Technical Note: Development of a cranial phantom for assessing perfusion, diffusion, and biomechanics

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Abstract

Purpose

A novel cranial phantom was developed to simulate the relationships among factors such as blood perfusion, water diffusion, and biomechanics in intracranial tissue.

Methods

The cranial phantom consisted of a high-density polypropylene filter (mimicking brain parenchyma) with intra- and extrafilter spaces (mimicking cerebral artery and vein, respectively), and a capacitor space (mimicking the cerebrospinal fluid space). Pulsatile and steady flow with different flow rates were applied to the cranial phantom using a programmable pump. On 3.0-T MRI, the measurements of the internal pressure in the phantom, apparent diffusion coefficient (ADC) with monoexponential analysis in the filter, and total simulated cerebral blood flow (tSCBF) into the phantom were synchronized with the pulsatile flow. We obtained their maximum changes during the pulsation period (ΔP, ΔADC, and ΔtSCBF, respectively). Then, the compliance index (CI) was calculated by dividing the volume change (ΔV) by the ΔP in the phantom. Moreover, the same measurements were repeated after the compliance of the phantom was reduced by increasing the water volume in the capacitor space. Under steady flow conditions, we determined the regional SCBF (rSCBF) and perfusion-related and restricted diffusion coefficients (D* and D, respectively) with biexponential analysis in the filter.

Results

The internal pressure, ADC, and tSCBF varied over the pulsation period depending on the input flow. Moreover, the ΔP, ΔADC, ΔtSCBF, and rSCBF increased with the input flow rate. Compared to the high compliance condition, in the low compliance condition, the ΔP and ΔADC were higher by factors of 2.5 and 1.3, respectively, and the CI was smaller by a factor of 2.7, whereas the ΔV was almost unchanged. The D* was strongly affected by the input flow.

Conclusion

Our original phantom models the relationships among the blood perfusion, water diffusion, and biomechanics of the intracranial tissue, potentially facilitating the validation of novel MRI techniques and optimization of imaging parameters.

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