QuPath: The global impact of an open source digital pathology system.

Area of Science:

• Digital Pathology
• Bioimage Analysis
• Computational Biology

Background:

• Digital pathology (DP) is rapidly expanding, necessitating advanced tools for whole slide image (WSI) analysis.
• Traditional pathological assessment struggles with the high-throughput and reproducibility demands of modern research.
• Large-scale biomarker quantification increasingly relies on computational methods.

Purpose of the Study:

• To highlight the impact and widespread adoption of the open-source Quantitative Pathology & Bioimage Analysis (QuPath) software.
• To showcase QuPath as a preferred system for researchers in digital pathology.
• To demonstrate the role of QuPath in addressing the challenges of analyzing large, complex tissue images.

Main Methods:

• Review of scientific literature citing QuPath.
• Analysis of QuPath's application scope in various research fields.
• Demonstration of QuPath's capabilities in handling large-format WSI and enabling reproducible analysis.

Main Results:

• QuPath is identified as the most widely used image analysis software in digital pathology.
• The software facilitates the visualization and analysis of massive WSI files (billions of pixels, GBs in size).
• QuPath supports high-throughput, reproducible analysis crucial for biomarker quantification.

Conclusions:

• QuPath has significantly impacted digital pathology research by providing a robust, open-source solution.
• The software is instrumental in advancing translational research through efficient and reproducible image analysis.
• QuPath is established as a system of choice for researchers in pathology and bioimage analysis.