Radiation Therapy Outcomes Models in the Era of Radiomics and Radiogenomics: Uncertainties and Validation
Models by their nature are mathematical approximations of reality, as conveyed by the statement that “all models are wrong but some are useful (1).” Their usefulness in radiation therapy (RT) is highlighted by the roles that outcome models play in improving the quality and efficacy of radiation treatment of tumors by predicting response, individualizing prescriptions, and optimizing and ranking planning options. These models are generally categorized into those for tumor response prediction by tumor control probability (TCP) and those for predicting radiation-induced toxicities by normal-tissue complication probability (NTCP).
Source: International Journal of Radiation Oncology * Biology * Physics - Category: Radiology Authors: Issam El Naqa, Gaurav Pandey, Hugo Aerts, Jen-Tzung Chien, Christian Nicolaj Andreassen, Andrzej Niemierko, Randall K. Ten Haken Tags: Radiomics and Machine Learning Source Type: research
More News: Biology | Cancer & Oncology | Learning | Physics | Radiation Therapy | Toxicology | Universities & Medical Training