Musculoskeletal Manifestations of COVID-19: Currently Described Clinical Symptoms and Multimodality Imaging Findings.

COVID-19, the clinical syndrome produced by infection with SARS-CoV-2, can result in multisystem organ dysfunction, including respiratory failure and hypercoagulability, which can lead to critical illness and death. Musculoskeletal (MSK) manifestations of COVID-19 are common but have been relatively underreported, possibly because of the severity of manifestations in other organ systems. Additionally, patients who have undergone sedation and who are critically ill are often unable to alert clinicians of their MSK symptoms. Furthermore, some therapeutic measures such as medications and vaccinations can worsen existing MSK symptoms or cause additional symptoms. Symptoms may persist or occur months after the initial infection, known as post-COVID condition or long COVID. As the global experience with COVID-19 and the vaccination effort increases, certain patterns of MSK disease involving the bones, muscles, peripheral nerves, blood vessels, and joints have emerged, many of which are likely related to a hyperinflammatory host response, prothrombotic state, or therapeutic efforts rather than direct viral toxicity. Imaging findings for various COVID-19-related MSK pathologic conditions across a variety of modalities are being recognized, which can be helpful for diagnosis, treatment guidance, and follow-up. The online slide presentation from the RSNA Annual Meeting is available for this article. ©RSNA, 2022.

Evaluation of image quality of wideband single-shot late gadolinium-enhancement MRI in patients with a cardiac implantable electronic device.

INTRODUCTION: While wideband segmented, breath-hold late gadolinium-enhancement (LGE) cardiovascular magnetic resonance (CMR) has been shown to suppress image artifacts associated with cardiac-implanted electronic devices (CIEDs), it may produce image artifacts in patients with arrhythmia and/or dyspnea. Single-shot LGE is capable of suppressing said artifacts. We sought to compare the performance of wideband single-shot free-breathing LGE against the standard and wideband-segmented LGEs in CIED patients. METHODS AND RESULTS: We retrospectively identified all 54 consecutive patients (mean age: 61 ± 15 years; 31% females) with CIED who had undergone CMR with standard segmented, wideband segmented, and/or wideband single-shot LGE sequences as part of quality assurance for determining best clinical practice at 1.5 T. Two raters independently graded the conspicuity of myocardial scar or normal myocardium and the presence of device artifact level on a 5-point Likert scale (1: worst; 3: acceptable; 5: best). Summed visual score (SVS) was calculated as the sum of conspicuity and artifact scores (SVS ≥ 6 defined as diagnostically interpretable). Median conspicuity and artifact scores were significantly better for wideband single-shot LGE (F = 24.2, p < .001) and wideband-segmented LGE (F = 20.6, p < .001) compared to standard-segmented LGE. Among evaluated myocardial segments, 72% were deemed diagnostically interpretable-defined as SVS ≥ 6-for standard-segmented LGE, 89% were deemed diagnostically interpretable for wideband-segmented LGE, and 94% segments were deemed diagnostically interpretable for wideband single-shot LGE. CONCLUSIONS: Wideband single-shot LGE and wideband-segmented LGE produced similarly improved image quality compared to standard LGE.

Rapid Reconstruction of Four-dimensional MR Angiography of the Thoracic Aorta Using a Convolutional Neural Network.

PURPOSE: To implement an integrated reconstruction pipeline including a graphics processing unit (GPU)-based convolutional neural network (CNN) architecture and test whether it reconstructs four-dimensional non-Cartesian, non-contrast material-enhanced MR angiographic k-space data faster than a central processing unit (CPU)-based compressed sensing (CS) reconstruction pipeline, without significant losses in data fidelity, summed visual score (SVS), or arterial vessel-diameter measurements. MATERIALS AND METHODS: Raw k-space data of 24 patients (18 men and six women; mean age, 56.8 years ± 11.8 [standard deviation]) suspected of having thoracic aortic disease were used to evaluate the proposed reconstruction pipeline derived from an open-source three-dimensional CNN. For training, 4800 zero-filled images and the corresponding CS-reconstructed images from 10 patients were used as input-output pairs. For testing, 6720 zero-filled images from 14 different patients were used as inputs to a trained CNN. Metrics for evaluating the agreement between the CNN and CS images included reconstruction times, structural similarity index (SSIM) and normalized root-mean-square error (NRMSE), SVS (3 = nondiagnostic, 9 = clinically acceptable, 15 = excellent), and vessel diameters. RESULTS: The mean reconstruction time was 65 times and 69 times shorter for the CPU-based and GPU-based CNN pipelines (216.6 seconds ± 40.5 and 204.9 seconds ± 40.5), respectively, than for CS (14 152.3 seconds ± 1708.6) (P < .001). Compared with CS as practical ground truth, CNNs produced high data fidelity (SSIM = 0.94 ± 0.02, NRMSE = 2.8% ± 0.4) and not significantly different (P = .25) SVS and aortic diameters, except at one out of seven locations, where the percentage difference was only 3% (ie, clinically irrelevant). CONCLUSION: The proposed integrated reconstruction pipeline including a CNN architecture is capable of rapidly reconstructing time-resolved volumetric cardiovascular MRI k-space data, without a significant loss in data quality, thereby supporting clinical translation of said non-contrast-enhanced MR angiograms. Supplemental material is available for this article. © RSNA, 2020.

Accelerated, free-breathing, noncontrast, electrocardiograph-triggered, thoracic MR angiography with stack-of-stars k-space sampling and GRASP reconstruction.

PURPOSE: To develop an accelerated, free-breathing, noncontrast, electrocardiograph-triggered, thoracic MR angiography (NC-MRA) pulse sequence capable of achieving high spatial resolution at clinically acceptable scan time and test whether it produces clinically acceptable image quality in patients with suspected aortic disease. METHODS: We modified a "coronary" MRA pulse sequence to use a stack-of-stars k-space sampling pattern and combined it with golden-angle radial sparse parallel (GRASP reconstruction to enable self-navigation of respiratory motion and high data acceleration. The performance of the proposed NC-MRA was evaluated in 13 patients, where clinical standard contrast-enhanced MRA (CE-MRA) was used as control. For visual analysis, two readers graded the conspicuity of vessel lumen, artifacts, and noise level on a 5-point scale (overall score index = sum of three scores). The aortic diameters were measured at seven standardized locations. The mean visual scores, inter-observer variability, and vessel diameters were compared using appropriate statistical tests. RESULTS: The overall mean visual score index (12.1 ± 1.7 for CE-MRA versus 12.1 ± 1.0 for NC-MRA) scores were not significantly different (P > 0.16). The two readers' scores were significantly different for CE-MRA (P = 0.01) but not for NC-MRA (P = 0.21). The mean vessel diameters were not significantly different, except at the proximal aortic arch (P < 0.03). The mean diameters were strongly correlated (R2 ≥ 0.96) and in good agreement (absolute mean difference ≤ 0.01 cm and 95% confidence interval ≤ 0.62 cm). CONCLUSION: This study shows that the proposed NC-MRA produces clinically acceptable image quality in patients at high spatial resolution (1.5 mm × 1.5 mm × 1.5 mm) and clinically acceptable scan time (~6 min).