Recommendations for the use of structural magnetic resonance imaging in the care of patients with epilepsy: A consensus report from the International League Against Epilepsy Neuroimaging Task Force

DeepFLAIR: A neural network approach to mitigate signal and contrast loss in temporal lobes at 7 Tesla FLAIR images

BACKGROUND AND PURPOSE

Higher magnetic field strength introduces stronger magnetic field inhomogeneities in the brain, especially within temporal lobes, leading to image artifacts. Particularly, T2-weighted fluid-attenuated inversion recovery (FLAIR) images can be affected by these artifacts. Here, we aimed to improve the FLAIR image quality in temporal lobe regions through image processing of multiple contrast images via machine learning using a neural network.

METHODS

Thirteen drug-resistant MR-negative epilepsy patients (age 29.2 ± 9.4y, 5 females) were scanned on a 7 T MRI scanner. Magnetization-prepared (MP2RAGE) and saturation-prepared with 2 rapid gradient echoes, multi-echo gradient echo with four echo times, and the FLAIR sequence were acquired. A voxel-wise neural network was trained on extratemporal-lobe voxels from the acquired structural scans to generate a new FLAIR-like image (i.e., deepFLAIR) with reduced temporal lobe inhomogeneities. The deepFLAIR was evaluated in temporal lobes through signal-to-noise (SNR), contrast-to-noise (CNR) ratio, the sharpness of the gray-white matter boundary and joint-histogram analysis. Saliency mapping demonstrated the importance of each input image per voxel.

RESULTS

SNR and CNR in both gray and white matter were significantly increased (p < 0.05) in the deepFLAIR's temporal ROIs, compared to the FLAIR. The gray-white matter boundary sharpness was either preserved or improved in 10/13 right-sided temporal regions and was found significantly increased in the ROIs. Multiple image contrasts were influential for the deepFLAIR reconstruction with the MP2RAGE second inversion image being the most important.

CONCLUSIONS

The deepFLAIR network showed promise to restore the FLAIR signal and reduce contrast attenuation in temporal lobe areas. This may yield a valuable tool, especially when artifact-free FLAIR images are not available.

Seizure or syncope: Is the history-based scale feasible to use in an emergency department setting?

BACKGROUND

This study aimed to assess the efficacy of a screening questionnaire, based on historical criteria, in distinguishing between seizures and syncope in patients experiencing their first episode of transient loss of consciousness (TLOC) in a neurology emergency department.

METHODS

A prospective cohort of 159 patients with initial TLOC episodes underwent clinical observation and answered a nine-question screening questionnaire. The questionnaire's predictive ability was compared to final diagnoses determined through detailed neurology, electrophysiology, and cardiology assessments during a minimum 12-month follow-up. Logistic regression (LR) analysis was performed with final diagnosis as the outcome variable. The calibration and discrimination of the models were assessed.

RESULTS

revealed that the screening score accurately classified 72.33% of patients. Among those with positive screening scores, 65 (67.71%) had seizures compared to 31 (32.29%) with syncope. Introducing a novel risk-scoring model incorporating age and gender, in addition to the screening score, significantly improved performance achieving an accurate classification rate of 81.48%. Among patients with a positive prediction, 63 (80.77%) had seizure, whereas 15 (19.23%) had syncope.

CONCLUSIONS

Employing a structured questionnaire based on common historical criteria is a valuable tool for distinguishing between seizure and syncope in the dynamic setting of the emergency department.

Breath-Hold-Triggered BOLD fMRI in Drug-Resistant Nonlesional Focal Epilepsy-A Pilot Study

PURPOSE

Individuals with drug-resistant epilepsy may benefit from epilepsy surgery. In nonlesional cases, where no epileptogenic lesion can be detected on structural magnetic resonance imaging, multimodal neuroimaging studies are required. Breath-hold-triggered BOLD fMRI (bh-fMRI) was developed to measure cerebrovascular reactivity in stroke or angiopathy and highlights regional network dysfunction by visualizing focal impaired flow increase after vasodilatory stimulus. This regional dysfunction may correlate with the epileptogenic zone. In this prospective single-center single-blind pilot study, we aimed to establish the feasibility and safety of bh-fMRI in individuals with drug-resistant non-lesional focal epilepsy undergoing presurgical evaluation.

METHODS

In this prospective study, 10 consecutive individuals undergoing presurgical evaluation for drug-resistant focal epilepsy were recruited after case review at a multidisciplinary patient management conference. Electroclinical findings and results of other neuroimaging were used to establish the epileptogenic zone hypothesis. To calculate significant differences in cerebrovascular reactivity in comparison to the normal population, bh-fMRIs of 16 healthy volunteers were analyzed. The relative flow change of each volume of interest (VOI) of the atlas was then calculated compared to the flow change of the whole brain resulting in an atlas of normal cerebral reactivity. Consequently, the mean flow change of every VOI of each patient was tested against the healthy volunteers group. Areas with significant impairment of cerebrovascular reactivity had decreased flow change and were compared to the epileptogenic zone localization hypothesis in a single-blind design.

RESULTS

Acquisition of bh-fMRI was feasible in 9/10 cases, with one patient excluded due to noncompliance with breathing maneuvers. No adverse events were observed, and breath-hold for intermittent hypercapnia was well tolerated. On blinded review, we observed full or partial concordance of the local network dysfunction seen on bh-fMRI with the electroclinical hypothesis in 6/9 cases, including cases with extratemporal lobe epilepsy and those with nonlocalizing 18F-fluorodeoxyglucose positron emission tomography (FDG-PET).

CONCLUSION

This represents the first report of bh-fMRI in individuals with epilepsy undergoing presurgical evaluation. We found bh-fMRI to be feasible and safe, with a promising agreement to electroclinical findings. Thus, bh-fMRI may represent a potential modality in the presurgical evaluation of epilepsy. Further studies are needed to establish clinical utility.

Approach to Patients with Seizures and Epilepsy: A Guide for Primary Care Physicians

Seizures and epilepsy are common neurologic conditions that are frequently encountered in the outpatient primary care setting. An accurate diagnosis relies on a thorough clinical history and evaluation. Understanding seizure semiology and classification is crucial in conducting the initial assessment. Knowledge of common seizure triggers and provoking factors can further guide diagnostic testing and initial management. The pharmacodynamic characteristics and side effect profiles of anti-seizure medications are important considerations when deciding treatment and counseling patients, particularly those with comorbidities and in special populations such as patient of childbearing potential.

Spatial omics reveals molecular changes in focal cortical dysplasia type II

Focal cortical dysplasia (FCD) represents a group of diverse localized cortical lesions that are highly epileptogenic and occur due to abnormal brain development caused by genetic mutations, involving the mammalian target of rapamycin (mTOR). These somatic mutations lead to mosaicism in the affected brain, posing challenges to unravel the direct and indirect functional consequences of these mutations. To comprehensively characterize the impact of mTOR mutations on the brain, we employed here a multimodal approach in a preclinical mouse model of FCD type II (Rheb), focusing on spatial omics techniques to define the proteomic and lipidomic changes. Mass Spectrometry Imaging (MSI) combined with fluorescence imaging and label free proteomics, revealed insight into the brain's lipidome and proteome within the FCD type II affected region in the mouse model. MSI visualized disrupted neuronal migration and differential lipid distribution including a reduction in sulfatides in the FCD type II-affected region, which play a role in brain myelination. MSI-guided laser capture microdissection (LMD) was conducted on FCD type II and control regions, followed by label free proteomics, revealing changes in myelination pathways by oligodendrocytes. Surgical resections of FCD type IIb and postmortem human cortex were analyzed by bulk transcriptomics to unravel the interplay between genetic mutations and molecular changes in FCD type II. Our comparative analysis of protein pathways and enriched Gene Ontology pathways related to myelination in the FCD type II-affected mouse model and human FCD type IIb transcriptomics highlights the animal model's translational value. This dual approach, including mouse model proteomics and human transcriptomics strengthens our understanding of the functional consequences arising from somatic mutations in FCD type II, as well as the identification of pathways that may be used as therapeutic strategies in the future.

Identification and treatment of surgically-remediable causes of infantile epileptic spasms syndrome

INTRODUCTION

Infantile epileptic spasms syndrome (IESS) is a common developmental and epileptic encephalopathy with poor long-term outcomes. A substantial proportion of patients with IESS have a potentially surgically remediable etiology. Despite this, epilepsy surgery is underutilized in this patient group. Some surgically remediable etiologies, such as focal cortical dysplasia and malformation of cortical development with oligodendroglial hyperplasia in epilepsy (MOGHE), are under-diagnosed in infants and young children. Even when a surgically remediable etiology is recognised, for example, tuberous sclerosis or focal encephalomalacia, epilepsy surgery may be delayed or not considered due to diffuse EEG changes, unclear surgical boundaries, or concerns about operating in this age group.

AREAS COVERED

In this review, the authors discuss the common surgically remediable etiologies of IESS, their clinical and EEG features, and the imaging techniques that can aid in their diagnosis. They then describe the surgical approaches used in this patient group, and the beneficial impact that early epilepsy surgery can have on developing brain networks.

EXPERT OPINION

Epilepsy surgery remains underutilized even when a potentially surgically remediable cause is recognized. Overcoming the barriers that result in under-recognition of surgical candidates and underutilization of epilepsy surgery in IESS will improve long-term seizure and developmental outcomes.

