Introduction
Novel MR acquisition and reconstruction techniques require data for testing, benchmarking, and deep-learning training. Digital twins can reduce development costs and time. While many frameworks include virtual phantom routines, a dedicated package for quantitative MRI (qMRI) is lacking. We propose MRTwin, a lightweight, reusable Python package for generating virtual objects (e.g., Shepp-Logan and brain-like relaxation distributions), realistic field inhomogeneities (B₀, B₁), coil sensitivities, gradient non-idealities, and motion patterns. MRTwin is freely available on GitHub (https://github.com/INFN-MRI/mrtwin).

Methods
Built in Python 3.10 for cross-platform portability, MRTwin has a modular design for easy reuse and extension. Its key features include:

• Virtual Phantoms: Models based on various anatomical sources (Shepp-Logan, Brainweb, CBS Neuroimaging Repository) with single, two-, or three-pool tissue representations (incorporating myelin water and MT compartments).
• Field Maps: Routines to generate realistic B₀ maps (derived from phantom susceptibility), B₁ maps with multiple RF modes, and coil sensitivity profiles.
• Motion Patterns: Markov chain–generated rigid motion (2D and 3D) to simulate varying motion severities.
• Gradient Non-Idealities: Gaussian-shaped Gradient Input Response Functions with linear phase components to mimic k-space trajectory shifts and deformations.

Results
We simulated a 7T multi-echo SPGR dataset (FA = 10°, TR = 50 ms, TE ranging from 5 to 41 ms, 6 ms echo spacing) over an 18.0×16.0 cm FOV at 0.7 mm resolution using an 8-channel coil, achieving realistic contrast and texture.

Conclusion
MRTwin enables rapid numerical experiments for trajectory and contrast optimization, quantitative relaxometry, and AI training, integrating seamlessly with frameworks like SigPy and DeepInverse.

Acknowledgements

This work was partially funded by the INFN-CSN5 PREDATOR project (“Grant Giovani”). Support from the Italian Ministry of Health under the grant RC 2024 to IRCCS Fondazione Stella Maris.