Emerging imaging techniques in spondyloarthritis dual-energy computed tomography and new MRI sequences

Imaging of the sacroiliac joint plays a critical role in the classification of patients with axial spondyloarthritis. New imaging techniques are emerging, changing the way clinicians look at the sacroiliac joint. This article introduces the novel techniques in imaging of spondyloarthritis, including dual-energy computed tomography and new MRI sequences, with a focus on the imaging of bone marrow edema and erosions of the sacroiliac joint

Retrospective correction of Rigid and Non-Rigid MR motion artifacts using GANs

Motion artifacts are a primary source of magnetic resonance (MR) image quality deterioration with strong repercussions on diagnostic performance. Currently, MR motion correction is carried out either prospectively, with the help of motion tracking systems, or retrospectively by mainly utilizing computationally expensive iterative algorithms. In this paper, we utilize a new adversarial framework, titled MedGAN, for the joint retrospective correction of rigid and non-rigid motion artifacts in different body regions and without the need for a reference image. MedGAN utilizes a unique combination of non-adversarial losses and a new generator architecture to capture the textures and fine-detailed structures of the desired artifact-free MR images. Quantitative and qualitative comparisons with other adversarial techniques have illustrated the proposed model performance.Comment: 5 pages, 2 figures, under review for the IEEE International Symposium for Biomedical Image

An fMRI Compatible Touchscreen to Measure Hand Kinematics During a Complex Drawing Task

ACKNOWLEDGMENTS This study was funded by the Northwood Trust and the Aberdeen Biomedical Imaging Centre, University of Aberdeen. GDW is part of the SINASPE collaboration (Scottish Imaging Network - A Platform for Scientific Excellence www.SINAPSE.ac.uk). The authors thank Baljit Jagpal, Nichola Crouch, Beverly Maclennan and Katrina Klaasen for their help with running the experiment and Dawn Younie and Teresa Morris for their help with recruitment and scheduling. We also thank the participants for their generous participation.Peer reviewedPublisher PD

Diagnostic value of MRI of the sacroiliac joints in juvenile spondyloarthritis

Early diagnosis of spondyloarthritis (SpA) is becoming more important as new medical treatment options have become available to treat inflammation and delay progression of the disease. Increasingly, magnetic resonance imaging (MRI) of the sacroiliac joints is obtained for early detection of inflammatory changes, as it shows active inflammatory and structural lesions of sacroiliitis long before radiographic changes become evident. MRI of the sacroiliac joints in children is a useful tool for suspected juvenile spondyloarthritis (JSpA), even though it is not yet included in the current pediatric classification systems. Recognizing MRI features of pediatric sacroiliitis is a challenge. As most radiologists are not familiar with the normal MRI appearance of the pediatric sacroiliac joint, clear definitions are mandatory. Actually, the adult Assessment of Spondyloarthritis International Society (ASAS) definition for sacroiliitis needs some adaptations for children. A proposal for a possible pediatric-specific definition for active sacroiliitis on MRI is presented in this review. Furthermore, MRI without contrast administration is sufficient to identify bone marrow edema (BME), capsulitis, and retroarticular enthesitis as features of active sacroiliitis in JSpA. In selected cases, when high short tau inversion recovery (STIR) signal in the joint is the only finding, gadolinium-enhanced images may help to confirm the presence of synovitis. Lastly, we found a high correlation between pelvic enthesitis and sacroiliitis on MRI of the sacroiliac joints in children. As pelvic enthesitis indicates active inflammation, it may play a role in assessment of the inflammatory status. Therefore, it should be carefully sought and noted when examining MRI of the sacroiliac joints in children

Recurrent Fully Convolutional Neural Networks for Multi-slice MRI Cardiac Segmentation

In cardiac magnetic resonance imaging, fully-automatic segmentation of the heart enables precise structural and functional measurements to be taken, e.g. from short-axis MR images of the left-ventricle. In this work we propose a recurrent fully-convolutional network (RFCN) that learns image representations from the full stack of 2D slices and has the ability to leverage inter-slice spatial dependences through internal memory units. RFCN combines anatomical detection and segmentation into a single architecture that is trained end-to-end thus significantly reducing computational time, simplifying the segmentation pipeline, and potentially enabling real-time applications. We report on an investigation of RFCN using two datasets, including the publicly available MICCAI 2009 Challenge dataset. Comparisons have been carried out between fully convolutional networks and deep restricted Boltzmann machines, including a recurrent version that leverages inter-slice spatial correlation. Our studies suggest that RFCN produces state-of-the-art results and can substantially improve the delineation of contours near the apex of the heart.Comment: MICCAI Workshop RAMBO 201