Consensus Guideline on the Management of Epilepsy in Egypt: A National Delphi Consensus Study

OBJECTIVE

In epilepsy, early diagnosis, accurate determination of epilepsy type, proper selection of antiseizure medication, and monitoring are all essential. However, despite recent therapeutic advances and conceptual reconsiderations in the classification and management of epilepsy, serious gaps are still encountered in day-to-day practice in Egypt as well as several other resource-limited countries. Premature mortality, poor quality of life, socio-economic burden, cognitive problems, poor treatment outcomes, and comorbidities are major challenges that require urgent actions to be implemented at all levels. In recognition of this, a group of Egyptian epilepsy experts met through a series of consecutive meetings to specify the main concepts concerning the diagnosis and management of epilepsy, with the ultimate goal of establishing a nationwide Egyptian consensus.

METHODS

The consensus was developed through a modified Delphi methodology. A thorough review of the most recent relevant literature and international guidelines was performed to evaluate their applicability to the Egyptian situation. Afterward, several remote and live rounds were scheduled to reach a final agreement for all listed statements.

RESULTS

Of 278 statements reviewed in the first round, 256 achieved ≥80% agreement. Live discussion and refinement of the 22 statements that did not reach consensus during the first round took place, followed by final live voting then consensus was achieved for all remaining statements.

SIGNIFICANCE

With the implementation of these unified recommendations, we believe this will bring about substantial improvements in both the quality of care and treatment outcomes for persons with epilepsy in Egypt.

PLAIN LANGUAGE SUMMARY

This work represents the efforts of a group of medical experts to reach an agreement on the best medical practice related to people with epilepsy based on previously published recommendations while taking into consideration applicable options in resource-limited countries. The publication of this document is expected to minimize many malpractice issues and pave the way for better healthcare services on both individual and governmental levels.

Phenotypic Variability in Novel Doublecortin Gene Variants Associated with Subcortical Band Heterotopia

Doublecortin, encoded by the DCX gene, plays a crucial role in the neuronal migration process during brain development. Pathogenic variants of the DCX gene are the major causes of the "lissencephaly (LIS) spectrum", which comprehends a milder phenotype like Subcortical Band Heterotopia (SBH) in heterozygous female subjects. We performed targeted sequencing in three unrelated female cases with SBH. We identified three DCX-related variants: a novel missense (c.601A>G: p.Lys201Glu), a novel nonsense (c.210C>G: p.Tyr70*), and a previously identified nonsense (c.907C>T: p.Arg303*) variant. The novel c.601A>G: p.Lys201Glu variant shows a mother-daughter transmission pattern across four generations. The proband exhibits focal epilepsy and achieved seizure freedom with a combination of oxcarbazepine and levetiracetam. All other affected members have no history of epileptic seizures. Brain MRIs of the affected members shows predominant fronto-central SBH with mixed pachygyria on the overlying cortex. The two nonsense variants were identified in two unrelated probands with SBH, severe drug-resistant epilepsy and intellectual disability. These novel DCX variants further expand the genotypic-phenotypic correlations of lissencephaly spectrum disorders. Our documented phenotypic descriptions of three unrelated families provide valuable insights and stimulate further discussions on DCX-SBH cases.

Improving epilepsy diagnosis across the lifespan: approaches and innovations

Epilepsy diagnosis is often delayed or inaccurate, exposing people to ongoing seizures and their substantial consequences until effective treatment is initiated. Important factors contributing to this problem include delayed recognition of seizure symptoms by patients and eyewitnesses; cultural, geographical, and financial barriers to seeking health care; and missed or delayed diagnosis by health-care providers. Epilepsy diagnosis involves several steps. The first step is recognition of epileptic seizures; next is classification of epilepsy type and whether an epilepsy syndrome is present; finally, the underlying epilepsy-associated comorbidities and potential causes must be identified, which differ across the lifespan. Clinical history, elicited from patients and eyewitnesses, is a fundamental component of the diagnostic pathway. Recent technological advances, including smartphone videography and genetic testing, are increasingly used in routine practice. Innovations in technology, such as artificial intelligence, could provide new possibilities for directly and indirectly detecting epilepsy and might make valuable contributions to diagnostic algorithms in the future.

A PET-based radiomics nomogram for individualized predictions of seizure outcomes after temporal lobe epilepsy surgery

PURPOSE

To establish and validate a novel nomogram based on clinical characteristics and [18F]FDG PET radiomics for the prediction of postsurgical seizure freedom in patients with temporal lobe epilepsy (TLE).

PATIENTS AND METHODS

234 patients with drug-refractory TLE patients were included with a median follow-up time of 24 months after surgery. The correlation coefficient redundancy analysis and LASSO Cox regression were used to characterize risk factors. The Cox model was conducted to develop a Clinic-PET nomogram to predict the relapse status in the training set (n = 171). The nomogram's performance was estimated through discrimination, calibration, and clinical utility. The prognostic prediction model was validated in the test set (n = 63).

RESULTS

Eight radiomics features were selected to assess the radiomics score (radscore) of the operation side (Lat_radscore) and the asymmetric index (AI) of the radiomics score (AI_radscore). AI_radscor, Lat_radscor, secondarily generalized seizures (SGS), and duration between seizure onset and surgery (Durmon) were significant predictors of seizure-free outcomes. The final model had a C-index of 0.68 (95 %CI: 0.59-0.77) for complete freedom from seizures and time-dependent AUROC was 0.65 at 12 months, 0.65 at 36 months, and 0.59 at 60 months in the test set. A web application derived from the primary predictive model was displayed for economic and efficient use.

CONCLUSIONS

A PET-based radiomics nomogram is clinically promising for predicting seizure outcomes after temporal lobe epilepsy surgery.

Fully automatic segmentation of brain lacunas resulting from resective surgery using a 3D deep learning model

The rapid and constant development of deep learning (DL) strategies is pushing forward the quality of object segmentation in images from diverse fields of interest. In particular, these algorithms can be very helpful in delineating brain abnormalities (lesions, tumors, lacunas, etc), enabling the extraction of information such as volume and location, that can inform doctors or feed predictive models. Here, we describe ResectVol DL, a fully automatic tool developed to segment resective lacunas in brain images of patients with epilepsy. ResectVol DL relies on the nnU-Net framework that leverages the 3D U-Net deep learning architecture. T1-weighted MRI datasets from 120 patients (57 women; 31.5 ± 15.9 years old at surgery) were used to train (n=78) and test (n=48) our tool. Manual segmentations were carried out by five different raters and were considered as ground truth for performance assessment. We compared ResectVol DL with two other fully automatic methods: ResectVol 1.1.2 and DeepResection, using the Dice similarity coefficient (DSC), Pearson's correlation coefficient, and relative difference to manual segmentation. ResectVol DL presented the highest median DSC (0.92 vs. 0.78 and 0.90), the highest correlation coefficient (0.99 vs. 0.63 and 0.94), and the lowest median relative difference (9 vs. 44 and 12 %). Overall, we demonstrate that ResectVol DL accurately segments brain lacunas, which has the potential to assist in the development of predictive models for postoperative cognitive and seizure outcomes.

Machine learning techniques based on 18F-FDG PET radiomics features of temporal regions for the classification of temporal lobe epilepsy patients from healthy controls

Background

This study aimed to investigate the clinical application of 18F-FDG PET radiomics features for temporal lobe epilepsy and to create PET radiomics-based machine learning models for differentiating temporal lobe epilepsy (TLE) patients from healthy controls.

Methods

A total of 347 subjects who underwent 18F-FDG PET scans from March 2014 to January 2020 (234 TLE patients: 25.50 ± 8.89 years, 141 male patients and 93 female patients; and 113 controls: 27.59 ± 6.94 years, 48 male individuals and 65 female individuals) were allocated to the training (n = 248) and test (n = 99) sets. All 3D PET images were registered to the Montreal Neurological Institute template. PyRadiomics was used to extract radiomics features from the temporal regions segmented according to the Automated Anatomical Labeling (AAL) atlas. The least absolute shrinkage and selection operator (LASSO) and Boruta algorithms were applied to select the radiomics features significantly associated with TLE. Eleven machine-learning algorithms were used to establish models and to select the best model in the training set.

Results

The final radiomics features (n = 7) used for model training were selected through the combinations of the LASSO and the Boruta algorithms with cross-validation. All data were randomly divided into a training set (n = 248) and a testing set (n = 99). Among 11 machine-learning algorithms, the logistic regression (AUC 0.984, F1-Score 0.959) model performed the best in the training set. Then, we deployed the corresponding online website version (https://wane199.shinyapps.io/TLE_Classification/), showing the details of the LR model for convenience. The AUCs of the tuned logistic regression model in the training and test sets were 0.981 and 0.957, respectively. Furthermore, the calibration curves demonstrated satisfactory alignment (visually assessed) for identifying the TLE patients.

Conclusion

The radiomics model from temporal regions can be a potential method for distinguishing TLE. Machine learning-based diagnosis of TLE from preoperative FDG PET images could serve as a useful preoperative diagnostic tool.

Evidence based noninvasive presurgical evaluation for patients with drug resistant epilepsies

PURPOSE OF REVIEW

To review the current practices and evidence for the diagnostic accuracy and the benefits of presurgical evaluation.

RECENT FINDINGS

Preoperative evaluation of patients with drug-resistant focal epilepsies and subsequent epilepsy surgery leads to a significant proportion of seizure-free patients. Even those who are not completely seizure free postoperatively often experience improved quality of life with better social integration. Systematic reviews and meta-analysis on the diagnostic accuracy are available for Video-electroencephalographic (EEG) monitoring, magnetic resonance imaging (MRI), electric and magnetic source imaging, and functional MRI for lateralization of language and memory. There are currently no evidence-based international guidelines for presurgical evaluation and epilepsy surgery.

SUMMARY

Presurgical evaluation is a complex multidisciplinary and multiprofessional clinical pathway. We rely on limited consensus-based recommendations regarding the required staffing or methodological expertise in epilepsy centers.

Epilepsy and education: A case-control analysis of the impact of an intensive epilepsy training program on undergraduate medical students

AIMS

To evaluate the knowledge, attitudes, and practical skills of students submitted to a 6-week intensive training in epilepsy compared to students without any training but mandatory neurology classes.

