Quantitative Sound Speed Imaging of Cortical Bone and Soft Tissue: Results From Observational Data Sets

This work presents the first quantitative ultrasonic sound speed images of ex vivo limb cross-sections containing both soft tissue and bone using Full Waveform Inversion (FWI) with level set (LS) and travel time regularization. The estimated bulk sound speed of bone and soft tissue are within 10% and 1%, respectively, of ground truth estimates. The sound speed imagery shows muscle, connective tissue and bone features. Typically, ultrasound tomography (UST) using FWI is applied to imaging breast tissue properties (e.g. sound speed and density) that correlate with cancer. With further development, UST systems have the potential to deliver volumetric operator independent tissue property images of limbs with non-ionizing and portable hardware platforms. This work addresses the algorithmic challenges of imaging the sound speed of bone and soft tissue by combining FWI with LS regularization and travel time methods to recover soft tissue and bone sound speed with improved accuracy and reduced soft tissue artifacts when compared to conventional FWI. The value of leveraging LS and travel time methods is realized by evidence of improved bone geometry estimates as well as promising convergence properties and reduced risk of final model errors due to un-modeled shear wave propagation. Ex vivo bulk measurements of sound speed and MRI cross-sections validates the final inversion results.

Automated summary

This study presents ultrasonic sound speed images of limb cross-sections containing soft tissue and bone using Full Waveform Inversion (FWI) with level set (LS) and travel time regularization. The accuracy of sound speed estimation for bone and soft tissue is within 10% and 1% of ground truth estimates, respectively. The potential of delivering volumetric operator independent tissue property images of limbs with non-ionizing and portable hardware platforms is demonstrated.