Validation of daily 0.35 T diffusion-weighted MRI for MRI-guided glioblastoma radiotherapy.

BACKGROUND: MRI-Linac systems enable daily diffusion-weighed imaging (DWI) MRI scans for assessing glioblastoma tumor changes with radiotherapy treatment. PURPOSE: Our study assessed the image quality of echoplanar imaging (EPI)-DWI scans compared with turbo spin echo (TSE)-DWI scans at 0.35 Tesla (T) and compared the apparent diffusion coefficient (ADC) values and distortion of EPI-DWI on 0.35 T MRI-Linac compared to high-field diagnostic MRI scanners. METHODS: The calibrated National Institute of Standards and Technology (NIST)/Quantitative Imaging Biomarkers Alliance (QIBA) Diffusion Phantom was scanned on a 0.35 T MRI-Linac, and 1.5 T and 3 T MRI with EPI-DWI. Five patients were scanned on a 0.35 T MRI-Linac with a TSE-DWI sequence, and five other patients were scanned with EPI-DWI on a 0.35 T MRI-Linac and a 3 T MRI. The quality of images was compared between the TSE-DWI and EPI-DWI on the 0.35 T MRI-Linac assessing signal-to-noise ratios and presence of artifacts. EPI-DWI ADC values and distortion magnitude were measured and compared between 0.35 T MRI-Linac and high-field MRI for both phantom and patient studies. RESULTS: The average ADC differences between EPI-DWI acquired on the 0.35 T MRI-Linac, 1.5 T and 3 T MRI scanners and published references in the phantom study were 1.7%, 0.4% and 1.0%, respectively. Comparing the ADC values based on EPI-DWI in glioblastoma tumors, there was a 3.36% difference between 0.35 and 3 T measurements. Susceptibility-induced distortions in the EPI-DWI phantoms were 0.46 ± 1.51 mm for 0.35 MRI-Linac, 0.98 ± 0.51 mm for 1.5 T MRI and 1.14 ± 1.88 mm for 3 T MRI; for patients -0.47 ± 0.78 mm for 0.35 T and 1.73 ± 2.11 mm for 3 T MRIs. The mean deformable registration distortion for a phantom was 1.1 ± 0.22 mm, 3.5 ± 0.39 mm and 4.7 ± 0.37 mm for the 0.35 T MRI-Linac, 1.5 T MRI, and 3 T MRI scanners, respectively; for patients this distortion was -0.46 ± 0.57 mm for 0.35 T and 4.2 ± 0.41 mm for 3 T. EPI-DWI 0.35 T MRI-Linac images showed higher SNR and lack of artifacts compared with TSE-DWI, especially at higher b-values up to 1000 s/mm2. CONCLUSION: EPI-DWI on a 0.35 T MRI-Linac showed superior image quality compared with TSE-DWI, minor and less distortions than high-field diagnostic scanners, and comparable ADC values in phantoms and glioblastoma tumors. EPI-DWI should be investigated on the 0.35 T MRI-Linac for prediction of early response in patients with glioblastoma.

Implementation and evaluation of a dynamic contrast-enhanced MR perfusion protocol for glioblastoma using a 0.35 T MRI-Linac system.

