The role of high-resolution ultrasound and MRI in the evaluation of peripheral nerves in the lower extremity.

Lower extremity peripheral neuropathy is a commonly encountered neurologic disorder, which can lead to chronic pain, functional disability, and decreased quality of life for a patient. As diagnostic imaging modalities have improved, imaging has started to play an integral role in the detection and characterization of peripheral nerve abnormalities by non-invasively and accurately identifying abnormal nerves as well as potential causes of neuropathy, which ultimately leads to precise and timely treatment. Ultrasound, which has high spatial resolution and can quickly and comfortably characterize peripheral nerves in real time along with associated denervation muscle atrophy, and magnetic resonance neurography, which provides excellent contrast resolution between nerves and other tissues and between pathologic and normal segments of peripheral nerves, in addition to assessing reversible and irreversible muscle denervation changes, are the two mainstay imaging modalities used in peripheral nerve assessment.

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.

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.

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.

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.