PhD Thesis Defense: Harshavardhan Devaraj

To attend via videoconference, email harshavardhan.devaraj.th@dartmouth.edu

"Towards Tissue Interface Detection with an Electrical Impedance Sensing Surgical Drill"

Abstract

There is a high likelihood of losing teeth during a person's lifetime. Loss of teeth leads to poor mastication, unhealthy oral conditions, and low self-esteem. Implanting an artificial replacement tooth is an effective treatment that is becoming increasingly common. However, when surgically drilling to prepare the bone for these implant procedures, there is a high risk of nerve injury and sinus perforation. A system able to provide real-time surgical feedback regarding the proximity of these tissues while drilling could help reduce the risk of these injuries. An electrical impedance-based sensor integrated into a standard surgical drill tip has been designed to measure local tissue impedance and provide useful feedback to surgeons when drilling near nerve and sinus tissues. By coupling a partially insulated drill bit, in which the active sensing tip is exposed, with a shoulder pad return electrode, localized electrical impedance can be measured in a monopolar configuration. Previous studies have shown the ability of this system to distinguish ex-vivo and in-situ bone based on their different impedance properties. This thesis discusses contributions made in advancing this technology toward clinical translation.

The device was evaluated and optimized for sensing using bench top experiments and a simulation framework based on the finite element method (FEM). The accuracy of the FEM framework was improved through use of a novel empirical contact impedance model with adaptive mesh refinement strategies. FEM models simulating a drill bit within bone and approaching an interface closely matched benchtop measurements with an overall mean experiment-simulation mismatch of +1.7%. Using the simulation platform, the optimal sensing geometry for a 2mm diameter twist-drill was determined to include a 1.6mm exposed length at the drill bit tip.

An in-vivo animal study protocol was developed and followed using 14 adult pigs. At least 8 holes per pig were drilled into maxilla and mandible, toward nerve and sinus interfaces, using the partially insulated drill bit. Monopolar electrical impedance was intermittently recorded along the length of the osteotomy between the drill bit tip and a shoulder return electrode. The drill tip was intra-operatively tracked and registered to post-operative microtomography sections of the bone. Bone density along the osteotomy was determined from microtomography analysis. Results of the in-vivo study are presented and discussed: For pigs aged 16–23 months (N=10), statistically different (p<0.0336) mean bone density changes were observed between a) when approaching nerve and sinus tissue interfaces from cancellous bone compared to b) when approaching cancellous bone from bone surface. The recorded impedance data was compared with bone density estimations. Significant phase differences were observed between cortical and cancellous regions of bone at 1kHz (paired t-test, p=0.0125). Multiple combinations of resistance (R), reactance (X), magnitude of impedance (|Z|), and θ between two different frequencies (100Hz-2.5MHz) showed significant differences between these groups (p<0.01). A linear regression analysis of density vs a) θ at 1kHz and b) impedance parameter ratios on a hole-by-hole basis was done. The average coefficient of determination (r²) for θ at 1kHz, R ratio, X ratio, |Z| ratio and θ ratio were 0.3050, 0.2612, 0.3443, 0.3411 and 0.2536, respectively. These findings suggest some promising aspects along with challenging limitations associated with in-vivo translation. Methods to overcome these limitations are discussed with suggestions to mitigate them for future development of this technology.

Thesis Committee

• Prof. Ryan Halter (chair)
• Prof. Ethan Murphy
• Prof. Xiaoyao Fan
• Prof. Kofi Odame
• Prof. Ørjan G. Martinsen (University of Oslo, Norway)

Contact

For more information, contact Theresa Fuller at theresa.d.fuller@dartmouth.edu.