Morphometric Analyses of Uveal Melanomas with QuPath

Published: 12 July 2022| Version 1 | DOI: 10.17632/3pkmvrmgbp.1
Mai Hoang


Extraction of nuclear features by computational method from high resolution whole-slide digital scans of histologic slides has been shown to be a valuable tool. Our study utilized QuPath, a free, open-source software and program for whole-slide image analysis, which allows cell detection and cell type classification (such as tumor cells, stromal cells, necrotic or apoptotic cells, and immune cells). Additionally, QuPath enables analysis of large numbers of tumor cells and generates detailed cell and nuclear features (nuclear area, nuclear diameter, and cell circularity). In our study, morphometric analyses have been performed on 80 uveal melanomas from Tumor Genome Cancer Atlas (TGCA) which have available virtual slides, clinical and genomic information.


Steps to reproduce

- The whole slide histologic images (WSI) of 80 Tumor Genome Cancer Atlas (TGCA) cases are downloaded from Genomics Data Commons ( and analyzed with the QuPath program (ref). - Cells and nuclei within ten annotated 10X fields are detected for each slide with the following parameters: Detection image: Optical density sum Requested pixel size: 0.5 µm Background radius: 8 µm Median filter radius 0 µm Sigma: 1.5 µm Minimum area: 15 µm2 Maximum area: 150 µm2 Threshold: 0.1 Max background intensity: 2 Split by shaped Cell expansion: 2 µm Include cell nucleus Smooth boundaries Nucleus DAB OD mean Single threshold 0.15 - Nuclear features including nuclear area, nuclear perimeter, nuclear circularity, maximum and minimum nuclear distance/nucleus caliper are extracted after cell detection and classification with QuPath. - These nuclear features are extracted for each nucleus and aggregated per patient by mean and standard deviation. Reference 1. Bankhead P, Loughrey MB, Fernandez JA, Dombrowski Y, McArt DG, Dunne PD, et al. QuPath: open source software for digital pathology image analysis. Sci Rep 2017;7:16878. doi:10.1038/s41598-017-17204-5.


Harvard Medical School, Massachusetts General Hospital