PURPOSE: MRI-linear accelerator (MRI-Linac) systems allow for daily tracking of MRI changes during radiotherapy (RT). Since one common MRI-Linac operates at 0.35 T, there are efforts towards developing protocols at that field strength. In this study we demonstrate the implementation of a post-contrast 3DT1-weighted (3D-T1w) and dynamic contrast-enhancement (DCE) protocol to assess glioblastoma response to RT using a 0.35 T MRI-Linac. METHODS AND MATERIALS: The protocol implemented was used to acquire 3D-T1w and DCE data from a flow phantom and two patients with glioblastoma (a responder and a non-responder) who underwent RT on a 0.35 T MRI-Linac. The detection of post-contrast-enhanced volumes was evaluated by comparing the 3DT1w images from the 0.35 T MRI-Linac to images obtained using a 3 T scanner. The DCE data were tested temporally and spatially using data from a flow phantom and patients. Ktrans maps were derived from DCE at three time points (a week before treatment-Pre RT, four weeks through treatment-Mid RT, and three weeks after treatment-Post RT) and were validated with patients' treatment outcomes. RESULTS: The 3D-T1w contrast-enhancement volumes were visually and volumetrically similar between 0.35 T MRI-Linac and 3 T. DCE images showed temporal stability, and associated Ktrans maps were consistent with patient response to treatment. On average, Ktrans values showed a 54 % decrease and 8.6 % increase for a responder and non-responder respectively when Pre RT and Mid RT images were compared. CONCLUSION: Our findings support the feasibility of obtaining post-contrast 3D-T1w and DCE data from patients with glioblastoma using a 0.35 T MRI-Linac system.

A Deep Learning Approach for Automatic Segmentation during Daily MRI-Linac Radiotherapy of Glioblastoma.

Glioblastoma changes during chemoradiotherapy are inferred from high-field MRI before and after treatment but are rarely investigated during radiotherapy. The purpose of this study was to develop a deep learning network to automatically segment glioblastoma tumors on daily treatment set-up scans from the first glioblastoma patients treated on MRI-linac. Glioblastoma patients were prospectively imaged daily during chemoradiotherapy on 0.35T MRI-linac. Tumor and edema (tumor lesion) and resection cavity kinetics throughout the treatment were manually segmented on these daily MRI. Utilizing a convolutional neural network, an automatic segmentation deep learning network was built. A nine-fold cross-validation schema was used to train the network using 80:10:10 for training, validation, and testing. Thirty-six glioblastoma patients were imaged pre-treatment and 30 times during radiotherapy (n = 31 volumes, total of 930 MRIs). The average tumor lesion and resection cavity volumes were 94.56 ± 64.68 cc and 72.44 ± 35.08 cc, respectively. The average Dice similarity coefficient between manual and auto-segmentation for tumor lesion and resection cavity across all patients was 0.67 and 0.84, respectively. This is the first brain lesion segmentation network developed for MRI-linac. The network performed comparably to the only other published network for auto-segmentation of post-operative glioblastoma lesions. Segmented volumes can be utilized for adaptive radiotherapy and propagated across multiple MRI contrasts to create a prognostic model for glioblastoma based on multiparametric MRI.

Implementation and evaluation of a dynamic contrast enhanced MR perfusion protocol for glioblastoma using a 0.35T MRI-Linac system.

Purpose: MRI-linear accelerator (MRI-Linac) systems allow for daily tracking of MRI changes during radiotherapy (RT). Since one common MRI-Linac operates at 0.35T, there are efforts towards developing protocols at that field strength. In this study we demonstrate the implementation of a post-contrast 3DT1-weighted (3DT1w) and dynamic contrast enhancement (DCE) protocol to assess glioblastoma response to RT using a 0.35T MRI-Linac. Methods and materials: The protocol implemented was used to acquire 3DT1w and DCE data from a flow phantom and two patients with glioblastoma (a responder and a non-responder) who underwent RT on a 0.35T-MRI-Linac. The detection of post-contrast enhanced volumes was evaluated by comparing the 3DT1w images from the 0.35T-MRI-Linac to images obtained using a 3T-standalone scanner. The DCE data were tested temporally and spatially using data from the flow phantom and patients. Ktrans maps were derived from DCE at three time points (a week before treatment-Pre RT, four weeks through treatment-Mid RT, and three weeks after treatment-Post RT) and were validated with patients' treatment outcomes. Results: The 3D-T1 contrast enhancement volumes were visually and volumetrically similar (±0.6-3.6%) between 0.35T MRI-Linac and 3T. DCE images showed temporal stability, and associated Ktrans maps were consistent with patient response to treatment. On average, Ktrans values showed a 54% decrease and 8.6% increase for a responder and non-responder respectively when Pre RT and Mid RT images were compared. Conclusion: Our findings support the feasibility of obtaining post-contrast 3DT1w and DCE data from patients with glioblastoma using a 0.35T MRI-Linac system.

