Purpose: To develop and validate a method for B0 mapping for knee imaging using the quantitative Double-Echo in Steady-State (qDESS) exploiting the phase difference (∆θ) between the two echoes acquired. Contrary to a standard two-gradient echo (2-GRE) method, the phase accumulation in qDESS depends only on the first echo time. Methods: Bloch simulations were applied to investigate the robustness to noise of the proposed methodology and all imaging studies were validated with phantoms and in vivo simultaneous bilateral knee acquisitions. Two phantoms and 5 healthy subjects were scanned using qDESS, water saturation shift referencing (WASSR), and multi GRE sequences. ∆B0 maps were calculated with the qDESS and the 2-GRE methods and compared against those obtained with WASSR. The comparison was quantitatively assessed by exploiting pixel-wise difference maps, Bland-Altman (BA) analysis, and Lin’s concordance coefficient (ρc). For in-vivo subjects, the comparison was assessed in cartilage using average values in 6 sub-regions. Results: The proposed method for measuring B0 inhomogeneities in phantom and in-vivo scans from a qDESS acquisition provided ∆B0 maps that were in good agreement with those obtained using WASSR. ∆B0 Lin’s coefficients were greater than or equal to 0.98 and 0.90 in phantoms and in vivo, respectively. The agreement between qDESS and WASSR was comparable to that of a standard 2-GRE method. Conclusion: The proposed method may allow B0 correction for qDESS T2 mapping using an inherently co-registered ∆B0 map without requiring an additional B0 measurement sequence. More generally, the method may help shorten knee imaging protocols that require an auxiliary ∆B0 map by exploiting a qDESS acquisition that also provides T2 measurements and high-quality morphological imaging. Conclusion: The proposed method may allow B0 correction for qDESS T2 mapping using an inherently co-registered ∆B0 map without requiring an additional B0 measurement sequence. More generally, the method may help shorten knee imaging protocols that require an auxiliary ∆B0 map by exploiting a qDESS acquisition that also provides T2 measurements and high-quality morphological imaging. This repository contains the data for reproducing the results reported in the paper. For the in-vivo data, python scripts are provided to perform the data analysis described in the paper. The data are provided in NIFTI format. Please cite the original paper (10.1002/mrm.29465) and this repository if you use any of the data or code contained here.

For the in vivo bilateral knee data, the python code provided makes use of DOSMA: Deep Open-Source Medical Image Analysis (https://github.com/ad12/DOSMA.git) for computing the average B0 in 6 femoral cartilage regions. Please follow the instruction provided on the GitHub page to set up DOSMA. You will notice that within the qresults folders, the parameter t2 is mentioned in the folder name. This is just due to the fact that, currently, DOSMA does not support negative values as a quantitative parameter. Thus, to be able to exploit DOSMA features with B0 quantitative maps (that also may have negative values), the t2 quantitative parameter was selected and a known offset was added to the B0 maps. The offset was then subtracted at the time of data analysis. Please review DOSMA documentation and the python code provided. You may reach out to the corresponding author for questions regarding the data and the code provided in the repository.