Applicability and usage of dose mapping/accumulation in radiotherapy

Radiother Oncol. 2023 May:182:109527. doi: 10.1016/j.radonc.2023.109527. Epub 2023 Feb 10.

Abstract

Dose mapping/accumulation (DMA) is a topic in radiotherapy (RT) for years, but has not yet found its widespread way into clinical RT routine. During the ESTRO Physics workshop 2021 on "commissioning and quality assurance of deformable image registration (DIR) for current and future RT applications", we built a working group on DMA from which we present the results of our discussions in this article. Our aim in this manuscript is to shed light on the current situation of DMA in RT and to highlight the issues that hinder consciously integrating it into clinical RT routine. As a first outcome of our discussions, we present a scheme where representative RT use cases are positioned, considering expected anatomical variations and the impact of dose mapping uncertainties on patient safety, which we have named the DMA landscape (DMAL). This tool is useful for future reference when DMA applications get closer to clinical day-to-day use. Secondly, we discussed current challenges, lightly touching on first-order effects (related to the impact of DIR uncertainties in dose mapping), and focusing in detail on second-order effects often dismissed in the current literature (as resampling and interpolation, quality assurance considerations, and radiobiological issues). Finally, we developed recommendations, and guidelines for vendors and users. Our main point include: Strive for context-driven DIR (by considering their impact on clinical decisions/judgements) rather than perfect DIR; be conscious of the limitations of the implemented DIR algorithm; and consider when dose mapping (with properly quantified uncertainties) is a better alternative than no mapping.

Keywords: Anatomical changes; DIR uncertainties; Deformable image registration (DIR); Dose mapping/accumulation; Dose mapping/accumulation landscape (DMAL); Impact of dose mapping uncertainties.

Publication types

  • Review
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Humans
  • Image Processing, Computer-Assisted / methods
  • Radiation Oncology*
  • Radiotherapy Dosage
  • Radiotherapy Planning, Computer-Assisted / methods