Simulated Adaptive Radiotherapy for Shrinking Glioblastoma Resection Cavities on a Hybrid MRI-Linear Accelerator.

During radiation therapy (RT) of glioblastoma, daily MRI with combination MRI-linear accelerator (MRI-Linac) systems has demonstrated significant anatomic changes, including evolving post-surgical cavity shrinkage. Cognitive function RT for brain tumors is correlated with radiation doses to healthy brain structures, especially the hippocampi. Therefore, this study investigates whether adaptive planning to the shrinking target could reduce normal brain RT dose with the goal of improving post-RT function. We evaluated 10 glioblastoma patients previously treated on a 0.35T MRI-Linac with a prescription of 60 Gy delivered in 30 fractions over six weeks without adaptation ("static plan") with concurrent temozolomide chemotherapy. Six weekly plans were created per patient. Reductions in the radiation dose to uninvolved hippocampi (maximum and mean) and brain (mean) were observed for weekly adaptive plans. The dose (Gy) to the hippocampi for static vs. weekly adaptive plans were, respectively: max 21 ± 13.7 vs. 15.2 ± 8.2 (p = 0.003) and mean 12.5 ± 6.7 vs. 8.4 ± 4.0 (p = 0.036). The mean brain dose was 20.6 ± 6.0 for static planning vs. 18.7 ± 6.8 for weekly adaptive planning (p = 0.005). Weekly adaptive re-planning has the potential to spare the brain and hippocampi from high-dose radiation, possibly reducing the neurocognitive side effects of RT for eligible patients.

Camera-based Prospective Motion Correction in Paediatric Epilepsy Patients Enables EEG-fMRI Localization Even in High-motion States.

BACKGROUND: EEG-fMRI is a useful additional test to localize the epileptogenic zone (EZ) particularly in MRI negative cases. However subject motion presents a particular challenge owing to its large effects on both MRI and EEG signal. Traditionally it is assumed that prospective motion correction (PMC) of fMRI precludes EEG artifact correction. METHODS: Children undergoing presurgical assessment at Great Ormond Street Hospital were included into the study. PMC of fMRI was done using a commercial system with a Moiré Phase Tracking marker and MR-compatible camera. For retrospective EEG correction both a standard and a motion educated EEG artefact correction (REEGMAS) were compared to each other. RESULTS: Ten children underwent simultaneous EEG-fMRI. Overall head movement was high (mean RMS velocity < 1.5 mm/s) and showed high inter- and intra-individual variability. Comparing motion measured by the PMC camera and the (uncorrected residual) motion detected by realignment of fMRI images, there was a five-fold reduction in motion from its prospective correction. Retrospective EEG correction using both standard approaches and REEGMAS allowed the visualization and identification of physiological noise and epileptiform discharges. Seven of 10 children had significant maps, which were concordant with the clinical EZ hypothesis in 6 of these 7. CONCLUSION: To our knowledge this is the first application of camera-based PMC for MRI in a pediatric clinical setting. Despite large amount of movement PMC in combination with retrospective EEG correction recovered data and obtained clinically meaningful results during high levels of subject motion. Practical limitations may currently limit the widespread use of this technology.

Sound-modulations of visual motion perception implicate the cortico-vestibular brain.

A widely used example of the intricate (yet poorly understood) intertwining of multisensory signals in the brain is the audiovisual bounce inducing effect (ABE). This effect presents two identical objects moving along the azimuth with uniform motion and towards opposite directions. The perceptual interpretation of the motion is ambiguous and is modulated if a transient (sound) is presented in coincidence with the point of overlap of the two objects' motion trajectories. This phenomenon has long been written-off to simple attentional or decision-making mechanisms, although the neurological underpinnings for the effect are not well understood. Using behavioural metrics concurrently with event-related fMRI, we show that sound-induced modulations of motion perception can be further modulated by changing motion dynamics of the visual targets. The phenomenon engages the posterior parietal cortex and the parieto-insular-vestibular cortical complex, with a close correspondence of activity in these regions with behaviour. These findings suggest that the insular cortex is engaged in deriving a probabilistic perceptual solution through the integration of multisensory data.

