MR imaging is the imaging modality of choice in epilepsy for detecting structural brain abnormalities, particularly those being considered for surgery. A dedicated epilepsy protocol typically includes high-resolution 3 dimensional (3D) T1-weighted imaging (eg, magnetization prepared rapid acquisition gradient echo) and 3D T2 fluid-attenuation inversion recovery (FLAIR) of the whole brain for anatomic detail and characterization of suspected malformations of cortical development including subtle focal cortical dysplasias. Coronal T2-weighted and/or T2/FLAIR sequences perpendicular to the hippocampus are critical for assessing the architecture of the hippocampus and evaluating for mesial temporal sclerosis and other temporal lobe pathologies.

BACKGROUND AND PURPOSE:The labyrinth is a complex anatomic structure in the temporal bone. However, high-resolution imaging of its membranous portion is challenging because of its small size and the limitations of current MRI techniques. Deep learning reconstruction (DLR) represents a promising approach to advancing MR image quality, enabling higher spatial resolution and reduced noise. This study aims to evaluate DLR high-resolution 3D heavy T2-weighted TSE (3D-T2) MRI sequences for visualizing the labyrinthine structures, comparing them with conventional 3D-T2 sequences. The goal is to improve spatial resolution without prolonging acquisition times, allowing a more detailed view of the labyrinthine microanatomy. MATERIALS AND METHODS:High-resolution heavy T2-weighted TSE SPACE images were acquired in patients by using 3D-T2 and improved T2 weighted turbo spin-echo sequence incorporating deep learning reconstruction (DLR-3D-T2). Two radiologists rated structure visibility on a 4-point qualitative scale for the spiral lamina, scala tympani, scala vestibuli, scala media, utricle, saccule, utricular and saccular maculae, membranous semicircular ducts, and ampullary nerves. Ex vivo 9.4T MRI served as an anatomic reference. RESULTS:DLR-3D-T2 significantly improved the visibility of several inner ear structures. The utricle and utricular macula were systematically visualized, achieving grades ≥3 in 95% of cases (P < .001), while the saccule remained challenging to assess, with grades ≥3 in only 10% of cases. The cochlear spiral lamina and scala tympani were better delineated in the first 2 turns but remained poorly visible in the apical turn. Semicircular ducts were only partially visualized, with grades ≥3 in 12.5% to 20% of cases, likely due to resolution limitations relative to their diameter. Ampullary nerves were moderately improved, with grades ≥3 in 52.5% to 55% of cases, depending on the nerve. CONCLUSIONS:While DLR does not yet provide a complete anatomic assessment, it represents a important step forward in the noninvasive evaluation of inner ear structures. Pending further technical refinements, this approach may help reduce reliance on delayed gadolinium-enhanced techniques for imaging membranous structures.

BACKGROUND AND PURPOSE:7T MRI has specific technical features that are advantageous for epilepsy. This study aims to evaluate whether new potentially epileptogenic abnormalities can be identified on 7T MRI in patients with epilepsy with negative 3T MRI findings. MATERIALS AND METHODS:Clinical 7T epilepsy MRI examinations in patients with prior negative 3T imaging findings were retrospectively reviewed by 3 neuroradiologists. Their consensus 7T scan interpretations were reviewed by a neurologist for concordance with EEG findings. Descriptive characteristics of any 7T MRI abnormalities and their locations were recorded. The clinical and EEG findings in subjects with abnormal 7T scan findings were compared with those of subjects without a 7T abnormality. RESULTS:In patients with epilepsy with nonlesional 3T MRI, new abnormal findings were identified on 7T MRI in 36% (18/50) of cases. Of the 14 pediatric cases, there were 7T MRI abnormal findings in 6/14 (42.9%). Across all cases, a total of 21 discrete abnormal findings were identified, including meningoencephaloceles (5/21, 23.8%), cavernous malformations/possible vascular lesions (5/21, 23.8%), focal cortical dysplasia (3/21, 14.3%), gray matter heterotopia (3/21, 14.3%), mesial temporal sclerosis (3/21, 14.3%), 1 indeterminant hippocampal morphology finding (1/21), and 1 case of a diffuse migrational abnormality (1/21). Noninvasive EEG monitoring unit data were concordant with the location of 7T abnormalities in 60.0% (9/15) of cases with these clinical data available. Participants with generalized seizures (OR, 0.2; 95% CI, 0.041-0.75) and those with multiple seizure types (OR, 0.14; 95% CI, 0.027-0.52) were significantly less likely to have new potentially epileptogenic lesions detected at 7T. Two 7T cases with abnormal findings underwent surgical resection with good clinical outcomes (Engel Class IA). CONCLUSIONS:In clinical practice, 7T MRI revealed additional epileptogenic lesions in 36% of nonlesional 3T MRI cases.

