Purpose: While MRI-only treatment planning is becoming more widespread, a robust clinical solution for patient-specific distortion corrections is not currently available. This work explores an alternative approach for B0- mapping estimated from mDixon, often acquired for MR-only planning, compared to a dedicated dual-echo gradient-recalled echo (GRE) sequence, with the overarching goal of developing an efficient and robust approach for patient-specific distortion correction maps. Methods: Healthy volunteers were imaged in the pelvis and head and neck (H&N) regions at 1.5T and 3T. B0 field maps were generated with two approaches: (1) conventional: dualecho GRE (using two in-phase echo times) and (2) experimental: mDIXON using much shorter echo times. Additionally, the impact of acquisition resolution was evaluated for 1.7 9 1.7 9 5 mm (low resolution, LR) vs. 1.2 9 1.2 9 2.4 mm (high resolution, HR) in H&N. Distortion maps were generated from B0 field maps based on bandwidth and acquisition pixel size and compared between approaches. Results: In H&N, mDIXON revealed similar distortion magnitudes between field strengths (\u3c0.5 mm). Distortions were higher near ear canals (∼1 mm), sinuses (∼1 mm) and dental fillings (\u3e1 mm). HR B0 maps were more sensitive at interfaces than LR, although LR was suitable given its overall accuracy in bulk voxels and shorter acquisition time (40% of HR). LR conventional GRE was well-approximated by mDIXON: 96% (1.5T) and 99% (3T) of voxels estimated by mDixon differed from their GRE maps by \u3c0.5 mm. In the pelvis, 99% of GRE distortion voxels and 100% of mDixon distortion voxels were within ±0.3 mm. Differences between techniques occurred near regions with high spatial variation and with phase unwrapping errors. Conclusion: mDIXON closely approximated GRE for patient-specific distortion assessment. Slight differences observed near tissue interfaces require further assessment to determine geometric and dosimetric impact. mDIXON-derived B0 maps may be advantageous for integration into in-line processing without requiring additional sequences
