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Fractal dimensions for tumour-related cell types of prostate cancer on histopathology images using multiple-threshold box counting algorithm
(Anton Schwarz, Hidetaka Arimura, Yunhao Cui, Shun Shimabukuro, Qijing Lin, Yu Jin, Satoshi Kobayashi, Takashi Matsumoto, Masaki Shiota, Masatoshi Eto, Yoshinao Oda, Biophysics and Physicobiology 22, e220026 (2025), DOI: 10.2142/biophysico.bppb-v22.0026)
Prostate cancer growth is a dynamic process that could exhibit fractal properties such as self-similarity. We have studied the associations between grade groups (GGs) of prostate cancer on histopathology images and fractal dimensions (FDs) of five types of prostate tumour-related cells, neoplastic epithelial, inflammatory, connective tissue, necrotic, and non-neoplastic epithelial cells (top left three images). We found that FD-threshold images like the right images can be leveraged to predict low and high grades of prostate cancer. Here, E: Eosin, H: Hematoxylin, N: Normalised image, neopla: Neoplastic epithelial, inflam: Inflammatory, necro: Necrotic, and no_neo: Non-neoplastic epithelial.