Case-based radiological anatomy instruction using cadaveric MRI imaging and delivered with extended reality web technology.

PURPOSE: Extended reality (XR) technology enhances learning in medical education. The purpose of this study was to develop and apply a case-based approach for teaching radiological anatomy utilizing XR technology for improved student exploration and engagement. METHODS: The workflow consisted of MRI scanning cadavers followed by radiological, pathological, and anatomical assessment, and finally case presentation based on XR visualizations and student interaction. Case information (Subject, History, and Physical Exam) was presented to student groups who generated and recorded hypotheses using Google Forms. RESULTS: Use of all components of the system was voluntary and a total of 74 students responded to the survey request (response rate = 95%). Assessment of the experience was conducted through a qualitative survey comprising four Likert scale questions (1-5, 1 lowest), three binary questions, and open-ended comments. Mean, standard deviation, and overall agreement (mean ± SD, OA) showed that students found MRI scans of cadavers to be helpful for dissections (4.14 ± 1.1, 74.3%) and provided an understanding of relevant anatomy (4.32 ± 0.9, 79.7%), while 78.4% of students used the DICOM viewer to visualize scans of cadavers. The difficulty of use was found to be average (2.90 ± 1.0, 23%). zSpace visualizations were used by 40.5% of students, generally agreeing that an understanding of spatial relationships improved as a result (3.60 ± 1.0, 43.2%). More case-based sessions were favored by 97.3% of students. CONCLUSIONS: Results suggest that cadaveric MRI radiological visualization and XR technology enhance understanding of case-based anatomical dissections and encourage student exploration and engagement.

Three dimensional radial echo planar imaging for functional MRI.

PURPOSE: To demonstrate a novel 3D radial echo planar imaging (3D REPI) sequence for flexible, rapid, and motion-robust sampling in fMRI. METHODS: The 3D REPI method expands on the recently described golden angle rotated EPI trajectory using radial batched internal navigator echoes (TURBINE) approach by exploiting the unused perpendicular direction in the EPI readout to form fast analogues of rotated stack of stars or spirals trajectories that cover all 3 dimensions of k-space. An iterative conjugate gradient algorithm with SENSE reconstruction and time-segmented non-uniform fast Fourier transform (FFT) was used for parallel imaging acceleration and to account for the effects of B0 inhomogeneity. The golden angle rotation allowed for sliding window reconstruction schemes to be applied in brain BOLD fMRI experiments. RESULTS: Combined whole brain visual and motor fMRI experiments were successfully carried out on a clinical 3T scanner at 2 mm isotropic and 1 × 1 × 2 mm3 resolutions using the 3D REPI design. Improved sampling characteristics and image quality were observed for twisted trajectories at the expense of prolonged readout times and off-resonance effects. The ability to correct for rigid motion correction was also demonstrated. CONCLUSIONS: 3D REPI presents a flexible approach for segmented volumetric fMRI with motion correction and high in-plane spatial resolutions. Improved BOLD fMRI brain activation maps were obtained using a sliding window reconstruction.

Multi-parametric MRI (mpMRI) for treatment response assessment of radiation therapy.

