Low-cost chest paediatric phantom for dose optimisation: construction and validation

INTRODUCTION AND OBJECTIVES

In order to perform chest dose optimisation studies, the imaging phantom should be adequate for image quality evaluation. Since high-end phantoms are cost prohibitive, there is a need for a low-cost construction method with fairly available tissue substitutes.

MATERIALS AND METHODS

Theoretical calculations of radiological characteristics were performed for each of lung, cortical bone and soft tissues in order to choose appropriate substitute, then, cork, P.V.C. (Polyvinyl chloride) and water were chosen, respectively. Validation included, firstly, measuring CT Hounsfield Units (HU) of a real patient's tissues then compared against their corresponding anatomies in the constructed phantom. Secondly, Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) values were acquired in this study to evaluate the quality of images generated from the constructed phantom, then, compare their trends with a valid phantom under different exposure parameters (kVp and mAs).

RESULTS

From theoretical calculations, the percentage differences showed high accuracy of tissue substitutes when simulating real patient tissues; P.V.C. was ≥5.78%, cork was ≥4.46% and water ≥5%. The percentage difference (CT HU) between lung and cortical bone and their equivalent tissue substitutes were 10.44% and 0.53%-3.17%, respectively. Strong positive correlations were found for SNR when changing both kVp (0.79) and mAs (0.65). While the correlation strength of CNR values were found to be moderate when changing both kVp (0.58) and mAs (0.53).

CONCLUSIONS

Our low-cost phantom approved through CT HU that their materials replicate the radiological characteristics of real one-year-old child while SNR and SNR correlations confirmed its applicability in imaging and optimisation studies.

Validation of diffusion MRI estimates of compartment size and volume fraction in a biomimetic brain phantom using a human MRI scanner with 300 mT/m maximum gradient strength

Diffusion microstructural imaging techniques have attracted great interest in the last decade due to their ability to quantify axon diameter and volume fraction in healthy and diseased human white matter. The estimates of compartment size and volume fraction continue to be debated, in part due to the lack of a gold standard for validation and quality control. In this work, we validate diffusion MRI estimates of compartment size and volume fraction using a novel textile axon ("taxon") phantom constructed from hollow polypropylene yarns with distinct intra- and extra-taxonal compartments to mimic white matter in the brain. We acquired a comprehensive set of diffusion MRI measurements in the phantom using multiple gradient directions, diffusion times and gradient strengths on a human MRI scanner equipped with maximum gradient strength (G_max) of 300 mT/m. We obtained estimates of compartment size and restricted volume fraction through a straightforward extension of the AxCaliber/ActiveAx frameworks that enables estimation of mean compartment size in fiber bundles of arbitrary orientation. The voxel-wise taxon diameter estimates of 12.2 ± 0.9 μm were close to the manufactured inner diameter of 11.8 ± 1.2 μm with G_max = 300 mT/m. The estimated restricted volume fraction demonstrated an expected decrease along the length of the fiber bundles in accordance with the known construction of the phantom. When G_max was restricted to 80 mT/m, the taxon diameter was overestimated, and the estimates for taxon diameter and packing density showed greater uncertainty compared to data with G_max = 300 mT/m. In conclusion, the compartment size and volume fraction estimates resulting from diffusion measurements on a human scanner were validated against ground truth in a phantom mimicking human white matter, providing confidence that this method can yield accurate estimates of parameters in simplified but realistic microstructural environments. Our work also demonstrates the importance of a biologically analogous phantom that can be applied to validate a variety of diffusion microstructural imaging methods in human scanners and be used for standardization of diffusion MRI protocols for neuroimaging research.