(Monday, 7/13/2020) 4:30 PM - 5:30 PM [Eastern Time (GMT-4)]
Room: Track 1
Purpose:
To investigate the feasibility of motion-resolved simultaneous multi-parameter quantification using Magnetic Resonance Fingerprinting (MRF) technique for radiation therapy applications.
Methods:
The extended cardiac-torso (XCAT) phantom was used to generate abdominal T1, T2, and PD maps for MRF simulation. MRF acquisition with an inversion-recovery unbalanced steady-state free precession sequence was simulated using the extended phase graph algorithm. MRF images were simulated with different number of repetitions from 1 to 15 and the simulation was repeated 200 times for each number of repetitions. Three different methods were used to generate motion-resolved MRF images: 1) continuous acquisition without delay between MRF repetitions; 2) continuous acquisition with 5 seconds delay between MRF repetitions; 3) triggered acquisition with variable delay between MRF repetitions to allow the next acquisition to start at different respiration phase. Different image quality indexes were used for evaluation. Three healthy volunteers were recruited to test the feasibility of the selected acquisition method from simulation. MRI was performed using 3.0 Tesla MRI scanner.
Results:
Motion-resolved simultaneous multi-parametric maps using three different acquisition methods were successfully estimated from XCAT phantom. The optimal number of MRF repetition is 10. The overall and liver T1 value error, liver signal-to-noise ratio (SNR) in T1 and T2 maps, and tumor SNR from T1 maps from triggered method is significantly different compared to the other two methods (p-value < 0.05). The other image quality indexes have no significant difference among the three methods. Numerical simulations showed that the tumor volume error is 1.6 ± 2.7% and the average absolute difference in tumor motion amplitude is 0.3 ± 0.7 mm for the selected technique. The triggered method was successfully implemented on the healthy volunteers.
Conclusion:
We have successfully demonstrated the feasibility of a novel motion-resolved multi-parameter quantification technique using MRF in both simulation and volunteer studies.
Keywords
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Taxonomy
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