Combining magnetic resonance fingerprinting with voxel-based morphometric analysis to reduce false positives for focal cortical dysplasia detection.

OBJECTIVE: We aim to improve focal cortical dysplasia (FCD) detection by combining high-resolution, three-dimensional (3D) magnetic resonance fingerprinting (MRF) with voxel-based morphometric magnetic resonance imaging (MRI) analysis. METHODS: We included 37 patients with pharmacoresistant focal epilepsy and FCD (10 IIa, 15 IIb, 10 mild Malformation of Cortical Development [mMCD], and 2 mMCD with oligodendroglial hyperplasia and epilepsy [MOGHE]). Fifty-nine healthy controls (HCs) were also included. 3D lesion labels were manually created. Whole-brain MRF scans were obtained with 1 mm3 isotropic resolution, from which quantitative T1 and T2 maps were reconstructed. Voxel-based MRI postprocessing, implemented with the morphometric analysis program (MAP18), was performed for FCD detection using clinical T1w images, outputting clusters with voxel-wise lesion probabilities. Average MRF T1 and T2 were calculated in each cluster from MAP18 output for gray matter (GM) and white matter (WM) separately. Normalized MRF T1 and T2 were calculated by z-scores using HCs. Clusters that overlapped with the lesion labels were considered true positives (TPs); clusters with no overlap were considered false positives (FPs). Two-sample t-tests were performed to compare MRF measures between TP/FP clusters. A neural network model was trained using MRF values and cluster volume to distinguish TP/FP clusters. Ten-fold cross-validation was used to evaluate model performance at the cluster level. Leave-one-patient-out cross-validation was used to evaluate performance at the patient level. RESULTS: MRF metrics were significantly higher in TP than FP clusters, including GM T1, normalized WM T1, and normalized WM T2. The neural network model with normalized MRF measures and cluster volume as input achieved mean area under the curve (AUC) of .83, sensitivity of 82.1%, and specificity of 71.7%. This model showed superior performance over direct thresholding of MAP18 FCD probability map at both the cluster and patient levels, eliminating ≥75% FP clusters in 30% of patients and ≥50% of FP clusters in 91% of patients. SIGNIFICANCE: This pilot study suggests the efficacy of MRF for reducing FPs in FCD detection, due to its quantitative values reflecting in vivo pathological changes. © 2024 International League Against Epilepsy.

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

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

Development of a generative deep learning model to improve epiretinal membrane detection in fundus photography.

BACKGROUND: The epiretinal membrane (ERM) is a common retinal disorder characterized by abnormal fibrocellular tissue at the vitreomacular interface. Most patients with ERM are asymptomatic at early stages. Therefore, screening for ERM will become increasingly important. Despite the high prevalence of ERM, few deep learning studies have investigated ERM detection in the color fundus photography (CFP) domain. In this study, we built a generative model to enhance ERM detection performance in the CFP. METHODS: This deep learning study retrospectively collected 302 ERM and 1,250 healthy CFP data points from a healthcare center. The generative model using StyleGAN2 was trained using single-center data. EfficientNetB0 with StyleGAN2-based augmentation was validated using independent internal single-center data and external datasets. We randomly assigned healthcare center data to the development (80%) and internal validation (20%) datasets. Data from two publicly accessible sources were used as external validation datasets. RESULTS: StyleGAN2 facilitated realistic CFP synthesis with the characteristic cellophane reflex features of the ERM. The proposed method with StyleGAN2-based augmentation outperformed the typical transfer learning without a generative adversarial network. The proposed model achieved an area under the receiver operating characteristic (AUC) curve of 0.926 for internal validation. AUCs of 0.951 and 0.914 were obtained for the two external validation datasets. Compared with the deep learning model without augmentation, StyleGAN2-based augmentation improved the detection performance and contributed to the focus on the location of the ERM. CONCLUSIONS: We proposed an ERM detection model by synthesizing realistic CFP images with the pathological features of ERM through generative deep learning. We believe that our deep learning framework will help achieve a more accurate detection of ERM in a limited data setting.

Spatiotemporal profile of atrophy in the first year following moderate-severe traumatic brain injury.

