A radiomic approach for adaptive radiotherapy in non-small cell lung cancer patients

• DOI: 10.1371/journal.pone.0207455
• Publication Date: 2018-11-21T19:53:41Z
• Authors: Sara Ramella; Michele Fiore; Carlo Greco; Ermanno Cordelli; Rosa Sicilia; Mario Merone; Elisabetta Molfese; Marianna Miele; Patrizia Cornacch...; Edy Ippolito; Giulio Iannello; Rolando Maria D’A...; Paolo Soda
• Keywords: Personalized Medicine

The primary goal of precision medicine is to minimize side effects and optimize efficacy treatments. Recent advances in medical imaging technology allow the use more advanced image analysis methods beyond simple measurements tumor size or radiotracer uptake metrics. extraction quantitative features from images characterize pathology heterogeneity an interesting process investigate, order provide information that may be useful guide therapies predict survival. This paper discusses rationale supporting concept radiomics feasibility its application Non-Small Cell Lung Cancer field radiation oncology research. We studied 91 stage III patients treated with concurrent chemoradiation adaptive approach case reduction during treatment. considered 12 statistics 230 textural extracted CT images. In our study, we used ensemble learning method classify patients' data into either non-adaptive group on basis starting simulation. Our supports hypothesis a specific signature can identified (AUC 0.82). experience, radiomic mixing semantic image-based has shown promising results for personalized radiotherapy non-small cell lung cancer.