Diffusion tensor imaging discriminates focal cortical dysplasia from normal brain parenchyma and differentiates between focal cortical dysplasia types

To the best of our knowledge, this is the first large paediatric cohort study to demonstrate that FA and MD can facilitate the discrimination between FCD and CBP, as well as between specific FCD subtypes, in paediatric focal epilepsy. Our results suggest that DTI may provide a powerful tool for FCD characterisation across the age spectrum, including the particularly vulnerable subgroup of very young children with focal structural epilepsy.

Although diffusion MRI has the potential to image microstructural changes within FCD and thus facilitate their differentiation from normal brain parenchyma, this promising technique has received little attention in previous FCD detection and characterisation studies that focused mainly on structural MRI [27]. Compared to anatomical images, diffusion MRI techniques offer a lower spatial resolution that limits their utility for lesion detection and delineation, which usually represents the primary outcome of radiological studies. However, the quantitative MRI assessment provided by DTI indices may help confirm subtle findings detected on anatomical images, such as those characterising FCD, thus resolving the ambiguity introduced by the inter-rater variability inherent in visual assessment. The present study reports several new and innovative findings in paediatric focal epilepsy, underscoring the potential utility of diffusion imaging techniques in this population.

FA and MD can discriminate FCD from the normal brain parenchyma

The reduction in the FA values and the increase in the MD values in the FCD region compared to CBP, as detected in our study, is in line with previous work [15, 28, 29]. Of note, FA provided the most robust discrimination between the various DTI metrics. This difference in DTI indices between FCD and CBP can be attributed mainly to the higher diffusivity of water molecules in FCD due to changes in white matter microstructure, including myelin loss, abnormal myelin sheet formation, neuronal death, diminished arborisation of dendrites and reactive gliosis induced by recurrent seizures [19, 30]. The impact of FCD-related myelin changes on DTI indices is further supported by anatomical MRI studies in different histopathological substrates, which showed that over 80% of the overall MRI signal reflects myelin density variation, even in different cortical layers [31]. Finally, although it would be tempting to attribute the DTI changes established in our study to the specific cytological alterations characterising the different FCD types, it should be noted that the large slice thickness used in the majority of DTI clinical protocols (2.5 mm) corresponds to the average cortical thickness [32], thus limiting the possibility to image subtle cortical changes.

Interestingly, our observations contrast with a previous study in paediatric FCD-associated epilepsy [18] that found no FCD-specific signal changes in FA and MD indices. However, in this previous cohort, roughly 70% of patients had histological findings and in one-third of them histopathology ruled out the presence of FCD [18]. Moreover, the discrepancy between the two studies may also be attributed to the differences in their methodology, since the diffusion values in this past study were sampled at steps of 0.5 mm down to 6 mm from the pial surface [18], with more extensive FCD-specific signal changes at sampling depths below 2.5 mm. In contrast, we chose to estimate the mean diffusion value within a predefined ROI. Although interesting, the intricate approach used in this past study [18] is time-consuming, requiring additional pre-processing steps, and may offer only a limited advantage over our more straightforward approach, considering the limitations posed to analysis precision by the 2 mm slice thickness of diffusion images.

FA values vary according to the history of status epilepticus

In our study, patients who experienced at least one episode of SE showed higher differences in FA between FCD and CBP. Therefore, these findings may reflect changes induced in the brain by such a disruptive event and are consistent with reports from animal studies that have previously demonstrated changes induced by a single episode of SE in the rat hippocampus [33, 34]. Interestingly, the FA of the dentate gyrus in animals with a history of SE has been considerably higher than in both healthy animals [33] and animals with a history of traumatic brain injury [34]. Histological analyses attributed these changes to an increase in astrocytes in the affected areas [33] without a concomitant increased vascularisation, suggesting that the increase in FA values is unlikely to be related to spurious signals from newly emerging vessels [35]. These results corroborate previous studies supporting that FA increases at the presence of astrogliosis and glial fibrillary acid protein deposition [36]. While no direct comparisons between animal findings and our results can be drawn, our results strongly motivate further investigation on this topic in a larger patient population, comparing diffusion imaging to histological analysis.

