Subject-specific acceleration of simultaneous quantification of blood flow and T<sub>1</sub> of the brain using a dual-flip-angle phase-contrast stack-of-stars sequence.
Authors
Affiliations (2)
Affiliations (2)
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China. Electronic address: [email protected].
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China.
Abstract
To develop a highly accelerated MRI technique for simultaneous quantification of blood flow and T<sub>1</sub> of the brain tissue. A dual-flip-angle phase-contrast stack-of-stars (DFA PC-SOS) sequence was developed for simultaneous acquisition of highly-undersampled data for the quantification of velocity of arterial blood and T<sub>1</sub> mapping of brain tissue. A deep learning-based algorithm, combining hybrid-feature hash encoding implicit neural representation with explicit sparse prior knowledge (INRESP), was used for image reconstruction. Magnitude and phase images were used for T<sub>1</sub> mapping and velocity measurements, respectively. The accuracy of the measurements was assessed in a quantitative phantom and six healthy volunteers. T<sub>1</sub> mapping obtained with DFA PC-SOS showed high correlation and consistency with reference measurements in phantom experiments (y = 0.916× + 4.71, R<sup>2</sup> = 0.9953, ICC = 0.9963). Blood flow measurements in healthy volunteers demonstrated strong correlation and consistency with reference values measured by SFA PC-SOS (y = 1.04×-0.187, R<sup>2</sup> = 0.9918, ICC = 0.9967). The proposed technique enabled an acceleration of 16× with high correlation and consistency with fully sampled data in volunteers (T<sub>1</sub>: y = 1.06× + 1.44, R<sup>2</sup> = 0.9815, ICC = 0.9818; flow: y = 1.01×-0.0525, R<sup>2</sup> = 0.9995, ICC = 0.9998). This study demonstrates the feasibility of 16-fold accelerated simultaneous acquisition for flow quantification and T<sub>1</sub> mapping in the brain. The proposed technique provides a rapid and comprehensive assessment of cerebrovascular diseases with both vascular hemodynamics and surrounding brain tissue characteristics, and has potential to be used in routine clinical applications.