AG Wintergerst

Focus on finding reliable endpoints to quantify intraocular inflammation using novel imaging techniques and automated image analysis

• Establishment of new qualitative and quantitative prognostic biomarkers for uveitis intermedia, posterior and panuveitis

• Validation of objectifiable readouts for intraocular inflammation suitable as a structural clinical endpoint for intervention studies

• Multimodal approach using non-invasive imaging methods

• • OCT-Angiography
    • enables high-resolution visualization of retinal and choriocapillary perfusion and analysis of the effects of inflammation on the microcirculation

• • Anterion -OCT
    • enables high-resolution visualization of the anterior segment - currently we’re probing the device for imaging of inflammatory cells in the anterior chamber and anterior vitreous

• • Multimodal Fundusautofluorescence (FAF)
    • promising approach in the diagnosis and monitoring of posterior uveitis and panuveitis, as changes in the FAF can be used to assess disease activity not visible by funduscopy or conventional color fundus photography

• • Slit-Lamp Imaging
    • color photography represents an optimal interface between conventional slit-lamp examination and novel imaging methods

Smartphone-based fundus imaging (SBFI)

SBFI can be widely used for the detection of several eye diseases of the fundus with the help of medical assistants, who transfer captured images to telemedic grading centers. This method brings out its benefit in underserved rural or urban areas, where it improves the eye care access and lowers the barrier for less privileged populations to undergo a medical examination. The main focus of our SBFI approach as of right know is Diabetic retinopathy (DR). An extension of this screening towards glaucoma, retinopathy of the premature, and other retinal diseases is planned and its feasibility has been shown.

Artificial intelligence (AI)

In collaboration with Microsoft and the Sankara Eye Foundation in Bangalore, India, we are developing artificial intelligence algorithms with a low-cost approach in association with smartphone-based image capturing in order to improve cataract surgery outcomes in LMIC with the help of AI powered direct response teaching systems. Additionally, in cooperation with the University of Maastricht, the University of Bonn computing department, and the Sankara Eye Foundation, we are developing AI algorithm for automated retinal imaging analysis, which allow to support grading ophthalmologist to improve the efficacy, as well as It gives the opportunity of immediate orientating diagnostic response for patients in screening areas, where no doctor is present. The feasibility for Diabetic retinopathy as well as glaucoma screening has been demonstrated.

The simplicity of SBFI

The SBFI principle of scaling is to teach medical aid personnel in SBFI with the help either of an e-Learning class based on the University of Bonn e-learning platform, which can be hosted locally on each project partners server and has shown good results in medical aid personnel teaching. Alternatively, in-person teaching is employed, where local doctors are instructed in SBFI to disseminate knowledge locally to their medical aid personnel. These personnel then conduct screening camps in hard-to-reach rural or urban areas without proper medical healthcare service access.

Medical assistants then captures images in vision camps using SBFI, which are then uploaded into the digital patient health record app. Within this app, results can be retrieved and telemedic doctors can grade those captured images.

• iOS
• Android  

Patients finally get results in which time period they may need a checkup or whether they should travel to the closest hospital for treatment if necessary.

International Collaboration Partners

We are proud of our cooperation with several namely institutions worldwide mainly in Low - middle Income Countries (LMIC).

India

Since 2016, we have successfully partnered with the Sankara Eye Hospital in Bangalore and the Sankara Eye Foundation, led by Dr. Kaushik, in telemedical smartphone-based DR Screening. Together, we have established several vision camps, as well as our the Sudarshan Eye Sight app. Presently, we are continuing this work and have extended our collaboration to our new cataract surgery improvement project.

Bangladesh

For several years, the ORCD Bangladesh, an organization dedicated to rural development and the University of Bonn have collaborated on several projects to enhance eye health in Bangladesh. Starting in 2022, we initiated the implementation of our SBFI approach in Bangladesh to further improve access to eye healthcare in Bangladesh.

Nigeria

Since 2022, we have started our Collaboration with the University of Calabar Teaching Hospital in Nigeria, where we are currently jointly establishing a SBFI DR Screening approach.

Ghana

Additionally, since 2022, we have begun a partnership with the University of Cape Coast in Ghana, where we have so far dedicated our work towards research on the adaptability of our SBFI approach to different smartphones. We aim to broaden our approach here and implement regular DR screenings based on our collaboratively established SBFI approach.