Traumatic brain injury (TBI) triggers progressive neurodegeneration resulting in brain atrophy that continues months-to-years following injury. However, a comprehensive characterization of the spatial and temporal evolution of TBI-related brain atrophy remains incomplete. Utilizing a sensitive and unbiased morphometry analysis pipeline optimized for detecting longitudinal changes, we analyzed a sample consisting of 37 individuals with moderate-severe TBI who had primarily high-velocity and high-impact injury mechanisms. They were scanned up to three times during the first year after injury (3 months, 6 months, and 12 months post-injury) and compared with 33 demographically matched controls who were scanned once. Individuals with TBI already showed cortical thinning in frontal and temporal regions and reduced volume in the bilateral thalami at 3 months post-injury. Longitudinally, only a subset of cortical regions in the parietal and occipital lobes showed continued atrophy from 3 to 12 months post-injury. Additionally, cortical white matter volume and nearly all deep gray matter structures exhibited progressive atrophy over this period. Finally, we found that disproportionate atrophy of cortex along sulci relative to gyri, an emerging morphometric marker of chronic TBI, was present as early as 3 month post-injury. In parallel, neurocognitive functioning largely recovered during this period despite this pervasive atrophy. Our findings demonstrate msTBI results in characteristic progressive neurodegeneration patterns that are divergent across regions and scale with the severity of injury. Future clinical research using atrophy during the first year of TBI as a biomarker of neurodegeneration should consider the spatiotemporal profile of atrophy described in this study.

Evaluating whole-brain tissue-property changes in MRI-negative pharmacoresistant focal epilepsies using MR fingerprinting.

OBJECTIVE: We aim to quantify whole-brain tissue-property changes in patients with magnetic resonance imaging (MRI)-negative pharmacoresistant focal epilepsy by three-dimensional (3D) magnetic resonance fingerprinting (MRF). METHODS: We included 30 patients with pharmacoresistant focal epilepsy and negative MRI by official radiology report, as well as 40 age- and gender-matched healthy controls (HCs). MRF scans were obtained with 1 mm3 isotropic resolution. Quantitative T1 and T2 relaxometry maps were reconstructed from MRF and registered to the Montreal Neurological Institute (MNI) space. A two-sample t test was performed in Functional Magnetic Resonance Imaging of the Brain (FMRIB) Software Library (FSL) to evaluate significant abnormalities in patients comparing to HCs, with correction by the threshold-free cluster enhancement (TFCE) method. Subgroups analyses were performed for extra-temporal epilepsy/temporal epilepsy (ETLE/TLE), and for those with/without subtle abnormalities detected by morphometric analysis program (MAP), to investigate each subgroup's pattern of MRF changes. Correlation analyses were performed between the mean MRF values in each significant cluster and seizure-related clinical variables. RESULTS: Compared to HCs, patients exhibited significant group-level T1 increase ipsilateral to the epileptic origin, in the mesial temporal gray matter (GM) and white matter (WM), temporal pole GM, orbitofrontal GM, hippocampus, and amygdala, with scattered clusters in the neocortical temporal and insular GM. No significant T2 changes were detected. The ETLE subgroup showed a T1-increase pattern similar to the overall cohort, with additional involvement of the ipsilateral anterior cingulate GM. The subgroup of MAP+ patients also showed a T1-increase pattern similar to the overall cohort, with additional cluster in the ipsilateral lateral orbitofrontal GM. Higher T1 was associated with younger seizure-onset age, longer epilepsy duration, and higher seizure frequency. SIGNIFICANCE: MRF revealed group-level T1 increase in limbic/paralimbic structures ipsilateral to the epileptic origin, in patients with pharmacoresistant focal epilepsy and no apparent lesions on MRI, suggesting that these regions may be commonly affected by seizures in the epileptic brain. The significant association between T1 increase and higher seizure burden may reflect progressive tissue damage.

Characterizing thalamic and basal ganglia nuclei in medically intractable focal epilepsy by MR fingerprinting.

