Comparison of morphometric analysis based on T1- and T2-weighted MRI data for visualization of focal cortical dysplasia

A radiomics nomogram based on multiparametric MRI for diagnosing focal cortical dysplasia and initially identifying laterality

BACKGROUND

Focal cortical dysplasia (FCD) is the most common epileptogenic developmental malformation. The diagnosis of FCD is challenging. We generated a radiomics nomogram based on multiparametric magnetic resonance imaging (MRI) to diagnose FCD and identify laterality early.

METHODS

Forty-three patients treated between July 2017 and May 2022 with histopathologically confirmed FCD were retrospectively enrolled. The contralateral unaffected hemispheres were included as the control group. Therefore, 86 ROIs were finally included. Using January 2021 as the time cutoff, those admitted after January 2021 were included in the hold-out set (n = 20). The remaining patients were separated randomly (8:2 ratio) into training (n = 55) and validation (n = 11) sets. All preoperative and postoperative MR images, including T1-weighted (T1w), T2-weighted (T2w), fluid-attenuated inversion recovery (FLAIR), and combined (T1w + T2w + FLAIR) images, were included. The least absolute shrinkage and selection operator (LASSO) was used to select features. Multivariable logistic regression analysis was used to develop the diagnosis model. The performance of the radiomic nomogram was evaluated with an area under the curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration and clinical utility.

RESULTS

The model-based radiomics features that were selected from combined sequences (T1w + T2w + FLAIR) had the highest performances in all models and showed better diagnostic performance than inexperienced radiologists in the training (AUCs: 0.847 VS. 0.664, p = 0.008), validation (AUC: 0.857 VS. 0.521, p = 0.155), and hold-out sets (AUCs: 0.828 VS. 0.571, p = 0.080). The positive values of NRI (0.402, 0.607, 0.424) and IDI (0.158, 0.264, 0.264) in the three sets indicated that the diagnostic performance of Model-Combined improved significantly. The radiomics nomogram fit well in calibration curves (p > 0.05), and decision curve analysis further confirmed the clinical usefulness of the nomogram. Additionally, the contrast (the radiomics feature) of the FCD lesions not only played a crucial role in the classifier but also had a significant correlation (r = -0.319, p < 0.05) with the duration of FCD.

CONCLUSION

The radiomics nomogram generated by logistic regression model-based multiparametric MRI represents an important advancement in FCD diagnosis and treatment.

Development and prospective clinical validation of a convolutional neural network for automated detection and segmentation of focal cortical dysplasias

PURPOSE

Focal cortical dysplasias (FCDs) are a leading cause of drug-resistant epilepsy. Early detection and resection of FCDs have favorable prognostic implications for postoperative seizure freedom. Despite advancements in imaging methods, FCD detection remains challenging. House et al. (2021) introduced a convolutional neural network (CNN) for automated FCD detection and segmentation, achieving a sensitivity of 77.8%. However, its clinical applicability was limited due to a low specificity of 5.5%. The objective of this study was to improve the CNN's performance through data-driven training and algorithm optimization, followed by a prospective validation on daily-routine MRIs.

MATERIAL AND METHODS

A dataset of 300 3 T MRIs from daily clinical practice, including 3D T1 and FLAIR sequences, was prospectively compiled. The MRIs were visually evaluated by two neuroradiologists and underwent morphometric assessment by two epileptologists. The dataset included 30 FCD cases (11 female, mean age: 28.1 ± 10.1 years) and a control group of 150 normal cases (97 female, mean age: 32.8 ± 14.9 years), along with 120 non-FCD pathological cases (64 female, mean age: 38.4 ± 18.4 years). The dataset was divided into three subsets, each analyzed by the CNN. Subsequently, the CNN underwent a two-phase-training process, incorporating subset MRIs and expert-labeled FCD maps. This training employed both classical and continual learning techniques. The CNN's performance was validated by comparing the baseline model with the trained models at two training levels.

RESULTS

In prospective validation, the best model trained using continual learning achieved a sensitivity of 90.0%, specificity of 70.0%, and accuracy of 72.0%, with an average of 0.41 false positive clusters detected per MRI. For FCD segmentation, an average Dice coefficient of 0.56 was attained. The model's performance improved in each training phase while maintaining a high level of sensitivity. Continual learning outperformed classical learning in this regard.

CONCLUSIONS

Our study presents a promising CNN for FCD detection and segmentation, exhibiting both high sensitivity and specificity. Furthermore, the model demonstrates continuous improvement with the inclusion of more clinical MRI data. We consider our CNN a valuable tool for automated, examiner-independent FCD detection in daily clinical practice, potentially addressing the underutilization of epilepsy surgery in drug-resistant focal epilepsy and thereby improving patient outcomes.

Evaluation of MRI post-processing methods combined with PET in detecting focal cortical dysplasia lesions for patients with MRI-negative epilepsy

OBJECTIVE

Accurate detection of focal cortical dysplasia (FCD) through magnetic resonance imaging (MRI) plays a pivotal role in the preoperative assessment of epilepsy. The integration of multimodal imaging has demonstrated substantial value in both diagnosing FCD and devising effective surgical strategies. This study aimed to enhance MRI post-processing by incorporating positron emission tomography (PET) analysis. We sought to compare the diagnostic efficacy of diverse image post-processing methodologies in patients presenting MRI-negative FCD.

METHODS

In this retrospective investigation, we assembled a cohort of patients with negative preoperative MRI results. T1-weighted volumetric sequences were subjected to morphometric analysis program (MAP) and composite parametric map (CPM) post-processing techniques. We independently co-registered images derived from various methods with PET scans. The alignment was subsequently evaluated, and its correlation was correlated with postoperative seizure outcomes.

RESULTS

A total of 41 patients were enrolled in the study. In the PET-MAP(p = 0.0189) and PET-CPM(p = 0.00041) groups, compared with the non-overlap group, the overlap group significantly associated with better postoperative outcomes. In PET(p = 0.234), CPM(p = 0.686) and MAP(p = 0.672), there is no statistical significance between overlap and seizure-free outcomes. The sensitivity of using the CPM alone outperformed the MAP (0.65 vs 0.46). The use of PET-CPM demonstrated superior sensitivity (0.96), positive predictive value (0.83), and negative predictive value (0.91), whereas the MAP displayed superior specificity (0.71).

CONCLUSIONS

Our findings suggested a superiority in sensitivity of CPM in detecting potential FCD lesions compared to MAP, especially when it is used in combination with PET for diagnosis of MRI-negative epilepsy patients. Moreover, we confirmed the superiority of synergizing metabolic imaging (PET) with quantitative maps derived from structural imaging (MAP or CPM) to enhance the identification of subtle epileptogenic zones (EZs). This study serves to illuminate the potential of integrated multimodal techniques in advancing our capability to pinpoint elusive pathological features in epilepsy cases.

