Hardware design, optimization and fabrication for a portable medical device to monitor chronic kidney disease

Author: Anh Tran Tam Pham

Pham, Anh Tran Tam, 2023 Hardware design, optimization and fabrication for a portable medical device to monitor chronic kidney disease, Flinders University, College of Science and Engineering

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The research in this thesis addresses the important question of how to develop a point of care (POC) device that can efficiently and accurately measure urinary albumin and creatinine levels to facilitate the monitoring of chronic kidney disease. It provides a new approach to the integration of fluorescence and colorimetric measurements and presents a comprehensive set of parameters that should be considered in the hardware design and manufacture of an optical POC device. Typically, the development of a POC device requires the harmonization of consumables, hardware, and software. Therefore, although the research focus is on hardware development, the impact on consumables and software are also considered. In this study, strategic choices for those hardware parameters, including decisions about the excitation light source, calibration method, optical filter of the output sensor, and the self-processing module, are presented in a scheme that comprehensively combines all three components. This differs from previous studies that generally focus only on developing some parameters of a single component. This research proves the feasibility of the proposed approach by evaluating the developed devices' performance through clinical validation using real urine samples from patients with kidney-related diseases. The results demonstrate that the developed POC devices have comparable results with clinical measurements. Finally, the research presents the limitations of the current developed POC devices in measuring urine albumin and creatinine to give an indication of the CKD stage for the patients and suggests proposed solutions for future works to further improve the developed devices' performance and expand clinical applications.

This research has provided several contributions to knowledge in optical measurement and hardware design features. For optical measurement features, the research introduces a simple and affordable process to fabricate reference samples, which are made of epoxy resin and cost around AUD 15 cents per sample. These reference samples support the ratiometric method in the calibration and referencing processes, which minimises the error in fluorescence measurement between the expected and simulated values to below 2 % across different measurements over 10 months of urine sample testing. For hardware design features, the research has provided step-by-step instruction for developing a POC device, which performs fluorescence or colorimetry measurement to monitor the albumin and creatinine levels in a urine sample. Also, the developed devices, using the modular structure with the “plug-in and plug-out mechanism”, have proved their ability to examine solution tests for monitoring different biomarkers under various optical conditions, which follow fluorescence and colorimetric measurements. Moreover, the developed devices use the Raspberry Pi, a single computer module, to locally analyse the optical images and provide the albumin and creatinine results in real time, and to enable users to communicate with medical specialists for healthcare discussion or appropriate therapy decision making. The findings of this study can contribute to the development of more cost-effective and accurate POC devices for monitoring kidney-related diseases, which can improve the diagnosis and management of these diseases in areas less served by clinical laboratories.

This thesis presents the development of two devices for running fluorescence and colorimetry measurements. The ability of both devices to perform the corresponding optical measurements have been confirmed. Their results measuring albumin and creatinine concentrations in artificial urine samples show a linear correlation with a commercial fluorescence spectrometer and a microplate reader, which are currently used in clinical laboratories. In the later stages of development, devices were clinically evaluated with tests for estimating albumin and creatinine concentrations on 88 urine samples from real patients having kidney related diseases. Both devices’ testing results have been statistically analysed using paired samples t-test and have shown no significant difference when compared with those provided from SA Pathology. The fluorescence open platform can provide albumin results in real time, and 86 % of the urine samples containing albumin concentration below 300 mg/L were estimated to have CKD status indications in line with the clinical method. Meanwhile, the colorimetry device currently shows a linear correlation in estimating the creatinine level in the urine samples with the clinical method. Moreover, the research has proved that the re-dilution method will potentially improve the quality of creatinine level estimation from the urine samples with strong background colour. Finally, the research utilizes the albumin and creatinine values calculated from both devices to establish the albumin-to-creatinine-ratio (ACR), which is one of the important factors for monitoring CKD in pathology. The calculated ACR values show a linear relationship with the ones from SA Pathology. From the Bland Altman analysis for those ACR values, the difference between the proposed devices and SA Pathology has a mean of 0.631 mg/mmol, showing the potential for these devices to be compared with the clinical method in estimating the ACR values to support CKD monitoring.

Keywords: Chronic Kidney Disease, Point of care, Portable Medical Device, Fluorescence, Colorimetry, Aggregation-induced emission, ASSURED, Microalbumin, Human Urine, Artificial Urine, Raspberry Pi, CMOS camera, Hardware, Spectrometer, Calibration, 3D printing, Clinincal Trial, Open platform for optical measurement.

Subject: Engineering thesis

Thesis type: Doctor of Philosophy
Completed: 2023
School: College of Science and Engineering
Supervisor: Youhong Tang