LAUSR

Abstract Purpose: We introduce a computational method to simultaneously estimate size, location and blood perfusion of the cancerous breast lesion from the surface temperature data. Methods: A 2D computational phantom of axisymmetric tumorous breast with six tissue layers, epidermis, papillary dermis, reticular dermis, fat, gland, muscle layer and spherical tumour was used to generate surface temperature distribution and thereby estimate tumour characteristics iteratively using an inverse algorithm based on Levenberg–Marquardt method. In addition to the steady state temperature data, we modified and expanded the inverse algorithm to include transient data that can be captured by dynamic infra-red imaging. Several test cases were considered for the transient analysis, where the depth, radii and blood perfusion of tumour were varied from 11 to 30 mm, 7 to 11 mm and 0.003 to 0.01 1/s, respectively. Results: Similar steady state temperature profile for different tumours makes it impossible to simultaneously estimate blood perfusion, size and location of tumour using steady state data alone. This becomes possible when transient data are used along with steady state data. For the cases discussed here, the estimates have errors below 1% for tumours with depths less than 20 mm, but for deeper tumours (25 mm) errors can be more than 10%. Conclusions: Combination of transient data and steady state data makes it possible to simultaneously estimate tumour size, location and blood perfusion. Blood perfusion is an indicator of the growth rate of the tumour and therefore its evaluation can possibly lead to the assessment of tumour malignancy.