Purpose: X-ray-induced acoustic computed tomography (XACT) is a promising imaging modality combining high x-ray absorption contrast with the 3D propagation advantages provided by high resolution ultrasound waves. The 3D XACT imaging with a single X-ray project is achieved by implementing a cup-shaped ultrasound (US) detector which houses 280 US sensors on a spherical surface. The purpose of this study was to test and optimize the configuration of the 3D XACT imaging system for bone imaging with the spherical ultrasound detector array.
Methods: A 280 ultrasonic sensors with peak frequency of 10 MHz was designed to distribute on a spherical surface to optimize the 3D volumetric imaging capability. The resolving power of the system was tested in three dimensions with small sphericals simulations. Then, the systemâ€™s complex structure imaging capability was demonstrated by simulating the X-ray induced acoustic signals from a neuron shaped structure. In addition, simulations were also used to simulate the X-ray induced acoustic signal generation, propagation, and attenuation in a digital phantom mouse paw generated from micro-CT images. The three-dimensional bone density distribution was successfully obtained from the digital phantom simulation.
Results: The resolution tests show that 3D XACT imaging system has a theoretical spatial resolution of 123 -130 Âµm. The reconstructed complex structure simulation demonstrates the lateral and axial resolving power of the cup-detector based 3D XACT system. In the end, the micro-CT generated digital phantom simulation results successfully revealed the bone microstructures on a mouse paw model.
Conclusion: The study demonstrated the feasibility of XACT system in 3D imaging with single X-ray projection. We performed K-Wave simulations of this optimized XACT imaging configuration with various simulated objects, including a digital phantom from real-world micro-CT slices. Given the advantages of 3D XACT system, the future of XACT systemâ€™s application in bone density distribution mapping is very promising.