Neuropathological analysis of intraoperatively obtained, fragmented tumor tissue using aspirate histology
This BMBF-funded study is being conducted at the Department of Neurosurgery at the Lübeck Campus under the direction of Dr. Matteo Mario Bonsanto in collaboration with the Medical Laser Center Lübeck (MLL), the Institute of Biomedical Optics (BMO) at the University of Lübeck and the Department of Neuropathology at the University Medical Center Hamburg Eppendorf (UKE) - planned duration until September 2027. The Federal Ministry of Education and Research is funding this joint project with a total of €3.3 million as part of the “Health Research Germany, Medical Technology” framework program.
Aims of this research project
The aim of this research project is to develop an innovative neuropathological examination method for brain tumor tissue. The method is based on the use of an ultrasound aspirator, which is already routinely used in brain tumor resections.
The objective is to support the resection of brain tumors while minimizing the risk, avoiding over-resection and simultaneously analyzing the removed tumor tissue neuropathologically. This is to be achieved through a novel technical development in order to achieve the best possible result for patients.
Background
The ultrasound aspirator generates ultrasound waves that are transmitted to the tumor tissue and can fragment it. The tissue fragments (aspirate) are removed from the resection area by suction after the automatic addition of saline solution. The aspirate was previously considered a "waste product" and will now be analyzed using AI. The information contained in the aspirate about the type of tumor and the gradient of the tumor cell count will be used to develop a new method of histology - Imaging Flow Histology.
During intra-operative tissue aspiration, the aspirate will be subjected to histological flow analysis using Spectro-temporal Laser Imaging by Diffractive Excitation (SLIDE) microscopy. In addition to the novel application of imaging analysis of the actual waste product aspirate, the high speed enables an extremely high throughput of image data. The digital images generated in this way are analyzed by computer using innovative algorithms and artificial intelligence to provide a neuropathological diagnosis.
Aspirate analysis thus represents an alternative method to intraoperative frozen section diagnosis. The aim of this research project is to compare the value of this digital diagnostic method with the standard of classical neuropathological HE-based frozen section diagnosis.