Work

Opportunities for improving brain cancer treatment outcomes through imaging-based mathematical modeling of the delivery of radiotherapy and immunotherapy

Year: 2022

Type: review

Source: Advanced Drug Delivery Reviews

DOI: 10.1016/j.addr.2022.114367

Authors: David A. Hormuth, Maguy Farhat, Chase Christenson, Brandon Curl, C. Chad Quarles, Caroline Chung, Thomas E. Yankeelov

Institutions: The University of Texas at Austin, The University of Texas MD Anderson Cancer Center, Barrow Neurological Institute

Language: English

Topic: Mathematical Biology Tumor Growth

Subfield: Modeling and Simulation

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: bronze

Funder: National Cancer Institute

Awards: INTEGRATING OMICS AND QUANTITATIVE IMAGING DATA IN CO-CLINICAL TRIALS TO PREDICT TREATMENT RESPONSE IN TRIPLE NEGATIVE BREAST CANCER, Clinical Development of Rhenium Nanoliposomes (RNL186) for Glioblastoma, Image Driven Multi-Scale Modeling to Predict Treatment Response in Breast Cancer

OpenAlex ID: W4281658060

FWCI: 1.043

Cites: 252

Cited by: 45

Related to: 10