Improving temporal resolution of pulmonary perfusion imaging in rats using the partially separable functions model

Area of Science:

• Medical Imaging
• Biophysics
• Cardiovascular Research

Background:

• Dynamic contrast-enhanced MRI (DCE-MRI) is crucial for assessing blood flow and perfusion, particularly in animal models.
• Challenges exist in applying DCE-MRI to small animals like rats due to technical difficulties.
• Existing methods like Interleaved Radial Imaging and Sliding window-keyhole (IRIS) have temporal resolution limitations.

Purpose of the Study:

• To develop an advanced DCE-MRI method for enhanced pulmonary perfusion imaging in small animals.
• To overcome the temporal resolution limitations of current DCE-MRI techniques.
• To improve the accuracy and feasibility of DCE-MRI in rat models.

Main Methods:

• A novel (k,t)-space sampling strategy based on partially separable functions (PSF) theory was developed.
• The method utilizes sparse sampling to acquire two distinct datasets: one for high temporal resolution and another for extended k-space coverage.
• PSF model's temporal basis functions and spatial variations are determined using the acquired datasets.

Main Results:

• The proposed PSF-based DCE-MRI method was validated through simulations and experimental studies.
• The technique successfully addressed the temporal averaging issues inherent in sliding window and keyhole methods.
• A superior temporal resolution of 32 milliseconds was achieved in the experimental study.

Conclusions:

• The novel PSF-based DCE-MRI method offers a significant advancement for pulmonary perfusion imaging in small animal research.
• This technique provides high temporal resolution, enabling more accurate assessment of dynamic physiological processes.
• The method demonstrates potential for overcoming previous limitations and improving DCE-MRI applications in preclinical studies.