Towards a barrier-free anthropomorphic brain phantom for quantitative magnetic resonance imaging: Design, first construction attempt, and challenges.

Existing magnetic resonance imaging (MRI) reference objects, or phantoms, are typically constructed from simple liquid or gel solutions in containers with specific geometric configurations to enable multi-year stability. However, there is a need for phantoms that better mimic the human anatomy without barriers between the tissues. Barriers result in regions without MRI signal between the different tissue mimics, which is an artificial image artifact. We created an anatomically representative 3D structure of the brain that mimicked the T1 and T2 relaxation properties of white and gray matter at 3 T. While the goal was to avoid barriers between tissues, the 3D printed barrier between white and gray matter and other flaws in the construction were visible at 3 T. Stability measurements were made using a portable MRI system operating at 64 mT, and T2 relaxation time was stable from 0 to 22 weeks. The phantom T1 relaxation properties did change from 0 to 10 weeks; however, they did not substantially change between 10 weeks and 22 weeks. The anthropomorphic phantom used a dissolvable mold construction method to better mimic anatomy, which worked in small test objects. The construction process, though, had many challenges. We share this work with the hope that the community can build on our experience.

Comparison of Phase Estimation Methods for Quantitative Susceptibility Mapping Using a Rotating-Tube Phantom.

Quantitative Susceptibility Mapping (QSM) is an MRI tool with the potential to reveal pathological changes from magnetic susceptibility measurements. Before phase data can be used to recover susceptibility (Δχ), the QSM process begins with two steps: data acquisition and phase estimation. We assess the performance of these steps, when applied without user intervention, on several variations of a phantom imaging task. We used a rotating-tube phantom with five tubes ranging from Δχ=0.05 ppm to Δχ=0.336 ppm. MRI data was acquired at nine angles of rotation for four different pulse sequences. The images were processed by 10 phase estimation algorithms including Laplacian, region-growing, branch-cut, temporal unwrapping, and maximum-likelihood methods, resulting in approximately 90 different combinations of data acquisition and phase estimation methods. We analyzed errors between measured and expected phases using the probability mass function and Cumulative Distribution Function. Repeatable acquisition and estimation methods were identified based on the probability of relative phase errors. For single-echo GRE and segmented EPI sequences, a region-growing method was most reliable with Pr (relative error <0.1) = 0.95 and 0.90, respectively. For multiecho sequences, a maximum-likelihood method was most reliable with Pr (relative error <0.1) = 0.97. The most repeatable multiecho methods outperformed the most repeatable single-echo methods. We found a wide range of repeatability and reproducibility for off-the-shelf MRI acquisition and phase estimation approaches, and this variability may prevent the techniques from being widely integrated in clinical workflows. The error was dominated in many cases by spatially discontinuous phase unwrapping errors. Any postprocessing applied on erroneous phase estimates, such as QSM's background field removal and dipole inversion, would suffer from error propagation. Our paradigm identifies methods that yield consistent and accurate phase estimates that would ultimately yield consistent and accurate Δχ estimates.