A digital-signal-processor-based optical tomographic system for dynamic imaging of joint diseases

Over the last decade, optical tomography (OT) has emerged as viable biomedical imaging modality. Various imaging systems have been developed that are employed in preclinical as well as clinical studies, mostly targeting breast imaging, brain imaging, and cancer related studies. Of particular interest are so-called dynamic imaging studies where one attempts to image changes in optical properties and/or physiological parameters as they occur during a system perturbation. To successfully perform dynamic imaging studies, great effort is put towards system development that offers increasingly enhanced signal-to-noise performance at ever shorter data acquisition times, thus capturing high fidelity tomographic data within narrower time periods.;Towards this goal, I have developed in this thesis a dynamic optical tomography system that is, unlike currently available analog instrumentation, based on digital data acquisition and filtering techniques. At the core of this instrument is a digital signal processor (DSP) that collects, collates, and processes the digitized data set. Complementary protocols between the DSP and a complex programmable logic device synchronizes the sampling process and organizes data flow. Instrument control is implemented through a comprehensive graphical user interface which integrates automated calibration, data acquisition, and signal post-processing. Real-time data is generated at frame rates as high as 140 Hz. An extensive dynamic range (∼190 dB) accommodates a wide scope of measurement geometries and tissue types. Performance analysis demonstrates very low system noise (∼1 pW rms noise equivalent power), excellent signal precision (∼0.04%--0.2%) and long term system stability (∼1% over 40 min). Experiments on tissue phantoms validate spatial and temporal accuracy of the system.;As a potential new application of dynamic optical imaging I present the first application of this method to use vascular hemodynamics as a means of characterizing joint diseases, especially effects of rheumatoid arthritis (RA) in the proximal interphalangeal finger joints. Using a dual-wavelength tomographic imaging system and previously implemented reconstruction scheme, I have performed initial dynamic imaging case studies on healthy volunteers and patients diagnosed with RA. These studies support our hypothesis that differences in the vascular and metabolic reactivity exist between affected and unaffected joints and can be used for diagnostic purposes.