Speed of sound characterization in skull bone via microCT and ultrasound

Transcranial ultrasound applications require accurate estimation of the speed of sound (SoS) to correct skull-induced phase aberrations. Numerous empirical models have been proposed to calculate SoS from clinical computed tomography (CT) data, with limited consensus regarding their accuracy and validation against direct experimental measurements. To address this gap, we evaluate microCT-based SoS mapping approaches, including a novel logarithmic intensity-to-density model, by comparing them to experimentally derived SoS maps. We propose a framework that integrates microCT imaging to calculate spatially varying thickness, and ultrasound data, to derive, validate, and compare SoS maps of human skull fragments. Estimated SoS maps from our model were compared to those from a linear intensity-to-density model and our proposed model. Applying logarithmic transformation to microCT intensities before linear scaling improved density estimation, which was then used to compute SoS via a linear model. Quantitative comparison against the mean SoS value derived using our ultrasound and microCT-based thickness data demonstrated that the proposed model outperformed the existing model, with a lower mean absolute error, thereby helping us to validate the accuracy and robustness of our framework. [Work supported by NIH R21EB032638.]