Visual light perceptions caused by medical linear accelerator: Findings of machine-learning algorithms in a prospective questionnaire-based case-control study

PLoS One. 2021 Feb 25;16(2):e0247597. doi: 10.1371/journal.pone.0247597. eCollection 2021.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Brain Neoplasms / radiotherapy*
  • Case-Control Studies
  • Female
  • Head and Neck Neoplasms / radiotherapy*
  • Humans
  • Light
  • Male
  • Middle Aged
  • Particle Accelerators
  • Prospective Studies
  • Retina
  • Surveys and Questionnaires
  • Visual Perception*

Grants and funding

The research and publication charge were supported in part by Ministry of Science and Technology, R.O.C. (Taiwan) under grant MOST 109-2221-E-038-018 to Emily Chia-Yu Su. https://www.most.gov.tw/ The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. There was no additional external funding received for this study.