MR imaging is a central component of the diagnosis and management of epilepsy, especially in identifying candidates for surgical resection or planning for neuromodulatory interventions. A standardized, high-resolution epilepsy protocol enables the detection of subtle epileptogenic abnormalities. Radiologists must be attuned to the wide spectrum of lesions and aware of potential imaging pitfalls.

For epilepsy, brain single-photon emission computed tomography and PET are noninvasive nuclear medicine studies that can guide complex management decisions and surgical intervention. Due to seizure-related changes in cerebral blood flow and glucose utilization during the ictal and interictal period, these nuclear medicine studies can localize epileptogenic regions and assess broad functional changes in epilepsy. Advanced quantitative and computational techniques can increase the yield of these studies and assist with interpretation. Future developments in PET radiopharmaceuticals targeted inflammation, synaptic density, or various neurotransmitter systems may provide additional diagnostic capabilities for epilepsy.

BACKGROUND AND PURPOSE:7T MRI is a promising clinical technology for epilepsy imaging. Quantification of hippocampus volume on MRI is a clinically useful biomarker in epilepsy. Applying automated hippocampus volume measurement tools to 7T MRI is needed to optimize the use of clinical ultra-high-field strength epilepsy imaging. The objective of this study is a performance evaluation of automated hippocampal volume measurement software at 7T MRI in both normal participants and those with seizure disorders. MATERIALS AND METHODS:7T MRI examinations were prospectively acquired in 50 participants. A subset of participants also underwent 3T MRI examinations, and a subset underwent 2 separate 7T acquisitions. Automated segmentation of the hippocampus was performed with 2 commonly used software packages (FreeSurfer and NeuroQuant) at 3T and 7T, with hippocampal volumes calculated for segmentations without any visually unacceptable errors as determined by radiologist review. Hippocampal volumes were also measured from manual segmentations, and the intraclass correlation coefficient (ICC) was used to compare data with automated segmentation volumes. RESULTS:Visually unacceptable automated hippocampus segmentation errors occurred more frequently at 7T than at 3T with NeuroQuant (11.0% versus 7.14%) and FreeSurfer (12.5% versus 0%). Computerized volume measurements at 7T correlated poorly with manual segmentation for both software programs (ICC <0.4). Hippocampal volume estimate correlation between matched 7T and 3T MRI in the same participant was fair (ICC = 0.4-0.59) to good (0.6-0.75) for software and manual segmentation. For repeated 7T MRI examinations in the same participant, hippocampus segmentation reproducibility was excellent (0.75) for automated software but poor (< 0.4) for manual segmentation. CONCLUSIONS:Computerized volume measurement of the hippocampus at 7T correlates poorly with volumes obtained through manual segmentation and suboptimally with matched 3T examination measurements, but is highly reproducible at 7T within the same participant. Segmentation errors are more common with 7T examinations, and further development of a hippocampal segmentation method specific to 7T MRI is needed to fully realize the benefits of 7T MRI for imaging patients with epilepsy.

