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A simulation framework for modeling tumor control probability in breast conserving therapy

Authors
Journal
Radiotherapy and Oncology
0167-8140
Publisher
Elsevier
Identifiers
DOI: 10.1016/j.radonc.2014.03.004
Keywords
  • Microscopic Disease
  • Tumor Control Probability
  • Monte-Carlo Simulation
  • Breast-Conserving Therapy
Disciplines
  • Biology
  • Design
  • Medicine

Abstract

Abstract Background and purpose Microscopic disease (MSD) left after tumorectomy is a major cause of local recurrence in breast conserving therapy (BCT). However, the effect of microscopic disease and RT dose on tumor control probability (TCP) was seldom studied quantitatively. A simulation framework was therefore constructed to explore the relationship between tumor load, radiation dose and TCP. Materials and methods First, we modeled total disease load and microscopic spread with a pathology dataset. Then we estimated the remaining disease load after tumorectomy through surgery simulation. The Webb–Nahum TCP model was extended by clonogenic cell fraction to model the risk of local recurrence. The model parameters were estimated by fitting the simulated results to the observations in two clinical trials. Results Higher histopathology grade has a strong correlation with larger MSD cell quantity. On average 12.5% of the MSD cells remained in the patient’s breast after surgery but varied considerably among patients (0–100%); illustrating the role of radiotherapy. A small clonogenic cell fraction was optimal in our model (one in every 2.7*106cells). The mean radiosensitivity was estimated at 0.067Gy−1 with standard deviation of 0.022Gy−1. Conclusion A relationship between radiation dose and TCP was established in a newly designed simulation framework with detailed disease load, surgery and radiotherapy models.

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