In the final episode of the three-part series on phenotyping, Dr Aleksandra Zuraw and our Scientific Consulting Sales Manager, Regan Baird, discuss important factors to consider when selecting image analysis software for phenotyping.
Further reading:
The two key considerations when selecting a phenotyping image analysis software are segmentation assistance and data visualization.
Segmentation assistance: To determine cell phenotypes, the boundaries of cells in tissue slides must first be defined. This is known as cell segmentation and can be automatically performed by image analysis software. Cells in tissue slides can vary in shape and size, making segmentation difficult. Image analysis software can use either rule-based classical computer vision or AI-powered approaches to estimate cell boundaries. Visiopharm offers an AI-based nuclear segmentation followed by a rule-based and marker-based step to achieve the most accurate cell segmentation for phenotyping.
Data visualization: The proper visualization and management of obtained data is crucial and depends on the software used. To interpret multidimensional multiplex and phenotyping data, visualizations such as graphs, plots, and two-dimensional reduction plots must be used for all images in multiplex studies. The right visualization tools are needed to evaluate phenotyping performance and export meaningful results.
- Let us know what you think of the episode and any topics you would like us to cover in the future by sending us an email at: podcasts@visiopharm.com
Get ready for an exciting journey into the world of tissue imaging with the first episode of our mini series. Dr Aleksandra Zuraw is joined by expert Regan Baird, our Scientific Consulting Sales Manager, to dive into the fascinating topic of multiplex staining. Find out the different modalities, what’s best suited for tissue image analysis and why, and the many benefits and uses of multiplex staining. Regan shares his expertise and insights to help you get the most out of your imaging modalities.
Further reading:
After his postdoc at Beth Israel Deaconess Medical Center in Boston, where he experimented with multidimensional, multimarker and multicolor single cell imaging modalities, 2D images of tissue stained with hematoxylin and eosin (H&E) seemed simplistic to Regan Baird, PhD. Tissue image analysis (IA) can be challenging when relying solely on H&E. So, multiplex staining was implemented to simplify the process and extract more information.
In this miniseries, Regan introduces us to the concepts of multiplexing and cell phenotyping and relevant image analysis approaches for multiplex data analysis. Multiplexing in life sciences refers to taking multiple measurements on the same specimen at the same time. The easiest method of multiplexing with tissue slides is IHC-based virtual multiplexing.
More precise methods of visualizing cellular colocalization of biomarkers include multicolor bright field IHC (up to five biomarkers per tissue, two biomarkers per cell), IF with spectral unmixing (up to nine biomarkers per tissue and cell), and imaging mass cytometry (up to 60 biomarkers in a single tissue section). The choice of method should be based on the experiment and scientific/diagnostic questions.
IF multiplexing is widely used for cell phenotyping in tissue, allowing for characterization of single cells and investigation of spatial relationships between cell populations. This provides information about the interactome of different cells and their environment.
- Let us know what you think of the episode and any topics you would like us to cover in the future by sending us an email at: podcasts@visiopharm.com
In the second episode of our series on phenotyping with Dr. Aleksandra Zuraw and our Scientific Consulting Sales Manager, Regan Baird, learn how to make sense of multiplex data with phenotyping. Find out how to classify individual cells in tissue based on biomarker panels and why this is crucial for personalized therapeutic approaches in oncology. Discover the challenges of interpreting multiplex data, the use of machine learning-based auto-clustering, and the importance of software in visualizing and handling generated data. Stay tuned for the next episode where we’ll discuss considerations when choosing an image analysis software program for phenotyping.
- Let us know what you think of the episode and any topics you would like us to cover in the future by sending us an email at: podcasts@visiopharm.com
Cancer immunotherapy, or immuno-oncology, harnesses the power of the immune system to fight cancer. Scientists are using tissue image analysis with digital pathology and whole slide imaging to detect and quantify the multiple processes and immune cell populations involved in tumor immunology. Join Dr Aleksandra Zuraw and Prof Elfriede Noessner in this episode as they explain the complexities of the immune system and its role in curing cancer, and the role of tissue image analysis in the process.
- Let us know what you think of the episode and any topics you would like us to cover in the future by sending us an email at: podcasts@visiopharm.com
In this 18-minute webinar, James presents Phenoplex™, a new workflow solution from Visiopharm for all multiplex image analysis requirements. He outlines the various workflow steps, which efficiently evaluate spatial biology assays with 8-40 or more biomarkers. With its interactive evaluation tools, it enables the extraction of more information from each cell and its relationships.
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- How pre-trained deep learning-based cell detection for DAPI or IMCTM stains accurately, robustly, and flexibly identifies cells.
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- The two workflows for phenotyping multiplex and highplex images
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- How to validate your results using interactive plots that link each data point with the underlying cell
James R. Mansfield, Senior Vice President, Research Business Development, Visiopharm
James R. Mansfield, a scientist with 30+ years of experience, including 15 in multiplex pathology and immune cell phenotyping. He is SVP of Research Business Development at Visiopharm, focused on their strategy for multiplex image analysis. Previously, he was Scientific Director at Magnetic Insight Inc, a start-up in magnetic particle imaging technology. He also held senior positions at Cambridge Research & Instrumentation, Inc (CRi) and PerkinElmer, where he played a key role in commercializing multispectral imaging for pathology.
Sheila Hansen
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An automated image analysis pipeline for highplex sequential immunofluorescence images
David Mason from Visiopharm spoke at Lunaphore’s Spatial Biology Week on an automated image analysis pipeline for high plex sequential immunofluorescent images. The challenges with this type of data include multiple platforms, unsatisfactory cell detection using traditional intensity-based approaches, and lack of confidence in results. David will use Lunaphore’s data sets, including a 22 Plex plus DPI tissue microarray, to demonstrate how Visiopharm can address these challenges in analyzing complex data sets.
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- A guided bi-directional workflow designed specifically for setting phenotypes with continuous quality control and result review.
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- Powerful pre-trained applications for detecting nuclei in multiplex immunofluorescence and imaging mass cytometry.
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- User-friendly channel management tools for quality control of images and review of biomarker localization. Group your channels of interest into meaningful 7-color groups for easy switching between panels.
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- An advanced interactive toolbox for data exploration and quality control, including t-SNE, scatter plots, and box plots.
David Mason, Senior Technical Specialist, Visiopharm
Dave Mason is a senior technical specialist in image analysis, supporting Visiopharm’s UK and European sales team. He has a background in cell biology and microbiology and has spent over a decade in academia, specializing in light microscopy and digital image analysis.