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Monte Carlo Simulations to Inform Clinical Applications of Optical Devices
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Thesis/Dissertation
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2024-05
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Bioengineering
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http://dx.doi.org/10.34944/dspace/10308
Abstract
Optical Point-of-Care (POC) devices provide a low-cost platform for real-time, non-invasive diagnosis of disease and quantitative estimation of physiological biomarkers, allowing use in a wide variety of institutional settings ranging from acute surgical care to long-term clinical monitoring. POC optical value has resulted in their widespread adoption with great interest in at-home monitoring and explosive growth within wearable consumer electronics. However, recent studies have highlighted the fact that well-established devices such as pulse oximeters can exhibit subtle but dangerous inaccuracies in measurements from some darker skin pigmentation patients whose basis is not completely understood. Emerging optical technologies, such as near-infrared spectroscopy (NIRS) monitoring of bone quality are promising, yet similarly suffer from an incomplete understanding of the relationship between probe design and performance.The focus of this dissertation is to develop next-generation approaches to improve the performance of optical diagnostic devices informed by computational simulations of light-tissue interactions using Monte Carlo (MC) modeling. Although MC simulations have been previously used to design and simulate devices such as Pulse Oximeters or Transcutaneous Bilirubinometers (TcB), the simulations were incapable of capturing population-level heterogeneity and thus evaluating underlying factors contributing to measurement bias. Here, an in-silico MC platform was developed to investigate how population-level heterogeneity impacts Pulse Oximeters and TcB devices. The results demonstrate that fundamental biases in optical measurements exist and are exacerbated by inequitable regulatory guidelines. These findings were used to further demonstrate the impact of changes in regulatory guidelines that can affect measurement accuracy and clinical decision-making. Additionally, simulation results were used to inform the development of spectroscopic oximetry and demonstrate the techniques clinical feasibility and potential to improve accuracy in a human-subjects pilot study. In the case of the NIRS bone quality assessment, a lack of fundamental knowledge of tissue optical properties to allow simulations to inform relative contributions from different tissue features to the overall signal or explore optimization of device design. Studies were performed to collect previously unreported optical properties from musculoskeletal tissues, and this data was used to perform MC simulations which informed bone contribution to NIRS signals and in turn resulted in the design and preliminary characterization of next-generation fiber optic probes for real-time non-ionizing assessment of bone quality. Collectively, this dissertation demonstrates the impact of advances in MC simulations of light-tissue interaction across pressing clinically focused engineering challenges.
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