Magnetic resonance imaging (MRI) plays an important role in the modern radiation therapy (RT) workflow. In comparison with computed tomography (CT) imaging, which is the dominant imaging modality in RT, MRI possesses excellent soft-tissue contrast for radiographic evaluation. Based on quantitative models, MRI can be used to assess tissue functional and physiological information. With the developments of scanner design, acquisition strategy, advanced data analysis, and modeling, multiparametric MRI (mpMRI), a combination of morphologic and functional imaging modalities, has been increasingly adopted for disease detection, localization, and characterization. Integration of mpMRI techniques into RT enriches the opportunities to individualize RT. In particular, RT response assessment using mpMRI allows for accurate characterization of both tissue anatomical and biochemical changes to support decision-making in monotherapy of radiation treatment and/or systematic cancer management. In recent years, accumulating evidence have, indeed, demonstrated the potentials of mpMRI in RT response assessment regarding patient stratification, trial benchmarking, early treatment intervention, and outcome modeling. Clinical application of mpMRI for treatment response assessment in routine radiation oncology workflow, however, is more complex than implementing an additional imaging protocol; mpMRI requires additional focus on optimal study design, practice standardization, and unified statistical reporting strategy to realize its full potential in the context of RT. In this article, the mpMRI theories, including image mechanism, protocol design, and data analysis, will be reviewed with a focus on the radiation oncology field. Representative works will be discussed to demonstrate how mpMRI can be used for RT response assessment. Additionally, issues and limits of current works, as well as challenges and potential future research directions, will also be discussed.

Unified Retrospective EEG Motion Educated Artefact Suppression for EEG-fMRI to Suppress Magnetic Field Gradient Artefacts During Motion.

The data quality of simultaneously acquired electroencephalography and functional magnetic resonance imaging (EEG-fMRI) can be strongly affected by motion. Recent work has shown that the quality of fMRI data can be improved by using a Moiré-Phase-Tracker (MPT)-camera system for prospective motion correction. The use of the head position acquired by the MPT-camera-system has also been shown to correct motion-induced voltages, ballistocardiogram (BCG) and gradient artefact residuals separately. In this work we show the concept of an integrated framework based on the general linear model to provide a unified motion informed model of in-MRI artefacts. This model (retrospective EEG motion educated gradient artefact suppression, REEG-MEGAS) is capable of correcting voltage-induced, BCG and gradient artefact residuals of EEG data acquired simultaneously with prospective motion corrected fMRI. In our results, we have verified that applying REEG-MEGAS correction to EEG data acquired during subject motion improves the data quality in terms of motion induced voltages and also GA residuals in comparison to standard Artefact Averaging Subtraction and Retrospective EEG Motion Artefact Suppression. Besides that, we provide preliminary evidence that although adding more regressors to a model may slightly affect the power of physiological signals such as the alpha-rhythm, its application may increase the overall quality of a dataset, particularly when strongly affected by motion. This was verified by analysing the EEG traces, power spectra density and the topographic distribution from two healthy subjects. We also have verified that the correction by REEG-MEGAS improves higher frequency artefact correction by decreasing the power of Gradient Artefact harmonics. Our method showed promising results for decreasing the power of artefacts for frequencies up to 250 Hz. Additionally, REEG-MEGAS is a hybrid framework that can be implemented for real time prospective motion correction of EEG and fMRI data. Among other EEG-fMRI applications, the approach described here may benefit applications such as EEG-fMRI neurofeedback and brain computer interface, which strongly rely on the prospective acquisition and application of motion artefact removal.

MR-Guided Radiotherapy for Brain and Spine Tumors.

MRI is the standard modality to assess anatomy and response to treatment in brain and spine tumors given its superb anatomic soft tissue contrast (e.g., T1 and T2) and numerous additional intrinsic contrast mechanisms that can be used to investigate physiology (e.g., diffusion, perfusion, spectroscopy). As such, hybrid MRI and radiotherapy (RT) devices hold unique promise for Magnetic Resonance guided Radiation Therapy (MRgRT). In the brain, MRgRT provides daily visualizations of evolving tumors that are not seen with cone beam CT guidance and cannot be fully characterized with occasional standalone MRI scans. Significant evolving anatomic changes during radiotherapy can be observed in patients with glioblastoma during the 6-week fractionated MRIgRT course. In this review, a case of rapidly changing symptomatic tumor is demonstrated for possible therapy adaptation. For stereotactic body RT of the spine, MRgRT acquires clear isotropic images of tumor in relation to spinal cord, cerebral spinal fluid, and nearby moving organs at risk such as bowel. This visualization allows for setup reassurance and the possibility of adaptive radiotherapy based on anatomy in difficult cases. A review of the literature for MR relaxometry, diffusion, perfusion, and spectroscopy during RT is also presented. These techniques are known to correlate with physiologic changes in the tumor such as cellularity, necrosis, and metabolism, and serve as early biomarkers of chemotherapy and RT response correlating with patient survival. While physiologic tumor investigations during RT have been limited by the feasibility and cost of obtaining frequent standalone MRIs, MRIgRT systems have enabled daily and widespread physiologic measurements. We demonstrate an example case of a poorly responding tumor on the 0.35 T MRIgRT system with relaxometry and diffusion measured several times per week. Future studies must elucidate which changes in MR-based physiologic metrics and at which timepoints best predict patient outcomes. This will lead to early treatment intensification for tumors identified to have the worst physiologic responses during RT in efforts to improve glioblastoma survival.

