Robotic assisted microsocopy for surgical resection margin assessment

Lead Research Organisation: University College London
Department Name: Computer Science

Abstract

Robotic assisted microsocopy for surgical resection margin assessment

Resection surgery can be a very important tool in treating many types of cancer, where cancerous tissue is surgically removed from a patient with the aim of preventing further spread. A significant challenge for surgeons is identifying the extent of the cancer (called the margin) to ensure as much cancerous tissue as possible is removed during surgery. The availability of better intraoperative tools to identify cancerous tissue would greatly improve the success rate of resection surgeries. Currently available tools range from basic manual palpation to frozen section intraoperative pathology, which involves keeping the patient under anaesthetic while an excised sample is transported to a nearby laboratory and assessed by a pathologist. The patient can be kept under anaesthetic for up to an hour in this case and the technique is not suitable for many types of surgeries.

This project will investigate novel imaging and measurement modalities with the aim of identifying cancerous tissue. Two possible areas of investigation will be 1) non-contact optical methods and 2) direct measurements of tissue properties such as elastic stiffness. In the former, the student will develop a mathematical scattering model for human tissue that is linked to known properties of cancerous tissue that can be probed using reflectance spectroscopy, where a change in the reflected spectrum will indicate the presence of cancer without the need for excision or staining. The student will also develop an optical phantom to test the accuracy of the model and the feasibility of using reflectance spectroscopy in an intraoperative setting. The latter investigation will use atomic force microscopy to accurately measure mechanical properties of cancerous tissue such as elastic modulus and combine these direct measurements with novel computer vision techniques to localize these measurements on bulk tissue and extrapolate them to draw larger conclusions about the tissue as a whole, which has not previously been achieved. This would provide a crucial link between easily measured properties of bulk tissue and the underlying structure that contributes to the development of cancer. The student will develop expertise in both digital microscopy-based histopathology and computer vision with the aim of developing better intraoperative measurement techniques for localizing cancer without the need for a full pathology workflow.

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Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/R512400/1 01/10/2017 31/03/2022
1931546 Studentship EP/R512400/1 25/09/2017 30/03/2022 Lydia Zajiczek
 
Title AFM liver tissue measurement dataset 
Description This dataset consists of 27 tissue samples collected from 7 patients suffering from colorectal or pancreatic cancer metastasis who underwent curative liver resection surgery. Tissue punches were collected from healthy and tumour regions during surgery. Each section was measured using an atomic force microscope (AFM) to extract the elastic modulus of the tissue at multiple sites. Microscope images were captured of the whole sample as well as at each measurement site, allowing for spatial localization of each measurement. In some cases, the section was stained post-hoc with haemotoxylin and eosin (H&E), providing ground-truth validation of tissue pathology. 
Type Of Material Database/Collection of data 
Year Produced 2021 
Provided To Others? Yes  
Impact This dataset was used in a publication that is currently in progress and has been invited to be submitted to Nature Biomedical Engineering 
URL https://www.ucl.ac.uk/interventional-surgical-sciences/afm-liver-tissue-data
 
Description Collaboration with University of Toronto - Funded by ESRC "Self-guided Microrobotics for Automated Brain Dissection" 
Organisation University of Toronto
Country Canada 
Sector Academic/University 
PI Contribution We are developing AI systems to study microscopic images and drive micro-scale robot control for cell harvesting
Collaborator Contribution UoT develop the optical system and the harvesting robot capabilities. They are also leading the clinical data management and translational pathway.
Impact Multi-disciplinary between computer science, engineering, chemisty and neuroscience.
Start Year 2020
 
Title AFM GAN 
Description Style transfer architecture for inferring pixelwise elastic modulus values of human tissue samples from grayscale microscope images. Based on the Pix2Pix architecture implementation in Keras by Erik Linder-Norén. 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact Associated with a journal article that is currently in progress to be submitted shortly. 
 
Title AFM Registration 
Description Comprehensive set of MATLAB processing functions for localizing AFM measurements on thick tissue sections, given AFM measurement data and microscopy images of unstained tissue. 
Type Of Technology Software 
Year Produced 2021 
Open Source License? Yes  
Impact This software is associated with a journal article that is currently under revision and due to be submitted shortly. 
 
Description Public engagement event (Surgical Standoff) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Supporters
Results and Impact 5 researchers gave 1 minute talks on their research in surgical science over four rounds, and on each round, a researcher was "voted off" based on how engagign the panel of judges found their presentation. The judges were largely from external organizations e.g. patient experience charities.
Year(s) Of Engagement Activity 2020
URL https://www.youtube.com/watch?v=QEcoGTEf_qU
 
Description Science Museum Lates 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Public/other audiences
Results and Impact The general public attended the Science Museum Lates event, and we gave several demonstrations on the use of robotics in surgery. It was very recent so the impacts are still unknown but people were very interested in how surgical robotics is evolving.
Year(s) Of Engagement Activity 2020
 
Description UCL Cancer Domain Symposium 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Local
Primary Audience Other audiences
Results and Impact A 5 minute talk was given during the Early Careers Network section, which sparked two separate statements of interest in future collaboration from different research groups, one that is in my research centre that I was previously unaware of.
Year(s) Of Engagement Activity 2019
URL https://www.ucl.ac.uk/research/domains/cancer/events/ucl-cancer-domain-symposium-2019
 
Description WEISS International Advisory Board Meeting 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact The International Advisory Board of my research centre visited and were given tours around the laboratory spaces as well as a poster presentation which I prepared two posters for and presented at.
Year(s) Of Engagement Activity 2019