Rapid pulmonary Xe ventilation MRI of discharged COVID-19 patients with zigzag sampling.

Purpose: To demonstrate the feasibility of zigzag sampling for 3D rapid hyperpolarized Xe ventilation MRI in human.

Methods: Zigzag sampling in one direction was combined with gradient-recalled echo sequence (GRE-zigzag-Y) to acquire hyperpolarized Xe ventilation images. Image quality was compared with a balanced SSFP (bSSFP) sequence with the same spatial resolution for 12 healthy volunteers (HVs).

Encoding Enhanced Complex CNN for Accurate and Highly Accelerated MRI.

Magnetic resonance imaging (MRI) using hyperpolarized noble gases provides a way to visualize the structure and function of human lung, but the long imaging time limits its broad research and clinical applications. Deep learning has demonstrated great potential for accelerating MRI by reconstructing images from undersampled data. However, most existing deep convolutional neural networks (CNN) directly apply square convolution to k-space data without considering the inherent properties of k-space sampling, limiting k-space learning efficiency and image reconstruction quality.

Complementation-reinforced network for integrated reconstruction and segmentation of pulmonary gas MRI with high acceleration.

Background: Hyperpolarized (HP) gas MRI enables the clear visualization of lung structure and function. Clinically relevant biomarkers, such as ventilated defect percentage (VDP) derived from this modality can quantify lung ventilation function. However, long imaging time leads to image quality degradation and causes discomfort to the patients.

Assessment of pulmonary morphometry using hyperpolarized Xe diffusion-weighted MRI with variable-sampling-ratio compressed sensing patterns.

Background: Hyperpolarized (HP) Xe multiple b-values diffusion-weighted magnetic resonance imaging (DW-MRI) has been widely used for quantifying pulmonary microstructural morphometry. However, the technique requires long acquisition times, making it hard to apply in patients with severe pulmonary diseases, who cannot sustain long breath holds.

Purpose: To develop and evaluate the technique of variable-sampling-ratio compressed sensing (VCS) patterns for accelerating HP Xe multiple b-values DW-MRI in humans.

Evaluation of injuries caused by coronavirus disease 2019 using multi-nuclei magnetic resonance imaging.

The ongoing pandemic of coronavirus disease 2019 (COVID-19) has been a great burden for the healthcare system in many countries because of its high transmissibility, severity, and fatality. Chest radiography and computed tomography (CT) play a vital role in the diagnosis, detection of complications, and prognostication of COVID-19. Additionally, magnetic resonance imaging (MRI), especially multi-nuclei MRI, is another important imaging technique for disease diagnosis because of its good soft tissue contrast and the ability to conduct structural and functional imaging, which has also been used to evaluate COVID-19-related organ injuries in previous studies.

A pilot study of function-based radiation therapy planning for lung cancer using hyperpolarized xenon-129 ventilation MRI.

Purpose: Radiation-induced lung injury (RILI) is a common side effect in patients with non-small cell lung cancer (NSCLC) treated with radiotherapy. Minimizing irradiation into highly functional areas of the lung may reduce the occurrence of RILI. The aim of this study is to evaluate the feasibility and utility of hyperpolarized xenon-129 magnetic resonance imaging (MRI), an imaging tool for evaluation of the pulmonary function, to guide radiotherapy planning.

Quantitative evaluation of lung injury caused by PM using hyperpolarized gas magnetic resonance.

Purpose: To demonstrate the feasibility of Xe MR in evaluating the pulmonary physiological changes caused by PM in animal models.

Methods: Six rats were treated with PM solution (16.2 mg/kg) by intratracheal instillation twice a week for 4 weeks, and another six rats treated with normal saline served as the control cohort.