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

October 1st, 2016

Categories: Applications, Visual Analytics, Visual Informatics

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.
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.

About

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”

Resources

URL

Citation

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., Development of a Predictive Quantitative Contrast Computed Tomography-Based Feature (Radiomics) Profile for Local Recurrence in Oropharyngeal Cancers, International Journal of Radiation Oncology, Biology, Physics 96(2):S191, vol 96, no 2, pp. S191, October 1st, 2016. https://doi.org/10.1016/j.ijrobp.2016.06.477