METHODS

It is a case-control study. After completing a 6-week intensive Academic, Clinical, and Research Program in epilepsy, TUMSs answered a validated Knowledge Attitudes and Practices (KAP) questionnaire. The control group, composed of undergraduate students who shared the same age, academic year, and compulsory hours for learning about epilepsy as TUMSs, was also assessed through the KAP instrument. Answers from both groups were submitted to Fisher exact and the χ2 test to observe differences among groups. Descriptive statistics were also performed.

RESULTS

TUMSs displayed better results in theoretical knowledge such as the definition and causes of epilepsy, and the application of paraclinical studies essential for diagnosing epilepsy. From their perspective, people with epilepsy encounter restricted opportunities for preserving their social life and employment and they are more prone to workplace accidents. They are convinced that facing epilepsy presents a notable risk due to the difficulties linked with diagnosis, considering epilepsy a challenging disease for general practitioners to identify and follow up. Likewise, they exhibited improvement in treatment adjustment and treatment monitoring of patients with epilepsy, mainly in pregnancy cases. Finally, they had greater knowledge about what to do when they witness a person experiencing a seizure.

CONCLUSION

Our study showed that a 6-week intensive education program in epilepsy increased the knowledge and practical skills and changed the attitude toward patients with epilepsy of undergraduate students.

Automated detection of focal cortical dysplasia based on magnetic resonance imaging and positron emission tomography

PURPOSE

Focal cortical dysplasia (FCD) is a common etiology of drug-resistant focal epilepsy. Visual identification of FCD is usually time-consuming and depends on personal experience. Herein, we propose an automated type II FCD detection approach utilizing multi-modal data and 3D convolutional neural network (CNN).

METHODS

MRI and positron emission tomography (PET) data of 82 patients with FCD were collected, including 55 (67.1%) histopathologically, and 27 (32.9%) radiologically diagnosed patients. Three types of morphometric feature maps and three types of tissue maps were extracted from the T1-weighted images. These maps, T1, and PET images formed the inputs for CNN. Five-fold cross-validations were carried out on the training set containing 62 patients, and the model behaving best was chosen to detect FCD on the test set of 20 patients. Furthermore, ablation experiments were performed to estimate the value of PET data and CNN.

RESULTS

On the validation set, FCD was detected in 90.3% of the cases, with an average of 1.7 possible lesions per patient. The sensitivity on the test set was 90.0%, with 1.85 possible lesions per patient. Without the PET data, the sensitivity decreased to 80.0%, and the average lesion number increased to 2.05 on the test set. If an artificial neural network replaced the CNN, the sensitivity decreased to 85.0%, and the average lesion number increased to 4.65.

SIGNIFICANCE

Automated detection of FCD with high sensitivity and few false-positive findings is feasible based on multi-modal data. PET data and CNN could improve the performance of automated detection.

ILAE neuroimaging task force highlight: Subcortical laminar heterotopia

The ILAE Neuroimaging Task Force publishes educational case reports that highlight basic aspects of neuroimaging in epilepsy consistent with the ILAE's educational mission. Subcortical laminar heterotopia, also known as subcortical band heterotopia (SBH) or "double cortex," is an intriguing and rare congenital malformation of cortical development. SBH lesions are part of a continuum best designated as agyria-pachygyria-band-spectrum. The malformation is associated with epilepsy that is often refractory, as well as variable degrees of developmental delay. Moreover, in an increasing proportion of cases, a distinct molecular-genetic background can be found. Diagnosing SBH can be a major challenge for many reasons, including more subtle lesions, and "non-classic" or unusual MRI-appearances. By presenting an illustrative case, we address the challenges and needs of diagnosing and treating SBH patients in epilepsy, especially the value of high-resolution imaging and specialized MRI-protocols.

Improving Diagnostic Performance of MRI for Temporal Lobe Epilepsy With Deep Learning-Based Image Reconstruction in Patients With Suspected Focal Epilepsy

OBJECTIVE

To evaluate the diagnostic performance and image quality of 1.5-mm slice thickness MRI with deep learning-based image reconstruction (1.5-mm MRI + DLR) compared to routine 3-mm slice thickness MRI (routine MRI) and 1.5-mm slice thickness MRI without DLR (1.5-mm MRI without DLR) for evaluating temporal lobe epilepsy (TLE).

MATERIALS AND METHODS

This retrospective study included 117 MR image sets comprising 1.5-mm MRI + DLR, 1.5-mm MRI without DLR, and routine MRI from 117 consecutive patients (mean age, 41 years; 61 female; 34 patients with TLE and 83 without TLE). Two neuroradiologists evaluated the presence of hippocampal or temporal lobe lesions, volume loss, signal abnormalities, loss of internal structure of the hippocampus, and lesion conspicuity in the temporal lobe. Reference standards for TLE were independently constructed by neurologists using clinical and radiological findings. Subjective image quality, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) were analyzed. Performance in diagnosing TLE, lesion findings, and image quality were compared among the three protocols.

RESULTS

The pooled sensitivity of 1.5-mm MRI + DLR (91.2%) for diagnosing TLE was higher than that of routine MRI (72.1%, P < 0.001). In the subgroup analysis, 1.5-mm MRI + DLR showed higher sensitivity for hippocampal lesions than routine MRI (92.7% vs. 75.0%, P = 0.001), with improved depiction of hippocampal T2 high signal intensity change (P = 0.016) and loss of internal structure (P < 0.001). However, the pooled specificity of 1.5-mm MRI + DLR (76.5%) was lower than that of routine MRI (89.2%, P = 0.004). Compared with 1.5-mm MRI without DLR, 1.5-mm MRI + DLR resulted in significantly improved pooled accuracy (91.2% vs. 73.1%, P = 0.010), image quality, SNR, and CNR (all, P < 0.001).

CONCLUSION

The use of 1.5-mm MRI + DLR enhanced the performance of MRI in diagnosing TLE, particularly in hippocampal evaluation, because of improved depiction of hippocampal abnormalities and enhanced image quality.

Morphometric magnetic resonance imaging (MRI) postprocessing in MRI-negative patients with first unprovoked seizure

OBJECTIVE

The aim of the study was to evaluate the benefits of morphometric magnetic resonance imaging (MRI) postprocessing in patients presenting with a first seizure and negative MRI results and to investigate these findings in the context of the clinical and electroencephalographic data, seizure recurrence rates, and epilepsy diagnosis in these patients.

METHODS

We retrospectively reviewed 97 MRI scans of patients with first unprovoked epileptic seizure and no evidence of epileptogenic lesion on clinical routine MRI. Morphometric Analysis Program (MAP; v2018), automated postprocessing software, was used to identify subtle, potentially epileptogenic lesions in the three-dimensional T1-weighted MRI data. The resulting probability maps were examined together with the conventional MRI images by a reviewer who remained blinded to the patients' clinical and electroencephalographical data. Clinical data were prospectively collected between February 2018 and May 2023.

RESULTS

Among the apparently MRI-negative patients, a total of 18 of 97 (18.6%) showed cortical changes suggestive of focal cortical dysplasia. Within the population with positive MAP findings (MAP+), seizure recurrence rates were 61.1% and 66.7% at 1 and 2 years after the first unprovoked seizure, respectively. Conversely, patients with negative MAP findings (MAP-) had lower seizure recurrence rates of 27.8% and 34.2% at 1 and 2 years after the first unprovoked seizure, respectively. Patients with MAP+ findings were significantly more likely to be diagnosed with epilepsy than those patients with MAP- findings (χ2 [1, n = 97] = 14.820, p < .001, odds ratio = 21.371, 95% CI = 2.710-168.531) during a mean follow-up time of 22.51 months (SD = 16.7 months, range = 1-61 months).

SIGNIFICANCE

MRI postprocessing can be a valuable tool for detecting subtle epileptogenic lesions in patients with a first seizure and negative MRI results. Patients with first seizure and MAP+ findings had high seizure recurrence rates, meeting the criteria for beginning epilepsy.

Deep learning-based automated lesion segmentation on pediatric focal cortical dysplasia II preoperative MRI: a reliable approach

OBJECTIVES

Focal cortical dysplasia (FCD) represents one of the most common causes of refractory epilepsy in children. Deep learning demonstrates great power in tissue discrimination by analyzing MRI data. A prediction model was built and verified using 3D full-resolution nnU-Net for automatic lesion detection and segmentation of children with FCD II.

METHODS

High-resolution brain MRI structure data from 65 patients, confirmed with FCD II by pathology, were retrospectively studied. Experienced neuroradiologists segmented and labeled the lesions as the ground truth. Also, we used 3D full-resolution nnU-Net to segment lesions automatically, generating detection maps. The algorithm was trained using fivefold cross-validation, with data partitioned into training (N = 200) and testing (N = 15). To evaluate performance, detection maps were compared to expert manual labels. The Dice-Sørensen coefficient (DSC) and sensitivity were used to assess the algorithm performance.

RESULTS

The 3D nnU-Net showed a good performance for FCD lesion detection at the voxel level, with a sensitivity of 0.73. The best segmentation model achieved a mean DSC score of 0.57 on the testing dataset.

CONCLUSION

This pilot study confirmed that 3D full-resolution nnU-Net can automatically segment FCD lesions with reliable outcomes. This provides a novel approach to FCD lesion detection.

CRITICAL RELEVANCE STATEMENT

Our fully automatic models could process the 3D T1-MPRAGE data and segment FCD II lesions with reliable outcomes.

KEY POINTS

• Simplified image processing promotes the DL model implemented in clinical practice. • The histopathological confirmed lesion masks enhance the clinical credibility of the AI model. • The voxel-level evaluation metrics benefit lesion detection and clinical decisions.