OBJECTIVES: Magnetic resonance fingerprinting (MRF) is a novel, quantitative, and noninvasive technique to measure brain tissue properties. We aim to use MRF for characterizing normal-appearing thalamic and basal ganglia nuclei in the epileptic brain. METHODS: A three-dimensional (3D) MRF protocol (1 mm3 isotropic resolution) was acquired from 48 patients with unilateral medically intractable focal epilepsy and 39 healthy controls (HCs). Whole-brain T1 and T2 maps (containing T1 and T2 relaxation times) were reconstructed for each subject. Ten subcortical nuclei in the thalamus and basal ganglia were segmented as regions of interest (ROIs), within which the mean T1 and T2 values, as well as their coefficient of variation (CV) were compared between the patients and HCs at the group level. Subgroup and correlation analyses were performed to examine the relationship between significant MRF measures and various clinical characteristics. Using significantly abnormal MRF measures from the group-level analyses, support vector machine (SVM) and logistic regression machine learning models were built and tested with 5-fold and 10-fold cross-validations, to separate patients from HCs, and to separate patients with left-sided and right-sided epilepsy, at the individual level. RESULTS: MRF revealed increased T1 mean value in the ipsilateral thalamus and nucleus accumbens; increased T1 CV in the bilateral thalamus, bilateral pallidum, and ipsilateral caudate; and increased T2 CV in the ipsilateral thalamus in patients compared to HCs (p < .05, false discovery rate [FDR] corrected). The SVM classifier produced 78.2% average accuracy to separate individual patients from HCs, with an area under the curve (AUC) of 0.83. The logistic regression classifier produced 67.4% average accuracy to separate patients with left-sided and right-sided epilepsy, with an AUC of 0.72. SIGNIFICANCE: MRF revealed bilateral tissue-property changes in the normal-appearing thalamus and basal ganglia, with ipsilateral predominance and thalamic preference, suggesting subcortical involvement/impairment in patients with medically intractable focal epilepsy. The individual-level performance of the MRF-based machine-learning models suggests potential opportunities for predicting lateralization.

Using magnetic resonance fingerprinting to characterize periventricular nodular heterotopias in pharmacoresistant epilepsy.

OBJECTIVE: We aimed to use a novel magnetic resonance fingerprinting (MRF) technique to examine in vivo tissue property characteristics of periventricular nodular heterotopia (PVNH). These characteristics were further correlated with stereotactic-electroencephalographic (SEEG) ictal onset findings. METHODS: We included five patients with PVNH who had SEEG-guided surgery and at least 1 year of seizure freedom or substantial seizure reduction. High-resolution MRF scans were acquired at 3 T, generating three-dimensional quantitative T1 and T2  maps. We assessed the differences between T1 and T2  values from the voxels in the nodules located in the SEEG-defined seizure onset zone (SOZ) and non-SOZ, on -individual and group levels. Receiver operating characteristic analyses were performed to obtain the optimal classification performance. Quantification of SEEG ictal onset signals from the nodules was performed by calculating power spectrum density (PSD). The association between PSD and T1 /T2  values was further assessed at different frequency bands. RESULTS: Individual-level analysis showed T1 was significantly higher in SOZ voxels than non-SOZ voxels (p < .05), with an average 73% classification accuracy. Group-level analysis also showed higher T1 was significantly associated with SOZ voxels (p < .001). At the optimal cutoff (normalized T1 of 1.1), a 76% accuracy for classifying SOZ nodules from non-SOZ nodules was achieved. T1  values were significantly associated with ictal onset PSD at the ultraslow, θ, ß, γ, and ripple bands (p < .05). T2  values were significantly associated with PSD only at the ultraslow band (p < .05). SIGNIFICANCE: Quantitative MRF measures, especially T1 , can provide additional noninvasive information to separate nodules in SOZ and non-SOZ. The T1 and T2 tissue property changes carry electrophysiological underpinnings relevant to the epilepsy, as shown by their significant positive associations with power changes during the SEEG seizure onset. The use of MRF as a supplementary noninvasive tool may improve presurgical evaluation for patients with PVNH and pharmacoresistant epilepsy.

Atrophy and cognitive profiles in older adults with temporal lobe epilepsy are similar to mild cognitive impairment.

