Groningen/Amsterdam, the Netherlands – The University Medical Center Groningen (UMCG) has announced the approval of a Public-Private Partnership (PPP) grant in collaboration with WSK Medical for an innovative project aimed at improving the early detection of cancer in oral cavity. This pioneering project is part of three artificial intelligence (AI) projects focussing on the upper aerodigestive tract and will leverage AI to enhance the diagnostic process for patients suspected of having cancerous or precancerous lesions in the oral cavity and throat, with the goal of reducing unnecessary referrals and streamlining patient care.
These projects aim for early recognition of primary cancer or recurrence and significantly can expedite treatment of patients where . To support this, the project seeks to advance and implement AI technologies to aid in the evaluation of images of the oral cavity during routine visual examination.
Head and neck cancer (HNC) is a term for malignancies of the upper aerodigestive tract (oral cavity, pharynx and larynx). HNC care is centralized in the Netherlands in the UMCG and 7 centers. Patients suspected of oral, pharyngeal or laryngeal cancer are visually examined by head and neck oncologic surgeons using visual inspection with or without additional optical instruments (like flexible endoscopes). Patients are referred to a certified HNC-center for diagnosis, treatment and follow-up for 5 years each 2-6 months. Nowadays, the question arises whether all patients need to travel to an HNC-center for diagnosis or follow-up by visual evaluation. Digital imaging techniques using high definition (HD) visual assessment allow transfer of these digital data from general hospitals in the region to a HNC center for assessment of selected patients by expert head and neck oncologists. Artificial intelligence (AI) during image analysis could be even more helpful in selection of patients to be evaluated in a HNC center for the detection of early (recurrent) cancer. Zeno AI is a novel AI-software tool developed by WSK Medical which aims to transfer the expertise of head and neck surgeons to the out-patient clinics. Zeno AI is the first AI system that offers real-time feedback during laryngoscopic procedures by providing predicted localization and classification of potential benign and malignant lesions of the larynx. The ongoing development and clinical validation of Zeno AI will play a crucial role in this initiative. Currently, two related projects are in progress (KWF and the MKB-call of Health-Holland), focusing on refining Zeno AI to distinguish benign and normal mucosal tissues from potentially malignant changes in subregions of the head and neck, including using Zeno AI for telemedicine purposes. The project funded by this PPP grant aims to further enhance Zeno AI for use in the oral cavity using digital cameras.
Once trained and tested, the Zeno AI oral algorithm will undergo clinical validation at UMCG. The ultimate goal is to integrate this technology into telemedicine practices, enabling the remote evaluation of images from regional hospitals by AI before they are transferred to UMCG’s oncology center. This implementation promises to enhance patient care by reducing the number of unnecessary specialist visits and ensuring that cases requiring immediate attention are prioritized.
Overview of common sites for oral cavity cancer.
“The approval of the PPP grant with UMCG is another step in the right direction of utilizing Zeno AI to assist – in real-time – in detection and classification of benign and malignant lesions in various subregions of the head and neck during routine examinations. The aim of Zeno AI is to capture the specialised knowledge of head and neck oncologists and dental oncology experts and make it available for ENT and dental clinicians (and in the future first-line care) to equip them with an easy, flexible and real-time AI solution that assists during endoscopic examinations and therefore provides support in getting real-time predictions on lesion location and lesion type, potentially enabling early detection and faster treatment, resulting in a better disease outcome in the end”, says Marius Wellenstein, CEO and founder of WSK Medical.
“Combining data from these three projects will speed up the process of AI assisted detection of cancer in oral cavity, throat and voice box. All AI-algorithms can learn form each other and we as oncologists will probably learn how to implement this new kind of AI-assisted cancer detection in care pathways. We expect to increase efficiency in diagnosis and treatment for those patients. The collaboration between WSK and UMCG is a good example how to combine technical expertise with clinical experience of care professionals as has been advised by the National Care Agreement (Integraal Zorg Akkoord) ” says Boudewijn Plaat, project leader of all three Head and Neck Cancer detection AI-projects
The collaboration between UMCG and WSK Medical is expected to drive significant advancements in this field of oncology, positioning the project as a leading example of how AI and telemedicine can transform cancer diagnosis and treatment. The successful implementation of Zeno AI will potentially reduce healthcare costs, decrease patient anxiety, and improve outcomes through earlier, more precise diagnosis.
For more information, please contact: Marius Wellenstein (CEO of WSK Medical).
About WSK Medical
WSK Medical develops Artificial Intelligence software solutions for the detection and classification of cancer. Our aim is to bring you the most advanced Artificial Intelligence technologies to assist Clinicians and Doctors. We do this by working in partnership, to develop sophisticated AI systems. For more information about our AI solutions, please contact us.
About UMC Groningen
The oncologic surgeons of The Department of Otolaryngology / Head and Neck surgery of the University Medical Center Groningen provide care for patients with malignancies of the head and neck area. As members of one of the eight Dutch Head and Neck Oncology Centers, they combine academic patient care in a multidisciplinary team with highly rated scientific research.
