Applying a systems engineering approach to improve clinical decision-making process for Cushing Syndrome Open Access
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Over the past few decades, the clinical trial process has faced more complexity causing remarkable increase of cost and time and complicating the health issues. Clinical trials are viewed as a problem from virtually every stakeholder’s viewpoint such as clinicians, researchers, technicians, medical managers, pharmacologists, insurance companies, public health officials, wellness policy analysts, patients, and even government policy makers. This dissertation applies a systems engineering approach on the clinical decision-making process by developing a bio-medical device. The general goal and objectives is enhancing the efficiency and effectiveness of the trial clinical decision-making process in order to reduce cost, time, uncertainty and the related risks, while also improving the patients’ quality of life and managing the treatment. This bio-medical device which is based on optical imaging technology was tested through designed experiment by recruiting Cushing Syndrome’s (CS) patients. The current treatment evaluations methods for Cushing Syndrome are not defined with certainty and there is no universally accepted measure to assess sustainable remission in the early stages after treatment. All these measures are dependent on thresholds that are pre-defined by evaluators. There are varying definitions of these thresholds in different clinical centers. The most important criterion for assessing sustainable remission appears to be serum cortisol after surgery. However, even after a successful surgery, recurrence of the disease may occur within a few months, and in some cases, after several years. The variability and uncertainty in the suggested criteria make it difficult to assess the final outcome of the treatment. Therefore, better criteria and more robust methods are necessary to evaluate the results of the surgery or other treatment. A quantitative approach can offer a more objective means of treatment outcome monitoring. Moreover, such approaches have the potential to present biomarkers for tumor activity and show how patients respond to their current treatments. Some elements of the systems engineering approach such as experimental design, system analysis and development are used to find the quantitative criterion of interest by applying near-infrared (NIR) spectroscopy. NIR spectroscopy has shown as most relevant technical method to monitor subcutaneous tissue. A multi-spectral image system as one modality of optical imaging is designed and upgraded to capture images at different wavelengths (700-1000 nm) from the CS patient’s cheek side as the region of interest based on the NIH protocol before and after treatment and comparing the images. The end goal is to reconstruct physiological chromophores by fitting corrected light intensity values to an analytical two layered-skin model. This is developed based on distinguishable optical properties of the epidermis and dermis layer of skin. These physiological parameters include the volume of melanin, water, blood, oxygenated- and deoxygenated-hemoglobin, and lipids.