Ever since its introduction as a diagnostic imaging tool the potential of magnetic resonance imaging (MRI) in radiation therapy (RT) treatment simulation and planning has been recognized. Recent technical advances have addressed many of the impediments to use of this technology and as a result have resulted in rapid and growing adoption of MRI in RT. The purpose of this article is to provide a broad review of the multiple uses of MR in the RT treatment simulation and planning process, identify several of the most used clinical scenarios in which MR is integral to the simulation and planning process, highlight existing limitations and provide multiple unmet needs thereby highlighting opportunities for the diagnostic MR imaging community to contribute and collaborate with our oncology colleagues.Evidence Level5Technical EfficacyStage 5

BackgroundMR fingerprinting (MRF) is a novel method for quantitative assessment of in vivo MR relaxometry that has shown high precision and accuracy. However, the method requires data acquisition using customized, complex acquisition strategies and dedicated post processing methods thereby limiting its widespread application.ObjectiveTo develop a deep learning (DL) network for synthesizing MRF signals from conventional magnitude-only MR imaging data and to compare the results to the actual MRF signal acquired.MethodsA U-Net DL network was developed to synthesize MRF signals from magnitude-only 3D T1-weighted brain MRI data acquired from 37 volunteers aged between 21 and 62 years of age. Network performance was evaluated by comparison of the relaxometry data (T1, T2) generated from dictionary matching of the deep learning synthesized and actual MRF data from 47 segmented anatomic regions. Clustered bootstrapping involving 10,000 bootstraps followed by calculation of the concordance correlation coefficient were performed for both T1 and T2 MRF data pairs. 95% confidence limits and the mean difference between true and DL relaxometry values were also calculated.ResultsThe concordance correlation coefficient (and 95% confidence limits) for T1 and T2 MRF data pairs over the 47 anatomic segments were 0.8793 (0.8136–0.9383) and 0.9078 (0.8981–0.9145) respectively. The mean difference (and 95% confidence limits) were 48.23 (23.0–77.3) s and 2.02 (−1.4 to 4.8) s.ConclusionIt is possible to synthesize MRF signals from MRI data using a DL network, thereby creating the potential for performing quantitative relaxometry assessment without the need for a dedicated MRF pulse sequence.

PURPOSE:Temporal encephaloceles are a cause of drug-resistant temporal lobe epilepsy; however, their relationship with epileptogenesis is unclear, and optimal surgical resection is uncertain. EEG source localization (ESL) may guide surgical decision-making. METHODS:We reviewed patients at Mayo Clinic Rochester with drug-resistant temporal lobe epilepsy and temporal encephaloceles, who underwent limited resection and had 1-year outcomes. EEG source localization was performed using standard density scalp EEG of ictal and interictal activity. Distance from dipole and standardized low-resolution brain electromagnetic tomography (sLORETA) solutions to the encephalocele were measured. Concordance of ESL with encephalocele and surgical resection was compared with 1-year surgical outcomes. RESULTS:Seventeen patients met criteria. The mean distances from ESL results to encephalocele center for dipole and sLORETA analyses were 23 mm (SD 9) and 22 mm (SD 11), respectively. Ten patients (55.6%) had Engel I outcomes at 1 year. Dipole-encephalocele distance and sLORETA-encephalocele distance were significantly longer in patients with Engel I outcome and patients whose encephalocele was contained by sLORETA had worse outcome as well; however, multiple logistic regression analysis found that only containment of encephalocele by the sLORETA current density was significant ( P < 0.05), odds ratio 0.12 (95% confidence interval [0.021, 0.71]). CONCLUSIONS:EEG source localization of scalp EEG localizes near encephaloceles, however, typically not in the encephalocele itself; this may be due to scalp EEG sampling propagated activity or alternatively that the seizure onset zone extends beyond the herniated cortex. Surprisingly, we observed increased ESL to encephalocele distances in patients with excellent surgical outcomes. Larger cohort studies including intracranial EEG data are needed to further explore this finding.