Automatic Detection of Focal Cortical Dysplasia Using MRI: A Systematic Review

Focal cortical dysplasia (FCD) is a congenital brain malformation that is closely associated with epilepsy. Early and accurate diagnosis is essential for effectively treating and managing FCD. Magnetic resonance imaging (MRI)-one of the most commonly used non-invasive neuroimaging methods for evaluating the structure of the brain-is often implemented along with automatic methods to diagnose FCD. In this review, we define three categories for FCD identification based on MRI: visual, semi-automatic, and fully automatic methods. By conducting a systematic review following the PRISMA statement, we identified 65 relevant papers that have contributed to our understanding of automatic FCD identification techniques. The results of this review present a comprehensive overview of the current state-of-the-art in the field of automatic FCD identification and highlight the progress made and challenges ahead in developing reliable, efficient methods for automatic FCD diagnosis using MRI images. Future developments in this area will most likely lead to the integration of these automatic identification tools into medical image-viewing software, providing neurologists and radiologists with enhanced diagnostic capabilities. Moreover, new MRI sequences and higher-field-strength scanners will offer improved resolution and anatomical detail for precise FCD characterization. This review summarizes the current state of automatic FCD identification, thereby contributing to a deeper understanding and the advancement of FCD diagnosis and management.

Quantitative analysis of the morphometric analysis program MAP in patients with truly MRI-negative focal epilepsy

OBJECTIVE

In the presurgical evaluation of epilepsy, identifying the epileptogenic zone is challenging if magnetic resonance imaging (MRI) is negative. Several studies have shown the benefit of using a morphometric analysis program (MAP) on T1-weighted MRI scans to detect subtle lesions. MAP can guide a focused re-evaluation of MRI to ultimately identify structural lesions that were previously overlooked. Data on patients where this additional review after MAP analysis did not reveal any lesions is limited. Here we evaluate the diagnostic yield of MAP in a large group of truly MRI-negative patients.

METHODS

We identified 68 patients with MRI-negative focal epilepsy and clear localization of the epileptogenic zone by intracranial EEG or postoperative seizure freedom. High resolution 3D T1 data of patients and 73 healthy controls were acquired on a 3 T scanner. Morphometric analysis was performed with MAP software, creating five z-score maps, reflecting different structural properties of the brain and a patient's deviation from the control population, and a neural network-based focal cortical dysplasia probability map. Ten brain regions were specified to quantify whether MAP findings were located in the correct region. Receiver operating characteristic (ROC) analyses were performed to identify the optimal thresholds for each map.

RESULTS

MAP-guided visual re-evaluation of the original MRI revealed overlooked lesions in three patients. The remaining 65 truly MRI-negative patients were included in the statistical analysis. At the optimal thresholds, maximum sensitivity was 84 %, with 35 % specificity. Balanced accuracy (arithmetic mean of sensitivity and specificity) of the respective maps ranged from 51 % to 60 %, creating three to six times more false positive than true positive findings.

CONCLUSION

This study confirms that MAP is useful in detecting previously overlooked subtle structural lesions. However, in truly MRI-negative patients, the additional diagnostic yield is very limited.

Normative quantitative relaxation atlases for characterization of cortical regions using magnetic resonance fingerprinting

Quantitative magnetic resonance (MR) has been used to study cyto- and myelo-architecture of the human brain non-invasively. However, analyzing brain cortex using high-resolution quantitative MR acquisition can be challenging to perform using 3T clinical scanners. MR fingerprinting (MRF) is a highly efficient and clinically feasible quantitative MR technique that simultaneously provides T1 and T2 relaxation maps. Using 3D MRF from 40 healthy subjects (mean age = 25.6 ± 4.3 years) scanned on 3T magnetic resonance imaging, we generated whole-brain gyral-based normative MR relaxation atlases and investigated cortical-region-based T1 and T2 variations. Gender and age dependency of T1 and T2 variations were additionally analyzed. The coefficient of variation of T1 and T2 for each cortical-region was 3.5% and 7.3%, respectively, supporting low variability of MRF measurements across subjects. Significant differences in T1 and T2 were identified among 34 brain regions (P < 0.001), lower in the precentral, postcentral, paracentral lobule, transverse temporal, lateral occipital, and cingulate areas, which contain sensorimotor, auditory, visual, and limbic functions. Significant correlations were identified between age and T1 and T2 values. This study established whole-brain MRF T1 and T2 atlases of healthy subjects using a clinical 3T scanner, which can provide a quantitative and region-specific baseline for future brain studies and pathology detection.

Prognostic analysis in children with focal cortical dysplasia II undergoing epilepsy surgery: Clinical and radiological factors

OBJECTIVE

The aim of this study was to investigate the value of clinical profiles and radiological findings in assessing postsurgical outcomes in children with focal cortical dysplasia (FCD) II while exploring prognostic predictors of this disease.

METHODS

We retrospectively reviewed 50 patients with postoperative pathologically confirmed FCD II from January 2016 to June 2021. The clinical profiles and preoperative radiological findings were measured and analyzed. The patients were classified into four classes based on the Engel Class Outcome System at the last follow-up. For the analysis, the patients were divided into two categories based on Engel I and Engel II-IV, namely, seizure-free and non-seizure-free groups. Qualitative and quantitative factors were subsequently compared by groups using comparative statistics. Receiver operating characteristic (ROC) curves were used to identify the predictors of prognosis in children with FCD II.

RESULTS

Thirty-seven patients (74%) had Engel class I outcomes. The minimum postsurgical follow-up was 1 year. At the epilepsy onset, patients who attained seizure freedom were older and less likely to have no apparent lesions on the preoperative MRI ("MRI-negative"). The non-seizure-free group exhibited a higher gray matter signal intensity ratio (GR) on 3D T1-MPRAGE images (p = 0.006), with a lower GR on T2WI images (p = 0.003) and FLAIR images (p = 0.032). The ROC curve indicated that the model that combined the GR value of all MRI sequences (AUC, 0.87; 95% CI, 0.77-0.97; p < 0.001; 86% sensitivity, 85% specificity) was able to predict prognosis accurately.

CONCLUSION

A lower age at the onset or the MRI-negative finding of FCD lesions suggests a poor prognosis for children with FCD II. The model consisting of GR values from three MRI sequences facilitates the prognostic assessment of FCD II patients with subtle MRI abnormalities to prevent worse outcomes.

Lesion Detection Through MRI Postprocessing in Pathology-Proven Focal Cortical Dysplasia: Experience at a Single Institution in the Republic of Korea

BACKGROUND AND PURPOSE

Focal cortical dysplasia (FCD) is one of the most common causes of drug-resistant epilepsy, and necessitates a multimodal evaluation to ensure optimal surgical treatment. This study aimed to determine the supportive value of the morphometric analysis program (MAP) in detecting FCD using data from a single institution in Korea.

