MOCOnet: Robust Motion Correction of Cardiovascular Magnetic Resonance T1 Mapping Using Convolutional Neural Networks

Background: Quantitative cardiovascular magnetic resonance (CMR) T1 mapping has shown promise for advanced tissue characterisation in routine clinical practise. However, T1 mapping is prone to motion artefacts, which affects its robustness and clinical interpretation. Current methods for motion correction on T1 mapping are model-driven with no guarantee on generalisability, limiting its widespread use. In contrast, emerging data-driven deep learning approaches have shown good performance in general image registration tasks. We propose MOCOnet, a convolutional neural network solution, for generalisable motion artefact correction in T1 maps.Methods: The network architecture employs U-Net for producing distance vector fields and utilises warping layers to apply deformation to the feature maps in a coarse-to-fine manner. Using the UK Biobank imaging dataset scanned at 1.5T, MOCOnet was trained on 1,536 mid-ventricular T1 maps (acquired using the ShMOLLI method) with motion artefacts, generated by a customised deformation procedure, and tested on a different set of 200 samples with a diverse range of motion. MOCOnet was compared to a well-validated baseline multi-modal image registration method. Motion reduction was visually assessed by 3 human experts, with motion scores ranging from 0% (strictly no motion) to 100% (very severe motion).Results: MOCOnet achieved fast image registration (<1 second per T1 map) and successfully suppressed a wide range of motion artefacts. MOCOnet significantly reduced motion scores from 37.1±21.5 to 13.3±10.5 (p < 0.001), whereas the baseline method reduced it to 15.8±15.6 (p < 0.001). MOCOnet was significantly better than the baseline method in suppressing motion artefacts and more consistently (p = 0.007).Conclusion: MOCOnet demonstrated significantly better motion correction performance compared to a traditional image registration approach. Salvaging data affected by motion with robustness and in a time-efficient manner may enable better image quality and reliable images for immediate clinical interpretation.

A Robust Multi-Channel EMG System for Lower Back and Abdominal Muscles Training

EMG is an established method to acquire the action potentials of contracted muscles. Although commercial EMG systems are available and it is one of the most researched biosignals, it has never become widely used in rehabilitation or fitness training monitoring. The reasons are technical challenges of wearable EMG systems regarding electrode placement, motion artefacts and the complex connectivity of multi-channel EMG measurements. We address this problem for the lower back and abdominal musculature, through a novel dry electrodes belt, multi-channel high density EMG circuitry and problem-specific signal processing. The subject can easily strap the dry electrodes belt around himself which provides 16 EMG channels. Interferences from the ECG and motion artefacts are reduced by a stationary wavelet decomposition. Afterwards, an inter-channel filter is applied to increase the robustness of the signals. Subject measurements during different kinds of typical abdominal and lower back training exercises were performed wearing the novel dry electrodes belt. The results show the possibility of robust EMG measurements from the lower back and abdominal muscles by utilizing the gathered redundancy, appropriately. The additional information obtained via the multi-channel EMG circuitry and spatial oversampling can be used to address current problems of EMG applications. It combines the advantages of robustness and the capability of using comfortable dry electrodes. Therefore, the proposed measurement method for acquiring spatial information about the muscle contractions from the lower trunk can be used for rehabilitation or fitness training monitoring.

The Promising Role of a Superb Microvascular Imaging Technique in the Evaluation of Raynaud’s Syndrome in Systemic Sclerosis: Theory and Practical Challenges

In recent years, a novel Doppler ultrasonography (US) modality—superb microvascular imaging (SMI)—has been presented as a reliable method to evaluate small vessel blood flow with minimised motion artefacts. In this review, we present the challenges of incorporating SMI in daily practice with detailed and comparable US images of a fingertip. The main focus of this paper is the discussion of all tested US techniques, artefacts, and practical challenges for evaluating Raynaud’s syndrome in systemic sclerosis. Despite a few reports on SMI use in assessing nailfold capillaries, there is still a need for more evidence of its value and possibilities for its standardisation.

Incorporating outlier information into diffusion MR tractogram filtering for robust structural brain connectivity and microstructural analyses

The white matter structures of the human brain can be represented via diffusion tractography. Unfortunately, tractography is prone to find false-positive streamlines causing a severe decline in its specificity and limiting its feasibility in accurate structural brain connectivity analyses. Filtering algorithms have been proposed to reduce the number of invalid streamlines but the currently available filtering algorithms are not suitable to process data that contains motion artefacts that are typical in clinical research. We augmented the Convex Optimization Modelling for Microstructure Informed Tractography (COMMIT) filtering algorithm to adjust for signal drop-out artifacts due to subject motion present in diffusion-weighted images. We demonstrate with comprehensive Monte-Carlo whole brain simulations and in vivo infant data that our robust algorithm is capable to properly filter tractography reconstructions despite these artefacts. We evaluated the results using parametric and non-parametric statistics and our results demonstrate that if not accounted for, motion artefacts can have severe adverse effect in the human brain structural connectivity analyses as well as in microstructural property mappings. In conclusion, the usage of robust filtering methods to mitigate motion related errors in tractogram filtering is highly beneficial especially in clinical studies with uncooperative patient groups such as infants. With our presented robust augmentation and open-source implementation, robust tractogram filtering is readily available.