PURPOSE:This study sought to evaluate the impact of surgical extent on seizure outcome in drug-resistant temporal lobe epilepsy (DR-TLE) with temporal encephaloceles (TE). METHODS:This was a single-institution retrospective study of patients who underwent surgery for DR-TLE with TE between January 2008 and December 2020. The impact of surgical extent on seizure outcome was evaluated. In a subset with dominant DR-TLE, the impact of surgical extent on neuropsychometric outcome was evaluated. RESULTS:Thirty-four patients were identified (female, 56%; median age at surgery, 43 years). TE were frequently overlooked on initial magnetic resonance imaging (MRI), with encephaloceles only detected after repeat or expert re-review of MRI, additional multi-modal imaging, or intra-operatively in 31 (91%). Sixteen (47%) underwent limited resections, including encephalocele resection only (n = 5) and encephalocele resection with more extensive temporal corticectomy sparing the amygdala and hippocampus (n = 11). The remainder (n = 18, 53%) underwent standard anterior temporal lobectomy and amygdalohippocampectomy (ATLAH). Limited resection was performed more frequently on the left (12/17 vs. 4/17, p = 0.015). Twenty-seven patients (79%) had a favourable outcome (Engel I/II), and 17 (50%) were seizure-free at the last follow-up (median seizure-free survival of 27.3 months). There was no statistically significant difference in seizure-free outcomes between limited resection and ATLAH. In dominant DR-TLE, verbal memory decline was more likely after ATLAH than limited resection (3/4 vs. 0/9, p = 0.014). CONCLUSION:Expert re-review of imaging and multi-modal advanced imaging improved TE identification. There was no statistical difference in seizure-free outcomes based on surgical extent. Preservation of verbal memory supports limited resection in dominant temporal cases.

BACKGROUND:Identification of the central sulcus can require inspection of subtle differences or require certain pulse sequences. This study identifies the central sulcus by signal intensity on double inversion recovery (DIR) images in multiple anatomic locations and imaging planes.METHODS:Forty-nine patients (98 hemispheres) were retrospectively reviewed by three neuroradiologists and one radiology resident. The central sulcus was compared to the surrounding sulci for differences in signal intensity at axial hand knob, axial operculum, and lateral convexity sagittal images (294 locations) on DIR images. The use of the "disappearing central sulcus sign" where the window level is increased at constant width and black/white inversion were also assessed.RESULTS:In 49 patients (22 females, 27 males; median age 36 years), the central sulcus cortex signal intensity was lower than adjacent sulci with a frequency of 90/98 (91.8%) at the axial hand knob level, 68/98 (69.4%) at the axial operculum level, and 76/98 (77.5%) at the sagittal level. With black and white inversion, the frequencies were of 96/98 (98%), 92/98 (94%), and 87/98 (89%). The central sulcus was the first to disappear at all three levels with high degrees of inter-reader agreement (86-99%). Traditional anatomic landmarks were absent or conflicting in seven hemispheres (5 patients). The central sulcus was identified by DIR signal intensity in all seven hemispheres.CONCLUSIONS:The central sulcus can be identified by differences in signal intensity of the perirolandic cortex on DIR. Use of black/white inversion and the disappearing central sulcus sign may further facilitate identification.

PURPOSE:To evaluate the performance of a new, highly flexible radiofrequency (RF) coil system for imaging patients undergoing MR simulation.METHODS:Volumetric phantom and in vivo images were acquired with a commercially available and prototype RF coil set. Phantom evaluation was performed using a silicone-filled humanoid phantom of the head and shoulders. In vivo assessment was performed in five healthy and six patient subjects. Phantom data included T1-weighted volumetric imaging, while in vivo acquisitions included both T1- and T2-weighted volumetric imaging. Signal to noise ratio (SNR) and uniformity metrics were calculated in the phantom data, while SNR values were calculated in vivo. Statistical significance was tested by means of a non-parametric analysis of variance test.RESULTS:At a threshold of p = 0.05, differences in measured SNR distributions within the entire phantom volume were statistically different in two of the three paired coil set comparisons. Differences in per slice average SNR between the two coil sets were all statistically significant, as well as differences in per slice image uniformity. For patients, SNRs within the entire imaging volume were statistically significantly different in four of the nine comparisons and seven of the nine comparisons performed on the per slice average SNR values. For healthy subjects, SNRs within the entire imaging volume were statistically significantly different in seven of the nine comparisons and eight of the nine comparisons when per slice average SNR was tested.CONCLUSIONS:Phantom and in vivo results demonstrate that image quality obtained from the novel flexible RF coil set was similar or improved over the conventional coil system. The results also demonstrate that image quality is impacted by the specific coil configurations used for imaging and should be matched appropriately to the anatomic site imaged to ensure optimal and reproducible image quality.

