gms | German Medical Science

Objective: Tactile intraoperative information is important for the neurosurgeon’s decision in tumor surgery. The haptic experience together with visual inspection through the microscope enables the surgeonto distinguish tumor tissue from healthy brain tissue.In this study, a standardized intraoperative indentation measurement is carried out to detect elasticities of tumor tissue quantitatively. This study is part of a comprehensive BMBF project (FKN: 13N14664) aimed at optimizing the resection of brain tumors through novel solutions, while minimizing surgical risks of functional damage.

Methods: In vivo-detected tumor elasticities of fresh tissue samples are measured within 5 minutes directly in the operating room. For this purpose, a metallic test specimen with cylindrical dimensions is pressed into the soft tissue and the counterforce is determined with respect to indentation depth. An objective measure of tumor elasticity is Young's modulus whichis determined by indentation for different specimens of each tumor. The resulting elasticities are correlated with neuropathological tissue properties, preoperative MRI imaging and the tactile impressions of the surgeon.

Results: The indentation measurementsare carried out on gliomas, metastases and meningeomes. There is a strong heterogeneity of local elasticity within each tumor. Generally, however, there is a systematic link between measured tumor elasticities and tactile findings. The intraoperative mechanical elasticity measurements of this study open up possibilities for distinguishing between healthy and tumor tissue. It is thus an alternative method to established intraoperative onlineelastographic ultrasound and MR elastography.

Conclusion: As far as the current scientific state of the art is concerned, there is no elastic data from indentation measurements of brain tumors measured in vivo. Thus, for the first time, such a reference system for tumor elasticity in brain tumors is to be established, which is the basis for an automated intelligent intraoperative detection of tumor tissue. For example, the automated adaptation of the supplied ultrasound energyduring the resection of brain tumors is a possible application.