T2*-weighted MRI produces viable fetal “Black-Bone” contrast with significant benefits when compared to current sequences

Objectives: Fetal “black bone” MRI could be useful in the diagnosis of various skeletal conditions during pregnancy without exposure to ionising radiation. Previously suggested Susceptibility-Weighted Imaging (SWI) is not available in the suggested form on all scanners leading to long imaging times that are susceptible to motion artefacts. We aimed to assess if an optimised T2*-weighted GRE sequence can provide viable “black bone” contrast and compared it to other sequences in the literature. Methods: A retrospective study was conducted on 17 patients who underwent fetal MRI. Patients were imaged with an optimised T2*-weighted GRE sequence, as well as at least one other “black-bone” sequence. Image quality was scored by four blinded observers on a five-point scale. Results: The T2*-weighted GRE sequence offered adequate to excellent image quality in 63% of cases and scored consistently higher than the three other comparison sequences when comparing images from the same patient. Image quality was found to be dependent on gestational age with good image quality achieved on almost all patients after 26 weeks. Conclusions: T2*-weighted GRE imaging can provide adequate fetal “black bone” contrast and performs at least as well as other sequences in the literature due to good bone to soft tissue contrast and minimal motion artefacts. Advances in knowledge: T2*-weighted fetal “black-bone” imaging can provide excellent bone to soft tissue contrast without using ionising radiation. It is as good as other “black bone” sequences and may be simpler and more widely implemented, with less motion artefacts.

Fast 3 T nigral hyperintensity magnetic resonance imaging in Parkinson’s disease

The absence of nigral hyperintensity is a promising MR marker for Parkinson’s disease (PD), but its small size imposes limitations on its routine use. Our aim was to compare Multi Echo Data Image Combination (MEDIC), segmented echo-planar imaging (EPISEG) and fluid-attenuated inversion recovery (FLAIR) sequences, as well as both magnitude (MAG) and susceptibility-weighted imaging (SWI) reconstructions of single-echo gradient echo for nigral hyperintensity imaging. Twenty-five healthy and twenty PD subjects were included. Sensitivity to motion artefacts, confidence of the radiologist in interpretation, rate of nondiagnostic scans and diagnostic accuracy were assessed. EPISEG was less motion-sensitive than MEDIC, MAG, and SWI, while FLAIR was less motion-sensitive than MAG and SWI. The reviewers were more confident when using EPISEG compared to any other techniques and MEDIC was superior to FLAIR. The proportions of nondiagnostic scans were lower for EPISEG than for other sequences. The best diagnostic performance was achieved for EPISEG (sensitivity = 65%, specificity = 96%). Using EPISEG, the absence of nigral hyperintensity in PD was associated with higher Hoehn-Yahr stage and MDS-UPDRS II + III. Nigral hyperintensity may be intact at the very early stages of PD. The promising properties of EPISEG may help the transfer of nigral hyperintensity imaging into daily clinical practice.

Acceptance and Image Quality of High-Resolution Peripheral Quantitative Computed Tomography of the Metacarpophalangeal Joints in Rheumatoid Arthritis.

Objective: To investigate the acceptance of the high-resolution peripheral quantitative computed tomography (HR-pQCT) in rheumatoid arthritis (RA). The second objective was to investigate the motion artefacts of the metacarpophalangeal (MCP) joints with two different custom-made positioning devices. Methods: Fifty patients with established RA had their MCP joints scanned by HR-pQCT with two different custom-made positioning devices and examined by conventional X-ray. Afterwards, the patients answered a questionnaire of imaging experience. The comparability of the erosion measures was investigated between the two different custom-made positioning devices by Bland-Altman plot, and intrareader repeatability by intraclass correlation coefficient. The motion artefacts were graded for each acquisition, and intrareader repeatability was investigated by Cohen's kappa coefficient.Results: Forty percent of the patients preferred HR-pQCT imaging, only 6% preferred conventional X-ray. Seventy-four percent found it difficult to keep their fingers steady during the scan. Fifty percent of the patients reported the inflatable immobilization device helped to keep their fingers steady while only 6% reported that it impaired their ability to do so. However, this difference was not reflected in the visual grading, as motion artefacts were sparse, and no clinically relevant difference could be observed. The intrareader repeatability and comparability for the erosion measures were excellent.Conclusion: The high acceptance among patients adds to the feasibility of HR-pQCT imaging of MCP joints in patients with RA. The inflatable immobilization device did not reduce motion-induced image degradation, as the overall visual grading for motion artefacts was low for imaging of the MCP joints in both acquisitions.