The overall goal of this dissertation is to describe the development of a dynamic diffuse optical tomographic (DDOT) imaging system for the diagnosis and monitoring of peripheral arterial disease (PAD) within the lower extremities. PAD affects 8-12 million individuals in the United States and is associated with significant morbidity and mortality. Early detection and monitoring of disease progression is crucial, but remains difficult. This is especially true for diabetic patients, as roughly 30 percent of all diabetic patients over the age of 50 are diagnosed with PAD. Diabetic patients have calcified arteries, which renders them incompressible. This falsely elevates blood pressure readings and causes false negative readings using traditional diagnostic techniques. DDOT offers an attractive opportunity to overcome current shortcomings in assessing PAD. This technology uses harmless near-infrared light to create three-dimensional, time-dependent images of biological tissues. Using DDOT to measure blood-perfusion in the foot should help diagnose and monitor the PAD. To test this hypothesis, I adapted an existing optical tomographic imaging system for the particular application of vascular imaging in the foot. In particular I design and tested various measuring probes that can accommodate different foot sizes and shapes. The result was a patient friendly interface that can be employed in a clinical setting. Using this modified DDOT imager, which we called vascular optical tomographic imaging (VOTI) system, I conducted a 40-subject pilot study to quantify its ability to diagnose PAD. The subjects were recruited into three cohorts, non-diabetic PAD patients (N=10), PAD Patients (N=10) and healthy volunteers (N=20). With this data in hand, I performed a comprehensive data analysis, in which I found imaging features that led to a good separation between the healthy and affected cohorts. In particular I demonstrated that statistically significant difference exist between the amount of blood pooling in the leg during a 1-minute, 60mmHg thigh cuff occlusion within healthy subjects and both affected cohorts (P=0.006, P=0.006). In addition, using receiver operating characteristic (ROC) curve analysis, I identified that the new VOTI system could diagnose PAD with a sensitivity and specificity of over 80%, even within the diabetic patients. This imaging modality was also capable of identifying the severity of the disease with similar accuracy to the existing diagnostic methods while not being inhibited by arterial calcifications. Furthermore, the VOTI system provided spatial information, helping identify which regions of the foot suffered from mal-perfusion. When combined with angiosome theory, the spatial information could help physicians in deciding how to intervene in PAD patients.
After completing this first clinical study, I developed a dedicated VOTI system by entirely redesigning the hard and software. This new system has many novelties over its predecessor. First it employs a contact-free patient interface that allows to imaging patients with ulcerations. The illumination fibers used do not need to make physical contact with the patient. Second, instead of using individual silicon photodiodes as detectors, a highly sensitive CCD camera is use to detect transmitted light intensity. The system has two wavelengths of light (660 and 860 nm), which can be illuminated at up to 20 different positions along the surface of the foot. The system is built for dynamic imaging and is capable of imaging at a multispectral-volumetric frame rate speeds of 1 Hz. This set-up allows us to create three-dimensional images of large portions of the foot. This imaging system was tested on phantom studies and healthy volunteers and was shown to be able to image blood flow dynamics within a three-dimensional volume of the foot.
Identifer | oai:union.ndltd.org:columbia.edu/oai:academiccommons.columbia.edu:10.7916/D8DF6PCQ |
Date | January 2014 |
Creators | Khalil, Michael |
Source Sets | Columbia University |
Language | English |
Detected Language | English |
Type | Theses |
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