Shraddha Pandey1,2, Arthur David Snider1, Wilfrido Moreno1, Harshan Ravi2, Ali Bilgin3, and Natarajan Raghunand2,4
1Electrical Engineering, University of South Florida, Tampa, FL, United States, 2Cancer Physiology, Moffitt Cancer Center, Tampa, FL, United States, 3Departments of Medical Imaging, Biomedical Engineering, and Electrical & Computer Engineering, University of Arizona, Tucson, AZ, United States, 4Department of Oncologic Sciences, University of South Florida, Tampa, FL, United States
1Electrical Engineering, University of South Florida, Tampa, FL, United States, 2Cancer Physiology, Moffitt Cancer Center, Tampa, FL, United States, 3Departments of Medical Imaging, Biomedical Engineering, and Electrical & Computer Engineering, University of Arizona, Tucson, AZ, United States, 4Department of Oncologic Sciences, University of South Florida, Tampa, FL, United States
A joint reconstruction framework is presented to concurrently reconstruct a series of complex MR images and their corresponding T1, T2 and T2* parameter maps. Tissue mapping and estimation of water and fat content within 4 objectively defined tissue types was possible using 18% k-space data.
Figure 1. k-space data
obtained from the scanner is undersampled using the cartesian sampling mask.
The Joint Reconstruction Algorithm is used to reconstruct the series of T1w
images and their parameter maps. The process is repeated to reconstruct
T2w/T2*w images and their parameter maps. Validation of the results is carried
out by identifying the tissue types like muscle, fluid, tumor and adipose and using the rules on T1 and T2 maps. The T2*w images are subjected [1]
to estimate PDFF, PDwF, & in the muscle, fluid, tumor and adipose tissue
type.
Figure 2. T1w
reconstructed images for 2 mouse slices with mask of ~27%, ~36% k-space
data are shown.The sampling masks are shown in col 1. The results
for the Repetition times (TR) 0.4s and 5s are shown in col 2 & 3 for mouse 1 and col 4 & 5 for mouse 2. The 5th
& 6th column shows the detailed version of the region
highlighted in the red box.The MI value is computed for 4 undersampling masks 18%, 27%, 36%, & 52% shown on x-axis. The y-axis shows the MI value when the ground truth |u| are compared to the reconstructed |u|. The mean MI and standard error of the mean (S.E.M) is calculated over n = 30 mouse slices.