METHODS

To develop a standard reference for the MAP, normal-looking MRIs by two scanners that are frequently used in this center were chosen. Patients with drug-resistant epilepsy and FCD after surgery were candidates for the analysis. The three-dimensional T1-weighted MRI scans of the patients were analyzed as test cases using the MAP.

RESULTS

The MRI scans of 87 patients were included in the analysis. The radiologist detected abnormal findings correlated with FCD (RAD positive [RAD(+)]) in 34 cases (39.1%), while the MAP could detect FCD in 25.3% of cases. A combination of the MAP (MAP[+] cases) with interpretations by the radiologist increased the detection to 42.5% (37 cases). The lesion detection rate was not different according to the type of reference scanners except in one case. MAP(+)/RAD(-) presented in three cases, all of which had FCD type IIa. The detection rate was slightly higher using the same kind of scanner as a reference, but not significantly (35.0% vs. 22.4% p=0.26).

CONCLUSIONS

The results of postprocessing in the MAP for detecting FCD did not depend on the type of reference scanner, and the MAP was the strongest in detecting FCD IIa. We suggested that the MAP could be widely utilized without developing institutional standards and could become an effective tool for detecting FCD lesions.

Decision-making in stereotactic epilepsy surgery

Surgery can cure or significantly improve both the frequency and the intensity of seizures in patients with medication-refractory epilepsy. The set of diagnostic and therapeutic interventions involved in the path from initial consultation to definitive surgery is complex and includes a multidisciplinary team of neurologists, neurosurgeons, neuroradiologists, and neuropsychologists, supported by a very large epilepsy-dedicated clinical architecture. In recent years, new practices and technologies have emerged that dramatically expand the scope of interventions performed. Stereoelectroencephalography has become widely adopted for seizure localization; stereotactic laser ablation has enabled more focal, less invasive, and less destructive interventions; and new brain stimulation devices have unlocked treatment of eloquent foci and multifocal onset etiologies. This article articulates and illustrates the full framework for how epilepsy patients are considered for surgical intervention, with particular attention given to stereotactic approaches.

PET/MRI in the Presurgical Evaluation of Patients with Epilepsy: A Concordance Analysis

The aim of our prospective study was to evaluate the clinical impact of hybrid [18F]-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging ([18F]-FDG PET/MRI) on the decision workflow of epileptic patients with discordant electroclinical and MRI data. A novel mathematical model was introduced for a clinical concordance calculation supporting the classification of our patients by subgroups of clinical decisions. Fifty-nine epileptic patients with discordant clinical and diagnostic results or MRI negativity were included in this study. The diagnostic value of the PET/MRI was compared to other modalities of presurgical evaluation (e.g., electroclinical data, PET, and MRI). The results of the population-level statistical analysis of the introduced data fusion technique and concordance analysis demonstrated that this model could be the basis for the development of a more accurate clinical decision support parameter in the future. Therefore, making the establishment of “invasive” (operable and implantable) and “not eligible for any further invasive procedures” groups could be much more exact. Our results confirmed the relevance of PET/MRI with the diagnostic algorithm of presurgical evaluation. The introduction of a concordance analysis could be of high importance in clinical and surgical decision-making in the management of epileptic patients. Our study corroborated previous findings regarding the advantages of hybrid PET/MRI technology over MRI and electroclinical data.

"Within a minute" detection of focal cortical dysplasia

PURPOSE

To evaluate a MRI postprocessing tool for the enhanced and rapid detection of focal cortical dysplasia (FCD).

METHODS

MP2RAGE sequences of 40 consecutive, so far MRI-negative patients and of 32 healthy controls were morphometrically analyzed to highlight typical FCD features. The resulting morphometric maps served as input for an artificial neural network generating a FCD probability map. The FCD probability map was inversely normalized, co-registered to the MPRAGE2 sequence, and re-transferred into the PACS system. Co-registered images were scrolled through "within a minute" to determine whether a FCD was present or not.

RESULTS

Fifteen FCD, three subcortical band heterotopias (SBH), and one periventricular nodular heterotopia were identified. Of those, four FCD and one SBH were only detected by MRI postprocessing while one FCD and one focal polymicrogryia were missed, respectively. False-positive results occurred in 21 patients and 22 healthy controls. However, true positive cluster volumes were significantly larger than volumes of false-positive clusters (p < 0.001). The area under the curve of the receiver operating curve was 0.851 with a cut-off volume of 0.05 ml best indicating a FCD.

CONCLUSION

Automated MRI postprocessing and presentation of co-registered output maps in the PACS allowed for rapid (i.e., "within a minute") identification of FCDs in our clinical setting. The presence of false-positive findings currently requires a careful comparison of postprocessing results with conventional MR images but may be reduced in the future using a neural network better adapted to MP2RAGE images.

Improving surgical outcome with electric source imaging and high field magnetic resonance imaging

While most patients with focal epilepsy present with clear structural abnormalities on standard, 1.5 or 3 T MRI, some patients are MRI-negative. For those, quantitative MRI techniques, such as volumetry, voxel-based morphometry, and relaxation time measurements can aid in finding the epileptogenic focus. High-field MRI, just recently approved for clinical use by the FDA, increases the resolution and, in several publications, was shown to improve the detection of focal cortical dysplasias and mild cortical malformations. For those cases without any tissue abnormality in neuroimaging, even at 7 T, scalp EEG alone is insufficient to delimitate the epileptogenic zone. They may benefit from the use of high-density EEG, in which the increased number of electrodes helps improve spatial sampling. The spatial resolution of even low-density EEG can benefit from electric source imaging techniques, which map the source of the recorded abnormal activity, such as interictal epileptiform discharges, focal slowing, and ictal rhythm. These EEG techniques help localize the irritative, functional deficit, and seizure-onset zone, to better estimate the epileptogenic zone. Combining those technologies allows several drug-resistant cases to be submitted to surgery, increasing the odds of seizure freedom and providing a must needed hope for patients with epilepsy.

Focal cortical dysplasia: an update on diagnosis and treatment

INTRODUCTION

Focal cortical dysplasias (FCDs) represent the most common etiology in pediatric drug-resistant focal epilepsies undergoing surgical treatment. The localization, extent and histopathological features of FCDs are considerably variable. Somatic mosaic mutations of genes that encode proteins in the PI3K-AKTmTOR pathway, which also includes the tuberous sclerosis associated genes TSC1 and TSC2, have been implicated in FCD type II in a substantial subset of patients. Surgery is the principal therapeutic option for FCD-related epilepsy. Advanced neurophysiological and neuroimaging techniques have improved surgical outcome and reduced the risk of postsurgical deficits. Pharmacological MTOR inhibitors are being tested in clinical trials and might represent an example of personalized treatment of epilepsy based on the known mechanisms of disease, used alone or in combination with surgery.

AREAS COVERED

This review will critically analyze the advances in the diagnosis and treatment of FCDs, with a special focus on the novel therapeutic options prompted by a better understanding of their pathophysiology.

