Development of 3D-printed Universal Adapter in Enhancing Retinal Imaging Accessibility - Aisya Amelia, Abdul Latip (Universiti Malaysia Sarawak (UNIMAS), 2025)
The concept of smartphone-based retinal image acquisition has been around for years where images of the retina are acquired using a portable device together with a smartphone. Having a device that is portable, easy to use, and low-cost enables eye care to be more widely accessible especially in geographically remote areas and enables early diseases detection for those who are in low- and middle- income populations that have very limited access to eye care. However, professionals still find this method limited to screening purposes only and incapable of competing against reference standards in terms of image quality and sensitivity. Studies have also expressed difficulty in optimizing the concept. This study investigates on existing smartphone-based retinal image acquisition devices to determine the best parameters or features for optimum image acquisition. Besides this, this study aims to develop a universal adapter that allows an existing smartphone ophthalmoscope to be used with a variety of smartphones and evaluate the performance of developed adapter. Adapter development was performed using AutoCAD 3D and Ultimaker Cura. Evaluation of performance includes stress test, and statistical and survey analysis. Finite element analysis (FEA) method was performed for the stress test where the minimum and maximum Von Mises stress and 1st principal stress were calculated and compared with PLA’s yield and ultimate tensile strength. Subjective Image Quality Assessment based on a 5-point scale involving a non-mydriatic clinical testing was performed and an end-user survey was prepared for the statistical and survey analysis. For the clinical testing, fourteen patients of age range 20 to 80 years old with various medical conditions were recruited. Images were obtained and graded by experts based on the clarity and field of view in accordance with the 5-point scale. From 140 images, 37.83% (95% CI = 22.16% to 53.47%) were clinically adequate (Grade 3 ≥) as graded by the examiners. Furthermore, median and frequency scores were calculated from the end-user survey.