May anti-seizure medications alter brain structure in temporal lobe epilepsy? A prospective study

Mild mesial temporal lobe epilepsy (MTLE) patients may remain untreated for a considerable time after disease onset or achieve seizure control with a single anti-seizures medication (ASM). Thus, they represent an optimal population to investigate whether ASMs might have influence on brain structure. We consecutively enrolled 56 mild MTLE patients (22/56 untreated, 34/56 on-monotherapy) and 58 healthy controls, matched for age and gender. All subjects underwent 3T-brain MRI, using FreeSurfer for automated morphometry. Differences in gray matter were assessed using one-way Analysis of Covariance (ANCOVA), adjusting for age, disease duration and intracranial volume. No significant change was observed between treated and untreated patients. We observed a significant reduction in cortical thickness of left inferior parietal, inferior temporal, middle temporal gyri, and right inferior parietal gyrus, temporal pole in monotherapy patients compared to healthy controls, as well as an increase in left isthmus of cingulate gyrus in untreated MTLE subjects compared to controls. Surface and subcortical volumes analysis revealed no differences among groups. Our study demonstrated no substantial morphological abnormalities between untreated mild MTLE patients and those undergoing monotherapy. Although exploratory, these results may reassure about safety of commonly used drugs and their marginal role in influencing neuroimaging results. PLAIN LANGUAGE SUMMARY: This study investigated the following question: can medications against epileptic seizures have an effect on brain structure in mild mesial temporal lobe? Preliminary results from our analyses suggest not, as we did not find any difference in brain gray matter between untreated patients and those treated with a single anti-seizures medication. On the other hand, epilepsy patients presented cortical thinning compared to healthy controls in several regions of the temporal and parietal lobes, in line with previous studies investigating the disease.

Focal electroclinical features in generalized tonic-clonic seizures: Decision flowchart for a diagnostic challenge

OBJECTIVE

Bilateral tonic-clonic seizures with focal semiology or focal interictal electroencephalography (EEG) can occur in both focal and generalized epilepsy types, leading to diagnostic errors and inappropriate therapy. We investigated the prevalence and prognostic values of focal features in patients with idiopathic generalized epilepsy (IGE), and we propose a decision flowchart to distinguish between focal and generalized epilepsy in patients with bilateral tonic-clonic seizures and focal EEG or semiology.

METHODS

We retrospectively analyzed video-EEG recordings of 101 bilateral tonic-clonic seizures from 60 patients (18 with IGE, 42 with focal epilepsy). Diagnosis and therapeutic response were extracted after ≥1-year follow-up. The decision flowchart was based on previous observations and assessed concordance between interictal and ictal EEG.

RESULTS

Focal semiology in IGE was observed in 75% of seizures and 77.8% of patients, most often corresponding to forced head version (66.7%). In patients with multiple seizures, direction of head version was consistent across seizures. Focal interictal epileptiform discharges (IEDs) were observed in 61.1% of patients with IGE, whereas focal ictal EEG onset only occurred in 13% of seizures and 16.7% of patients. However, later during the seizures, a reproducible pattern of 7-Hz lateralized ictal rhythm was observed in 56% of seizures, associated with contralateral head version. We did not find correlation between presence of focal features and therapeutic response in IGE patients. Our decision flowchart distinguished between focal and generalized epilepsy in patients with bilateral tonic-clonic seizures and focal features with an accuracy of 96.6%.

SIGNIFICANCE

Focal semiology associated with bilateral tonic-clonic seizures and focal IEDs are common features in patients with IGE, but focal ictal EEG onset is rare. None of these focal findings appears to influence therapeutic response. By assessing the concordance between interictal and ictal EEG findings, one can accurately distinguish between focal and generalized epilepsies.

Intraoperative ECoG in bottom-of-the-sulcus syndrome using a novel flexible strip electrode

The recording of epileptiform discharges from bottom-of-sulcus focal cortical dysplasia (BOSD) is often difficult during intraoperative electrocorticography (ECoG) due to the deep localization. We describe the use in this scenario of a new-generation electrode strip with high flexibility, easily adapted to cortical gyri and sulci. A right-handed 20-year-old male with drug-resistant focal epilepsy due to BOSD of the inferior frontal gyrus and daily focal aware seizures was evaluated for epilepsy surgery. Based on electroclinical and neuroimaging results, a focal cortectomy guided by ECoG was proposed. ECoG recordings were performed with new-generation cortical strips (Wise Cortical Strip; WCS®) and standard cortical strips. ECoG, performed on the convexity of the frontal cortical surface, recorded only sporadic spikes with both types of strips. Then, after microsurgical trans-sulcal dissection, WCS was molded along the sulcal surface of the suspected BOSD based on 3D-imaging reconstruction, showing continuous/subcontinuous 3-4-Hz rhythmic spike activity from the deepest electrode. Registration after resection of the BOSD did not show any epileptiform activity. Pathology showed dysmorphic neurons and gliosis. No surgical complications occurred. The patient is seizure-free after 12 months. This single case experience shows that highly flexible electrode strips with adaptability to cortical gyrations can identify IEDs originating from deep location and could therefore be useful in cases of bottom of the sulcus dysplasia.

Guidelines for Specialized Epilepsy Centers: Executive Summary of the Report of the National Association of Epilepsy Centers Guideline Panel

The National Association of Epilepsy Centers first published the guidelines for epilepsy centers in 1990, which were last updated in 2010. Since that update, epilepsy care and the science of guideline development have advanced significantly, including the importance of incorporating a diversity of stakeholder perspectives such as those of patients and their caregivers. Currently, despite extensive published data examining the efficacy of treatments and diagnostic testing for epilepsy, there remain significant gaps in data identifying the essential services needed for a comprehensive epilepsy center and the optimal manner for their delivery. The trustworthy consensus-based statements (TCBS) process produces unbiased, scientifically valid guidelines through a transparent process that incorporates available evidence and expert opinion. A systematic literature search returned 5937 relevant studies from which 197 articles were retained for data extraction. A panel of 41 stakeholders with diverse expertise evaluated this evidence and drafted recommendations following the TCBS process. The panel reached consensus on 52 recommendations covering services provided by specialized epilepsy centers in both the inpatient and outpatient settings in major topic areas including epilepsy monitoring unit care, surgery, neuroimaging, neuropsychology, genetics, and outpatient care. Recommendations were informed by the evidence review and reflect the consensus of a broad panel of expert opinions.

Neurological morbidity of surgery for suprasylvian operculoinsular epilepsy

OBJECTIVE

The objective of this study was to identify risk factors associated with surgery-related neurological morbidity in patients with drug-resistant epilepsy undergoing suprasylvian operculoinsular resections. As secondary outcomes, we also analyzed the risk factors for ischemic lesion (IL) of corona radiata and seizure recurrence.

METHODS

A retrospective analysis was conducted on a cohort of patients who underwent suprasylvian operculoinsular resections for drug-resistant epilepsy. The association of several presurgical, surgical, and postsurgical factors with both primary (persistent neurological deficits) and secondary (structural abnormalities on postoperative magnetic resonance imaging [MRI] and seizure recurrence) postoperative outcomes was investigated with univariate and multivariate statistical analysis.

RESULTS

The study included a total of 65 patients; 46.2% of patients exhibited postoperative neurological deficits, but only 12.3% experienced persistent deficits. On postoperative MRI, IL in the corona radiata and corticospinal tract Wallerian degeneration (CSTWd) were seen in 68% and 29% of cases, respectively. Only CSTWd was significantly associated with persistent neurological deficits (relative risk [RR] = 2.6). Combined operculoinsular resection (RR = 3.62) and surgery performed on the left hemisphere (RR = .37) were independently associated with IL in the corona radiata. Variables independently associated with CSTWd were the presence of malacic components in the IL (RR = 1.96), right central operculum resection (RR = 1.79), and increasing age at surgery (RR = 1.03). Sixty-two patients had a postoperative follow-up > 12 months (median = 56, interquartile range = 30.75-73.5), and 62.9% were in Engel class I at last outpatient control. The risk of seizure recurrence was reduced by selective opercular resection (RR = .25) and increased by the histological diagnosis of aspecific gliosis (RR = 1.39).

SIGNIFICANCE

This study provides insights into the risk factors associated with surgery-related neurological morbidity, as well as further evidence on the postoperative occurrence of subcortical injury and seizure recurrence in epileptic patients undergoing suprasylvian operculoinsular resections. The findings highlighted in this study may be useful to better understand the processes supporting the increased surgical risk in the operculoinsular region.

Implementation of a 7T Epilepsy Task Force consensus imaging protocol for routine presurgical epilepsy work-up: effect on diagnostic yield and lesion delineation

OBJECTIVE

Recently, the 7 Tesla (7 T) Epilepsy Task Force published recommendations for 7 T magnetic resonance imaging (MRI) in patients with pharmaco-resistant focal epilepsy in pre-surgical evaluation. The objective of this study was to implement and evaluate this consensus protocol with respect to both its practicability and its diagnostic value/potential lesion delineation surplus effect over 3 T MRI in the pre-surgical work-up of patients with pharmaco-resistant focal onset epilepsy.

METHODS

The 7 T MRI protocol consisted of T1-weighted, T2-weighted, high-resolution-coronal T2-weighted, fluid-suppressed, fluid-and-white-matter-suppressed, and susceptibility-weighted imaging, with an overall duration of 50 min. Two neuroradiologists independently evaluated the ability of lesion identification, the detection confidence for these identified lesions, and the lesion border delineation at 7 T compared to 3 T MRI.