EXPERT OPINION

Focal cortical dysplasia is a main cause of drug-resistant epilepsy, especially in children. Novel, personalized approaches are needed to more effectively treat FCD-related epilepsy and its cognitive consequences.

Focal Cortical Dysplasia IIIa in Hippocampal Sclerosis-Associated Epilepsy: Anatomo-Electro-Clinical Profile and Surgical Results From a Multicentric Retrospective Study

BACKGROUND

Hippocampal sclerosis (HS) may be associated with focal cortical dysplasia IIIa (FCD IIIa) in patients undergoing surgery for temporal lobe epilepsy (TLE).

OBJECTIVE

To investigate whether the anatomo-electro-clinical profile and surgical outcome in patients with HS-related TLE are affected by coexisting FCD IIIa.

METHODS

A total of 220 patients, operated in 5 centers, with at least 24 mo follow-up (FU), were retrospectively studied. Preliminary univariate and subsequent multivariate analyses were performed to investigate possible associations between several potential presurgical, surgical, and postsurgical predictors and different variables (Engel's class I and Engel's class Ia, co-occurrence of FCD IIIa).

RESULTS

At last available postoperative control (FU: range 24-95 mo, median 47 mo), 182 (82.7%) patients were classified as Engel's class I and 142 (64.5%) as Engel's class Ia. At multivariate analysis, extension of neocortical resection and postoperative electroencephalogram were significantly associated with Engel's class I, whereas length of FU had a significant impact on class Ia in the whole cohort and in isolated HS (iHS) patients, but not in the FCD IIIa group. No differences emerged in the anatomo-electro-clinical profile and surgical results between patients with FCD IIIa and with iHS.

CONCLUSION

Coexistence of FCD IIIa did not confer a distinct anatomo-electro-clinical profile to patients with HS-related epilepsy. Postoperative seizure outcome was similar in FCD IIIa and iHS cases. These findings indicate limited clinical relevance of FCD IIIa in HS-related epilepsy and might be useful for refining future FCD classifications. Further studies are needed to clarify the correlation of class Ia outcome with the duration of FU.

Automated detection and segmentation of focal cortical dysplasias (FCDs) with artificial intelligence: Presentation of a novel convolutional neural network and its prospective clinical validation

PURPOSE

Focal cortical dysplasias (FCDs) represent one of the most frequent causes of pharmaco-resistant focal epilepsies. Despite improved clinical imaging methods over the past years, FCD detection remains challenging, as FCDs vary in location, size, and shape and commonly blend into surrounding tissues without clear definable boundaries. We developed a novel convolutional neural network for FCD detection and segmentation and validated it prospectively on daily-routine MRIs.

MATERIAL AND METHODS

The neural network was trained on 201 T1 and FLAIR 3 T MRI volume sequences of 158 patients with mainly FCDs, regardless of type, and 7 focal PMG. Non-FCD/PMG MRIs, drawn from 100 normal MRIs and 50 MRIs with non-FCD/PMG pathologies, were added to the training. We applied the algorithm prospectively on 100 consecutive MRIs of patients with focal epilepsy from daily clinical practice. The results were compared with corresponding neuroradiological reports and morphometric MRI analyses evaluated by an experienced epileptologist.

RESULTS

Best training results reached a sensitivity (recall) of 70.1 % and a precision of 54.3 % for detecting FCDs. Applied on the daily-routine MRIs, 7 out of 9 FCDs were detected and segmented correctly with a sensitivity of 77.8 % and a specificity of 5.5 %. The results of conventional visual analyses were 33.3 % and 94.5 %, respectively (3/9 FCDs detected); the results of morphometric analyses with overall epileptologic evaluation were both 100 % (9/9 FCDs detected) and thus served as reference.

CONCLUSION

We developed a 3D convolutional neural network with autoencoder regularization for FCD detection and segmentation. Our algorithm employs the largest FCD training dataset to date with various types of FCDs and some focal PMG. It provided a higher sensitivity in detecting FCDs than conventional visual analyses. Despite its low specificity, the number of false positively predicted lesions per MRI was lower than with morphometric analysis. We consider our algorithm already useful for FCD pre-screening in everyday clinical practice.

Value of 7T MRI and post-processing in patients with nonlesional 3T MRI undergoing epilepsy presurgical evaluation

OBJECTIVE

Ultra-high-field 7-Tesla (7T) magnetic resonance imaging (MRI) offers increased signal-to-noise and contrast-to-noise ratios, which may improve visualization of cortical malformations. We aim to assess the clinical value of in vivo structural 7T MRI and its post-processing for the noninvasive identification of epileptic brain lesions in patients with pharmacoresistant epilepsy and nonlesional 3T MRI who are undergoing presurgical evaluation.

METHODS

Sixty-seven patients were included who had nonlesional 3T MRI by official radiology report. Epilepsy protocols were used for the 3T and 7T acquisitions. Post-processing of the 7T T1-weighted magnetization-prepared two rapid acquisition gradient echoes sequence was performed using the morphometric analysis program (MAP) with comparison to a normal database consisting of 50 healthy controls. Review of 7T was performed by an experienced board-certified neuroradiologist and at the multimodal patient management conference. The clinical significance of 7T findings was assessed based on intracranial electroencephalography (ICEEG) ictal onset, surgery, postoperative seizure outcomes, and histopathology.

RESULTS

Unaided visual review of 7T detected previously unappreciated subtle lesions in 22% (15/67). When aided by 7T MAP, the total yield increased to 43% (29/67). The location of the 7T-identified lesion was identical to or contained within the ICEEG ictal onset in 13 of 16 (81%). Complete resection of the 7T-identified lesion was associated with seizure freedom (P = .03). Histopathology of the 7T-identified lesions encountered mainly focal cortical dysplasia (FCD). 7T MAP yielded 25% more lesions (6/24) than 3T MAP, and showed improved conspicuity in 46% (11/24).

SIGNIFICANCE

Our data suggest a major benefit of 7T with post-processing for detecting subtle FCD lesions for patients with pharmacoresistant epilepsy and nonlesional 3T MRI.

Improved Visualization of Focal Cortical Dysplasia With Surface-Based Multiparametric Quantitative MRI

Purpose

In the clinical routine, detection of focal cortical dysplasia (FCD) by visual inspection is challenging. Still, information about the presence and location of FCD is highly relevant for prognostication and treatment decisions. Therefore, this study aimed to develop, describe and test a method for the calculation of synthetic anatomies using multiparametric quantitative MRI (qMRI) data and surface-based analysis, which allows for an improved visualization of FCD.

