Tracking the Invisible: A Probabilistic Approach to Field Cancerization

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" summary

A lattice spatial Moran/biased voter model with zeros, ones and twos and three asymptotic regimes predicts how invisible premalignant fields grow, produces closed formulas for the size-biased field distribution at tumor initiation, and uses simulations showing early type‑2 mutations (sometimes at clone boundaries). Parameters are matched to SEER incidence to estimate mutation rates and selection coefficients, predict 20–30% local recurrence 1–5 years out, and give recurrence probability versus resection margin (0, 2, 4, 6 cm); pathology/IRB data collection is underway.

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" chapters (19)

1. 0:00Intro
2. 2:28Diagnosis
3. 3:51Treatment
4. 4:49Resected tongue cancer
5. 5:331-5 years later
6. 7:12Field Cancerization
7. 8:25Invisibility = Uncertainty
8. 10:08Cellular dynamics
9. 12:22Focus on basal layer
10. 18:09Biased voter model Jasmine Foo's talk
11. 19:04Assumptions
12. 21:29Important notion: size-biased pick
13. 22:40Local field area
14. 23:29Distant field area
15. 29:48Excision Margin III
16. 30:49Recurrence: local vs distant
17. 32:57Reference
18. 34:48Added complexity
19. 35:33Patient data spectroscopic probe imaging biopsies