To compare verbal learning outcomes for limited resection vs. anterior temporal lobectomy with amygdalohippocampectomy (ATLAH) in dominant hemisphere drug-resistant temporal lobe epilepsy (DR-TLE) related to temporal encephaloceles (TE).

MR fingerprinting (MRF) is a MR technique that allows assessment of tissue relaxation times. The purpose of this study is to evaluate the clinical application of this technique in patients with meningioma. A whole-brain 3D isotropic 1mm3 acquisition under a 3.0T field strength was used to obtain MRF T1 and T2-based relaxometry values in 4:38 s. The accuracy of values was quantified by scanning a quantitative MR relaxometry phantom. In vivo evaluation was performed by applying the sequence to 20 subjects with 25 meningiomas. Regions of interest included the meningioma, caudate head, centrum semiovale, contralateral white matter and thalamus. For both phantom and subjects, mean values of both T1 and T2 estimates were obtained. Statistical significance of differences in mean values between the meningioma and other brain structures was tested using a Friedman’s ANOVA test. MR fingerprinting phantom data demonstrated a linear relationship between measured and reference relaxometry estimates for both T1 (r2 = 0.99) and T2 (r2 = 0.97). MRF T1 relaxation times were longer in meningioma (mean ± SD 1429 ± 202 ms) compared to thalamus (mean ± SD 1054 ± 58 ms; p = 0.004), centrum semiovale (mean ± SD 825 ± 42 ms; p < 0.001) and contralateral white matter (mean ± SD 799 ± 40 ms; p < 0.001). MRF T2 relaxation times were longer for meningioma (mean ± SD 69 ± 27 ms) as compared to thalamus (mean ± SD 27 ± 3 ms; p < 0.001), caudate head (mean ± SD 39 ± 5 ms; p < 0.001) and contralateral white matter (mean ± SD 35 ± 4 ms; p < 0.001) Phantom measurements indicate that the proposed 3D-MRF sequence relaxometry estimations are valid and reproducible. For in vivo, entire brain coverage was obtained in clinically feasible time and allows quantitative assessment of meningioma in clinical practice.

Background MR fingerprinting (MRF) is a novel imaging method proposed for the diagnosis of Multiple Sclerosis (MS). This study aims to determine if MR Fingerprinting (MRF) relaxometry can differentiate frontal normal appearing white matter (F-NAWM) and splenium in patients diagnosed with MS as compared to controls and to characterize the relaxometry of demyelinating plaques relative to the time of diagnosis. Methods Three-dimensional (3D) MRF data were acquired on a 3.0T MRI system resulting in isotropic voxels (1 × 1 × 1 mm 3 ) and a total acquisition time of 4 min 38 s. Data were collected on 18 subjects paired with 18 controls. Regions of interest were drawn over MRF-derived T 1 relaxometry maps encompassing selected MS lesions, F-NAWM and splenium. T 1 and T 2 relaxometry features from those segmented areas were used to classify MS lesions from F-NAWM and splenium with T-distributed stochastic neighbor embedding algorithms. Partial least squares discriminant analysis was performed to discriminate NAWM and Splenium in MS compared with controls. Results Mean out-of-fold machine learning prediction accuracy for discriminant results between MS patients and controls for F-NAWM was 65 % (p = 0.21) and approached 90 % (p < 0.01) for the splenium. There was significant positive correlation between time since diagnosis and MS lesions mean T2 (p = 0.015), minimum T1 (p = 0.03) and negative correlation with splenium uniformity (p = 0.04). Perfect discrimination (AUC = 1) was achieved between selected features from MS lesions and F-NAWM. Conclusions 3D-MRF has the ability to differentiate between MS and controls based on relaxometry properties from the F-NAWM and splenium. Whole brain coverage allows the assessment of quantitative properties within lesions that provide chronological assessment of the time from MS diagnosis.