Materials and Methods

Quantitative T1-, T2- and PD-maps and conventional clinical datasets of patients with FCD and epilepsy were acquired. Tissue segmentation and delineation of the border between white matter and cortex was performed. In order to detect blurring at this border, a surface-based calculation of the standard deviation of each quantitative parameter (T1, T2, and PD) was performed across the cortex and the neighboring white matter for each cortical vertex. The resulting standard deviations combined with measures of the cortical thickness were used to enhance the signal of conventional FLAIR-datasets. The resulting synthetically enhanced FLAIR-anatomies were compared with conventional MRI-data utilizing regions of interest based analysis techniques.

Results

The synthetically enhanced FLAIR-anatomies showed higher signal levels than conventional FLAIR-data at the FCD sites (p = 0.005). In addition, the enhanced FLAIR-anatomies exhibited higher signal levels at the FCD sites than in the corresponding contralateral regions (p = 0.005). However, false positive findings occurred, so careful comparison with conventional datasets is mandatory.

Conclusion

Synthetically enhanced FLAIR-anatomies resulting from surface-based multiparametric qMRI-analyses have the potential to improve the visualization of FCD and, accordingly, the treatment of the respective patients.

Pilot Study of Voxel-Based Morphometric MRI Post-processing in Patients With Non-lesional Operculoinsular Epilepsy

Objective: The aim of this study was to use voxel-based MRI post-processing in detection of subtle FCD in drug-resistant operculoinsular epilepsy patients with negative presurgical MRI, and by combining magnetoencephalography (MEG) to improve the localization of epileptogenic zone.

Methods: Operculoinsular epilepsy patients with a negative presurgical MRI were included in this study. MRI post-processing was performed using a Morphometric Analysis Program (MAP) on T1-weighted volumetric MRI. Clinical information including semiology, MEG, scalp electroencephalogram (EEG), intracranial EEG and surgical strategy was retrospectively reviewed. The pertinence of MAP-positive areas was confirmed by surgical outcome and pathology.

Results: A total of 20 patients were diagnosed with operculoinsular epilepsy had non-lesional MRI during 2010–2018, of which 11 patients with resective surgeries were included. MEG showed clusters of single equivalent current dipole (SECD) in inferior frontal regions in five patients and temporal-insular/ frontal-temporal-insular/parietal-insular regions in five patients. Four out of 11 patients had positive MAP results. The MAP positive rate was 36.4%. The positive regions were in insular in one patient and operculoinsular regions in three patients. Three of the four patients who were MAP-positive got seizure-free after successfully resect the MAP-positive and MEG-positive regions (the pathology results were FCD IIb in two patients and FCD IIa in one patient).

Conclusions: MAP is a useful tool in detection the epileptogenic lesions in patients with MRI-negative operculoinsular epilepsy. Notably, in order to make a right surgical regime decision, MAP results should always be interpreted in the context of the patient's anatomo-electroclinical presentation.

Ultrasonographic features of focal cortical dysplasia and their relevance for epilepsy surgery

OBJECTIVE Surgery has proven to be the best therapeutic option for drug-refractory cases of focal cortical dysplasia (FCD)-associated epilepsy. Seizure outcome primarily depends on the completeness of resection, rendering the intraoperative FCD identification and delineation particularly important. This study aims to assess the diagnostic yield of intraoperative ultrasound (IOUS) in surgery for FCD-associated drug-refractory epilepsy. METHODS The authors prospectively enrolled 15 consecutive patients with drug-refractory epilepsy who underwent an IOUS-assisted microsurgical resection of a radiologically suspected FCD between January 2013 and July 2016. The findings of IOUS were compared with those of presurgical MRI postprocessing and the sonographic characteristics were analyzed in relation to the histopathological findings. The authors investigated the added value of IOUS in achieving completeness of resection and improving postsurgical seizure outcome. RESULTS The neurosurgeon was able to identify the dysplastic tissue by IOUS in all cases. The visualization of FCD type I was more challenging compared to FCD II and the demarcation of its borders was less clear. Postsurgical MRI showed residual dysplasia in 2 of the 3 patients with FCD type I. In all FCD type II cases, IOUS allowed for a clear intraoperative visualization and demarcation, strongly correlating with presurgical MRI postprocessing. Postsurgical MRI confirmed complete resection in all FCD type II cases. Sonographic features correlated with the histopathological classification of dysplasia (sonographic abnormalities increase continuously in the following order: FCD IA/IB, FCD IC, FCD IIA, FCD IIB). In 1 patient with IOUS features atypical for FCD, histopathological investigation showed nonspecific gliosis. CONCLUSIONS Morphological features of FCD, as identified by IOUS, correlate well with advanced presurgical imaging. The resolution of IOUS was superior to MRI in all FCD types. The appreciation of distinct sonographic features on IOUS allows the intraoperative differentiation between FCD and non-FCD lesions as well as the discrimination of different histological subtypes of FCD. Sonographic demarcation depends on the underlying degree of dysplasia. IOUS allows for more tailored resections by facilitating the delineation of the dysplastic tissue.

Novel vertebral computed tomography indices in normal and spinal disorder dogs

This study was carried out to derive and evaluate reference computed tomography (CT)-based indices for normal canine spine. CT and magnetic resonance images were acquired from 12 clinically normal Beagle dogs (normal group) and 50 dogs with 56 spinal disorders (patient group). Image acquisition regions were cervical spine (C2–T1), thoracic spine (T1–T13), and lumbar spine (L1–L7). Measured indices were: the ratios of width to height of the spinal cord including the dura matter (CR) and of the vertebral foramen (FR), and the ratio of the cross-sectional area of the spinal cord to that of the vertebral foramen (CFAR). Reliability analysis was performed to evaluate intermodality agreement. Student's t-tests and receiver operating characteristic curves were used to discriminate the normal and patient groups on CT. Intermodality agreements of the normal and patient groups were acceptable to excellent. The highest discriminating levels of CR at the vertebral body level and the intervertebral disc space level were 1.25 or more and 1.44 or more, respectively. FR and CFAR had the highest discriminating level at the cervical region. This report presents quantitative information on canine spinal morphometry; the obtained indices may be helpful for CT screening of dogs with spinal disorders.

Quantitative positron emission tomography-guided magnetic resonance imaging postprocessing in magnetic resonance imaging-negative epilepsies

OBJECTIVE

Detection of focal cortical dysplasia (FCD) is of paramount importance in epilepsy presurgical evaluation. Our study aims at utilizing quantitative positron emission tomography (QPET) analysis to complement magnetic resonance imaging (MRI) postprocessing by a morphometric analysis program (MAP) to facilitate automated identification of subtle FCD.

METHODS

We retrospectively included a consecutive cohort of surgical patients who had a negative preoperative MRI by radiology report. MAP was performed on T1-weighted volumetric sequence and QPET was performed on PET/computed tomographic data, both with comparison to scanner-specific normal databases. Concordance between MAP and QPET was assessed at a lobar level, and the significance of concordant QPET-MAP⁺ abnormalities was confirmed by postresective seizure outcome and histopathology. QPET thresholds of standard deviations (SDs) of -1, -2, -3, and -4 were evaluated to identify the optimal threshold for QPET-MAP analysis.

