Heuristics for the direct aperture optimisation in intensity modulated radiotion therapy: a systematic literature review

Intensity-modulated radiation therapy (IMRT) is an advanced technique for cancer treatment that uses a computer-controlled linear accelerator to customise beams’ radiation intensities for patients, optimising the treatment effectiveness. The complexity of IMRT planning requires sophisticated algorithms to solve the different optimisation problems that arise in the context of IMRT treatment planning. One of those optimisation problems is the Direct Aperture Optimisation (DAO). The DAO problem aims to find a set of aperture shapes for each beam angle to enhance precision and improve clinical outcomes. However, this process is computationally intensive and thus, heuristic approaches have been proposed to balance computational efficiency and solution quality, offering nearly optimal solutions within clinically acceptable times. This systematic literature review aims to trace the development and application of heuristic algorithms for the DAO problem in the context of IMRT over the past two decades. We synthesised 41 studies published between 2002 and 2023, sourced from seven major databases (ACM, IEEE Xplore, PubMed, ScienceDirect, Springer, Scopus, and Web of Science). The review highlights key trends, innovations, and future directions in using heuristic methods for DAO, providing valuable insights for researchers and practitioners in radiotherapy optimisation.

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Publication Details

Journal
Artificial Intelligence Review
Published
2025-11-11
DOI
https://doi.org/10.1007/s10462-025-11378-5
Primary Topic
Advanced Radiotherapy Techniques
Type
article
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article

Heuristics for the direct aperture optimisation in intensity modulated radiotion therapy: a systematic literature review

Mauricio Moyano, Guillermo Cabrera‐Guerrero, Gonzalo Tello-Valenzuela, Keiny Meza-Vasquez et al.
Artificial Intelligence Review
Advanced Radiotherapy Techniques
article

Heuristics for the direct aperture optimisation in intensity modulated radiotion therapy: a systematic literature review

Mauricio Moyano, Guillermo Cabrera‐Guerrero, Gonzalo Tello-Valenzuela, Keiny Meza-Vasquez, Nicolle Ojeda-Ortega, Vinicius Cabrera Jameli, Maximiliano Beltran-Villarroel, Sebastian Muñoz-Bustos
article en

Abstract

Intensity-modulated radiation therapy (IMRT) is an advanced technique for cancer treatment that uses a computer-controlled linear accelerator to customise beams’ radiation intensities for patients, optimising the treatment effectiveness. The complexity of IMRT planning requires sophisticated algorithms to solve the different optimisation problems that arise in the context of IMRT treatment planning. One of those optimisation problems is the Direct Aperture Optimisation (DAO). The DAO problem aims to find a set of aperture shapes for each beam angle to enhance precision and improve clinical outcomes. However, this process is computationally intensive and thus, heuristic approaches have been proposed to balance computational efficiency and solution quality, offering nearly optimal solutions within clinically acceptable times. This systematic literature review aims to trace the development and application of heuristic algorithms for the DAO problem in the context of IMRT over the past two decades. We synthesised 41 studies published between 2002 and 2023, sourced from seven major databases (ACM, IEEE Xplore, PubMed, ScienceDirect, Springer, Scopus, and Web of Science). The review highlights key trends, innovations, and future directions in using heuristic methods for DAO, providing valuable insights for researchers and practitioners in radiotherapy optimisation.

Artificial Intelligence ReviewVol. 59(1)
Pontificia Universidad Católica de Valparaíso (CL), National Autonomous University of Honduras (HN), University of Toronto (CA), Universidad Católica del Norte (CL), University of Valparaíso (CL)
Openalex Percentile: Top 57%
Advanced Radiotherapy Techniques
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Heuristics for the direct aperture optimisation in intensity modulated radiotion therapy: a systematic literature review — Mauricio Moyano, Guillermo Cabrera‐Guerrero, et al. · Artificial Intelligence Review (2025) | TGRS Research Map | TGRS