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

Wang Y,Wang M,Liu B,Ding Z,She H,Du YP

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.

Topics

Journal Article

Ready to Sharpen Your Edge?

Join hundreds of your peers who rely on RadAI Slice. Get the essential weekly briefing that empowers you to navigate the future of radiology.

We respect your privacy. Unsubscribe at any time.