RESULTS

Of 41 recruited patients > 12 years of age, 38 were successfully measured and analyzed. Mean detection confidence scores were non-significantly higher at 7 T (1.95 ± 0.84 out of 3 versus 1.64 ± 1.19 out of 3 at 3 T, p = 0.050). In 50% of epilepsy patients measured at 7 T, additional findings compared to 3 T MRI were observed. Furthermore, we found improved border delineation at 7 T in 88% of patients with 3 T-visible lesions. In 19% of 3 T MR-negative cases a new potential epileptogenic lesion was detected at 7 T.

CONCLUSIONS

The diagnostic yield was beneficial, but with 19% new 7 T over 3 T findings, not major. Our evaluation revealed epilepsy outcomes worse than ILAE Class 1 in two out of the four operated cases with new 7 T findings.

The role of the amygdala in ictal central apnea: insights from brain MRI morphometry

OBJECTIVE

Ictal central apnea (ICA) is a frequent correlate of focal seizures, particularly in temporal lobe epilepsy (TLE), and regarded as a potential electroclinical biomarker of sudden unexpected death in epilepsy (SUDEP). Aims of this study are to investigate morphometric changes of subcortical structures in ICA patients and to find neuroimaging biomarkers of ICA in patients with focal epilepsy.

METHODS

We prospectively recruited focal epilepsy patients with recorded seizures during a video-EEG long-term monitoring with cardiorespiratory polygraphic recordings from April 2020 to September 2022. Participants were accordingly subdivided into two groups: patients with focal seizures with ICA (ICA) and without (noICA). A pool of 30 controls matched by age and sex was collected. All the participants underwent MRI scans with volumetric high-resolution T1-weighted images. Post-processing analyses included a whole-brain VBM analysis and segmentation algorithms performed with FreeSurfer.

RESULTS

Forty-six patients were recruited (aged 15-60 years): 16 ICA and 30 noICA. The whole-brain VBM analysis showed an increased gray matter volume of the amygdala ipsilateral to the epileptogenic zone (EZ) in the ICA group compared to the noICA patients. Amygdala sub-segmentation analysis revealed an increased volume of the whole amygdala, ipsilateral to the EZ compared to controls [F(1, 76) = 5.383, pFDR = 0.042] and to noICA patients ([F(1, 76) = 5.383, pFDR = 0.038], specifically of the basolateral complex (respectively F(1, 76) = 6.160, pFDR = 0.037; F(1, 76) = 5.121, pFDR = 0.034).

INTERPRETATION

Our findings, while confirming the key role of the amygdala in participating in ictal respiratory modifications, suggest that structural modifications of the amygdala and its subnuclei may be valuable morphological biomarkers of ICA.

[Hypothalamic hamartoma dissection using focused ultrasound under MRI control. The first successful experience in Russia]

Treatment of motor disorders by MRI-guided focused ultrasound is an alternative to neuro- and radiosurgery such as stereotactic radiofrequency ablation and thalamotomy with a gamma knife. However, safety, efficacy and feasibility of this technology for intracranial neoplasms are still unclear. The authors report successful hypothalamic hamartoma dissection by MRI-guided focused ultrasound in a 32-year-old woman with drug-resistant gelastic epilepsy and violent laughter and crying attacks. Magnetic resonance imaging revealed type II hypothalamic hamartoma. The last one was detached from surrounding brain tissue by MRI-guided focused ultrasound without side effects. Symptoms regressed immediately after surgery. No laughter and crying attacks were observed throughout 6-month follow-up.

MRI Data Analysis in Malformations of Cortical Development

Brain magnetic resonance imaging (MRI) is a noninvasive imaging modality that utilizes powerful magnets and radio waves to generate detailed images of the brain, making it a valuable tool for investigating malformations of cortical development (MCD). Various MRI techniques, including 3D T1-weighted, multiplanar thin-sliced T2-weighted, and 3D fluid-attenuated inversion recovery (FLAIR) sequences, can provide high-resolution images with excellent spatial and contrast resolution, allowing for a detailed visualization of cortical anatomy and abnormalities. Almost all MCD can be detected and characterized using MRI. Advanced techniques, such as arterial spin labeling MR perfusion, diffusion tensor imaging (DTI), and functional MRI (fMRI), may be used to improve the detection rate of these malformations and to plan surgery in case of drug-resistant epilepsy. However, there are also limitations related to high cost, relatively low availability, need for sedation or anesthesia, and limited sensitivity for detecting subtle focal cortical malformations. Despite these limitations, brain MRI plays a crucial role in the investigation of MCD, providing valuable information for diagnosis, treatment planning, and patient management.

Imaging biomarkers of sleep-related hypermotor epilepsy and sudden unexpected death in epilepsy: a review

In recent years, imaging has emerged as a promising source of several intriguing biomarkers in epilepsy, due to the impressive growth of imaging technology, supported by methodological advances and integrations of post-processing techniques. Bearing in mind the mutually influencing connection between sleep and epilepsy, we focused on sleep-related hypermotor epilepsy (SHE) and sudden unexpected death in epilepsy (SUDEP), aiming to make order and clarify possible clinical utility of emerging multimodal imaging biomarkers of these two epilepsy-related entities commonly occurring during sleep. Regarding SHE, advanced structural techniques might soon emerge as a promising source of diagnostic and predictive biomarkers, tailoring a targeted therapeutic (surgical) approach for MRI-negative subjects. Functional and metabolic imaging may instead unveil SHE's extensive and night-related altered brain networks, providing insights into distinctions and similarities with non-epileptic sleep phenomena, such as parasomnias. SUDEP is considered a storm that strikes without warning signals, but objective subtle structural and functional alterations in autonomic, cardiorespiratory, and arousal centers are present in patients eventually experiencing SUDEP. These alterations could be seen both as susceptibility and diagnostic biomarkers of the underlying pathological ongoing loop ultimately ending in death. Finally, given that SHE and SUDEP are rare phenomena, most evidence on the topic is derived from small single-center experiences with scarcely comparable results, hampering the possibility of performing any meta-analytic approach. Multicenter, longitudinal, well-designed studies are strongly encouraged.

Epileptogenesis and drug-resistant in focal cortical dysplasias: Update on clinical, cellular, and molecular markers

Focal cortical dysplasia (FCD) is a cortical malformation in brain development and is considered as one of the major causes of drug-resistant epilepsiesin children and adults. The pathogenesis of FCD is yet to be fully understood. Imaging markers such as MRI are currently the surgeons major obstacle due to the difficulty in delimiting the precise dysplasic area and a mosaic brain where there is epileptogenic tissue invisible to MRI. Also increased gene expression and activity may be responsible for the alterations in cell proliferation, migration, growth, and survival. Altered expressions were found, particularly in the PI3K/AKT/mTOR pathway. Surgery is still considered the most effective treatment option, due to drug-resistance, and up to 60 % of patients experience complete seizure control, varying according to the type and location of FCD. Both genetic and epigenetic factors may be involved in the pathogenesis of FCD, and there is no conclusive evidence whether these alterations are inherited or have an environmental origin.

The impact of referring patients with drug-resistant focal epilepsy to an epilepsy center for presurgical diagnosis

BACKGROUND

Epilepsy surgery is an established treatment for drug-resistant focal epilepsy (DRFE) that results in seizure freedom in about 60% of patients. Correctly identifying an epileptogenic lesion in magnetic resonance imaging (MRI) is challenging but highly relevant since it improves the likelihood of being referred for presurgical diagnosis. The epileptogenic lesion's etiology directly relates to the surgical intervention's indication and outcome. Therefore, it is vital to correctly identify epileptogenic lesions and their etiology presurgically.

METHODS

We compared the final histopathological diagnoses of all patients with DRFE undergoing epilepsy surgery at our center between 2015 and 2021 with their MRI diagnoses before and after presurgical diagnosis at our epilepsy center, including MRI evaluations by expert epilepsy neuroradiologists. Additionally, we analyzed the outcome of different subgroups.

RESULTS

This study included 132 patients. The discordance between histopathology and MRI diagnoses significantly decreased from 61.3% for non-expert MRI evaluations (NEMRIs) to 22.1% for epilepsy center MRI evaluations (ECMRIs; p < 0.0001). The MRI-sensitivity improved significantly from 68.6% for NEMRIs to 97.7% for ECMRIs (p < 0.0001). Identifying focal cortical dysplasia (FCD) and amygdala dysplasia was the most challenging for both subgroups. 65.5% of patients with negative NEMRI were seizure-free 12 months postoperatively, no patient with negative ECMRI achieved seizure-freedom. The mean duration of epilepsy until surgical intervention was 13.6 years in patients with an initial negative NEMRI and 9.5 years in patients with a recognized lesion in NEMRI.

CONCLUSIONS

This study provides evidence that for patients with DRFE-especially those with initial negative findings in a non-expert MRI-an early consultation at an epilepsy center, including an ECMRI, is important for identifying candidates for epilepsy surgery. NEMRI-negative findings preoperatively do not preclude seizure freedom postoperatively. Therefore, patients with DRFE that remain MRI-negative after initial NEMRI should be referred to an epilepsy center for presurgical evaluation. Nonreferral based on NEMRI negativity may harm such patients and delay surgical intervention. However, ECMRI-negative patients have a reduced chance of becoming seizure-free after epilepsy surgery. Further improvements in MRI technique and evaluation are needed and should be directed towards improving sensitivity for FCDs and amygdala dysplasias.

Added value of advanced workup after the first seizure: A 7-year cohort study

OBJECTIVE

This study was undertaken to establish whether advanced workup including long-term electroencephalography (LT-EEG) and brain magnetic resonance imaging (MRI) provides an additional yield for the diagnosis of new onset epilepsy (NOE) in patients presenting with a first seizure event (FSE).

