Quantifying inner ear diseases

Wilhelm Wimmer, February 2023

Inner ear diseases are highly prevalent with daily constant exposure to noise and the high stress levels of modern technologized society. Today, many of these disorders, e.g., sudden deafness, Meniere’s disease, or vestibular migraine, remain poorly understood. Tackling them from an engineering perspective leads to exciting multidisciplinary approaches that may have great potential for patient-specific and effective treatment.

The ear is often underestimated in its complexity. The ear is extremely sensitive – it can, for example, perceive tiniest deflections corresponding to the size of atoms—while at the same time offering a huge dynamic range that tolerates very loud sounds. The “sensor” ear also performs impressively in terms of frequency range and discrimination, as well as spatial hearing, making it a fascinating wonder of evolution.

There is still so much that we do not understand about our hearing sense. A remarkable example is that although the snail-like shape of the cochlea was discovered about 500 years ago, we still do not really know why this shape is present in humans (and in general, only in mammals). So, to understand hearing physiology and further hearing impairment, I decided to also investigate basic mechanisms related to the sense of hearing. And one of the most exciting research projects I have been working on is about trying to investigate the “cochlear shape mystery”.

The cochlear implant is the living proof of what medical technology can achieve.

The cochlear implant is the living proof of what medical technology can achieve. It has been around for more than 30 years, and it is the first technical solution ever that has managed to successfully replace a human sense (in itself unique!). With it, children born deaf can learn to speak normally, go to school, listen to music, and work like everybody else.

When it comes to hearing implants to restore hearing loss, more emphasis is now put on preserving residual hearing and on not damaging delicate inner ear structures during the surgical access and placement of a cochlear implant. Towards this goal, our group has been pioneering the field with radiology-based surgical planning approaches and computational models for minimally invasive and patient-specific treatment procedures. We hope that ultimately the fusion of radiological information (i.e., improved anatomical knowledge) with audiological procedures (e.g., the fitting of audio processors) will offer the patient a quicker recovery and better hearing outcomes, also for other kind of implants, such as bone conduction implants.

I have been fascinated with medicine since watching a cartoon series about the human body (“Es war einmal das Leben…”) as a child. Then there is my other passion for music. I started playing the violin from the age of six and later the electric guitar. So, medicine, music, and hearing were always very dear to me. I studied Biomedical Engineering at the Technical University of Graz, and combined it with the Audio Engineering course at the University of Music and Performing Arts in Graz. During my master’s studies, personal reasons shifted my focus to Bern and I discovered the ARTORG Center. I got accepted to complete my thesis here in the context of an ERASMUS stay. Afterward, I stayed for a PhD on cochlear implants at the ARTORG and in 2017, I was offered to lead the Hearing Research Lab together with Prof. Marco Caversaccio as clinical co-head at the Inselspital. Since then, our group has been focusing on Experimental Audiology and diagnostics of inner ear diseases (hearing loss, tinnitus, vertigo), as well as image processing, computational modelling, and robotics for improved hearing implant outcomes.

For tinnitus diagnostics, there is still a lot of potential for improvement. In our lab, we have developed the first generative computational tinnitus model that simulates the perceptual responses of individual patients to acoustic stimuli. It could allow identifying patient-specific tinnitus pathologies and foresee the treatment success. The model can also help to develop new quantitative strategies in tinnitus research. Currently, we are finishing the analysis which relates the model to physiological evidence of a tinnitus biomarker in EEG recordings. These are early findings, and I will further follow up on them aiming to provide objective diagnostics for tinnitus.

Tackling research questions at the interface of different disciplines is the most enjoyable aspect of my job.

By training, I am a Biomedical Engineer with focus on Bioimaging. During my PhD, I gained knowledge in Audiology, but also Otology, Radiology, and Medical Image Analysis thanks to the close collaboration with the clinicians here in Bern, which is a trademark of the ARTORG Center. Equipped with this experience, I will continue pursuing interdisciplinary approaches that combine radiology, audiology, neurotology, and data science. Tackling research questions at the interface of different disciplines is the most enjoyable aspect of my job. It is a relatively unexplored area that I believe promises many helpful basic and clinical-translational findings.

Wilhelm Wimmer studied Biomedical Engineering at Graz University of Technology (master's) and the University of Bern (PhD). Since 2017 he has been leading the Hearing Research Laboratory group of the ARTORG Center at the University of Bern. In January 2021, he received the Venia Docendi for Experimental Audiology. His research focuses on the diagnosis and treatment of hearing loss, tinnitus, and vertigo. Between 2018 and 2019, he joined the Epoine team, INRIA, Sophia Antipolis (France) as SNSF postdoctoral fellow to investigate novel inner ear morphometric approaches. He is a member of the MICCAI society, the German Society of Audiology, the German Society for Medical Physics, the Swiss Society of Otorhinolaryngology, and the scientific advisory board of the Swiss Tinnitus League. Starting with March 2023, he will be an Assistant Professor for Experimental Audiology at the Technical University of Munich (Germany).