Hessel Wijkstra is part-time Full Professor in the Signal Processing Systems group. He is also principal investigator in the department of Urology of the AMC in Amsterdam. His research focuses on medical imaging, especially contrast-enhanced ultrasound. His main interest is the clinical validation and implementation of advanced imaging technology as developed in the Signal Processing Systems group.
The focus of research is initially on prostate cancer - hard to visualize, usually only detected at a late stage and the second-highest cause of cancer deaths in men. Perfecting visualization techniques for prostate cancer would enable more effective screening, targeted biopsies and more timely and less radical treatments. The technology can be applied to other cancer types as well. Angiogenesis, the aberrant growth of new blood vessels that supplies growing tumors with the oxygen and nutrients to become malignant, is a factor in most cancers.
Wijkstra, an engineer among urologists and a urologist among engineers, believes engineers can help generate tremendous progress in medical care, improve diagnostics and treatment and help to realize more cost-effective care.
Engineers need to truly become part of the medical world and understand the requirements and needs of clinicians to be able to deliver the improvements they are capable of.”
Hessel Wijkstra holds an MSc and PhD in Electrical Engineering from Twente University. His interest in medical and clinical research led him to accept an appointment at the Urology department of the Radboud Medical Center in 1989. In 2004 he moved to the Urology department at the Academic Medical Center in Amsterdam in 2004. His intensive collaboration with Massimo Mischi at the Eindhoven University of Technology led to an appointment as part-time professor in the Signal Processing Systems group in 2010.
Clinical Trial ProtocolEuropean Urology Open Science (2023)
Pharmacokinetic modeling of the Second-wave Phenomenon in Nanobubble-based Contrast-enhanced UltrasoundIEEE Transactions on Biomedical Engineering (2023)
Multiparametric ultrasound and machine learning for prostate cancer localization30th European Signal Processing Conference, EUSIPCO 2022 (2022)
How reliable is endoscopic stone recognition?Journal of Endourology (2022)
Pharmacokinetic modeling of PSMA-targeted nanobubbles for quantification of extravasation and binding in mice models of prostate cancerMedical Physics (2022)
- Adviseur, Angiogenesis Analytics bv