RESULTS

A total of 104 patients were included. When QPET thresholds of SD = -1, -2, and -3 were used, complete resection of the QPET-MAP⁺ region was significantly associated with seizure-free outcome when compared with the partial resection group (P = 0.023, P < 0.001, P = 0.006) or the no resection group (P = 0.002, P < 0.001, P = 0.001). The SD threshold of -2 showed the best combination of positive rate (55%), sensitivity (0.68), specificity (0.88), positive predictive value (0.88), and negative predictive value (0.69). Surgical pathology of the resected QPET-MAP⁺ areas revealed mainly FCD type I. Multiple QPET-MAP⁺ regions were present in 12% of the patients at SD = -2.

SIGNIFICANCE

Our study demonstrates a practical and effective approach to combine quantitative analyses of functional (QPET) and structural (MAP) imaging data to improve identification of subtle epileptic abnormalities. This approach can be readily adopted by epilepsy centers to improve postresective seizure outcomes for patients without apparent lesions on MRI.

Detection of Lesions in Mesial Temporal Lobe Epilepsy by Using MR Fingerprinting

Purpose To improve diagnosis of hippocampal sclerosis (HS) in patients with mesial temporal lobe epilepsy (MTLE) by using MR fingerprinting and compare with visual assessment of T1- and T2-weighted MR images. Materials and Methods For this prospective study performed between April and November 2016, T1 and T2 maps were obtained and tissue segmentation performed in consecutive patients with drug-resistant MTLE with unilateral or bilateral HS. T1 and T2 maps were compared between 33 patients with MTLE (23 women and 10 men; mean age, 32.6 years; age range, 16-60 years) and 30 healthy participants (20 women and 10 men; mean age, 28.8 years; age range, 18-40 years). Differences in individual bilateral hippocampi were compared by using a Wilcoxon signed rank test, whereas the Wilcoxon rank-sum test was used for difference analysis between healthy control participants and patients with MTLE. Results The diagnosis rate (ie, ratio of HS diagnosed on the basis of a 2.5-minute MR fingerprinting examination compared with standard methods: MRI, electroencephalography, and PET) was 32 of 33 (96.9%; 95% confidence interval: 84.9%, 100%), reflecting improved accuracy of diagnosis (P = 1.92 × 10^-12) over routine MR examinations that had a diagnostic rate of 23 of 33 (69.7%; 95% confidence interval: 51.5%, 81.6%). The comparison between atrophic and normal-appearing hippocampus in 33 patients with MTLE and healthy control participants demonstrated that both T1 and T2 values in HS lesions were higher than those of normal hippocampal tissue of healthy participants (T1: 1361 msec ± 85 vs 1249 msec ± 59, respectively; T2: 135 msec ± 15 vs 104 msec ± 9, respectively; P < .0001). Conclusion MR fingerprinting allowed for multiparametric mapping of temporal lobe within 2.5 minutes and helped to identify lesions suspicious for HS in patients with MTLE with improved accuracy.

Impact of focal cortical dysplasia Type IIIa on seizure outcome following anterior mesial temporal lobe resection for the treatment of epilepsy

OBJECTIVE

Temporal lobe epilepsy (TLE) is the most common type of pharmacoresistant focal epilepsy, for which anterior mesial temporal lobe resection (AMTLR) is a treatment option. Focal cortical dysplasia Type IIIa (FCD IIIa), a developmental lesion resulting from defects in neuronal formation and migration into the temporal pole (FCD I) combined with hippocampal sclerosis (HS), can be a neuropathological finding. In this study, the authors investigate the impact of FCD IIIa on seizure outcome in patients with TLE who underwent AMTLR.

METHODS

The authors performed a retrospective analysis of all patients with TLE who underwent AMTLR at their institution between June 2011 and April 2014. Histopathological analysis was used to determine whether patients had HS together with FCD I (FCD IIIa) or HS alone. The groups were compared with regard to age, sex, years of epilepsy, and seizure outcome using the Engel classification.

RESULTS

A total of 51 patients with TLE underwent AMTLR at the authors’ institution. FCD IIIa was diagnosed in 13 cases. The patients experienced seizures for a mean duration of 31.1 years. The mean length of follow-up after the procedure was 18 months. All patients with FCD IIIa had a favorable seizure outcome (Engel Class I or II) compared with 71% of the patients with no pathological findings in the temporal pole (p < 0.01).

CONCLUSIONS

Patients with histopathologically proven FCD IIIa had a significantly better seizure outcome after AMTLR than patients with HS alone. Further effort should be made during presurgical evaluation to detect FCD IIIa so that the most suitable resection technique can be chosen and postoperative seizure outcome can be predicted for patient counseling.

Personalized structural image analysis in patients with temporal lobe epilepsy

Volumetric and morphometric studies have demonstrated structural abnormalities related to chronic epilepsies on a cohort- and population-based level. On a single-patient level, specific patterns of atrophy or cortical reorganization may be widespread and heterogeneous but represent potential targets for further personalized image analysis and surgical therapy. The goal of this study was to compare morphometric data analysis in 37 patients with temporal lobe epilepsies with expert-based image analysis, pre-informed by seizure semiology and ictal scalp EEG. Automated image analysis identified abnormalities exceeding expert-determined structural epileptogenic lesions in 86% of datasets. If EEG lateralization and expert MRI readings were congruent, automated analysis detected abnormalities consistent on a lobar and hemispheric level in 82% of datasets. However, in 25% of patients EEG lateralization and expert readings were inconsistent. Automated analysis localized to the site of resection in 60% of datasets in patients who underwent successful epilepsy surgery. Morphometric abnormalities beyond the mesiotemporal structures contributed to subtype characterisation. We conclude that subject-specific morphometric information is in agreement with expert image analysis and scalp EEG in the majority of cases. However, automated image analysis may provide non-invasive additional information in cases with equivocal radiological and neurophysiological findings.

Voxel-based magnetic resonance image postprocessing in epilepsy

Objective

Although the general utility of voxel‐based processing of structural magnetic resonance imaging (MRI) data for detecting occult lesions in focal epilepsy is established, many differences exist among studies, and it is unclear which processing method is preferable. The aim of this study was to compare the ability of commonly used methods to detect epileptogenic lesions in magnetic resonance MRI‐positive and MRI‐negative patients, and to estimate their diagnostic yield.

Methods

We identified 144 presurgical focal epilepsy patients, 15 of whom had a histopathologically proven and MRI‐visible focal cortical dysplasia; 129 patients were MRI negative with a clinical hypothesis of seizure origin, 27 of whom had resections. We applied four types of voxel‐based morphometry (VBM), three based on T1 images (gray matter volume, gray matter concentration, junction map [JM]) and one based on normalized fluid‐attenuated inversion recovery (nFSI). Specificity was derived from analysis of 50 healthy controls.