Prospective motion correction of fMRI: Improving the quality of resting state data affected by large head motion.

The quality of functional MRI (fMRI) data is affected by head motion. It has been shown that fMRI data quality can be improved by prospectively updating the gradients and radio-frequency pulses in response to head motion during image acquisition by using an MR-compatible optical tracking system (prospective motion correction, or PMC). Recent studies showed that PMC improves the temporal Signal to Noise Ratio (tSNR) of resting state fMRI data (rs-fMRI) acquired from subjects not moving intentionally. Besides that, the time courses of Independent Components (ICs), resulting from Independent Component Analysis (ICA), were found to present significant temporal correlation with the motion parameters recorded by the camera. However, the benefits of applying PMC for improving the quality of rs-fMRI acquired under large head movements and its effects on resting state networks (RSN) and connectivity matrices are still unknown. In this study, subjects were instructed to cross their legs at will while rs-fMRI data with and without PMC were acquired, which generated head motion velocities ranging from 4 to 30 â€‹mm/s. We also acquired fMRI data without intentional motion. Independent component analysis of rs-fMRI was performed to evaluate IC maps and time courses of RSNs. We also calculated the temporal correlation among different brain regions and generated connectivity matrices for the different motion and PMC conditions. In our results we verified that the crossing leg movements reduced the tSNR of sessions without and with PMC by 45 and 20%, respectively, when compared to sessions without intentional movements. We have verified an interaction between head motion speed and PMC status, showing stronger attenuation of tSNR for acquisitions without PMC than for those with PMC. Additionally, the spatial definition of major RSNs, such as default mode, visual, left and right central executive networks, was improved when PMC was enabled. Furthermore, motion altered IC-time courses by decreasing power at low frequencies and increasing power at higher frequencies (typically associated with artefacts). PMC partially reversed these alterations of the power spectra. Finally, we showed that PMC provides temporal correlation matrices for data acquired under motion conditions more comparable to those obtained by fMRI sessions where subjects were instructed not to move.

A circular echo planar sequence for fast volumetric fMRI.

PURPOSE: To demonstrate a circular EPI (CEPI) sequence as well as a generalized EPI reconstruction for fast fMRI with parallel imaging acceleration. METHODS: The CEPI acquisition was constructed using variable readout lengths and maximum ramp sampling as well as blipped-CAIPI z-gradient encoding for simultaneous multislice (SMS) and 3D volumetric imaging. A signal equation model with constant and linear phase terms was used to iteratively reconstruct images with low ghosting. Simulation, phantom, and human imaging experiments including audio/visual fMRI were performed at 3T using a 52-channel coil. RESULTS: Application of CEPI gradients with duration of 27 ms covering a 22-cm FOV at a 64 × 64 pixel resolution in SMS and 3D acquisitions resulted in images with comparable quality to those of standard Cartesian EPI. With parallel imaging techniques robust detection of BOLD fMRI activation with temporal sampling down to 275 ms was possible. The high temporal resolution enabled higher activation statistics at a penalty in increased noise and residual aliasing. The un-accelerated 3D acquisition showed large temporal instability compared with a standard 2D acquisition. CONCLUSION: Nonuniform sampling and generalized image reconstructions can be applied to EPI acquisitions including those with blipped-CAIPI z gradients. The same gradients can be used for either SMS or 3D acquisitions providing identical coverage.

