Quantitative Photoacoustic Tomography And Its Application To The Diagnosis Of Osteoarthritis

Osteoarthritis (OA) is a common degenerative, slowly progressive joint disease. According to the World Heath Organization (WHO), approximately 50% of people over 50 year-old suffer from OA today. While there is currently no cure for this disease, numerous clinical studies have shown that the progression of the diseased joint may be modified by medical or surgical intervention if the disease is detected early.The goal of this thesis research is to develop a novel biomedical imaging modality called photoacoustic tomography (PAT), which promises to significantly advance our ability to detect such diseased joints at an early stage, and thereby offer the potential for curative OA treatment for this devastating disease. PAT is a newly developed in vivo imaging method for biomedical tissues, which uniquely combines high optical contrast and high ultrasound resolution in a single modality. In addition, it offers better sensitivity to the tissue changes in an OA joint at an early stage over all the cuurent medical imaging modalities.The key to the development of successful PAT for joint imaging is an effective image reconstruction algorithm that allows one to characterize the joint tissues. In this thesis we have developed and implemented finite element based reconstruction algorithms for recovering tissue optical property, functional/ physiological parameters such as hemoglobin concentration and water content and acoustic property using both single-and multi-spectral photoacoustic measurements. A unique advantage of our reconstruction method is that it allows us to obtain the distribution of absolute optical absorption coefficient by incorporating a light transport model into our PAT reconstruction framework to realize quantitative PAT. This reconstruction method also has eliminated the assumption of homogenous acoustic velocity in the image domain so that it allows direct recovery of tissue chromophore concentrations and acoustic velocity using tomographic multi-spectral photoacoustic measurements.Extensive simulations and laboratory experiments using tissue-like phantoms have been conducted using both single- and multi-spectral photoacoustic data in order to assess the overall imaging capabilities of the reconstruction algorithms developed. Both the single- and multi-spectral reconstruction algorithms have also been tested and evaluated using pilot clinical data from patients with hand OA and healthy volunteers.To our knowledge, the quantitative reconstruction algorithms developed represent the first of their kind. Their applications to osteoarthritis imaging as well as hard tissue imaging are also for the first time. The successful pilot clinical experience indicates that the single- and multi-spectral quantitative PAT methods developed in this thesis have great potential to serve as a clinical tool for early detection of osteoarthritis in the hand.