Robust Photoacoustic Eigen Waveform Analysis for Characterization of Cancellous Bone.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 40031704.
- Also identified by DOI 10.1109/TBME.2025.3544876.
- No licence information is recorded for this record.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
Noninvasive photoacoustic (PA) imaging techniques afford abundant microstructure information for the diagnosis and therapeutic monitoring of diseases. However, their use for bone tissue imaging is challenging owing to the high scattering and attenuation properties of bone tissue. The PA signal waveforms inherently contain optical and ultrasonic properties related to bone health. This study entailed the development of a robust, compensation-free PA eigen waveform analysis (PEWA) method for characterizing high-scattering cancellous bone in transmission mode. Numerical simulations and experimental studies were conducted on cancellous bone models with various bone mineral densities (BMDs), optical, and ultrasonic properties. The resulting PA signals were analyzed using PEWA method, facilitating the quantification of parameters related to bone conditions, such as the exponential growth coefficient. The simulation results indicate that bone specimens with lower BMDs have lower exponential growth coefficients. Furthermore, we found that the exponential growth coefficient has better robustness and stability than conventional amplitude-based parameter. The experimental findings from animal cancellous bone tissues ex vivo with different BMDs were in close agreement with the simulation results, thus demonstrating that the PEWA method can perform BMD assessments for cancellous bone. Considering that PA measurements are nonionizing and noninvasive and have sufficient penetration in both nonorganic (bone matrix) and organic tissues (bone marrow), the proposed compensation-free, PEWA bone evaluation method has the potential to facilitate early and rapid clinical assessment of osteoporosis. The proposed approach has considerable applicability in the domains of miniaturization equipment intelligent evaluation of bone health.
Medical subject headings
- Photoacoustic Techniques
- Cancellous Bone
- Signal Processing, Computer-Assisted
- Image Processing, Computer-Assisted