1. Visual light perceptions caused by medical linear accelerator: Findings of machine-learning algorithms in a prospective questionnaire-based case-control study
- Author
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Emily Chia Yu Su, Cheng Chun Lee, Jia Cheng Lee, Yuh Lin Lee, Shueh Chun Liou, Chao Yang Kuo, and Yi Wei Chen
- Subjects
Male ,Questionnaires ,Light ,Vision ,medicine.medical_treatment ,Cancer Treatment ,Social Sciences ,Logistic regression ,computer.software_genre ,Machine Learning ,0302 clinical medicine ,Surveys and Questionnaires ,Medicine and Health Sciences ,Psychology ,Prospective Studies ,0303 health sciences ,Multidisciplinary ,Brain Neoplasms ,Applied Mathematics ,Simulation and Modeling ,Incidence (epidemiology) ,Area under the curve ,Middle Aged ,Random forest ,Oncology ,Head and Neck Neoplasms ,Research Design ,030220 oncology & carcinogenesis ,Physical Sciences ,Visual Perception ,Medicine ,Female ,Sensory Perception ,Anatomy ,Algorithm ,Algorithms ,Research Article ,Clinical Oncology ,Computer and Information Sciences ,Ocular Anatomy ,Science ,Radiation Therapy ,Research and Analysis Methods ,Machine learning ,Retina ,Machine Learning Algorithms ,03 medical and health sciences ,Ocular System ,Artificial Intelligence ,medicine ,Humans ,Categorical variable ,Aged ,030304 developmental biology ,Survey Research ,business.industry ,Cognitive Psychology ,Case-control study ,Correction ,Biology and Life Sciences ,Radiation therapy ,Case-Control Studies ,Test set ,Cognitive Science ,Eyes ,Perception ,Artificial intelligence ,Particle Accelerators ,Clinical Medicine ,business ,Head ,computer ,Mathematics ,Neuroscience - Abstract
This study aimed to investigate the possible incidence of visual light perceptions (VLPs) during radiation therapy (RT). We analyzed whether VLPs could be affected by differences in the radiation energy, prescription doses, age, sex, or RT locations, and whether all VLPs were caused by radiation. From November 2016 to August 2018, a total of 101 patients who underwent head-and-neck or brain RT were screened. After receiving RT, questionnaires were completed, and the subjects were interviewed. Random forests (RF), a tree-based machine learning algorithm, and logistic regression (LR) analyses were compared by the area under the curve (AUC), and the algorithm that achieved the highest AUC was selected. The dataset sample was based on treatment with non-human units, and a total of 293 treatment fields from 78 patients were analyzed. VLPs were detected only in 122 of the 293 exposure portals (40.16%). The dataset was randomly divided into 80% and 20% as the training set and test set, respectively. In the test set, RF achieved an AUC of 0.888, whereas LR achieved an AUC of 0.773. In this study, the retina fraction dose was the most important continuous variable and had a positive effect on VLP. Age was the most important categorical variable. In conclusion, the visual light perception phenomenon by the human body during RT is induced by radiation rather than being a self-suggested hallucination or induced by phosphenes.
- Published
- 2021