Epilepsy incidence and prevalence peaks in older adults yet systematic studies of brain ageing and cognition in older adults with epilepsy remain limited. Here, we characterize patterns of cortical atrophy and cognitive impairment in 73 older adults with temporal lobe epilepsy (>55 years) and compare these patterns to those observed in 70 healthy controls and 79 patients with amnestic mild cognitive impairment, the prodromal stage of Alzheimer's disease. Patients with temporal lobe epilepsy were recruited from four tertiary epilepsy surgical centres; amnestic mild cognitive impairment and control subjects were obtained from the Alzheimer's Disease Neuroimaging Initiative database. Whole brain and region of interest analyses were conducted between patient groups and controls, as well as between temporal lobe epilepsy patients with early-onset (age of onset <50 years) and late-onset (>50 years) seizures. Older adults with temporal lobe epilepsy demonstrated a similar pattern and magnitude of medial temporal lobe atrophy to amnestic mild cognitive impairment. Region of interest analyses revealed pronounced medial temporal lobe thinning in both patient groups in bilateral entorhinal, temporal pole, and fusiform regions (all P < 0.05). Patients with temporal lobe epilepsy demonstrated thinner left entorhinal cortex compared to amnestic mild cognitive impairment (P = 0.02). Patients with late-onset temporal lobe epilepsy had a more consistent pattern of cortical thinning than patients with early-onset epilepsy, demonstrating decreased cortical thickness extending into the bilateral fusiform (both P < 0.01). Both temporal lobe epilepsy and amnestic mild cognitive impairment groups showed significant memory and language impairment relative to healthy control subjects. However, despite similar performances in language and memory encoding, patients with amnestic mild cognitive impairment demonstrated poorer delayed memory performances relative to both early and late-onset temporal lobe epilepsy. Medial temporal lobe atrophy and cognitive impairment overlap between older adults with temporal lobe epilepsy and amnestic mild cognitive impairment highlights the risks of growing old with epilepsy. Concerns regarding accelerated ageing and Alzheimer's disease co-morbidity in older adults with temporal lobe epilepsy suggests an urgent need for translational research aimed at identifying common mechanisms and/or targeting symptoms shared across a broad neurological disease spectrum.

Exploring linearity of deep neural network trained QSM: QSMnet.

Recently, deep neural network-powered quantitative susceptibility mapping (QSM), QSMnet, successfully performed ill-conditioned dipole inversion in QSM and generated high-quality susceptibility maps. In this paper, the network, which was trained by healthy volunteer data, is evaluated for hemorrhagic lesions that have substantially higher susceptibility than healthy tissues in order to test "linearity" of QSMnet for susceptibility. The results show that QSMnet underestimates susceptibility in hemorrhagic lesions, revealing degraded linearity of the network for the untrained susceptibility range. To overcome this limitation, a data augmentation method is proposed to generalize the network for a wider range of susceptibility. The newly trained network, which is referred to as QSMnet+, is assessed in computer-simulated lesions with an extended susceptibility range (-1.4 â€‹ppm to +1.4 â€‹ppm) and also in twelve hemorrhagic patients. The simulation results demonstrate improved linearity of QSMnet+ over QSMnet (root mean square error of QSMnet+: 0.04 â€‹ppm vs. QSMnet: 0.36 â€‹ppm). When applied to patient data, QSMnet+ maps show less noticeable artifacts to those of conventional QSM maps. Moreover, the susceptibility values of QSMnet+ in hemorrhagic lesions are better matched to those of the conventional QSM method than those of QSMnet when analyzed using linear regression (QSMnet+: slope â€‹= â€‹1.05, intercept â€‹= â€‹-0.03, R2 â€‹= â€‹0.93; QSMnet: slope â€‹= â€‹0.68, intercept â€‹= â€‹0.06, R2 â€‹= â€‹0.86), consolidating improved linearity in QSMnet+. This study demonstrates the importance of the trained data range in deep neural network-powered parametric mapping and suggests the data augmentation approach for generalization of network. The new network can be applicable for a wide range of susceptibility quantification.

Artificial neural network for myelin water imaging.

