Development of a Predictive Quantitative Contrast Computed Tomography-Based Feature (Radiomics) Profile for Local Recurrence in Oropharyngeal Cancers
Head and neck cancer treatment and toxicity Big Data collected at U Texas MD Anderson Cancer Center; jointly analyzed at EVL, MDACC, UMN and Iowa.
Authors: Kanwar, A., Mohamed, A., Court, L., Zhang, L., Marai, G.E, Canahuate, G., Lee, J.Perni, A., Messer, J., Pham, B., Youssef, B., Vock, D., Rao, A., Kalpathy-Cramer, J., Gunn, G., Rosenthal, D., Fuller, D.
Publication: International Journal of Radiation Oncology, Biology, Physics 96(2):S191, vol 96, no 2, pp. S191
Radiomics involves the application of image processing algorithms to define a series of quantitative image characteristics. We sought to develop a clinically usable radiomics signature for primary oropharyngeal cancers (OPC), using the gross tumor volume (GTV) regions of interest (ROIs) to derive a “phenotypic profile” associated with time to local recurrence (LR).
National Institutes of Health:
NCI-R01-CA214825, “SMART-ACT: Spatial Methodologic Approaches for Risk Assessment and Therapeutic Adaptation in Cancer Treatment”
NCI-R01CA225190,“QuBBD: Precision E –Radiomics for Dynamic Big Head & Neck Cancer Data”
Date: October 1, 2016