METHODS

In this population-based study, all adult (≥16 years) patients presenting with FSE in the emergency department (ED) between March 1, 2010 and March 1, 2017 were assessed. Patients with obvious nonepileptic or acute symptomatic seizures were excluded. Routine EEG, LT-EEG, brain computed tomography (CT), and brain MRI were performed as part of the initial workup. These examinations' sensitivity and specificity were calculated on the basis of the final diagnosis after 2 years, along with the added value of advanced workup (MRI and LT-EEG) over routine workup (routine EEG and CT).

RESULTS

Of the 1010 patients presenting with FSE in the ED, a definite diagnosis of NOE was obtained for 501 patients (49.6%). Sensitivity of LT-EEG was higher than that of routine EEG (54.39% vs. 25.5%, p < .001). Similarly, sensitivity of MRI was higher than that of CT (67.98% vs. 54.72%, p = .009). Brain MRI showed epileptogenic lesions in an additional 32% compared to brain CT. If only MRI and LT-EEG were considered, five would have been incorrectly diagnosed as nonepileptic (5/100, 5%) compared to patients with routine EEG and MRI (25/100, 25%, p = .0001). In patients with all four examinations, advanced workup provided an overall additional yield of 50% compared to routine workup.

SIGNIFICANCE

Our results demonstrate the remarkable added value of the advanced workup launched already in the ED for the diagnosis of NOE versus nonepileptic causes of seizure mimickers. Our findings suggest the benefit of first-seizure tracks or even units with overnight EEG, similar to stroke units, activated upon admission in the ED.

Clinical Evaluation of a Quantitative Imaging Biomarker Supporting Radiological Assessment of Hippocampal Sclerosis

OBJECTIVE

To evaluate the influence of quantitative reports (QReports) on the radiological assessment of hippocampal sclerosis (HS) from MRI of patients with epilepsy in a setting mimicking clinical reality.

METHODS

The study included 40 patients with epilepsy, among them 20 with structural abnormalities in the mesial temporal lobe (13 with HS). Six raters blinded to the diagnosis assessed the 3T MRI in two rounds, first using MRI only and later with both MRI and the QReport. Results were evaluated using inter-rater agreement (Fleiss' kappa [Formula: see text]) and comparison with a consensus of two radiological experts derived from clinical and imaging data, including 7T MRI.

RESULTS

For the primary outcome, diagnosis of HS, the mean accuracy of the raters improved from 77.5% with MRI only to 86.3% with the additional QReport (effect size [Formula: see text]). Inter-rater agreement increased from [Formula: see text] to [Formula: see text]. Five of the six raters reached higher accuracies, and all reported higher confidence when using the QReports.

CONCLUSION

In this pre-use clinical evaluation study, we demonstrated clinical feasibility and usefulness as well as the potential impact of a previously suggested imaging biomarker for radiological assessment of HS.

Safely Shifting MRIs for Seizure Evaluation to the Outpatient Setting

BACKGROUND AND OBJECTIVES

When a patient is admitted for seizure-like activity, in addition to obtaining a thorough history and physical exam, the evaluation may include a neurology consultation, EEG, and brain MRI. The cost of an inpatient MRI is significant and only 2% of MRIs yield clinically significant findings. At our institution, there was a 20% increase in patients undergoing inpatient MRI from 2018 to 2020. Our aim: Decrease the percentage of patient encounters receiving inpatient brain MRIs for seizure evaluation from 50% to 40% in 6 months by safely shifting MRIs to the outpatient setting.

METHODS

Initially, provider variability in ordering practices of MRIs was analyzed. Stakeholders were gathered and a local guideline was developed to standardize MRI utilization. A process map was created and highlighted barriers to obtaining an outpatient MRI. A new standard process was developed that streamlined and automated processes, and reduced delays and reliance on patients' families.

RESULTS

Since implementation of the new clinical guideline, the percentage of inpatient MRIs ordered for patient encounters presenting with seizures and seizure-like episodes decreased from a mean of 50% to 26%. Significant reductions occurred for patients with complex febrile seizures, provoked but afebrile seizures, and unprovoked seizures. The MRI guideline recommendations were followed in 93% of encounters in the final 12 months. None of the patients who underwent outpatient MRI required readmission for acute findings.

CONCLUSIONS

In this project, the percentage of inpatient MRIs was safely decreased with the implementation of a clinical guideline and standardized process.

Machine Learning and Artificial Intelligence Applications to Epilepsy: a Review for the Practicing Epileptologist

PURPOSE OF REVIEW

Machine Learning (ML) and Artificial Intelligence (AI) are data-driven techniques to translate raw data into applicable and interpretable insights that can assist in clinical decision making. Some of these tools have extremely promising initial results, earning both great excitement and creating hype. This non-technical article reviews recent developments in ML/AI in epilepsy to assist the current practicing epileptologist in understanding both the benefits and limitations of integrating ML/AI tools into their clinical practice.

RECENT FINDINGS

ML/AI tools have been developed to assist clinicians in almost every clinical decision including (1) predicting future epilepsy in people at risk, (2) detecting and monitoring for seizures, (3) differentiating epilepsy from mimics, (4) using data to improve neuroanatomic localization and lateralization, and (5) tracking and predicting response to medical and surgical treatments. We also discuss practical, ethical, and equity considerations in the development and application of ML/AI tools including chatbots based on Large Language Models (e.g., ChatGPT). ML/AI tools will change how clinical medicine is practiced, but, with rare exceptions, the transferability to other centers, effectiveness, and safety of these approaches have not yet been established rigorously. In the future, ML/AI will not replace epileptologists, but epileptologists with ML/AI will replace epileptologists without ML/AI.

Review of standard paediatric neuroradiology MRI protocols from 12 UK tertiary paediatric hospitals: is there much variation between centres?

AIM

To investigate how magnetic resonance imaging (MRI) examinations are protocolled in tertiary paediatric neuroradiology centres around the UK for some of the more common presentations encountered in paediatric neuroradiology, and to identify any variations of note.

MATERIALS AND METHODS

All 19 UK tertiary paediatric neuroradiology centres registered with the British Society of Neuroradiologists-Paediatric Group were contacted and asked if they could provide a copy of their standard MRI protocols. Twelve responded (63%) and 10 of the more common presentations were selected and the standard acquired sequences obtained at each participating centre were compared. Where available the collated protocols were also compared against current published guidance.

RESULTS

The basic sequences carried out by centres around the UK are similar; however, there are lots of variations overall. The only standardised protocol currently being implemented nationally in paediatric imaging is that for brain tumours. Otherwise, chosen protocols are generally dependent on the preferences and technical capabilities of individual centres. Suggested published protocols also exist for non-accidental injury (NAI), multiple sclerosis, epilepsy, and head and neck imaging.

CONCLUSIONS

The differences in MRI protocolling depend in part on technical capabilities and in part on the experience and preferences of the paediatric neuroradiologists at each centre. For most presentations, there is no consensus as to what constitutes the perfect protocol. The present results will be useful for specialist centres who may wish to review their current protocols, and for more generalist centres to use as a reference to guide their MRI protocolling.

Application value of multimodal MRI combined with PET metabolic parameters in temporal lobe epilepsy with dual pathology

OBJECTIVES

To investigate the application value of multimodal MRI combined with PET metabolic parameters in detecting temporal lobe epilepsy (TLE) with dual pathology (DP) and the prediction effect of post-surgical outcomes in these patients.

METHODS

We retrospectively reviewed 50 patients with TLE-DP who underwent surgery at our hospital between January 2016 and December 2021 and collected the demographics, clinical characteristics, video-electroencephalography (v-EEG), neuroimaging, and surgical data. Seizure outcome data were collected during a regular follow-up of at least 12 months and were graded using Engel scores. Fisher's exact test was used to compare the differences in DP detection rates of various diagnostic modalities. Univariate and multivariate analyses were performed to explore the prognostic factors for predicting seizure outcomes post-surgery.

RESULTS

Of the 50 patients, 20 were males. The median age was 30, the median age at first seizure was 14, and the median duration was ten years. Voxel-based morphometry-PET statistical parametric mapping-PET/MRI (VBM-PSPM-PET/MRI) had the highest detection rate, followed by PET/MRI, VBM analysis, and PET-SPM. Regardless of follow-up duration, v-EEG, PET, image post-processing methods, and VBM-PSPM-PET/MRI statistically correlated with seizure outcomes using the log-rank test in the Kaplan-Meier analysis. Multivariate analysis showed that VBM-PSPM-PET/MRI was an independent predictor of TLE-DP (hazard ratio (HR) = 15.674, 95 % CI = 0.002-0.122, P < 0.00 1).

CONCLUSIONS

Our study illustrates that VBM-PSPM-PET/MRI has the highest detection value in patients with TLE-DP and can provide independent prognostic information for patients who undergo surgery. This approach has the most substantial potential for the selection of candidates for patients who undergo surgical treatment and for prognostic stratification.