Two-Dimensional Temporal Clustering Analysis for Patients with Epilepsy: Detecting Epilepsy-Related Information in EEG-fMRI Concordant, Discordant and Spike-Less Patients.

EEG acquired simultaneously with fMRI (EEG-fMRI) is a multimodal method that has shown promise in mapping the seizure onset zone in patients with focal epilepsy. However, there are many instances when this method is unsuccessful or not applicable, and other data driven fMRI methods may be utilized. One such method is the two-dimensional temporal clustering analysis (2dTCA). In this study we compared the classic EEG-fMRI and 2dTCA performance in mapping regions related to the seizure onset region in 18 focal epilepsy patients (12 presenting interictal epileptiform discharges (IEDs), during EEG-fMRI acquisition) with Engel I or II surgical outcome. Activation maps of both 2dTCA timing outputs (positive and negative histograms) and EEG detected IEDs were computed and compared to the region of epilepsy surgical resection. Patients were evaluated in three categories based on frequency of EEG detected spiking during the MRI. EEG-fMRI maps were concordant to the epilepsy region in 5/12 subjects, four with frequent IEDs on EEG. The 2dTCA was successful in mapping 13/18 patients including 3/6 with no IEDs detected (10/12 with IEDs detected). The epilepsy-related activities were successfully mapped by both methods in only 4/12 patients. This work suggests that the epilepsy-related information detected by each method may be different: while EEG-fMRI is more accurate in patients with high rather than lower numbers of EEG detected IEDs; 2dTCA can be useful in evaluating patients even when no concurrent EEG spikes are detected or EEG-fMRI is not effective. Therefore, our results support that 2dTCA might be an alternative for mapping epilepsy-related BOLD activity in negative EEG-fMRI (6/7 patients) and spike-less patients.

Towards motion insensitive EEG-fMRI: Correcting motion-induced voltages and gradient artefact instability in EEG using an fMRI prospective motion correction (PMC) system.

The simultaneous acquisition of electroencephalography and functional magnetic resonance imaging (EEG-fMRI) is a multimodal technique extensively applied for mapping the human brain. However, the quality of EEG data obtained within the MRI environment is strongly affected by subject motion due to the induction of voltages in addition to artefacts caused by the scanning gradients and the heartbeat. This has limited its application in populations such as paediatric patients or to study epileptic seizure onset. Recent work has used a Moiré-phase grating and a MR-compatible camera to prospectively update image acquisition and improve fMRI quality (prospective motion correction: PMC). In this study, we use this technology to retrospectively reduce the spurious voltages induced by motion in the EEG data acquired inside the MRI scanner, with and without fMRI acquisitions. This was achieved by modelling induced voltages from the tracking system motion parameters; position and angles, their first derivative (velocities) and the velocity squared. This model was used to remove the voltages related to the detected motion via a linear regression. Since EEG quality during fMRI relies on a temporally stable gradient artefact (GA) template (calculated from averaging EEG epochs matched to scan volume or slice acquisition), this was evaluated in sessions both with and without motion contamination, and with and without PMC. We demonstrate that our approach is capable of significantly reducing motion-related artefact with a magnitude of up to 10mm of translation, 6° of rotation and velocities of 50mm/s, while preserving physiological information. We also demonstrate that the EEG-GA variance is not increased by the gradient direction changes associated with PMC. Provided a scan slice-based GA template is used (rather than a scan volume GA template) we demonstrate that EEG variance during motion can be supressed towards levels found when subjects are still. In summary, we show that PMC can be used to dramatically improve EEG quality during large amplitude movements, while benefiting from previously reported improvements in fMRI quality, and does not affect EEG data quality in the absence of large amplitude movements.

A Comparison of Independent Component Analysis (ICA) of fMRI and Electrical Source Imaging (ESI) in Focal Epilepsy Reveals Misclassification Using a Classifier.