PURPOSE: To demonstrate the application of artificial neural network (ANN) for real-time processing of myelin water imaging (MWI). METHODS: Three neural networks, ANN-IMWF , ANN-IGMT2 , and ANN-II, were developed to generate MWI. ANN-IMWF and ANN-IGMT2 were designed to output myelin water fraction (MWF) and geometric mean T2 of intra- and extra-cellular water signal (GMT2,IEW ), respectively, whereas ANN-II generates a T2 distribution. For the networks, gradient and spin echo data from 18 healthy controls (HC) and 26 multiple sclerosis patients (MS) were utilized. Among them, 10 HC and 12 MS had the same scan parameters and were used for training (6 HC and 6 MS), validation (1 HC and 1 MS), and test sets (3 HC and 5 MS). The remaining data had different scan parameters and were applied to exam effects of the scan parameters. The network results were compared with those of conventional MWI in the white matter mask and regions of interest. RESULTS: The networks produced highly accurate results, showing averaged normalized root-mean-squared error under 3% for MWF and 0.4% for GMT2,IEW in the white matter mask of the test set. In the region of interest analysis, the differences between ANNs and conventional MWI were less than 0.1% in MWF and 0.1 ms in GMT2,IEW (no statistical difference and R2 > 0.97). Datasets with different scan parameters showed increased errors. The average processing time was 0.68 s in ANNs, gaining 11,702 times acceleration in the computational speed (conventional MWI: 7,958 s). CONCLUSION: The proposed neural networks demonstrate the feasibility of real-time processing for MWI with high accuracy.

CycleGAN-based deep learning technique for artifact reduction in fundus photography.

PURPOSE: A low quality of fundus photograph with artifacts may lead to false diagnosis. Recently, a cycle-consistent generative adversarial network (CycleGAN) has been introduced as a tool to generate images without matching paired images. Therefore, herein, we present a deep learning technique that removes the artifacts automatically in a fundus photograph using a CycleGAN model. METHODS: This study included a total of 2206 anonymized retinal images including 1146 with artifacts and 1060 without artifacts. In this experiment, we applied the CycleGAN model to color fundus photographs with a pixel resolution of 256 × 256 × 3. To apply the CycleGAN to an independent dataset, we randomly divided the data into training (90%) and test (10%) datasets. Additionally, we adopted the automated quality evaluation (AQE) to assess the retinal image quality. RESULTS: From the results, we observed that the artifacts such as overall haze, edge haze, lashes, arcs, and uneven illumination were successfully reduced by the CycleGAN in the generated images, and the main information of the retina was essentially retained. Further, we observed that most of the generated images exhibited improved AQE grade values when compared with the original images with artifacts. CONCLUSION: Thus, we could conclude that the CycleGAN technique can effectively reduce the artifacts and improve the quality of fundus photographs, and it may be beneficial for clinicians in analyzing the low-quality fundus photographs. Future studies should improve the quality and resolution of the generated image to provide a more detailed fundus photography.

Advances in gradient echo myelin water imaging at 3T and 7T.

Gradient echo myelin water imaging (GRE-MWI) is an MRI technique to measure myelin concentration and involves the analysis of signal decay characteristics of the multi-echo gradient echo data. The method provides a myelin water fraction as a quantitative biomarker for myelin. In this work, a new sequence and post-processing methods were proposed to generate high quality GRE-MWI images at 3T and 7T. In order to capture the rapidly decaying myelin water signals, a bipolar readout GRE sequence was designed with "gradient pairing," compensating for the eddy current effects. The flip angle dependency from the multi-compartmental T1 effects was explored and avoided using a 2D multi-slice acquisition with a long TR. Additionally, the sequence was tested for the effects of inflow and magnetization transfer and demonstrated robustness to these error sources. Lastly, the temporal and spatial B0 inhomogeneity effects were mitigated by using the B0 navigator and field inhomogeneity corrections. Using the method, high-quality myelin water images were successfully generated for the in-vivo human brain at both field strengths. When the myelin water fraction at 3T and 7T were compared, they showed a good correlation (R2≥ 0.88; p < 0.001) with a larger myelin water fraction at 7T. The proposed method also opens the possibility of high resolution (isotropic 1.5 mm resolution) myelin water mapping at 7T.

Improvement of reproducibility in quantitative susceptibility mapping (QSM) and transverse relaxation rates ( R2* ) after physiological noise correction.

