Resective epilepsy surgery is an evidence-based curative treatment option for patients with drug-resistant focal epilepsy. The major preoperative predictor of a good surgical outcome is detection of an epileptogenic lesion by magnetic resonance imaging (MRI). Application of ultra-high field (UHF) MRI, i.e. field strengths ≥ 7 Tesla (T), may increase the sensitivity to detect such a lesion. A keyword search strategy was submitted to Pubmed, EMBASE, Cochrane Database and clinicaltrials.gov to select studies on UHF MRI in patients with epilepsy. Follow-up study selection and data extraction were performed following PRISMA guidelines. We focused on I) diagnostic gain of UHF- over conventional MRI, II) concordance of MRI-detected lesion, seizure onset zone and surgical decision-making, and III) postoperative histopathological diagnosis and seizure outcome. Sixteen observational cohort studies, all using 7T MRI were included. Diagnostic gain of 7T over conventional MRI ranged from 8% to 67%, with a pooled gain of 31%. Novel techniques to visualize pathological processes in epilepsy and lesion detection are discussed. Seizure freedom was achieved in 73% of operated patients; no seizure outcome comparison was made between 7T MRI positive, 7T negative and 3T positive patients. 7T could influence surgical decision-making, with high concordance of lesion and seizure onset zone. Focal cortical dysplasia (54%), hippocampal sclerosis (12%) and gliosis (8.1%) were the most frequently diagnosed histopathological entities. UHF MRI increases, yet variably, the sensitivity to detect an epileptogenic lesion, showing potential for use in clinical practice. It remains to be established whether this results in improved seizure outcome after surgical treatment. Prospective studies with larger cohorts of epilepsy patients, uniform scan and sequence protocols, and innovative post-processing technology are equally important as further increasing field strengths. Besides technical ameliorations, improved correlation of imaging features with clinical semiology, histopathology and clinical outcome has to be established.

The blood-brain barrier (BBB) is dysfunctional in temporal lobe epilepsy (TLE). In this regard, microvascular changes are likely present. The aim of this review is to provide an overview of the current knowledge on microvascular changes in epilepsy, and includes clinical and preclinical evidence of seizure induced angiogenesis, barriergenesis and microcirculatory alterations. Anatomical studies show increased microvascular density in the hippocampus, amygdala, and neocortex accompanied by BBB leakage in various rodent epilepsy models. In human TLE, a decrease in afferent vessels, morphologically abnormal vessels, and an increase in endothelial basement membranes have been observed. Both clinical and experimental evidence suggests that basement membrane changes, such as string vessels and protrusions, indicate and visualize a misbalance between endothelial cell proliferation and barriergenesis. Vascular endothelial growth factor (VEGF) appears to play a crucial role. Following an altered vascular anatomy, its physiological functioning is affected as expressed by neurovascular decoupling that subsequently leads to hypoperfusion, disrupted parenchymal homeostasis and potentially to seizures”. Thus, epilepsy might be a condition characterized by disturbed cerebral microvasculature in which VEGF plays a pivotal role. Additional physiological data from patients is however required to validate findings from models and histological studies on patient biopsies.

Background Anterior temporal lobectomy (ATL) as a treatment for drug-resistant temporal lobe epilepsy (TLE) frequently causes visual field deficits (VFDs). Reported VFD encompasses homonymous contralateral upper quadrantanopia. Its reported incidence ranges from 15 to 90%. To date, a quantitative method to evaluate postoperative VFD in static perimetry is not available. A method to quantify postoperative VFD, which allows for comparison between groups of patients, was developed. Methods Fifty-five patients with drug-resistant TLE, who underwent ATL with pre- and postoperative perimetry, were included. Temporal lobe resection length was measured on postoperative MRI. Percentage VFD was calculated for the total visual field, contralateral upper quadrant, or other three quadrants combined. Results Patients were divided into groups by resection size (< 45 and ≥ 45 mm) and side of surgery (right and left). We found significant higher VFD in the ≥ 45 vs. < 45 mm group (2.3 ± 4.4 vs. 0.7 ± 2.4%,p = 0.04) for right-sided ATL. Comparing VFD in both eyes, we found more VFD in the right vs. left eye following left-sided ATL (14.5 ± 9.8 vs. 12.9 ± 8.3%, p = 0.03). We also demonstrated significantly more VFD in the < 45 mm group for left- vs. right-sided surgery (6.7 ± 6.7 vs. 13.1 ± 7.0%, p = 0.016). A significant quantitative correlation between VFD and resection size for right-sided ATL was shown (r = 0.52, p < 0.01). Conclusions We developed a new quantitative scoring method for the assessment of postoperative visual field deficits after temporal lobe epilepsy surgery and assessed its feasibility for clinical use. A significant correlation between VFD and resection size for right-sided ATL was confirmed.

Purpose: Resective epilepsy surgery is a well-established, evidence-based treatment option in patients with drug-resistant focal epilepsy. A major predictive factor of good surgical outcome is visualization and delineation of a potential epileptogenic lesion by MRI. However, frequently, these lesions are subtle and may escape detection by conventional MRI (≤ 3 T). Methods: We present the EpiUltraStudy protocol to address the hypothesis that application of ultra-high field (UHF) MRI increases the rate of detection of structural lesions and functional brain aberrances in patients with drug-resistant focal epilepsy who are candidates for resective epilepsy surgery. Additionally, therapeutic gain will be addressed, testing whether increased lesion detection and tailored resections result in higher rates of seizure freedom 1 year after epilepsy surgery. Sixty patients enroll the study according to the following inclusion criteria: aged ≥ 12 years, diagnosed with drug-resistant focal epilepsy with a suspected epileptogenic focus, negative conventional 3 T MRI during pre-surgical work-up. Results: All patients will be evaluated by 7 T MRI; ten patients will undergo an additional 9.4 T MRI exam. Images will be evaluated independently by two neuroradiologists and a neurologist or neurosurgeon. Clinical and UHF MRI will be discussed in the multidisciplinary epilepsy surgery conference. Demographic and epilepsy characteristics, along with postoperative seizure outcome and histopathological evaluation, will be recorded. Conclusion: This protocol was reviewed and approved by the local Institutional Review Board and complies with the Declaration of Helsinki and principles of Good Clinical Practice. Results will be submitted to international peer-reviewed journals and presented at international conferences. Trial registration number: www.trialregister.nl: NTR7536.

Focal epilepsy is a common and severe neurologic disorder. Neuroimaging aims to identify the epileptogenic zone (EZ), preferably as a macroscopic structural lesion. For approximately a third of patients with chronic drug-resistant focal epilepsy, the EZ cannot be precisely identified using standard 3.0-T MRI. This may be due to either the EZ being undetectable at imaging or the seizure activity being caused by a physiologic abnormality rather than a structural lesion. Computational image processing has recently been shown to aid radiologic assessments and increase the success rate of uncovering suspicious regions by enhancing their visual conspicuity. While structural image analysis is at the forefront of EZ detection, physiologic image analysis has also been shown to provide valuable information about EZ location. This narrative review summarizes and explains the current state-of-the-art computational approaches for image analysis and presents their potential for EZ detection. Current limitations of the methods and possible future directions to augment EZ detection are discussed.