Deep histopathology genotype-phenotype analysis of focal cortical dysplasia type II differentiates between the GATOR1-altered autophagocytic subtype IIa and MTOR-altered migration deficient subtype IIb

Focal cortical dysplasia type II (FCDII) is the most common cause of drug-resistant focal epilepsy in children. Herein, we performed a deep histopathology-based genotype-phenotype analysis to further elucidate the clinico-pathological and genetic presentation of FCDIIa compared to FCDIIb. Seventeen individuals with histopathologically confirmed diagnosis of FCD ILAE Type II and a pathogenic variant detected in brain derived DNA whole-exome sequencing or mTOR gene panel sequencing were included in this study. Clinical data were directly available from each contributing centre. Histopathological analyses were performed from formalin-fixed, paraffin-embedded tissue samples using haematoxylin-eosin and immunohistochemistry for NF-SMI32, NeuN, pS6, p62, and vimentin. Ten individuals carried loss-of-function variants in the GATOR1 complex encoding genes DEPDC5 (n = 7) and NPRL3 (n = 3), or gain-of-function variants in MTOR (n = 7). Whereas individuals with GATOR1 variants only presented with FCDIIa, i.e., lack of balloon cells, individuals with MTOR variants presented with both histopathology subtypes, FCDIIa and FCDIIb. Interestingly, 50% of GATOR1-positive cases showed a unique and predominantly vacuolizing phenotype with p62 immunofluorescent aggregates in autophagosomes. All cases with GATOR1 alterations had neurosurgery in the frontal lobe and the majority was confined to the cortical ribbon not affecting the white matter. This pattern was reflected by subtle or negative MRI findings in seven individuals with GATOR1 variants. Nonetheless, all individuals were seizure-free after surgery except four individuals carrying a DEPDC5 variant. We describe a yet underrecognized genotype-phenotype correlation of GATOR1 variants with FCDIIa in the frontal lobe. These lesions were histopathologically characterized by abnormally vacuolizing cells suggestive of an autophagy-altered phenotype. In contrast, individuals with FCDIIb and brain somatic MTOR variants showed larger lesions on MRI including the white matter, suggesting compromised neural cell migration.

A novel deep learning model for glioma epilepsy associated with the identification of human cytomegalovirus infection injuries based on head MR

Purpose

In this study, a deep learning model was established based on head MRI to predict a crucial evaluation parameter in the assessment of injuries resulting from human cytomegalovirus infection: the occurrence of glioma-related epilepsy. The relationship between glioma and epilepsy was investigated, which serves as a significant indicator of labor force impairment.

Methods

This study enrolled 142 glioma patients, including 127 from Shengjing Hospital of China Medical University, and 15 from the Second Affiliated Hospital of Dalian Medical University. T1 and T2 sequence images of patients' head MRIs were utilized to predict the occurrence of glioma-associated epilepsy. To validate the model's performance, the results of machine learning and deep learning models were compared. The machine learning model employed manually annotated texture features from tumor regions for modeling. On the other hand, the deep learning model utilized fused data consisting of tumor-containing T1 and T2 sequence images for modeling.

Results

The neural network based on MobileNet_v3 performed the best, achieving an accuracy of 86.96% on the validation set and 75.89% on the test set. The performance of this neural network model significantly surpassed all the machine learning models, both on the validation and test sets.

Conclusion

In this study, we have developed a neural network utilizing head MRI, which can predict the likelihood of glioma-associated epilepsy in untreated glioma patients based on T1 and T2 sequence images. This advancement provides forensic support for the assessment of injuries related to human cytomegalovirus infection.

Unveiling the power of imaging techniques: comparing high-resolution ultrasound and functional MR neurography in peripheral nervous system pathology: a short communication

MRI and ultrasonography are used for diagnosing and helping manage peripheral nervous system pathologies. Multiple studies have compared the diagnostic accuracy of these two modalities, but the results can vary depending on the specific conditions being evaluated. In general, high-resolution ultrasound is considered a reliable and accurate tool for evaluating peripheral nerves, with high sensitivity and specificity. High-resolution ultrasound and functional MR neurography are both noninvasive imaging techniques used to evaluate nerve structures in the body. However, they differ in several technical aspects like imaging modality, spatial resolution, field of view, image quality, and accessibility. Establishing consensus on image acquisition techniques, and reporting formats to facilitate effective communication and comparison of results will further enhance the outcomes. The use of advanced ultrasound techniques, such as contrast-enhanced ultrasound, elastography, and ultrasound biomicroscopy, should be promoted for better visualization and characterization of nervous tissues, like transcranial Doppler for cerebrovascular evaluation.

Microsurgery Robots: Applications, Design, and Development

Microsurgical techniques have been widely utilized in various surgical specialties, such as ophthalmology, neurosurgery, and otolaryngology, which require intricate and precise surgical tool manipulation on a small scale. In microsurgery, operations on delicate vessels or tissues require high standards in surgeons' skills. This exceptionally high requirement in skills leads to a steep learning curve and lengthy training before the surgeons can perform microsurgical procedures with quality outcomes. The microsurgery robot (MSR), which can improve surgeons' operation skills through various functions, has received extensive research attention in the past three decades. There have been many review papers summarizing the research on MSR for specific surgical specialties. However, an in-depth review of the relevant technologies used in MSR systems is limited in the literature. This review details the technical challenges in microsurgery, and systematically summarizes the key technologies in MSR with a developmental perspective from the basic structural mechanism design, to the perception and human-machine interaction methods, and further to the ability in achieving a certain level of autonomy. By presenting and comparing the methods and technologies in this cutting-edge research, this paper aims to provide readers with a comprehensive understanding of the current state of MSR research and identify potential directions for future development in MSR.

Referral odyssey plot to visualize causes of surgical delay in mesial temporal lobe epilepsy with hippocampal sclerosis

The "odyssey plot" was used to visualize referral delays in epilepsy surgery. Participants were 36 patients (19 males; 13-67 years, median 27 years) with mesial temporal lobe epilepsy with hippocampal sclerosis (HS) who underwent resection surgery. The "referral odyssey plot" included five clinical episodes: seizure onset (T1), first visits to a non-epileptologist (T2) and to an epileptologist (T3), first admission to our epilepsy monitoring unit (EMU) (T4), and resection surgery (T5). For each patient, we identified the first seizure type: the physician who first diagnosed focal aware seizure (FAS), focal impaired awareness seizure (FIAS), focal to bilateral tonic-clonic seizure (FBTCS), and radiologically suspected HS. Within the overall delay (T1-T5, median 18 years; interquartile range [IQR] 14), non-epileptologist's delay (T2-T3, 11.5 years; IQR 12.25) was far (p < 0.0001) longer than patient's (T1-T2, 0 year; IQR 2.25), epileptologist's (T3-T4, 1 year; IQR 4), or after-EMU delay (T4-T5, 1 year; IQR 1). FAS onset cases had significantly longer T1-T2 (N = 5, median 7 years; IQR 6) than FIAS (N = 22, 0 year; IQR 1, p < 0.005) or FBTCS onset cases (N = 9, 0 year; IQR 0, p < 0.001). FAS was correctly diagnosed first by non-epileptologists in 17.9%, by out-patient epileptologists in 35.7%, and at the EMU in 46.4%. FIAS was correctly diagnosed first by non-epileptologists in 94.4% and by out-patient epileptologists in 5.6%. Non-epileptologists diagnosed FBTCS in all cases. HS was diagnosed by non-epileptologists in 13.9%, by out-patient epileptologists in 47.2%, and at the EMU in 38.9%. Early referral to epileptologists is most critical for early surgery. Early utilization of the EMU is highly recommended because FAS is often overlooked by outpatient epileptologists. The odyssey plot will be useful to improve the healthcare system for other types of epilepsy.

Comprehensive nursing program for children with epilepsy: A randomized controlled trial

Background

Epilepsy is a relatively common childhood neurological disease. Children with epilepsy need to take precautions to minimize seizure damage in order to adapt to seizures and manage them.

Aim

The current study aimed to evaluate the feasibility and effects of a comprehensive nursing program for children with epilepsy to reduce children's symptoms of epilepsy.

Subject and Methods

Participants were children suffering from epilepsy between 2019 and 2021 at Ningbo Women and Children's Hospital. Seventy children were included in a randomized controlled trial with a comprehensive nursing group (CNG) and an active control group (ACG). Measurements were assessed pre- and post-intervention and at a one- and three-month follow-ups. Children in the CNG learned and practiced the strategies related to the comprehensive nursing intervention. The outcomes were anxiety and depression.

Results

The results showed that anxiety and depression scores were significantly lower in the CNG than the ACG at 1 and 3 months after intervention (P < 0.05). According to the feasibility results, whereas most participants believed that the program was informative and meaningful, a minority reported that it was time-consuming.

Conclusion

The intervention has the potential to support children with epilepsy. The program is easily accessible, cost-effective and could be implemented in epilepsy care rehabilitation.

Charting the Progress of Epilepsy Classification: Navigating a Shifting Landscape

Epilepsy, a neurological disorder characterized by recurrent seizures, has witnessed a remarkable transformation in its classification paradigm, driven by advances in clinical understanding, neuroimaging, and molecular genetics. This narrative review navigates the dynamic landscape of epilepsy classification, offering insights into recent developments, challenges, and the promising horizon. Historically, epilepsy classification relied heavily on clinical observations, categorizing seizures based on their phenomenology and presumed etiology. However, the field has profoundly shifted from a symptom-based approach to a more refined, multidimensional system. One pivotal aspect of this evolution is the integration of neuroimaging techniques, particularly magnetic resonance imaging (MRI) and functional imaging modalities. These tools have unveiled the intricate neural networks implicated in epilepsy, facilitating the identification of distinct brain abnormalities and the categorization of epilepsy subtypes based on structural and functional findings. Furthermore, the role of genetics has become increasingly prominent in epilepsy classification. Genetic discoveries have not only unraveled the molecular underpinnings of various epileptic syndromes but have also provided valuable diagnostic and prognostic insights. This narrative review delves into the expanding realm of genetic testing and its impact on tailoring treatment strategies to individual patients. As the classification landscape evolves, there are accompanying challenges. The narrative review underscores the transformative potential of artificial intelligence and machine learning in epilepsy classification. These technologies hold promise in automating the analysis of complex neuroimaging and genetic data, offering enhanced accuracy and efficiency in epilepsy diagnosis and classification. In conclusion, navigating the shifting landscape of epilepsy classification is a journey marked by progress, complexity, and the prospect of improved patient care. We are charting a course toward more precise diagnoses and tailored treatments by embracing advanced neuroimaging, genetics, and innovative technologies. As the field continues to evolve, collaborative efforts and a holistic understanding of epilepsy's diverse manifestations will be instrumental in harnessing the full potential of this dynamic landscape.

