Using a photographic image processing method as a part of the QA program in some radiotherapy departments where CTs are involved with COVID-19 patients

Abstract

Background & Aims: Owing to the significant role of CT images in diagnosis and follow up of patients affected with coronavirus, the imaging section of cancer centers in some countries engaged in providing services to COVID-19 patients. The aim of this study was to introduce a CT-independent photographic-based QA method in some radiotherapy departments where CTs are involved with COVID-19 patients. Materials & Methods: An anthropomorphic woman-like torso phantom was used in the first step of study for setup arrangement and preliminary data extractions. Then in the second step, four patients with early stage breast cancer were evaluated. In all steps, the key parameters extracted from photographic-based method were compared with the same parameters extracted from CT system, which was considered as the gold standard method. A home-made computer code developed in MATLAB was used to extract parameters in the new method. Finally, the corresponding parameters were compared using the non-parametric Wilcoxon method. Results: Our results showed that the newly introduced method can predict desired parameters equal to CT-based method. Using this method, a part of the QA program will be performed with no dependency on CT systems. Also, the image sections load work in some radiotherapy departments, which their CT systems are involved with COVID-19 patients, can reduce. Conclusion: The proposed method could help identify and remove important uncertainties and errors in radiotherapy courses, especially between fractions, without imposing ionizing radiation on patients in pandemic conditions.

Keywords

• geometric uncertainty
• photographic based image processing
• qa
• radiotherapy
• setup error