Our work with Dr. Hesham Elhalawani (Dept. of Radiation Oncology, M.D Anderson Cancer Center) on early prediction of Osteo-radio-necrosis (ORN) using radiomics has been accepted to the American Society for Radiation Oncology’s Head and Neck cancer (ASTRO-HNC) symposium in 2018. We show that a functional principal component analysis (FPCA) of radiomic features extracted at multiple time points before and after radiotherapy, can predict for ORN development in patients. We significantly outperform prediction models based on pre-radiotherapy images and delta radiomics (current practice). We envisage our FPCA screening tool can be used by radiologists to optimize radiation plan for patients undergoing radiotherapy!
Back in Houston after a refreshing trip to India, with a small escapade to Thailand in between. Great food, and great times with family!
Our invited book chapter on the advances made in radiology and histopathology analysis in glioblastoma using image processing and machine learning. Great job Michael Lehrer in integrating all our contributions to this chapter! Check it out here.
Our work on showing the spatial distribution of intratumoral T cells in the tumor has a significant effect on survival is now published in Nature Communications! Find the paper here. It was a great experience to combine our ideas on spatial statistics with the cancer biology expertise of Julienne Carstens and Pedro Correa at MD Anderson.