QSM outside the brain has recently gained interest, particularly in the abdominal region. However, the absence of reliable ground truths makes difficult to assess reconstruction algorithms, whose quality is already compromised by additional signal contributions from fat, gases, and different kinds of motion. This work presents a realistic in silico phantom for the development, evaluation and comparison of abdominal QSM reconstruction algorithms.
Methods
Synthetic susceptibility and R2* maps were generated by segmenting and postprocessing the abdominal 3T MRI data from a healthy volunteer. Susceptibility and R2* values in different tissues/organs were assigned according to literature and experimental values and were also provided with realistic textures. The signal was simulated using as input the synthetic QSM and R2* maps and fat contributions. Three susceptibility scenarios and two acquisition protocols were simulated to compare different reconstruction algorithms.
Results
QSM reconstructions show that the phantom allows to identify the main strengths and limitations of the acquisition approaches and reconstruction algorithms, such as in-phase acquisitions, water-fat separation methods, and QSM dipole inversion algorithms.
Conclusion
The phantom showed its potential as a ground truth to evaluate and compare reconstruction pipelines and algorithms. The publicly available source code, designed in a modular framework, allows users to easily modify the susceptibility, R2* and TEs, and thus creates different abdominal scenarios.
I am not sure why numerical phantoms will not model current abdominal phantoms well. Having piecewise susceptibility values in the phantoms is a good thing. That allows us to use a least squares fit method for susceptibility measurements.
The PDF method used to remove background phase is known to affect susceptibility values. From Table 1, we see susceptibility values of hepatic veins and porta veins less than the expected value, 0.4-0.45 ppm. This is most likely due to the pdf method.
It is hard to believe that subcutaneous fat and visceral fat have high susceptibility values. Fat typically has a susceptibility value very close to that of water. The authors may have mixed susceptibility values with chemical shifts. Or this again is a problem of the pdf method.
Also in Table 1, the susceptibility values of internal air and external air have to be 9.4 ppm relative to the susceptibility of water. Any deviation from the 9.4 ppm is likely due to the partial volume effect, e.g., ill-defined boundary between the air and tissue. The authors quote 4.84 ppm for the internal air from reference 64 but this is not appropriate at all. This 4.84 ppm apparently is from the susceptibility of lung from reference 64 which states that the lung was air-filled to 15%. This agrees with what I just said. It is due to the partial volume effect such that the susceptibility of internal air in tissues deviates from 9.4 ppm. Thus it is misleading to quote 4.84 ppm for the internal air. The authors should still quote 9.4 ppm for the internal air and model the partial volume effect so the phase value can be correctly calculated.
It is also important to note that some susceptibility values provided in reference 64 are incorrect.