The STTARR Innovation Centre is a core facility that provides fee-for-service preclinical imaging, biomedical image analysis and digital pathology image analysis for researchers at the University Health Network, University of Toronto, and surrounding academic centers. The image analysis team at STTARR will be holding its first inaugural workshop this May to train individuals in the use of Definiens Tissue Studio Image Analysis software. With whole slide scanning becoming more accessible and popular, it is advantageous to analyze the entire tissue to obtain the relevant information in the slide, rather than analyzing a small subset, which can be prone to bias and lead to non-representative findings.
Outline: This STTARR workshop is designed to inform and train interested parties in the use of Definiens Tissue Studio image analysis software. Definiens is a market leader in digital tissue pathology analysis, particularly for complex immune-oncology related biomarkers, and is in use by many pharmaceutical companies for biomarker discovery to identify meaningful companion diagnostics. TissueStudio can analyze brightfield, immunofluorescence, or imaging mass cytometry data, in a reproducible, batch format, and is the only analysis solution to provide built-in quality control / manual correction steps to ensure validation of results against a pathologist’s interpretation. STTARR has 5 years of experience utilizing the TissueStudio platform, with extensive data analysis performed on H&E, immunofluorescent, immunohistochemical, multi-stained and aligned tissue bioluminescence, and Tissue Microarray (TMA) images, and has 3 permanent licenses of the software that we provide for use on a fee-for-service basis. This analysis platform will allow users to carry out a number of measurements including marker intensity and area analysis, positive pixel count, nuclear and nuclear membrane intensity, cell count, and vessel density, along with measurements of various regions of interest, such as tumor areas, hypoxic fractions, necrotic regions, and calculation of distance relationships between these different regions.
Target Audience: Graduate students, technicians, research associates, PI’s, and postdocs who require image analysis for their projects. Even if you already have used image analysis extensively, this course will inform you of new methods for tissue and cellular segmentation using machine-learning tools, and will help you to optimize your image analysis methods, in order to get the most reliable data from your images through careful image processing and analysis.
$175 (UHN/internal participants)
$195 (external academics)
Note: The cost of the workshop includes a complimentary pilot analysis of your data (valued up to $300).
Date: Friday, 19th May 2017, 10:00am – 4:00pm
Location: STTARR Innovation Centre, 101 College Street, 7th floor, MaRS Building,
Princess Margaret Cancer Research Tower – East, Toronto, ON M5G 1L7
10:00am Presentations/lectures* by Dr. Trevor McKee, Ms. Sehrish Butt, BSc Hons, and Mr. Mark Zaidi
12:30-1:30pm Lunch (provided)
1:30pm Hands-on training/demo on Definiens Tissue Studio image analysis software
Please RSVP via this Registration Form, by 5pm on Tuesday, 16th May 2017.
We have limited seats available. First-come-first-served.
A light sandwich lunch and refreshments will be provided. Please include any dietary restrictions or allergies on your registration form, and we will do our best to accommodate you.
Dr. Trevor McKee received his Ph.D. in Biological Engineering from the Massachusetts Institute of Technology in 2005, in the laboratory of Dr. Rakesh Jain. His focus was on developing imaging and analysis methods to overcome barriers to drug and gene therapeutic delivery in tumors, and pioneering the application of multiphoton imaging methods to preclinical cancer models. Dr. McKee continued his training as a postdoctoral fellow at the Ontario Cancer Institute in the laboratory of Dr. Rama Khokha, utilizing multi-modality imaging techniques to study animal models of heart and liver disease and cancer.
Joining the STTARR facility in 2010, he simultaneously managed industry partnered research collaborations with Pfizer Oncology and Molecular Insights Pharmaceuticals to develop a preclinical imaging pipeline for cancer phenotyping and drug development, and test novel drug and molecular imaging agents in that pipeline. He is the recipient of the Susan Komen Postdoctoral Fellowship, a Department of Defense Idea Award, and a Certificate of Entrepreneurship from MaRS Discovery District; and his 22 peer-reviewed publications have collectively been cited over 2300 times.
He is currently Image Analysis Core Manager of the STTARR Innovation Centre, and manages a team of analysts to develop new algorithms for image segmentation and quantification.
Ms. Sehrish Butt received her Honors BSc in Biochemistry from the University of Toronto in 2011. She then moved to the University of Windsor, where she completed her Masters in Neuroscience working on a project to study the effects of sodium salicylate on the level of GABAB receptors in the rat’s central auditory structures, and its implications on tinnitus. Her Masters thesis involved extensive utilization of image analysis methods on pathology tissue sections, and resulted in two publications, most recently in the journal Neuroscience in 2016.
She joined STTARR Innovation Centre in 2015 and works as a research analyst to help users of the facility acquire immunofluorescence images of their tissue sections, help them analyze their data, and help them develop and use new algorithms for image analysis on brightfield and immunofluorescence stained tissue sections.
Mr. Mark Zaidi is a Biology undergraduate student at Ryerson University. He is currently a member of the Wouters-Koritzinsky group as a student researcher since 2016, performing quantitative image analysis on tumor hypoxia at the STTARR Innovation Center.
His aim is to develop a reusable and versatile image analysis pipeline to quantify tumor hypoxia and proliferation gradients as a function of distance to the nearest perfused blood vessel, using Definiens Tissue Studio. He also has experience in MATLAB programming to develop various data visualization methods, and is currently developing an automated image registration program to align serial tumor sections.
He has received the Terry Fox Research Institute poster award, the Sheldon and Tracy Levy Aspiring Innovators Award, the Ryerson Student Union sustainability award, the G. Raymond Chang – Sheldon Levy Partnership award, the FOS Undergraduate Interdisciplinary Research Opportunities position, and is currently on the Dean’s List at Ryerson University. Some of his other research foci include investigating alternate synthesis pathways for the production of Aerogel, as well as their potential commercial applications.