BACKGROUND: Numerous studies have suggested that quantitative susceptibility mapping (QSM) and transverse relaxation rates ( R2* ) are useful to monitor neurological diseases. For clinical use of QSM and R2* , reproducibility is an important feature. However, respiration-induced local magnetic field variation makes artifacts in gradient echo-based images and reduces the reproducibility of QSM and R2* . PURPOSE: To investigate the improvement of reproducibility of QSM and R2* after the correction of respiration-induced field variation, and to assess the effect of varying types of the region of interest (ROI) analysis on reproducibility. STUDY TYPE: Reproducibility study. POPULATION: Ten controls. FIELD STRENGTH/SEQUENCE: 3T/multiecho gradient echo sequence. ASSESSMENT: Intrascan reproducibility of QSM and R2* was investigated in ROIs before and after the respiration correction. STATISTICAL TESTS: Reproducibility was obtained by the square of voxel-wise correlation coefficients between scans. A paired t-test was performed for comparison between before and after the respiration correction and between QSM and R2* . RESULTS: Based on the ROI analysis, reproducibility increased after the respiration correction. Reproducibility in the white matter (11.89% increased in QSM and 23.38% in R2* , P = 0.009 and 0.024, respectively) and deep gray matter (5.50% increased in QSM and 13.96% in R2* , P = 0.024 and 0.019, respectively) increased significantly after the respiration correction. Reproducibility of R2* was higher than that of QSM in the whole brain and cortical gray matter, while QSM maps showed higher reproducibility than R2* in the white matter and deep gray matter. DATA CONCLUSION: Respiration-induced error correction significantly improved reproducibility in QSM and R2* mapping. QSM and R2* mapping showed a different level of reproducibility depending on the types of ROI analysis. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018.

Evaluation of Normal-Appearing White Matter in Multiple Sclerosis Using Direct Visualization of Short Transverse Relaxation Time Component (ViSTa) Myelin Water Imaging and Gradient Echo and Spin Echo (GRASE) Myelin Water Imaging.

BACKGROUND: In multiple sclerosis (MS), not only lesions but also normal MRI-appearing white matter (NAWM) may undergo demyelination. PURPOSE: To demonstrate the detection of NAWM demyelination using direct visualization of short transverse relaxation time component myelin water imaging (ViSTa-MWI) and to compare the results with those of conventional gradient echo and spin echo (GRASE)-MWI. STUDY TYPE: Control/cohort. POPULATION: Twenty-five MS patients and 18 healthy controls (HC). FIELD STRENGTH/SEQUENCE: 3T/ViSTa and GRASE-MWI. ASSESSMENT: Using ViSTa and GRASE-MWI, myelin water fraction (MWF) of NAWM or normal WM was compared between MS (all patients or early-stage MS patients) and HC. The comparison was performed for a global WM mask and five regional WM masks. STATISTICAL TESTS: A general linear model was applied for the comparison. A statistical power and a minimum sample size for the significant difference were obtained. Spearman's correlation coefficient was calculated between MWF and clinical measures and between ViSTa-MWF and GRASE-MWF for the global WM mask. RESULTS: MWFs of ViSTa were significantly lower in the MS patients than those in the HC in all masks (P < 0.001). GRASE-MWI results revealed reduced MWFs only in global WM, genu, and optic radiation. ViSTa-MWI had higher statistical powers than that of GRASE-MWI (power: ViSTa = 99.2 ± 1.6% and GRASE = 75.5 ± 31.0%; sample size: ViSTa = 18 ± 9 and GRASE = 78 ± 75). In early-stage MS, MWFs of ViSTa were significantly lower than those of the HC in all masks except for centrum semiovale; however, MWFs of GRASE MWI were significantly lower only in optic radiation. Disease duration was correlated with both MWIs (ViSTa; r = -0.437 and GRASE; r = -0.445). ViSTa and GRASE MWFs were significantly correlated in the HC (r = 0.664) and MS (r = 0.768). DATA CONCLUSION: ViSTa-MWI may detect a reduction of MWF in NAWM of MS. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:1091-1098.

Mechanisms of T2 * anisotropy and gradient echo myelin water imaging.

