SODOS

Wat het doet

The Smart Optical Diagnostic Of Schistosomiasis, or SODOS, can automatically analyse urine for the presence of Schistosoma eggs. It is designed to replace the current manual method in rural conditions and to be affordable and usable without medical knowledge.

Je inspriatie

Urinary Schistosomiasis is with over 110 million infected people one of the most common parasitic infections worldwide. Still, current diagnostic solutions are often unavailable or expensive. As a result, people do not receive treatment and are exposed to long term effects, including kidney failure and bladder cancer. Due to the clear need for a suitable diagnostic solution and the challenges this presents, I decided to work on the SODOS as my graduation project for my double master’s degree at the TU Delft. In this, I continued on the context analysis by Mirte Vendel for such a diagnostic device, and the experimental setup by Patrick Nijman.

Hoe het werkt

The SODOS analyses unprocessed urine using holography. In this, holographic images are taken of urine through a special hollow slide, and reconstructed to automatically see whether eggs of the Schistosoma Haematobium parasite are present. To capture these images, a box has been designed to block out external light and to hold a camera without lens close to the slide using springs. A laser diode casts light through the slide to create the holographic images. After a photo is taken, the urine is moved for the next photo. For this, an automatic syringe system has been designed to allow precise movement of urine in both directions. The system can be rinsed between measurements by placing a syringe with water. The SODOS is completely controlled by an internal Raspberry Pi, and includes a screen and buttons to interact with the programmed interfaces, sensors to monitor its conditions, and a retractable stand and a handle for easy transportation.

Ontwerpproces

To design the SODOS, I subdivided the product into different components that required development. These included the measurement box, the syringe system, a placement tool for the vulnerable hollow slides, and the overall physical and digital interaction. From here, parallel rapid design and prototype iterations were performed on each component individually. Prototypes were quickly realized using 3D-printing and standard parts. The components were tested with eggs in saline solution and user tests. The components had varying numbers of iterations, with 2 to 6 iterations during the last 8 months. Once the individual components were expected to meet the requirements, they were combined into a single design and prototype. This prototype also meets general requirements, such as easy transportation, connections to external devices, and internal sensors. This prototype was again tested with eggs in saline solution, after which final improvements were made, and the SODOS was born. Finally, the SODOS has been validated in Ivory Coast in June 2019. Here, 95 urine samples from villagers have been analysed by both the SODOS and manual microscopy. This to test the performance of the SODOS in the actual field, and to gather raw data to allow the optimization of the algorithms inside.

Hoe onderscheidend is het?

Currently, diagnosis of Schistosomiasis is most commonly performed using microscopy. In this, the urine sample is filtrated or centrifuged, after which it is stained before eggs are manually counted via the microscope. For this, a well-trained lab technician, expensive microscope, and disposables are required. Disposables may include filters, filter holders, syringes, and chemicals for staining. The SODOS could become an affordable alternative to the microscope, as it does not contain any of the expensive lenses of the microscope and only has syringes as disposables. As the diagnostic process is automated, the user does not require extensive training and risks of user errors are reduced. Also, a single user could operate multiple devices simultaneously. As statistical data including location, number of eggs, and quality of urine is already automatically uploaded to a central server, it can help in a country’s ability to map the prevalence of Schistosomiasis

Toekomstplannen

With the recent data of urine samples gathered in Ivory Coast, it now has become possible to optimize the algorithms for reconstruction and automatic classification, as developed by Patrick Nijman. Once these algorithms have been further developed they can be incorporated into the SODOS to turn it into a fully functional diagnostic device. Besides this, I want to simplify the current design as much as possible. Right now, there are still a lot of complex parts that could still be simplified and improved upon. This, to transform the design for the prototype into a design that could potentially be used in mass production.

Premi