Key points are not available for this paper at this time.
Abstract High-plex immunofluorescence imaging allows researchers to perform deep cellular phenotyping with spatial context. However, high-plex immunofluorescence imaging requires the end user to painstakingly optimize antibody concentrations and image acquisition settings before producing reproducible imaging data with sufficient and quantifiable dynamic range. Mismatches of reagent concentration and camera exposures will result in under and over-saturated images, and both outcomes are detrimental for signal quantification and downstream interpretation. As the number of markers deployed in spatial biology increases, it becomes necessary to develop strategies that streamline or automate parameter setting that is needed to capture data with optimal dynamic range. The CellScape™ platform for Precise Spatial Multiplexing, featuring ChipCytometry™ technology, utilizes multi-exposure high dynamic range (HDR) microscopy as a tool to produce data with consistent and reliable detection of biomarker signals. CellScape replaces the standard single exposure with an exposure series calibrated to the physical limitations of the detector system. Each exposure series captures linear data, ranging from the dimmest to the brightest signals that the system can detect, as well as everything in between. HDR capture is thus akin to capturing an image at every possible exposure length, and it thus includes data from the ‘optimal’ matched exposure. By these means, HDR obviates the need for exposure selection by covering the entire exposure gamut. Here, we use CellScape to collect a high-plex immunofluorescence spatial biology dataset. Analysis of the dataset highlights the extended linear dynamic range of the integrated luminance HDR data, including a calculation of the expected ‘best-matched’ exposure. Further, we extend this analysis to show how HDR can handle biological variation and allow normalization that is not possible with single exposure imaging. Finally, we examine a reagent concentration series to demonstrate how HDR can be used to maximize the sensitivity of the assay by allowing increasing detection reagent concentration without compromising overall dynamic range for the signal. Our data demonstrates that HDR microscopy supports the deployment of spatial biology as a tool to interrogate the tumor microenvironment, unravel responsiveness to drug treatments and cell therapies, and ultimately stratify patients for targeted treatment and clinical trial enrollment. Citation Format: J Spencer Schwarz, Matthew H. Ingalls, Xenia Meshik, Adam Northcutt, Oliver Braubach. Multi-exposure high dynamic range microscopy obviates the requirement for matching camera exposure to reagent concentration in high-plex spatial biology applications abstract. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts) ; 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84 (6Suppl): Abstract nr 1042.
Schwarz et al. (Fri,) studied this question.