In MRI, structurally aligned molecular or micro-organization (e.g. axonal fibers) can be a source of substantial signal variations that depend on the structural orientation and the applied magnetic field. This signal anisotropy gives us a unique opportunity to explore information that exists at a resolution several orders of magnitude smaller than that of typical MRI. In this review, one of the signal anisotropies, T2 * anisotropy in white matter, and a related imaging method, gradient echo myelin water imaging (GRE-MWI), are explored. The T2 * anisotropy has been attributed to isotropic and anisotropic magnetic susceptibility of myelin and compartmentalized microstructure of white matter fibers (i.e. axonal, myelin, and extracellular space). The susceptibility and microstructure create magnetic frequency shifts that change with the relative orientation of the fiber and the main magnetic field, generating the T2 * anisotropy. The resulting multi-component magnitude decay and nonlinear phase evolution have been utilized for GRE-MWI, assisting in resolving the signal fraction of the multiple compartments in white matter. The GRE-MWI method has been further improved by signal compensation techniques including physiological noise compensation schemes. The T2 * anisotropy and GRE-MWI provide microstructural information on a voxel (e.g. fiber orientation and tissue composition), and may serve as sensitive biomarkers for microstructural changes in the brain. Copyright © 2016 John Wiley & Sons, Ltd.

Comparison of myelin water fraction values in periventricular white matter lesions between multiple sclerosis and neuromyelitis optica spectrum disorder.

Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are inflammatory autoimmune diseases of the central nervous system. We hypothesized that the degree of demyelination within lesions in MS and NMOSD would differ as the pathophysiology of the two diseases do. We used myelin water imaging to compare the myelin water fraction (MWF) in 106 periventricular white matter (PVWM) lesions in 27 MS patients and 51 PVWM lesions in 20 NMOSD patients. The MWF was significantly reduced in the MS compared with the NMOSD lesions, suggesting that myelin loss was more severe in MS than in NMOSD.

Deep learning prediction of steep and flat corneal curvature using fundus photography in post-COVID telemedicine era.

Recently, fundus photography (FP) is being increasingly used. Corneal curvature is an essential factor in refractive errors and is associated with several pathological corneal conditions. As FP-based examination systems have already been widely distributed, it would be helpful for telemedicine to extract information such as corneal curvature using FP. This study aims to develop a deep learning model based on FP for corneal curvature prediction by categorizing corneas into steep, regular, and flat groups. The EfficientNetB0 architecture with transfer learning was used to learn FP patterns to predict flat, regular, and steep corneas. In validation, the model achieved a multiclass accuracy of 0.727, a Matthews correlation coefficient of 0.519, and an unweighted Cohen's κ of 0.590. The areas under the receiver operating characteristic curves for binary prediction of flat and steep corneas were 0.863 and 0.848, respectively. The optic nerve and its peripheral areas were the main focus of the model. The developed algorithm shows that FP can potentially be used as an imaging modality to estimate corneal curvature in the post-COVID-19 era, whereby patients may benefit from the detection of abnormal corneal curvatures using FP in the telemedicine setting.

Effects of 60 Hz magnetic fields on teenagers and adults.

BACKGROUND: As use of electrical devices has increased, social concerns about the possible effects of 60 Hz electromagnetic fields on human health have increased. Accordingly, the number of people who complain of various symptoms such as headache and insomnia has risen. Many previous studies of the effects of extremely low frequency (ELF) magnetic field exposure on children have focused on the occurrence of childhood leukaemia and central nervous system cancers. However, very few provocation studies have examined the health effects of ELF magnetic fields on teenagers. METHODS: In this double-blind study, we simultaneously investigated physiological changes (heart rate, respiration rate, and heart rate variability), subjective symptoms, and magnetic field perception to determine the reliable effects of 60 Hz 12.5 µT magnetic fields on teenagers. Two volunteer groups of 30 adults and 30 teenagers were tested with exposure to sham and real magnetic fields for 32 min. RESULTS: ELF magnetic field exposure did not have any effects on the physiological parameters or eight subjective symptoms in either group. Neither group correctly perceived the magnetic fields. CONCLUSIONS: Physiological data were analysed, subjective symptoms surveyed, and the percentages of those who believed they were being exposed were measured. No effects were observed in adults or teenagers resulting from 32 min of 60 Hz 12.5 µT magnetic field exposure.

