Peripheral arterial disease (PAD) affects approximately 200 million individuals worldwide. It is characterized by a reduction in blood flow to the lower extremities due to atherosclerosis. This can result in leg pain, tissue loss, and ultimately amputation. Revascularization procedures aim to restore blood flow, but up to 50% of patients require another intervention within a year. Revascularization monitoring and early detection of failure are crucial in preventing limb loss and adverse cardiovascular events. However, current evaluation methods do not directly measure perfusion and are limited in a significant segment of PAD patients, such as those with diabetes and renal insufficiency. Diffuse optical imaging (DOI) techniques are promising tools to overcome these limitations. Employing near-infrared light, they are non-invasive, non-ionizing, contrast-free, and cost-effective methods that are sensitive to hemodynamic parameters such as changes in oxy-, deoxy-, and total hemoglobin concentration, making DOI ideal for revascularization monitoring.
In this dissertation, I investigate and develop DOI systems for the purpose of monitoring lower extremity revascularization procedures in PAD patients. We utilize a contact-based diffuse optical spectroscopy (DOS) system to monitor localized foot perfusion in an ongoing clinical study of 100 patients undergoing lower extremity angiography. I demonstrate the utility of DOS measurements to provide valuable insights into revascularization related hemodynamic remodeling and to predict revascularization success. Furthermore, I also develop a clinic friendly contact-free diffuse optical tomography (DOT) system that is better-suited for PAD patients with ulcers. I show that this system can provide spatial maps of perfusion within the foot. Collectively, this work establishes diffuse optical imaging as a valuable imaging modality for the evaluation of lower extremity perfusion.
Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/D8F4961S |
Date | January 2018 |
Creators | Hoi, Jennifer |
Source Sets | Columbia University |
Language | English |
Detected Language | English |
Type | Theses |
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