Using prediction models to evaluate magnetic resonance image guided radiation therapy plans

Thomas, Maria; Olick-Gibson, Joshua; Fu, Yabo; Parikh, Parag J.; Green, Olga; Yang, Deshan

doi:10.1016/j.phro.2020.10.002

Cited by 4 publications

(2 citation statements)

References 24 publications

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“…These are usually based on a reference plan, which should be robust to anatomy changes, such that online planning constraints are easily tuned to the new situation. Few studies have yet compared the quality of adaptive and reference plans 47,48 and this requires more data.…”

Section: Adaptive Planningmentioning

confidence: 99%

Plan quality in radiotherapy treatment planning – Review of the factors and challenges

et al. 2022

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A high-quality treatment plan aims to best achieve the clinical prescription, balancing high target dose to maximise tumour control against sufficiently low organ-at-risk dose for acceptably low toxicity. Treatment planning (TP) includes multiple steps from simulation/imaging and segmentation to technical plan production and reporting. Consistent quality across this process requires close collaboration and communication between clinical and technical experts, to clearly understand clinical requirements and priorities and also practical uncertainties, limitations and compromises. TP quality depends on many aspects, starting from commissioning and quality management of the treatment planning system (TPS), including its measured input data and detailed understanding of TPS models and limitations. It requires rigorous quality assurance of the whole planning process and it links to plan deliverability, assessable by measurement-based verification. This review highlights some factors influencing plan quality, for consideration for optimal plan construction and hence optimal outcomes for each patient. It also indicates some challenges, sources of difference and current developments. The topics considered include: the evolution of TP techniques; dose prescription issues; tools and methods to evaluate plan quality; and some aspects of practical TP. The understanding of what constitutes a high-quality treatment plan continues to evolve with new techniques, delivery methods and related evidence-based science. This review summarises the current position, noting developments in the concept and the need for further robust tools to help achieve it.

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Section: Adaptive Planningmentioning

confidence: 99%

Plan quality in radiotherapy treatment planning – Review of the factors and challenges

et al. 2022

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“…A major challenge of real-time adaptive RT is the methodology of real-time dose calculation or reconstruction. Fast et al ( 61 ) proposed a tool for online dose reconstruction which determined the delivered dose based on pre-calculated dose influence data in less than 10 ms. After initial investigations of online dose reconstruction based on 2D cine MR images ( 62 ) and 3D cine MR in addition to treatment log files ( 63 ), recent studies proposed deep learning strategies to empower real-time dose calculation and motion prediction ( 64 , 65 ). Even though proposed for offline planning, methods for deep learning-based dose prediction seem to be promising tools to support real-time dose reconstruction ( 66 , 67 ).…”

Section: Online Adaptive Rtmentioning

confidence: 99%

Technical Challenges of Real-Time Adaptive MR-Guided Radiotherapy

Thorwarth

Low

2021

Front. Oncol.

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In the past few years, radiotherapy (RT) has experienced a major technological innovation with the development of hybrid machines combining magnetic resonance (MR) imaging and linear accelerators. This new technology for MR-guided cancer treatment has the potential to revolutionize the field of adaptive RT due to the opportunity to provide high-resolution, real-time MR imaging before and during treatment application. However, from a technical point of view, several challenges remain which need to be tackled to ensure safe and robust real-time adaptive MR-guided RT delivery. In this manuscript, several technical challenges to MR-guided RT are discussed. Starting with magnetic field strength tradeoffs, the potential and limitations for purely MR-based RT workflows are discussed. Furthermore, the current status of real-time 3D MR imaging and its potential for real-time RT are summarized. Finally, the potential of quantitative MR imaging for future biological RT adaptation is highlighted.

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