Effects of radiation emitted by WCDMA mobile phones on electromagnetic hypersensitive subjects.

BACKGROUND: With the use of the third generation (3 G) mobile phones on the rise, social concerns have arisen concerning the possible health effects of radio frequency-electromagnetic fields (RF-EMFs) emitted by wideband code division multiple access (WCDMA) mobile phones in humans. The number of people with self-reported electromagnetic hypersensitivity (EHS), who complain of various subjective symptoms such as headache, dizziness and fatigue, has also increased. However, the origins of EHS remain unclear. METHODS: In this double-blind study, two volunteer groups of 17 EHS and 20 non-EHS subjects were simultaneously investigated for physiological changes (heart rate, heart rate variability, and respiration rate), eight subjective symptoms, and perception of RF-EMFs during real and sham exposure sessions. Experiments were conducted using a dummy phone containing a WCDMA module (average power, 24 dBm at 1950 MHz; specific absorption rate, 1.57 W/kg) within a headset placed on the head for 32 min. RESULTS: WCDMA RF-EMFs generated no physiological changes or subjective symptoms in either group. There was no evidence that EHS subjects perceived RF-EMFs better than non-EHS subjects. CONCLUSIONS: Considering the analyzed physiological data, the subjective symptoms surveyed, and the percentages of those who believed they were being exposed, 32 min of RF radiation emitted by WCDMA mobile phones demonstrated no effects in either EHS or non-EHS subjects.

Black Line Sign in Focal Cortical Dysplasia IIB: A 7T MRI and Electroclinicopathologic Study.

BACKGROUND AND OBJECTIVES: We aim to provide detailed imaging-electroclinicopathologic characterization of the black line sign, a novel MRI marker for focal cortical dysplasia (FCD) IIB. METHODS: 7T T2*-weighted gradient-echo (T2*w-GRE) images were retrospectively reviewed in a consecutive cohort of patients with medically intractable epilepsy with pathology-proven FCD II, for the occurrence of the black line sign. We examined the overlap between the black line region and the seizure-onset zone (SOZ) defined by intracranial EEG (ICEEG) and additionally assessed whether complete inclusion of the black line region in the surgical resection was associated with postoperative seizure freedom. The histopathologic specimen was aligned with the MRI to investigate the pathologic underpinning of the black line sign. Region-of-interest-based quantitative MRI (qMRI) analysis on the 7T T1 map was performed in the black line region, entire lesional gray matter (GM), and contralateral/ipsilateral normal gray and white matter (WM). RESULTS: We included 20 patients with FCD II (14 IIB and 6 IIA). The black line sign was identified in 12/14 (85.7%) of FCD IIB and 0/6 of FCD IIA on 7T T2*w-GRE. The black line region was highly concordant with the ICEEG-defined SOZ (5/7 complete and 2/7 partial overlap). Seizure freedom was seen in 8/8 patients whose black line region was completely included in the surgical resection; in the 2 patients whose resection did not completely include the black line region, both had recurring seizures. Inclusion of the black line region in the surgical resection was significantly associated with seizure freedom (p = 0.02). QMRI analyses showed that the T1 mean value of the black line region was significantly different from the WM (p < 0.001), but similar to the GM. Well-matched histopathologic slices in one case revealed accumulated dysmorphic neurons and balloon cells in the black line region. DISCUSSION: The black line sign may serve as a noninvasive marker for FCD IIB. Both MRI-pathology and qMRI analyses suggest that the black line region was an abnormal GM component within the FCD. Being highly concordant with ICEEG-defined SOZ and significantly associated with seizure freedom when included in resection, the black line sign may contribute to the planning of ICEEG/surgery of patients with medically intractable epilepsy with FCD IIB. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in individuals with intractable focal epilepsy undergoing resection who have a 7T MRI with adequate image quality, the presence of the black line sign may suggest FCD IIB, be concordant with SOZ from ICEEG, and be associated with more seizure freedom if fully included in resection.