EEG–fMRI of idiopathic and secondarily generalized epilepsies

We used simultaneous EEG and functional MRI (EEG–fMRI) to study generalized spike wave activity (GSW) in idiopathic and secondary generalized epilepsy (SGE). Recent studies have demonstrated thalamic and cortical fMRI signal changes in association with GSW in idiopathic generalized epilepsy (IGE). We report on a large cohort of patients that included both IGE and SGE, and give a functional interpretation of our findings. Forty-six patients with GSW were studied with EEG–fMRI; 30 with IGE and 16 with SGE. GSW-related BOLD signal changes were seen in 25 of 36 individual patients who had GSW during EEG–fMRI. This was seen in thalamus (60%) and symmetrically in frontal cortex (92%), parietal cortex (76%), and posterior cingulate cortex/precuneus (80%). Thalamic BOLD changes were predominantly positive and cortical changes predominantly negative. Group analysis showed a negative BOLD response in the cortex in the IGE group and to a lesser extent a positive response in thalamus. Thalamic activation was consistent with its known role in GSW, and its detection in individual cases with EEG–fMRI may in part be related to the number and duration of GSW epochs recorded. The spatial distribution of the cortical fMRI response to GSW in both IGE and SGE involved areas of association cortex that are most active during conscious rest. Reduction of activity in these regions during GSW is consistent with the clinical manifestation of absence seizures

PND-Net: Physics based Non-local Dual-domain Network for Metal Artifact Reduction

Metal artifacts caused by the presence of metallic implants tremendously degrade the reconstructed computed tomography (CT) image quality, affecting clinical diagnosis or reducing the accuracy of organ delineation and dose calculation in radiotherapy. Recently, deep learning methods in sinogram and image domains have been rapidly applied on metal artifact reduction (MAR) task. The supervised dual-domain methods perform well on synthesized data, while unsupervised methods with unpaired data are more generalized on clinical data. However, most existing methods intend to restore the corrupted sinogram within metal trace, which essentially remove beam hardening artifacts but ignore other components of metal artifacts, such as scatter, non-linear partial volume effect and noise. In this paper, we mathematically derive a physical property of metal artifacts which is verified via Monte Carlo (MC) simulation and propose a novel physics based non-local dual-domain network (PND-Net) for MAR in CT imaging. Specifically, we design a novel non-local sinogram decomposition network (NSD-Net) to acquire the weighted artifact component, and an image restoration network (IR-Net) is proposed to reduce the residual and secondary artifacts in the image domain. To facilitate the generalization and robustness of our method on clinical CT images, we employ a trainable fusion network (F-Net) in the artifact synthesis path to achieve unpaired learning. Furthermore, we design an internal consistency loss to ensure the integrity of anatomical structures in the image domain, and introduce the linear interpolation sinogram as prior knowledge to guide sinogram decomposition. Extensive experiments on simulation and clinical data demonstrate that our method outperforms the state-of-the-art MAR methods.Comment: 19 pages, 8 figure

Grey and White Matter Magnetisation Transfer Ratio Measurements in the Lumbosacral Enlargement: A Pilot In Vivo Study at 3T

Magnetisation transfer (MT) imaging of the central nervous system has provided further insight into the pathophysiology of neurological disease. However, the use of this method to study the lower spinal cord has been technically challenging, despite the important role of this region, not only for motor control of the lower limbs, but also for the neural control of lower urinary tract, sexual and bowel functions. In this study, the feasibility of obtaining reliable grey matter (GM) and white matter (WM) magnetisation transfer ratio (MTR) measurements within the lumbosacral enlargement (LSE) was investigated in ten healthy volunteers using a clinical 3T MRI system. The mean cross-sectional area of the LSE (LSE-CSA) and the mean GM area (LSE-GM-CSA) were first obtained by means of image segmentation and tissue-specific (i.e. WM and GM) MTR measurements within the LSE were subsequently obtained. The reproducibility of the segmentation method and MTR measurements was assessed from repeated measurements and their % coefficient of variation (%COV). Mean (± SD) LSE-CSA across 10 healthy subjects was 59.3 (± 8.4) mm2 and LSE-GM-CSA was 17.0 (± 3.1) mm2. The mean intra- and inter-rater % COV for measuring the LSE-CSA were 0.8% and 2.3%, respectively and for the LSE-GM-CSA were 3.8% and 5.4%, respectively. Mean (± SD) WM-MTR was 43.2 (± 4.4) and GM-MTR was 40.9 (± 4.3). The mean scan-rescan % COV for measuring WM-MTR was 4.6% and for GM-MTR was 3.8%. Using a paired t-test, a statistically significant difference was identified between WM-MTR and GM-MTR in the LSE (p<0.0001). This pilot study has shown that it is possible to obtain reliable tissue-specific MTR measurements within the LSE using a clinical MR system at 3T. The MTR acquisition and analysis protocol presented in this study can be used in future investigations of intrinsic spinal cord diseases that affect the LSE