FA can distinguish between FCD subtypes

Although based on a limited number of patients, our findings underline the potential of FA difference values in facilitating the distinction between FCD types, particularly between types I and IIb, which represent the two ends of the FCD severity spectrum. This finding is crucial since neurite orientation dispersion and density imaging (NODDI) and spherical mean technique (SMT) have been so far the only diffusion-based techniques to differentiate between FCD subtypes in paediatric focal epilepsy [18]. Here, it is essential to note that DTI reflects myelin changes, whereas NODDI and SMT additionally reflect intra- and extracellular neuropathological processes. Therefore, DTI may facilitate distinguishing type I and type II FCD based on their different effects on myelin [37], and NODDI and SMT may provide complementary information differentiating type IIa and IIb based on their specific cytological alterations [18]. In parallel with a visual MRI assessment, quantitative DTI indices may therefore provide a valuable tool for discriminating between FCD types, thus facilitating patient management, counselling and prognostication in all patients with FCD-associated focal epilepsy, irrespective of their candidacy for epilepsy surgery [38]. Moreover, in patients eventually undergoing epilepsy surgery, DTI indices could be combined with genetic markers to refine the characterisation of FCD types by histopathology [39, 40]. It should be noted that genetic studies in FCD rely on the availability of resected brain tissue that has considerably decreased over time, in line with the increased implementation of minimally invasive surgical techniques, such as laser interstitial thermal therapy, thus impeding histological evaluation in these patients [41]. Therefore, in the future, diffusion-weighted sequences and other MRI methods sensitive to cytological alterations may become increasingly important for the definition of FCD types. However, one potential confound to consider in the assessment of FA difference values within FCDs is that of astrogliosis, since histopathological assessments described various grades of astrogliosis within FCDs [42], and the severity appears to be linked to epilepsy activity rather than to FCD type [42]. Since astrogliosis may affect FA difference values, further studies exploring the effects of epileptic activity on imaging and histopathological findings in FCD are needed before implementing this promising tool in the diagnostic workup of these patients.

Our results, including those related to SE-specific changes in DTI metrics, derive from a paediatric cohort strongly focusing on the first years of life, thus reflecting the characteristics of this particularly vulnerable age group. Roughly one-half of patients who had experienced SE in our cohort were aged three years or younger at the MRI scan. Moreover, one-half of all patients were aged three years or younger at enrolment and one-half of surgically treated patients were diagnosed with FCD type I. Type I FCD manifests as early-onset epilepsy, often taking a refractory course [5] that may account for the very young age at presentation and comprehensive presurgical evaluation, including imaging, in our cohort. Although these characteristics underline the representativity of our cohort for the paediatric population undergoing presurgical assessment and, eventually, epilepsy surgery [8, 9, 43,44,45], more extensive multicentric studies are required to investigate the applicability of our findings across the paediatric age spectrum and refine the accuracy of our observations.

Limitations

Our study has several limitations. Firstly, it is a retrospective, single-centre study, with all the inherent limitations of this study design. However, it should be noted that our findings derive from a large homogeneous cohort extending across the paediatric age spectrum with one-half of patients aged three years or younger, thus supporting the representativity of our cohort for the paediatric population with FCD-associated epilepsy undergoing presurgical evaluation and, eventually, epilepsy surgery. Secondly, we considered data acquired using two different DTI protocols, before and after a major upgrade of the scanner. However, a previous study has reported similar FA and MD values in healthy volunteers who underwent various DTI protocols with varying numbers of gradient directions [46]. Moreover, a simulation study showed that the variability in FA values asymptotically decreases as the number of gradient encoding directions increase; a gradient scheme with 20 encoding directions were deemed the point of minimal effect, in which FA difference with increasing gradient directions become negligible [47]. Thirdly, the inclusion of children < 3 years old in our analysis might have biased our results. However, this age category has already been included in the work of other authors, although to a lesser extent [18], and by using a region of healthy brain parenchyma as control region, we endeavoured to control for age-related changes in diffusion indices. Additionally, our within-participant comparison approach accounted for global differences arising from the DTI protocol and gradient scheme, as well as other global effects arising from developmental differences. Fourthly, DTI images were acquired using images from a single scanner vendor. However, previous studies have shown that the FA values do not vary significantly between different vendors [48], thus supporting the broad applicability of our results. Fifthly, only one-half of our patients had histologically proven FCD. Nevertheless, the strict radiological inclusion and exclusion criteria used in our study allowed the selection of a patient cohort with lesions highly suggestive of an FCD. Finally, the absence of MRI-negative patients in our study limits the possibility to extend our results to this patient cohort. However, we are planning to validate our findings in a larger cohort of patients including MRI-negative cases.

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