Differentiation of soft biological tissues and phantoms using a piezoelectric tactile sensor for applications in brain tumor resection

authored by

David Oliva Uribe

supervised by

Jörg Wallaschek

Abstract

The mortality rate of brain cancer is one of the highest next to lung cancer. Unfortunately, for brain cancer there are no well-established preventive procedures to avoid risk factors. The surgical procedure to remove (i.e. resection) malignant brain tumors is a critical task that requires from a surgeon well-trained skills to perform with high precision the evaluation of the brain tissue during the operation. Additionally, during skull opening, the so-called brain shift effect causes undesirable brain movements that introduce errors in the neuro navigation system, causing the loss of the exact location of the tumor. In practice, a surgeon uses the information acquired by the visual sense and the tactile perception. While visual information is magnified by the use of a microscope, tactile perception is diminished by the used of surgical instruments. As a consequence, brain tumor resection depends on the grade of sensibility of surgeon's tactile ability and subjective perception.
This thesis presents a piezoelectric tactile sensor aimed to be utilized as an intraoperative tool by neurosurgeons to improve the tactile evaluation of brain tissue, in particular, delineation of tumor boundaries where distinction between healthy and tumorous tissue is highly challenging because of their slight differences in mechanical properties.
The proposed sensor uses random phase multisines to generate mechanical vibrations. The mechanical information is transformed into electrical signals and the Frequency Response Function (FRF) is used to estimate mechanical properties such as stiffness and damping. Multisine excitation allows the tactile sensor to perform a fast measurement procedure for intraoperative use.

Organisation(s)

Institute of Dynamics and Vibration Research

Type

Doctoral thesis

No. of pages

112

Publication date

2017

Publication status

Published

Sustainable Development Goals

SDG 3 - Good Health and Well-being