Assessment of a tumour growth model for virtual clinical trials of breast cancer screening

Image-based analysis of breast tumour growth rate may help optimize breast cancer screening and diagnosis. It may improve the identification of aggressive tumours and suggest optimal screening intervals. Virtual clinical trial (VCT) is a simulation-based method used to evaluate and optimize medical imaging systems and design clinical trials. Our work is motivated by desire to simulate multiple screening rounds with growing tumours. We have developed a model to simulate tumours with various growth rates; this study aims at evaluating the model. We used clinical data on tumour volume doubling times (TVDT) from our previous study, to fit a probability distribution ("clinical fit"). Growing tumours were inserted into 30 virtual breasts ("simulated cohort"). Based on the clinical fit we simulated two successive screening rounds for each virtual breast. TVDT from clinical and simulated images were compared. Tumour size was measured from simulated mammograms by a radiologist in three repeated sessions, to estimate TVDT ("estimated TVDT"). Reproducibility of measured sizes decreased slightly for small tumours. The mean TVDT from the clinical fit was 297±169 days, whereas the simulated cohort had 322±217 days, and the average estimated TVDT 340 ± 287 days. The median difference between the simulated and estimated TVDT was 12 days (4% of the mean clinical TVDT). Comparisons between other data sets suggest no significant difference (p>0.5). The proposed tumour growth model suggested close agreement with clinical results, supporting potential use in VCTs of temporal breast imaging.