinal and piriform cortices and diffuse, mainly ipsilateral thalamic atrophy. Such changes are likely secondary to post-surgical disconnection followed by deafferentation, a hypothesis supported by reports in preclinical models showing that the removal of tonic commissural excitatory inputs projecting to contralateral hippocampus results in volume loss (Annese et al., 2014, Bonilha et al., 2010); deafferented regions are known to undergo dendritic atrophy, astrocyte activation, and reactive gliosis (Andersson et al., 2013, Deitch and Rubel, 1989). Hippocampal deafferentation could play a role in the bi-thalamic atrophy we observed (Bonilha et al., 2010). Entorhinal and piriform hypertrophy could be due to an adaptive metabolic response to transneuronal degeneration (Ryufuku et al., 2011); incurred cellular stress during surgery has been shown to result in morphological and immunohistochemical profiles of hypertrophic neurons (Ryufuku et al., 2011). Another explanation could be that MTL damage through surgery could deprive distant neurons, either directly or indirectly, of their targets, which may result in increased aberrant synaptogenesis appearing as hypertrophy on MRI (Bothwell et al., 2001).

5 Conclusion

Precise delineation of MTL anomalies through surface-based morphometry provides valuable prognostic information in TLE presurgical evaluation and help promoting individualized resective surgery. Such methods can optimize the choice of surgical targets in minimally-invasive approaches, such as MRI-guided laser interstitial thermal ablations for which the optimal ablation volume are still matter of debate.

Funding sources

This work was funded by the Natural Sciences and research Council (10.13039/501100000038 NSERC ; Discovery-243141 to AB and 24,779 to NB), 10.13039/100023422 Epilepsy Canada (Jay & Aiden Barker 10.13039/501100022542 Breakthrough Grant in Clinical & Basic Sciences to AB), 10.13039/100009408 Brain Canada .

7 Ethical publication statement

The Ethics Committee of the Montreal Neurological Institute and Hospital approved the study and written informed consent was obtained from all participants.

CRediT authorship contribution statement

Fatemeh Fadaie: Writing – original draft, Validation, Methodology, Formal analysis, Conceptualization. Benoit Caldairou: Writing – review & editing, Methodology, Formal analysis, Data curation, Conceptualization. Ravnoor S. Gill: Writing – review & editing, Methodology, Formal analysis, Conceptualization. Niels A. Foit: Writing – review & editing, Formal analysis. Jeffery A. Hall: Writing – review & editing, Conceptualization. Boris C. Bernhardt: Writing – review & editing, Methodology, Conceptualization. Neda Bernasconi: Writing – review & editing, Supervision, Resources, Project administration, Funding acquisition, Data curation, Conceptualization. Andrea Bernasconi: Writing – review & editing, Supervision, Resources, Project administration, Funding acquisition, Conceptualization.

Appendix A Supplementary data

The following are the Supplementary data to this article:Supplementary Data 1

Data availability

Data will be made available on request.

Appendix A Supplementary data to this article can be found online at https://doi.org/10.1016/j.nicl.2024.103658.
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