Results

The four maps had different sensitivity and specificity profiles. All maps showed detection rates for focal cortical dysplasia patients (MRI positive and negative) of >30% at a strict threshold of p < 0.05 (family‐wise error) and >60% with a liberal threshold of p < 0.0001 (uncorrected), except for gray matter volume (14% and 27% detection rate). All maps except nFSI showed poor specificity, with high rates of false‐positive findings in controls. In the MRI‐negative patients, absolute detection rates were lower. A concordant nFSI finding had a significant positive odds ratio of 7.33 for a favorable postsurgical outcome in the MRI‐negative group. Spatial colocalization of JM and nFSI was rare, yet showed good specificity throughout the thresholds.

Significance

All VBM variants had specific diagnostic properties that need to be considered for an adequate interpretation of the results. Overall, structural postprocessing can be a useful tool in presurgical diagnostics, but the low specificity of some maps has to be taken into consideration.

Towards in vivo focal cortical dysplasia phenotyping using quantitative MRI

Focal cortical dysplasias (FCDs) are a range of malformations of cortical development each with specific histopathological features. Conventional radiological assessment of standard structural MRI is useful for the localization of lesions but is unable to accurately predict the histopathological features. Quantitative MRI offers the possibility to probe tissue biophysical properties in vivo and may bridge the gap between radiological assessment and ex-vivo histology. This review will cover histological, genetic and radiological features of FCD following the ILAE classification and will explain how quantitative voxel- and surface-based techniques can characterise these features. We will provide an overview of the quantitative MRI measures available, their link with biophysical properties and finally the potential application of quantitative MRI to the problem of FCD subtyping. Future research linking quantitative MRI to FCD histological properties should improve clinical protocols, allow better characterisation of lesions in vivo and tailored surgical planning to the individual.

Novel surface features for automated detection of focal cortical dysplasias in paediatric epilepsy

Focal cortical dysplasia is a congenital abnormality of cortical development and the leading cause of surgically remediable drug-resistant epilepsy in children. Post-surgical outcome is improved by presurgical lesion detection on structural MRI. Automated computational techniques have improved detection of focal cortical dysplasias in adults but have not yet been effective when applied to developing brains. There is therefore a need to develop reliable and sensitive methods to address the particular challenges of a paediatric cohort. We developed a classifier using surface-based features to identify focal abnormalities of cortical development in a paediatric cohort. In addition to established measures, such as cortical thickness, grey-white matter blurring, FLAIR signal intensity, sulcal depth and curvature, our novel features included complementary metrics of surface morphology such as local cortical deformation as well as post-processing methods such as the "doughnut" method - which quantifies local variability in cortical morphometry/MRI signal intensity, and per-vertex interhemispheric asymmetry. A neural network classifier was trained using data from 22 patients with focal epilepsy (mean age = 12.1 ± 3.9, 9 females), after intra- and inter-subject normalisation using a population of 28 healthy controls (mean age = 14.6 ± 3.1, 11 females). Leave-one-out cross-validation was used to quantify classifier sensitivity using established features and the combination of established and novel features. Focal cortical dysplasias in our paediatric cohort were correctly identified with a higher sensitivity (73%) when novel features, based on our approach for detecting local cortical changes, were included, when compared to the sensitivity using only established features (59%). These methods may be applicable to aiding identification of subtle lesions in medication-resistant paediatric epilepsy as well as to the structural analysis of both healthy and abnormal cortical development.

MRI postprocessing in presurgical evaluation

PURPOSE OF REVIEW

Advanced MRI postprocessing techniques are increasingly used to complement visual analysis and elucidate structural epileptogenic lesions. This review summarizes recent developments in MRI postprocessing in the context of epilepsy presurgical evaluation, with the focus on patients with unremarkable MRI by visual analysis (i.e. 'nonlesional' MRI).

RECENT FINDINGS

Various methods of MRI postprocessing have been reported to show additional clinical values in the following areas: lesion detection on an individual level; lesion confirmation for reducing the risk of over reading the MRI; detection of sulcal/gyral morphologic changes that are particularly difficult for visual analysis; and delineation of cortical abnormalities extending beyond the visible lesion. Future directions to improve the performance of MRI postprocessing include using higher magnetic field strength for better signal-to-noise ratio and contrast-to-noise ratio adopting a multicontrast frame work and integration with other noninvasive modalities.

SUMMARY

MRI postprocessing can provide essential value to increase the yield of structural MRI and should be included as part of the presurgical evaluation of nonlesional epilepsies. MRI postprocessing allows for more accurate identification/delineation of cortical abnormalities, which should then be more confidently targeted and mapped.

Re-review of MRI with post-processing in nonlesional patients in whom epilepsy surgery has failed

Management of MRI-negative patients with intractable focal epilepsy after failed surgery is particularly challenging. In this study, we aim to investigate whether MRI post-processing could identify relevant targets for the re-evaluation of MRI-negative patients who failed the initial resective surgery. We examined a consecutive series of 56 MRI-negative patients who underwent resective surgery and had recurring seizures at 1-year follow-up. T1-weighted volumetric sequence from the pre-surgical MRI was used for voxel-based MRI post-processing which was implemented in a morphometric analysis program (MAP). MAP was positive in 15 of the 56 patients included in this study. In 5 patients, the MAP+ regions were fully resected. In 10 patients, the MAP+ regions were not or partially resected: two out of the 10 patients had a second surgery including the unresected MAP+ region, and both became seizure-free; the remaining 8 patients did not undergo further surgery, but the unresected MAP+ regions were concordant with more than one noninvasive modality in 7. In the 8 patients who had unresected MAP+ regions and intracranial-EEG before the previous surgery, the unresected MAP+ regions were concordant with ictal onset in 6. Our data suggest that scrutiny of the presurgical MRI guided by MRI post-processing may reveal relevant targets for reoperation in nonlesional epilepsies. MAP findings, when concordant with the patient's other noninvasive data, should be considered when planning invasive evaluation/reoperation for this most challenging group of patients.

Voxel-based morphometric magnetic resonance imaging (MRI) postprocessing in MRI-negative epilepsies

OBJECTIVE

In the presurgical workup of magnetic resonance imaging (MRI)-negative (MRI(-) or "nonlesional") pharmacoresistant focal epilepsy (PFE) patients, discovering a previously undetected lesion can drastically change the evaluation and likely improve surgical outcome. Our study utilizes a voxel-based MRI postprocessing technique, implemented in a morphometric analysis program (MAP), to facilitate detection of subtle abnormalities in a consecutive cohort of MRI(-) surgical candidates.

METHODS

Included in this retrospective study was a consecutive cohort of 150 MRI(-) surgical patients. MAP was performed on T1-weighted MRI, with comparison to a scanner-specific normal database. Review and analysis of MAP were performed blinded to patients' clinical information. The pertinence of MAP(+) areas was confirmed by surgical outcome and pathology.

