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Mistic: An open-source multiplexed image t-SNE viewer

ABSTRACT: Summary Understanding the complex ecology of a tumor tissue and the spatiotemporal relationships between its cellular and microenvironment components is becoming a key component of translational research, especially in immuno-oncology. The generation and analysis of multiplexed images from patient samples is of paramount importance to facilitate this understanding. Here, we present Mistic, an open-source multiplexed image t-SNE viewer that enables the simultaneous viewing of multiple 2D images rendered using multiple layout options to provide an overall visual preview of the entire dataset. In particular, the positions of the images can be t-SNE or UMAP coordinates. This grouped view of all images allows an exploratory understanding of the specific expression pattern of a given biomarker or collection of biomarkers across all images, helps to identify images expressing a particular phenotype, and can help select images for subsequent downstream analysis. Currently, there is no freely available tool to generate such image t-SNEs. Highlights • Mistic is a multiplexed image t-SNE viewer• Mistic enables the simultaneous viewing of multiple 2D images• This grouped overview allows visualization of existing patterns in the data• Mistic supports images from Vectra, CyCIF, t-CyCIF, and CODEX The bigger picture A crucial component of translational research is in exploiting tumor tissue for diagnostic or prognostic purposes. We believe this can best be achieved through a deeper understanding of the complex ecology of a tumor tissue and the spatiotemporal relationships between its cellular and microenvironment components. Multiplexed images from patient samples facilitate this understanding. We present Mistic, an open-source multiplexed image t-SNE viewer that enables the simultaneous viewing of multiple 2D multiplexed images to provide an overall visual preview of the entire dataset. This allows an exploratory understanding of underlying patterns in the data such as the specific expression pattern of a given biomarker across all images. Currently, there is no free tool to generate such image t-SNEs. Mistic aims to fill this gap by providing an easy to implement tool with simple functionality to view multiple images at once. Mistic supports images from Vectra, CyCIF, t-CyCIF, and CODEX. Multiplex imaging of tissues allows the simultaneous imaging of multiple biomarkers on a tissue specimen of interest and is a critical tool for clinical cancer diagnosis and prognosis. A common way to visualize and better understand such multiplexed images is to utilize dimensionality reduction (DR) methods, where each image is abstracted as a point in the reduced space. We developed Mistic to enable the simultaneous viewing of multiple 2D multiplexed images by combining DR, image processing, and GUI programming.

SUBMITTER: Prabhakaran S

PROVIDER: S-EPMC9278502 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:PurposeZero-footprint Web architecture enables imaging applications to be deployed on premise or in the cloud without requiring installation of custom software on the user's computer. Benefits include decreased costs and information technology support requirements, as well as improved accessibility across sites. The Open Health Imaging Foundation (OHIF) Viewer is an extensible platform developed to leverage these benefits and address the demand for open-source Web-based imaging applications. The platform can be modified to support site-specific workflows and accommodate evolving research requirements.Materials and methodsThe OHIF Viewer provides basic image review functionality (eg, image manipulation and measurement) as well as advanced visualization (eg, multiplanar reformatting). It is written as a client-only, single-page Web application that can easily be embedded into third-party applications or hosted as a standalone Web site. The platform provides extension points for software developers to include custom tools and adapt the system for their workflows. It is standards compliant and relies on DICOMweb for data exchange and OpenID Connect for authentication, but it can be configured to use any data source or authentication flow. Additionally, the user interface components are provided in a standalone component library so that developers can create custom extensions.ResultsThe OHIF Viewer and its underlying components have been widely adopted and integrated into multiple clinical research platforms (e,g Precision Imaging Metrics, XNAT, LabCAS, ISB-CGC) and commercial applications (eg, Osirix). It has also been used to build custom imaging applications (eg, ProstateCancer.ai, Crowds Cure Cancer [presented as a case study]).ConclusionThe OHIF Viewer provides a flexible framework for building applications to support imaging research. Its adoption could reduce redundancies in software development for National Cancer Institute-funded projects, including Informatics Technology for Cancer Research and the Quantitative Imaging Network.

Project description:Roots are central to the function of natural and agricultural ecosystems by driving plant acquisition of soil resources and influencing the carbon cycle. Root characteristics like length, diameter and volume are critical to measure to understand plant and soil functions. RhizoVision Explorer is an open-source software designed to enable researchers interested in roots by providing an easy-to-use interface, fast image processing and reliable measurements. The default broken roots mode is intended for roots sampled from pots and soil cores, washed and typically scanned on a flatbed scanner, and provides measurements like length, diameter and volume. The optional whole root mode for complete root systems or root crowns provides additional measurements such as angles, root depth and convex hull. Both modes support providing measurements grouped by defined diameter ranges, the inclusion of multiple regions of interest and batch analysis. RhizoVision Explorer was successfully validated against ground truth data using a new copper wire image set. In comparison, the current reference software, the commercial WinRhizo™, drastically underestimated volume when wires of different diameters were in the same image. Additionally, measurements were compared with WinRhizo™ and IJ_Rhizo using a simulated root image set, showing general agreement in software measurements, except for root volume. Finally, scanned root image sets acquired in different labs for the crop, herbaceous and tree species were used to compare results from RhizoVision Explorer with WinRhizo™. The two software showed general agreement, except that WinRhizo™ substantially underestimated root volume relative to RhizoVision Explorer. In the current context of rapidly growing interest in root science, RhizoVision Explorer intends to become a reference software, improve the overall accuracy and replicability of root trait measurements and provide a foundation for collaborative improvement and reliable access to all.

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Mistic: An open-source multiplexed image t-SNE viewer

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