Clinical, imaging, and biomarker evidence of amyloid- and tau-related neurodegeneration in late-onset epilepsy of unknown etiology

Accumulating evidence suggests amyloid and tau-related neurodegeneration may play a role in development of late-onset epilepsy of unknown etiology (LOEU). In this article, we review recent evidence that epilepsy may be an initial manifestation of an amyloidopathy or tauopathy that precedes development of Alzheimer's disease (AD). Patients with LOEU demonstrate an increased risk of cognitive decline, and patients with AD have increased prevalence of preceding epilepsy. Moreover, investigations of LOEU that use CSF biomarkers and imaging techniques have identified preclinical neurodegeneration with evidence of amyloid and tau deposition. Overall, findings to date suggest a relationship between acquired, non-lesional late-onset epilepsy and amyloid and tau-related neurodegeneration, which supports that preclinical or prodromal AD is a distinct etiology of late-onset epilepsy. We propose criteria for assessing elevated risk of developing dementia in patients with late-onset epilepsy utilizing clinical features, available imaging techniques, and biomarker measurements. Further research is needed to validate these criteria and assess optimal treatment strategies for patients with probable epileptic preclinical AD and epileptic prodromal AD.

Diagnostic Accuracy of Epilepsy-dedicated MRI with Post-processing

PURPOSE

To evaluate the diagnostic accuracy of epilepsy-dedicated 3 Tesla MRI including post-processing by correlating MRI, histopathology, and postsurgical seizure outcomes.

METHODS

3 Tesla-MRI including a magnetization-prepared two rapid acquisition gradient echo (MP2RAGE) sequence for post-processing using the morphometric analysis program MAP was acquired in 116 consecutive patients with drug-resistant focal epilepsy undergoing resection surgery. The MRI, histopathology reports and postsurgical seizure outcomes were recorded from the patient's charts.

RESULTS

The MRI and histopathology were concordant in 101 and discordant in 15 patients, 3 no hippocampal sclerosis/gliosis only lesions were missed on MRI and 1 of 28 focal cortical dysplasia (FCD) type II associated with a glial scar was considered a glial scar only on MRI. In another five patients, MRI was suggestive of FCD, the histopathology was uneventful but patients were seizure-free following surgery. The MRI and histopathology were concordant in 20 of 21 glioneuronal tumors, 6 cavernomas, and 7 glial scars. Histopathology was negative in 10 patients with temporal lobe epilepsy, 4 of them had anteroinferior meningoencephaloceles. Engel class IA outcome was reached in 71% of patients.

CONCLUSION

The proposed MRI protocol is highly accurate. No hippocampal sclerosis/gliosis only lesions are typically MRI negative. Small MRI positive FCD can be histopathologically missed, most likely due to sampling errors resulting from insufficient harvesting of tissue.

Exploring the impact of hippocampal sclerosis on white matter tracts and memory in individuals with mesial temporal lobe epilepsy

OBJECTIVE

To investigate how the presence/side of hippocampal sclerosis (HS) are related to the white matter structure of cingulum bundle (CB), arcuate fasciculus (AF), and inferior longitudinal fasciculus (ILF) in mesial temporal lobe epilepsy (MTLE).

METHODS

We acquired diffusion-weighted magnetic resonance imaging (MRI) from 86 healthy and 71 individuals with MTLE (22 righ-HS; right-HS, 34 left-HS; left-HS, and 15 nonlesional MTLE). We utilized two-tensor tractography and fiber clustering to compare fractional anisotropy (FA) of each side/tract between groups. Additionally, we examined the association between FA and nonverbal (WMS-R) and verbal (WMS-R, RAVLT codification) memory performance for MTLE individuals.

RESULTS

White matter abnormalities depended on the side and presence of HS. The left-HS demonstrated widespread abnormalities for all tracts, the right-HS showed lower FA for ipsilateral tracts and the nonlesional MTLE group did not differ from healthy individuals. Results indicate no differences in verbal/nonverbal memory performance between the groups, but trend-level associations between higher FA of visual memory and the left CB (r = 0.286, P = 0.018), verbal memory (RAVLT) and -left CB (r = 0.335, P = 0.005), -right CB (r = 0.286, P = 0.016), and -left AF (r = 0.287, P = 0.017).

SIGNIFICANCE

Our results highlight that the presence and side of HS are crucial to understand the pathophysiology of MTLE. Specifically, left-sided HS seems to be related to widespread bilateral white matter abnormalities. Future longitudinal studies should focus on developing diagnostic and treatment strategies dependent on HS's presence/side.

Automated Identification of Stereoelectroencephalography Contacts and Measurement of Factors Influencing Accuracy of Frame Stereotaxy

OBJECTIVE

Stereoelectroencephalography (SEEG) is an established invasive diagnostic technique for use in patients with drug-resistant focal epilepsy evaluated before resective epilepsy surgery. The factors that influence the accuracy of electrode implantation are not fully understood. Adequate accuracy prevents the risk of major surgery complications. Precise knowledge of the anatomical positions of individual electrode contacts is crucial for the interpretation of SEEG recordings and subsequent surgery.

METHODS

We developed an image processing pipeline to localize implanted electrodes and detect individual contact positions using computed tomography (CT), as a substitute for time-consuming manual labeling. The algorithm automates measurement of parameters of the electrodes implanted in the skull (bone thickness, implantation angle and depth) for use in modeling of predictive factors that influence implantation accuracy.

RESULTS

Fifty-four patients evaluated by SEEG were analyzed. A total of 662 SEEG electrodes with 8,745 contacts were stereotactically inserted. The automated detector localized all contacts with better accuracy than manual labeling (p < 0.001). The retrospective implantation accuracy of the target point was 2.4 ± 1.1 mm. A multifactorial analysis determined that almost 58% of the total error was attributable to measurable factors. The remaining 42% was attributable to random error.

CONCLUSION

SEEG contacts can be reliably marked by our proposed method. The trajectory of electrodes can be parametrically analyzed to predict and validate implantation accuracy using a multifactorial model.

SIGNIFICANCE

This novel, automated image processing technique is a potentially clinically important, assistive tool for increasing the yield, efficiency, and safety of SEEG.

PET/MRI Applications in Pediatric Epilepsy

Epilepsy neuroimaging assessment requires exceptional anatomic detail, physiologic and metabolic information. Magnetic resonance (MR) protocols are often time-consuming necessitating sedation and positron emission tomography (PET)/computed tomography (CT) comes with a significant radiation dose. Hybrid PET/MRI protocols allow for exquisite assessment of brain anatomy and structural abnormalities, in addition to metabolic information in a single, convenient imaging session, which limits radiation dose, sedation time, and sedation events. Brain PET/MRI has proven especially useful for accurate localization of epileptogenic zones in pediatric seizure cases, providing critical additional information and guiding surgical decision making in medically refractory cases. Accurate localization of seizure focus is necessary to limit the extent of the surgical resection, preserve healthy brain tissue, and achieve seizure control. This review provides a systematic overview with illustrative examples demonstrating the applications and diagnostic utility of PET/MRI in pediatric epilepsy.

Validation of a highly accelerated post-contrast wave-controlled aliasing in parallel imaging (CAIPI) 3D-T1 MPRAGE compared to standard 3D-T1 MPRAGE for detection of intracranial enhancing lesions on 3-T MRI

OBJECTIVES

High-resolution post-contrast T1-weighted imaging is a workhorse sequence in the evaluation of neurological disorders. The T1-MPRAGE sequence has been widely adopted for the visualization of enhancing pathology in the brain. However, this three-dimensional (3D) acquisition is lengthy and prone to motion artifact, which often compromises diagnostic quality. The goal of this study was to compare a highly accelerated wave-controlled aliasing in parallel imaging (CAIPI) post-contrast 3D T1-MPRAGE sequence (Wave-T1-MPRAGE) with the standard 3D T1-MPRAGE sequence for visualizing enhancing lesions in brain imaging at 3 T.

METHODS

This study included 80 patients undergoing contrast-enhanced brain MRI. The participants were scanned with a standard post-contrast T1-MPRAGE sequence (acceleration factor [R] = 2 using GRAPPA parallel imaging technique, acquisition time [TA] = 5 min 18 s) and a prototype post-contrast Wave-T1-MPRAGE sequence (R = 4, TA = 2 min 32 s). Two neuroradiologists performed a head-to-head evaluation of both sequences and rated the visualization of enhancement, sharpness, noise, motion artifacts, and overall diagnostic quality. A 15% noninferiority margin was used to test whether post-contrast Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE. Inter-rater and intra-rater agreement were calculated. Quantitative assessment of CNR/SNR was performed.

RESULTS

Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE for delineating enhancing lesions with unanimous agreement in all cases between raters. Wave-T1-MPRAGE was noninferior in the perception of noise (p < 0.001), motion artifact (p < 0.001), and overall diagnostic quality (p < 0.001).

CONCLUSION

High-accelerated post-contrast Wave-T1-MPRAGE enabled a two-fold reduction in acquisition time compared to the standard sequence with comparable performance for visualization of enhancing pathology and equivalent perception of noise, motion artifacts and overall diagnostic quality without loss of clinically important information.

KEY POINTS

• Post-contrast wave-controlled aliasing in parallel imaging (CAIPI) T1-MPRAGE accelerated the acquisition of three-dimensional (3D) high-resolution post-contrast images by more than two-fold. • Post-contrast Wave-T1-MPRAGE was noninferior to standard T1-MPRAGE with unanimous agreement between reviewers (100% in 80 cases) for the visualization of intracranial enhancing lesions. • Wave-T1-MPRAGE was equivalent to the standard sequence in the perception of noise in 94% (75 of 80) of cases and was preferred in 16% (13 of 80) of cases for decreased motion artifact.