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Updated: May 9, 2026

Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
Published on: December 15, 2014
The time-evolution of DCIS size distributions with applications to breast cancer growth and progression
James G Dowty1, Graham B Byrnes2, Dorota M Gertig3
1Melbourne School of Population and Global Health, University of Melbourne, Level 3/207 Bouverie St., Carlton 3053, Australia jdowty@unimelb.edu.au.
Abstract:
Ductal carcinoma in situ (DCIS) lesions are non-invasive tumours of the breast that are thought to precede most invasive breast cancers (IBCs). As individual DCIS lesions are initiated, grow and invade (i.e. become IBC), the size distribution of the DCIS lesions present in a given human population will evolve. We derive a differential equation governing this evolution and show, for given assumptions about growth and invasion, that there is a unique distribution which does not vary with time. Further, we show that any initial distribution converges to this stationary distribution exponentially quickly. Therefore, it is reasonable to assume that the stationary distribution governs the size of DCIS lesions in human populations which are relatively stable with respect to the determinants of breast cancer. Based on this assumption and the size data of 110 DCIS lesions detected in a mammographic screening programme between 1993 and 2000, we produce maximum likelihood estimates for certain growth and invasion parameters. Assuming that DCIS size is proportional to a positive power p of the time since tumour initiation, we estimate p to be 0.50 with a 95% confidence interval of (0.35, 0.71). Therefore, we estimate that DCIS lesions follow a square-root growth law and hence that they grow rapidly when small and relatively slowly when large. Our approach and results should be useful for other mathematical studies of cancer, especially those investigating biological mechanisms of invasion.
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