RESULTS

MAP showed a 43% positive rate, sensitivity of 0.9, and specificity of 0.67. Overall, patients with the MAP(+) region completely resected had the best seizure outcomes, followed by the MAP(-) patients, and patients who had no/partial resection of the MAP(+) region had the worst outcome (p < 0.001). Subgroup analysis revealed that visually identified subtle findings are more likely correct if also MAP(+) . False-positive rate in 52 normal controls was 2%. Surgical pathology of the resected MAP(+) areas contained mainly non-balloon-cell focal cortical dysplasia (FCD). Multiple MAP(+) regions were present in 7% of patients.

INTERPRETATION

MAP can be a practical and valuable tool to: (1) guide the search for subtle MRI abnormalities and (2) confirm visually identified questionable abnormalities in patients with PFE due to suspected FCD. A MAP(+) region, when concordant with the patient's electroclinical presentation, should provide a legitimate target for surgical exploration.

Post-processing of structural MRI for individualized diagnostics

Currently, a relevant proportion of all histopathologically proven focal cortical dysplasia (FCD) escape visual detection; this shows the need for additional improvements in analyzing MRI data. A positive MRI is still the strongest prognostic factor for postoperative freedom of seizures. Among several post-processing methods voxel-based morphometry (VBM) of T1- and T2-weighted sequences and T2 relaxometry are routinely applied in pre-surgical diagnostics of cryptogenic epilepsy in epilepsy centers. VBM is superior to conventional visual analysis with 9-15% more identified epileptogenic foci, while T2 relaxometry has its main application in (mesial) temporal lobe epilepsy. Further methods such as surface-based morphometry (SBM) or diffusion tensor imaging are promising but there is a lack of current studies comparing their individual diagnostic value. Post-processing methods represent an important addition to conventional visual analysis but need to be interpreted with expertise and experience so that they should be apprehended as a complementary tool within the context of the multi-modal evaluation of epilepsy patients. This review will give an overview of existing post-processing methods of structural MRI and outline their clinical relevance in detection of epileptogenic structural changes.

Sulcus-based MR analysis of focal cortical dysplasia located in the central region

Objective

Focal cortical dysplasias (FCDs) are mainly located in the frontal region, with a particular tropism for the central sulcus. Up to 30% of lesions are undetected (magnetic resonance [MR]-negative FCD patients) or belatedly diagnosed by visual analysis of MR images. We propose an automated sulcus-based method to analyze abnormal sulcal patterns associated with central FCD, taking into account the normal interindividual sulcal variability.

Methods

We retrospectively studied 29 right-handed patients with FCD in the central region (including 12 MR negative histologically-confirmed cases) and 29 right-handed controls. The analysis of sulcal abnormalities from T1-weighted MR imaging (MRI) was performed using a graph-based representation of the cortical folds and an automated sulci recognition system, providing a new quantitative criterion to describe sulcal patterns, termed sulcus energy.

Results

Group analysis showed that the central sulcus in the hemisphere ipsilateral to the FCD exhibited an abnormal sulcal pattern compared with controls (p = 0.032). FCDs were associated with abnormal patterns of the central sulci compared with controls (p = 0.006), a result that remained significant when MR-negative and MR-positive patients were considered separately, while the effects of sex, age and MR-field were not significant. At the individual level, sulcus energy alone failed to detect the FCD lesion. We found, however, a significant association between maximum z-scores and the site of FCD (p = 0.0046) which remained significant in MR-negative (p = 0.024) but not in MR-positive patients (p = 0.058). The maximum z-score pointed to an FCD sulcus in four MR-negative and five MR-positive patients.

Conclusions

We identified abnormal sulcal patterns in patients with FCD of the central region compared with healthy controls. The abnormal sulcal patterns ipsilateral to the FCD and the link between sulcus energy and the FCD location strengthen the interest of sulcal abnormalities in FCD patients.

Contrast enhancement by combining T1- and T2-weighted structural brain MR Images

PURPOSE

In order to more precisely differentiate cerebral structures in neuroimaging studies, a novel technique for enhancing the tissue contrast based on a combination of T1-weighted (T1w) and T2-weighted (T2w) MRI images was developed.

METHODS

The combined image (CI) was calculated as CI = (T1w - sT2w)/(T1w + sT2w), where sT2w is the scaled T2-weighted image. The scaling factor was calculated to adjust the gray- matter (GM) voxel intensities in the T2w image so that their median value equaled that of the GM voxel intensities in the T1w image. The image intensity homogeneity within a tissue and the discriminability between tissues in the CI versus the separate T1w and T2w images were evaluated using the segmentation by the FMRIB Software Library (FSL) and FreeSurfer (Athinoula A. Martinos Center for Biomedical Imaging at Massachusetts General Hospital, Boston, MA) software.

RESULTS

The combined image significantly improved homogeneity in the white matter (WM) and GM compared to the T1w images alone. The discriminability between WM and GM also improved significantly by applying the CI approach. Significant enhancements to the homogeneity and discriminability also were achieved in most subcortical nuclei tested, with the exception of the amygdala and the thalamus.

CONCLUSION

The tissue discriminability enhancement offered by the CI potentially enables more accurate neuromorphometric analyses of brain structures.

Linking MRI postprocessing with magnetic source imaging in MRI-negative epilepsy

OBJECTIVE

MRI-negative (MRI-) pharmacoresistant focal epilepsy (PFE) patients are most challenging for epilepsy surgical management. This study utilizes a voxel-based MRI postprocessing technique, implemented using a morphometric analysis program (MAP), aiming to facilitate detection of subtle focal cortical dysplasia (FCD) in MRI- patients. Furthermore, the study examines the concordance between MAP-identified regions and localization from magnetic source imaging (MSI).

METHODS

Included in this retrospective study were 25 MRI- surgical patients. MAP was performed on T1-weighted MRI, with comparison to a normal database. The pertinence of MAP+ areas was confirmed by MSI, surgical outcome and pathology. Analyses of MAP and MSI were performed blindly from patients' clinical information and independently from each other.

RESULTS

The detection rate of subtle changes by MAP was 48% (12/25). Once MAP+ areas were resected, patients were more likely to be seizure-free (p=0.02). There were no false positives in the 25 age-matched normal controls. Seven patients had a concordant MSI correlate. Patients in whom a concordant area was identified by both MAP and MSI had a significantly higher chance of achieving a seizure-free outcome following complete resection of this area (p=0.008). In the 9 resected MAP+ areas, pathology revealed FCD type IA in 7 and type IIB in 2.

INTERPRETATION

MAP shows promise in identifying subtle FCD abnormalities and increasing the diagnostic yield of conventional MRI visual analysis in presurgical evaluation of PFE. Concordant MRI postprocessing and MSI analyses may lead to the noninvasive identification of a structurally and electrically abnormal subtle lesion that can be surgically targeted.