Refaat E Gabr1, Lingzhi Hu2, Xingxian Shou2, Yongquan Ye2, Weiguo Zhang2, and Ponnada A Narayana1
1Diagnostic and Interventional Imaging, University of Texas Health Science Center at Houston, Houston, TX, United States, 2UIH America Inc., Houston, TX, United States
Synopsis
We developed a multi-flip multi-spoiling
phase angle method for quantitative assessment of tissue parameters.
Application in phantom studies and in vivo knee imaging shows promising performance
for high resolution parameter mapping in clinically feasible scan time.
Introduction
Quantitative measurement of tissue parameters remains one
of the most active research areas in MRI.1–3 Imaging protocols to
quantify T1, T2, and other tissue parameters such as the macromolecular pool
fraction and exchange rates are often time-consuming or require special pulse
sequences not available on clinical scanners1. We investigated the
feasibility of quantitative imaging using a simple protocol based on
radiofrequency (RF)-spoiled gradient echo (SPGR) pulse sequence, commonly available
on MRI scanners.
The proposed protocol collects a set of gradient echo
acquisitions with variable flip angle and RF spoiling phase increment. Each
acquisition establishes a distinct steady state signal pathway with different
weighting of tissue parameters.3 Reconstruction is
achieved by signal modelling of these signal pathways. The short repetition
times allows the acquisition of high-resolution data within a clinically
feasible scan time. The feasibility of the proposed approach is demonstrated in
phantom and human knee imaging experiments. Methods
Imaging protocol. A total of 15 3D RF-spoiled
gradient echo acquisitions were acquired with TR/TE = 7/3 ms and all
combinations of three flip angles (10°, 20°, and 30°) and five RF spoiling
phase increments (0°, 45°, 117°, 120°, and 150°). Using this protocol, the NIST
phantom containing various spheres filled with solutions with a wide range of
T1 and T2 values4 was scanned on a 3T
scanner (uMR790, United Imaging Healthcare, Houston, TX) with FOV=256×256×180 mm3,
voxel dimensions=1x1x3 mm3. A sagittal 3D knee (FOV=256×255×120 mm3,
voxel dimensions=0.64x0.64x2 mm3) scan was acquired in a healthy
volunteer (M, 34yo) with the same acquisition parameters on a 1.5T scanner (uMR
570, UIH). Each 3D volume was acquired in 106.8 and 91.2 seconds in the phantom
and knee scans, respectively. For the knee scan, T1 and T2 maps were
additionally acquired using a multi flip angle (TR/TE=9.2/4.3 ms, FA=4, 9, 15, and 25 degrees) and 5-echo
CPMG (TR=1503 ms, ΔTE= 13.8 ms) sequences.
Image analysis. Dictionaries for a range of
tissue parameters were built using simulations based on the extended phase
graph method using the EPG-X toolbox5 employing two models:
(1) a single compartment model with a range of T1 and T2 values; and (2) a
two-compartment model with magnetization transfer (MT) effect. The simulated
parameters for the two-compartment model included different combinations of T1
and T2 values for the free water pool (T1f, T2f) and for the fraction of the
semi-solid pool (f) and exchange rate constant (k). Model fitting
was performed using Matlab (v2017b; MathWorks, Natick, MA). For the NIST phantom,
the T1 and T2 values were compared with the standard values of the T1- and T2-spheres.
Reference knee T1 and T2 maps were generated by fitting standard spoiled
gradient echo and spin echo signal equations. Regions of interest were manually
drawn in the cartilage and muscle regions. Results
In the NIST phantom, the estimated T1 and T2 values for the
T1- and T2-spheres show good agreement with the known values of the phantom, as
shown in Fig. 1. Fig. 2 shows representative images acquired with the proposed
protocol in the human knee. The reconstructed maps for T1f, T2f, f, and k
are shown in Fig. 3. ROI analysis of the cartilage / muscle yielded T1f = 718±135
/ 790±39 ms, T2f = 35.2±38.9 / 19.0±7.5 ms, f = 0.15±0.07 /
0.08±0.04,
and k = 8.8±3.6 / 10.4±3.4 s-1. The reference T1 and
T2 values for cartilage / muscle were 795±53 / 795±59 ms and 30.7±48.2 / 29.7±46.0
ms, respectively. The tissue parameters were comparable to reported values in
the literature.6–9Conclusion
The proposed approach allows high-resolution quantitative
mapping of the tissue parameters in a clinically acceptable scan time. A major feature
of the proposed method is the easy implementation on most MRI systems without
the need for programming the scanner. Our results demonstrated the feasibility
of single- and two-compartment modeling of the signal behavior using this
approach. Optimization of the acquisition schemes will be explored to obtain
higher efficiency and signal to noise ratio in tissue parameters. Acknowledgements
We thank Jian Xu for assistance in conducting the MRI
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