A new approach for reproducible water fraction and T1 mapping across different qMRI protocols

2290 

Abstract Submission 

Eden Mama¹, Jose Marques², Aviv Mezer¹

¹Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel, ²Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, Gelderland

Eden Mama  
Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem
Jerusalem, Israel

Jose Marques  
Donders Institute for Brain, Cognition and Behaviour, Radboud University
Nijmegen, Gelderland

Aviv Mezer  
Edmond and Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem
Jerusalem, Israel

Quantitative MRI (qMRI) is highly valuable method to estimate the human brain microstructural changes during aging and disease. An important goal of qMRI field is to provide reliable multi-parametric brain maps¹, with T1 map being commonly used. Two main acquisition approaches to quantify T1 on clinical scanners are variable flip angle (VFA) and Magnetization Prepared with 2 Rapid Gradient Echoes (MP2RAGE), yet the agreement between these approaches was not determined. A potential benefit of VFA is that it also allows the extraction of proton density (PD) map², which is not often explicitly extracted using the MP2RAGE formalism or mentioned in the original publications^3,4. In the brain, normalized PD is used to estimate the water fraction (WF). In this work, we first examined the agreement between the T1 maps obtained from these two approaches. Second, we presented a pipeline to obtain PD and WF maps from the MP2RAGE protocol that agree well with the VFA's maps. Hence, this work obtains an additional qMRI map for the MP2RAGE approach which is in agreement with the VFA approach.

Data- In this work, we used 14 healthy individuals aged 26-75, who were scanned in both VFA and MP2RAGE protocols:
(i) VFA, Gradient echo sequence was acquired with the parameters TR=19 ms, five equally spaced TEs=3.34-14.02 ms, four different FA=4°,10°,20°,30°, T_Acquisition=~25 min, resolution=1mm isotropic.
(ii) MP2RAGE sequence was acquired with the parameters TR=5000 ms, TE=2.98 ms, TI= 700, 2500 ms, FA=4°,5°, T_Acquisition=~8 min, resolution=1mm isotropic.
(iii) We computed a B1 bias correction on the maps extracted from VFA protocol using mrQ software⁵. We used spin-echo inversion recovery images acquired with echo-planar imaging readout (SEIR-EPI). Parameters were TE=49 ms, TR=2920 ms, TI=200, 400, 1200, 2400 ms. The resolution was 2mm in-plane and slice thickness was 3mm.
T1 map- First we registered MP2RAGE maps to the VFA maps' space using FSL's FLIRT⁶. T1 and M0 were estimated using methods described before (for VFA see Ref. 5 and for MP2RAGE see Ref. 4).
Calculating PD and WF maps- We followed the algorithm in Mezer et al. work^2,5. We assumed that M0 = Coil Gain*PD considering a neglected T2* contribution when TE<3.34ms. We then estimated the coil gain bias and separated it from the PD contribution. For this we assumed a local linear relationship between 1/T1 and 1/PD values.
Next, we normalized the PD by the CSF values to estimate the WF map. First, we identified the CSF ROI using the FreeSurfer segmentation algorithm and eliminated any voxel with T1 outside the range of 3.7-4.7. Then, we calculated the linear trend between 1/PD and 1/T1 in the CSF. Last, we calculated a calibration value which determines that in pure water where T1 is equal to 4.3⁷, WF should be equal to 1, and calibrated the entire map.

First, we tested the correlation between T1 values of the VFA protocol and the MP2RAGE protocol. We found a strong correlation between the two maps. Next, we tested the correlations between PD maps. We found a similarly strong agreement in those maps. Normalization of PD maps to obtain WF from both protocols also showed a high correlation.

Our study suggests that maps extracted from VFA and MP2RAGE protocols can both provide similar qMRI values, highlighting the agreement between the two methods. Here, we found that by using the same postprocessing algorithm a great similarity can also be obtained for the PD and WF maps. WF map is valuable because it allows for more precise tissue characterization^5,8. Furthermore, a join modeling of the T1 and WF values has been proposed for calculating the tissue reflexivity⁹. Last, a great effort in the qMRI community is pointed to reliable values across scanner and protocol¹⁰, this work is adding an important benchmark for this research.

Other Methods

Cortical Anatomy and Brain Mapping ²

Neuroanatomy Other

Anatomical MRI ¹

Imaging Methods Other

MRI PHYSICS

STRUCTURAL MRI