Dynamic pulmonary MRI using motion-state weighted motion-compensation (MostMoCo) reconstruction with ultrashort TE: A...

Area of Science:

• Medical Imaging
• Pulmonary MRI
• Image Reconstruction

Background:

• Free-breathing dynamic pulmonary MRI requires advanced techniques for high-quality imaging and accurate ventilation assessment.
• Existing methods like eXtra-Dimensional (XD) UTE and iterative motion-compensation (iMoCo) have limitations in image quality and functional quantification.

Purpose of the Study:

• To enhance structural image quality and improve ventilation quantification in free-breathing dynamic pulmonary MRI.
• To introduce and evaluate a novel motion-state weighted motion-compensation (MostMoCo) reconstruction algorithm for pulmonary MRI.

Main Methods:

• Utilized a 3D radial ultrashort TE (UTE) sequence with superior-inferior navigators for free-breathing data acquisition.
• Implemented motion-resolved reconstruction using eXtra-Dimensional (XD) UTE and developed a motion-state weighted motion-compensation (MostMoCo) algorithm.
• Compared MostMoCo-UTE with XD-UTE and iMoCo on porcine lung and human subjects.

Main Results:

• MostMoCo-UTE demonstrated superior peak Signal-to-Noise Ratio (SNR) and structural similarity compared to XD-UTE and iMoCo in porcine lung experiments.
• Human experiments showed higher apparent SNR and contrast-to-noise ratio with MostMoCo.
• MostMoCo reconstruction preserved temporal signal variations, reduced noise, and improved anatomical sharpness, leading to more accurate ventilation quantification.

Conclusions:

• The proposed MostMoCo-UTE technique significantly improves structural image quality and ventilation quantification in free-breathing pulmonary MRI.
• This method holds potential for clinical detection of structural and functional lung disorders.