# Model-Based Reconstruction for Quantitative MRI using the Bloch Equations

## TL;DR

This paper introduces a comprehensive model-based MRI reconstruction method that directly incorporates Bloch equations, enabling accurate quantification of relaxation parameters from complex sequences.

## Contribution

It integrates the full Bloch equations into the reconstruction process using a Runge-Kutta solver, advancing beyond simplified models for more precise MRI parameter mapping.

## Key findings

- Successfully estimated T1, T2, M0 maps from experimental data.
- Demonstrated improved accuracy over simplified models.
- Validated with a custom T1-T2 phantom.

## Abstract

In this work a generic model-based reconstruction for the quantification of relaxation parameters is developed. In contrast to previous approaches that rely on simplified models derived from the Bloch equations, this work includes the Bloch equations directly into the reconstruction. Therefore, non-linear calibrationless parallel imaging is combined with a generic Runge-Kutta 5(4) based forward operator to simulate spin dynamics described by arbitrary sequences. Gradients are determined by using a sensitivity analysis and solving the resulting ordinary differential equations parallel to the signal simulation. Based on this formulation an IRGNM-FISTA algorithm is used to estimate quantitative maps for $T_1$, $T_2$, $M_0$, and the coil profiles $c_N$ from fully-sampled multi-inversion and golden-angle single-shot inversion-recovery radial bSSFP measurement with a custom-built $T_1$-$T_2$ phantom.