"Development of a Predictive Quantitative Contrast Computed Tomography-Based Feature (Radiomics) Profile for Local Recurrence in Oropharyngeal Cancers"
Development of a Predictive Quantitative Contrast Computed Tomography-Based Feature (Radiomics) Profile for Local Recurrence in Oropharyngeal Cancers
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.
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.
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).
Support:
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”