Interictal epileptiform discharges (IEDs) can produce haemodynamic responses that can be detected by electroencephalography-functional magnetic resonance imaging (EEG-fMRI) using different analysis methods such as the general linear model (GLM) of IEDs or independent component analysis (ICA). The IEDs can also be mapped by electrical source imaging (ESI) which has been demonstrated to be useful in presurgical evaluation in a high proportion of cases with focal IEDs. ICA advantageously does not require IEDs or a model of haemodynamic responses but its use in EEG-fMRI of epilepsy has been limited by its ability to separate and select epileptic components. Here, we evaluated the performance of a classifier that aims to filter all non-BOLD responses and we compared the spatial and temporal features of the selected independent components (ICs). The components selected by the classifier were compared to those components selected by a strong spatial correlation with ESI maps of IED sources. Both sets of ICs were subsequently compared to a temporal model derived from the convolution of the IEDs (derived from the simultaneously acquired EEG) with a standard haemodynamic response. Selected ICs were compared to the patients' clinical information in 13 patients with focal epilepsy. We found that the misclassified ICs clearly related to IED in 16/25 cases. We also found that the classifier failed predominantly due to the increased spectral range of fMRIs temporal responses to IEDs. In conclusion, we show that ICA can be an efficient approach to separate responses related to epilepsy but that contemporary classifiers need to be retrained for epilepsy data. Our findings indicate that, for ICA to contribute to the analysis of data without IEDs to improve its sensitivity, classification strategies based on data features other than IC time course frequency is required.

Imagem por Fontes Eletroencefalográficas - Uma Revisão Sistemática Sobre Sua Acurácia na Determinação da Zona Epileptogênica em Pacientes com Epilepsia Focal Refratária / EEG source imaging - a systematic review about its accuracy in defining the epileptogenic zone in patients with refractory focal epilepsy

O objetivo da avaliação pré-cirúrgica em pacientes com epilepsia refratária é delimitar a zona epileptogênica (ZE), área do encéfalo capaz de gerar crises e cuja ressecção tem o potencial para abolir ou reduzir as crises do paciente. Neste sentido, há um grande esforço no desenvolvimento e aprimoramento de técnicas diagnósticas não invasivas que possam localizar a ZE com precisão, buscando evitar ou diminuir a utilização de métodos invasivos, de custo e risco elevados. Uma técnica diagnóstica que tem recebido renovada atenção é a Imagem de Fontes Eletroencefalográficas (IFE). O uso dessa técnica se baseia no fato de que a localização da área do encéfalo geradora das descargas interictais (zona irritativa) guarda próxima relação com a ZE. Estudos recentes têm sugerido que a IFE tem um potencial para determinar a localização da ZE similar à magnetoencefalografia. Nesta revisão, analisamos estudos recentes utilizando a técnica na localização da ZE de pacientes com epilepsia refratária. Encontramos evidências de que a acurácia média do teste foi de 79%, bastante similar à acurácia da Imagem por Fontes Magnéticas reportada na literatura, que é de aproximadamente 77%.

The main goal of presurgical evaluation in patients with refractory epilepsy is to define the localization and extension of epileptogenic zone (EZ), the brain area responsible for generating seizures and whose resection has the potential to reduce or abolish epileptic seizures. Therefore, there has been an effort to develop diagnostic tests that can accurately localize the EZ non-invasively, avoiding invasive investigations that are risky and expensive. A diagnostic technique that has received renewed interest is electroencephalographic source imaging (ESI). This technique is based on the assumption that the irritative zone, the brain area that generates interictal EEG spikes, is spatially related with the EZ. Recent studies have shown that EEG has the potential to determine the localization of EZ similar to magnetoencephalography. In this review, we searched for studies reporting the accuracy of ESI on presurgical evaluation of patients with refractory epilepsy. We found that the accuracy of the test was 79% overall, similar to the accuracy of magnetic source imaging reported in the literature (77%).