Speaker
Description
This work presents an open-source framework that integrates MRI sequence design, execution, and model-based reconstruction into a single reproducible workflow within the BART toolbox. The motivation is to address reproducibility challenges in quantitative MRI (qMRI), where both sequence implementation and reconstruction details are often difficult to replicate due to proprietary software and incomplete methodological descriptions. The framework represents MRI sequences on the lowest level as events such as gradients, RF pulses, ADC readouts, and triggers. These events are combined into sequence blocks which represent a modular functionality, such as acquisition of a radial spoke. Blocks are a function of a controlable high-level parameter set. We propose two methods of acquisition. First, the sequence is generated prospectively offline, saved to a well-established open-source format (Pulseq) and executed via an appropriate interpreter program. Second, we integrate BART as a library dynamically on the scanner which allows for adjustment of parameters online while planning the scan and generates interpretable sequence events just-in-time during execution. In both cases, all necessary details of the acquisition, including timing, and k-space trajectory can be regenerated to ensure consistent reconstruction. We validated the framework with phantom and in-vivo experiments using radial sampling and model-based reconstruction in two advanced qMRI applications. First, subspace-based T1 mapping is performed using an inversion-recovery radial FLASH sequence with highly accelerated acquisition. Second, a multi-echo radial FLASH sequence is used for joint estimation of R2* and B0 maps. In both cases, parameter maps from different acquisition strategies show strong agreement, with small differences mainly attributed to noise or physiological variations. In summary, an end-to-end open-source framework for joint sequence design and model-based reconstruction in BART for full replicability of qMRI techniques is introduced. Both, a direct integration with online parameter adjustment on the scanner and an offline Pulseq export, is presented.