Identifying prognostic structural features in tissue sections of colon cancer patients using point pattern analysis |
| |
Authors: | Charlotte M. Jones-Todd Peter Caie Janine B. Illian Ben C. Stevenson Anne Savage David J. Harrison James L. Bown |
| |
Affiliation: | 1. National Institute of Water and Atmospheric Research, Hamilton, New Zealand;2. School of Medicine, University of St Andrews, St Andrews, UK;3. Centre for Research into Ecological & Environmental Modelling, School of Mathematics and Statistics, University of St Andrews, St Andrews, UK;4. Department of Statistics, University of Auckland, New Zealand;5. School of Science, Engineering and Technology, Abertay University, UK;6. School of Arts, Media and Computer Games, Abertay University, UK |
| |
Abstract: | Diagnosis and prognosis of cancer are informed by the architecture inherent in cancer patient tissue sections. This architecture is typically identified by pathologists, yet advances in computational image analysis facilitate quantitative assessment of this structure. In this article, we develop a spatial point process approach to describe patterns in cell distribution within tissue samples taken from colorectal cancer (CRC) patients. In particular, our approach is centered on the Palm intensity function. This leads to taking an approximate-likelihood technique in fitting point processes models. We consider two Neyman-Scott point processes and a void process, fitting these point process models to the CRC patient data. We find that the parameter estimates of these models may be used to quantify the spatial arrangement of cells. Importantly, we observe characteristic differences in the spatial arrangement of cells between patients who died from CRC and those alive at follow up. |
| |
Keywords: | colorectal cancer Palm intensity function spatial point patterns |
|
|