The All-Around Duo for Multiplex Fluorescence Pathology Analysis: Visiopharm Gives PA53 FS6 SCAN an Extra Edge
The All-Around Duo for Multiplex Fluorescence Pathology Analysis: Visiopharm Gives PA53 FS6 SCAN an Extra Edge
Pathology is moving from "morphological observation" to "quantitative analysis." Multiplex fluorescence technology can simultaneously label multiple targets on a single slide, revealing the spatial relationships among different proteins and cells—but the multi-channel data volume is large and manual counting is highly subjective. This is exactly where the pairing of PA53 FS6 SCAN and Visiopharm comes into its own.
On the hardware side, the PA53 FS6 SCAN is a research-grade multiplex fluorescence whole-slide scanning system: a motorized stage and autofocus ensure stable imaging of large slide batches, a fast fluorescence turret paired with a dual-camera scanning head efficiently completes multi-channel acquisition, and a long-life LED light source provides stable intensity while automatically recognizing objectives and filter cubes and actively managing light intensity to ensure consistent acquisition conditions—the prerequisite for trustworthy quantitative analysis.
Acquisition is only the first step; the main event is data analysis. Visiopharm is a world-leading tissue image analysis platform, with more than 120 ready-to-use apps covering scenarios such as immunohistochemistry quantification, immunofluorescence cell phenotyping, tissue segmentation, microvessel analysis, and RNAscope and FISH scoring. Simply invoke an app and set the parameters, and the system automatically performs tissue recognition, nucleus/cytoplasm/membrane segmentation, and positive-signal interpretation, outputting quantitative data such as counts, positivity rates, fluorescence intensity, and area.
Even more noteworthy is its "data mining" capability: Visiopharm supports deep learning, allowing custom AI models to be trained on one's own samples; batch analysis runs dozens of slides with a single click; and it can also analyze the spatial co-localization relationships of markers—for example, the distance distribution between PD-L1-positive cells and CD8-positive T cells in the tumor microenvironment, spatial information of a kind that is becoming a hot topic for predicting immunotherapy efficacy.
Together, this combination connects the entire workflow of multiplex fluorescence pathology research: stable imaging ensures reliable data, AI analysis frees up manpower, and data mining uncovers patterns that are hard to see with the naked eye, turning pathology images into mineable, reproducible research data assets.