Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Doctor of Philosophy

Program

Biomedical Engineering

Supervisor

Carson, Jeffrey

Abstract

Approximately 19% of breast cancer patients undergoing breast conserving surgery (BCS) must return for a re-excision surgery due to positive margin reported by pathology. This problem is mainly associated with lack of intraoperative cancer margin assessment tools. Our previous work demonstrated that lipid-weighted photoacoustic imaging (PAI) can be used intraoperatively to successfully differentiate between cancerous and healthy tissue with high sensitivity. However, the technology was cumbersome and significantly prolonged the procedure time. The goal of this work was to develop a compact hand-held probe, working on lipid-weighted PAI principles, that can provide feedback during BSC without significantly altering the surgical workflow. In addition, one of the early goals was to develop a method for estimating optical properties of imaging phantoms to assist in the evaluation of imaging devices under development.

In this thesis, we present (i) a novel method for optical property estimation in turbid media for PAI phantom quality assurance, (ii) perform a proof-of-concept study using a prototype hand-held PAI probe and use the lessons from this study to (iii) develop a second-generation hand-held PAI probe with integrated optical positional tracking system and show preliminary imaging results.

We developed a method for estimating the optical fluence distribution in an optically scattering medium using a full-view PAI system. Volumetric similarity (dice coefficient) between simulation and experimental results ranged from 51 to 82%, with an average of 76%. The system was also able to accurately estimate the reduced scattering coefficient for values below 0.5 mm-1.

The prototype probe incorporated a single acoustic sensor, a 1-to-4 optical fibre bundle and an axicon lens for light delivery. It was tested on imaging phantoms designed to mimic positive breast cancer margins and was able to detect margins as small as 1 mm in width. While several imaging artifacts were present related to limited view-angle and frequency bandwidth the results showed promise for detection of residual breast cancer tissue during BCS.

Subsequently, a miniaturized, fully hand-held version of the prototype probe with an integrated optical tracking system was developed. The optical tracking reported average translational and angular accuracy of 0.14 mm and 0.12°, respectively. Free-hand PAI showed accurate reconstructions of point-like objects, with reduction in axial and lateral resolution of 0.12 and 0.94 mm, respectively, compared to the resolution achieved using a robot for positioning. Preliminary imaging showed that the surface of an object can be successfully reconstructed and visualized in three-dimensions using this free-hand single-sensor imaging approach.

This work establishes the foundation for the use of PAI for intraoperative breast cancer margin assessment. The next step involves performing a clinical study to estimate the specificity and sensitivity of this approach towards positive margin detection. In order to accomplish this, hardware updates are required to enhance the image acquisition speed and enable real-time 3D PAI reconstruction. Following the improvements the developed technology has the potential to be used during BSC and in return lower the number of required re-excision surgeries.

Summary for Lay Audience

Most patients diagnosed with early breast cancer (stage I or II) undergo cancer removal surgery called breast conserving surgery (BSC). Approximately 19% of patients undergoing BCS must return for a secondary surgery due to incomplete cancer removal. This problem is mainly associated with lack of information about the cancer location during the surgery.

Our previous work demonstrated that a technique called photoacoustic imaging (PAI) can be used during the surgery to help the surgeon to locate the cancerous tissue. In PAI, lasers are used to illuminate tissue. This laser light is absorbed by tissue and generates ultrasound (US) waves, which can be detected using ultrasound sensors. In this previous work specific light that is only absorbed by breast fat tissue was used and it proved to be very accurate at determining what is cancerous and what is healthy tissue.

However, the system was too bulky to be used inside the operating room (OR) and prolonged the procedure time beyond what would be acceptable. The goal of this work was to develop a hand-held tool, based on the same principles, that is more compact and does not significantly affect surgery duration.

In this study, first a proof-of-concept study using a prototype hand-held PAI probe was performed, followed by a study reporting the design of the final version of the hand-held probe along with the first imaging results.

The prototype probe consisting of a single US sensor, an optical fibre bundle and a lens for laser light delivery was tested on imaging phantoms designed to mimic breast cancer and demonstrated ability to detect mimicked cancer lesions as small as 1 mm in width. Despite several imaging artifacts (distortions or errors in the image) present in the images, the results showed this imaging approach has potential for use during BCS.

Smaller version of the prototype probe with an included positional tracking system was developed. The positional tracking system is needed when the tool is freely moved by the surgeon and not attached to a mechanical arm moving the tool. The tracking system was able to locate the tool with average accuracy of 0.14 mm when moved straight and 0.12° when tilted. Images using the positional tracking system had only slightly lower resolution compared to resolution achieved using a mechanical arm. Preliminary imaging of breast cancer phantoms and breast cancer tissue showed feasibility of the concept.

This work establishes the foundation for PAI use during BCS. The next step involves performing a clinical study to estimate how accurately this approach can detect cancerous tissue. In order to accomplish this, hardware updates are required to enhance the image acquisition speed and enable real-time image reconstruction. Following the improvements the developed technology has the potential to lower the number of required secondary surgeries.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

Share

COinS