Cancer is one of the most debilitating diseases in the world, affecting over 9.6 million people worldwide every year. Breast cancer remains the second largest cause of death in women. Despite major advances in treatment, over 40,920 women died of breast cancer in 2018 in the United States alone. Early detection of abnormal masses can be crucial for diagnosis and dramatically increase survival. Current screening techniques have varying accuracy and perform poorly when used on heterogeneously and extremely dense breast tissue. Infrared imaging has the potential to detect growing tumors within the breast based on thermal signatures on the breast surface by imaging temperature gradients induced by blood perfusion and tumor metabolic activity. Using clinical patient images, previous methods to estimate tumor properties involve an iterative algorithm to estimate the tumor position and diameter. The details from the MRI are used in estimating the volumetric heat generation rate. This is compared with the published values and the reasons for differences are investigated. The tumor pathology is used in estimating the expected growth rate and compared with the predicted values. The correlation between the tumor characteristics and heat generation rate is fundamental information that is needed in accurately predicting the tumor size and location.