Literature DB >> 32987045

What is plan quality in radiotherapy? The importance of evaluating dose metrics, complexity, and robustness of treatment plans.

Victor Hernandez1, Christian Rønn Hansen2, Lamberto Widesott3, Anna Bäck4, Richard Canters5, Marco Fusella6, Julia Götstedt7, Diego Jurado-Bruggeman8, Nobutaka Mukumoto9, Laura Patricia Kaplan10, Irena Koniarová11, Tomasz Piotrowski12, Lorenzo Placidi13, Ana Vaniqui5, Nuria Jornet14.   

Abstract

Plan evaluation is a key step in the radiotherapy treatment workflow. Central to this step is the assessment of treatment plan quality. Hence, it is important to agree on what we mean by plan quality and to be fully aware of which parameters it depends on. We understand plan quality in radiotherapy as the clinical suitability of the delivered dose distribution that can be realistically expected from a treatment plan. Plan quality is commonly assessed by evaluating the dose distribution calculated by the treatment planning system (TPS). Evaluating the 3D dose distribution is not easy, however; it is hard to fully evaluate its spatial characteristics and we still lack the knowledge for personalising the prediction of the clinical outcome based on individual patient characteristics. This advocates for standardisation and systematic collection of clinical data and outcomes after radiotherapy. Additionally, the calculated dose distribution is not exactly the dose delivered to the patient due to uncertainties in the dose calculation and the treatment delivery, including variations in the patient set-up and anatomy. Consequently, plan quality also depends on the robustness and complexity of the treatment plan. We believe that future work and consensus on the best metrics for quality indices are required. Better tools are needed in TPSs for the evaluation of dose distributions, for the robust evaluation and optimisation of treatment plans, and for controlling and reporting plan complexity. Implementation of such tools and a better understanding of these concepts will facilitate the handling of these characteristics in clinical practice and be helpful to increase the overall quality of treatment plans in radiotherapy.
Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Complexity; Complexity metrics; Dose metrics; Plan quality; Robust evaluation; Robust optimisation; Robustness

Mesh:

Year:  2020        PMID: 32987045     DOI: 10.1016/j.radonc.2020.09.038

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  18 in total

1.  Machine learning-based automated planning for hippocampal avoidance prophylactic cranial irradiation.

Authors:  Rodríguez de Dios N; Martínez Moñino A; Cristina Liu; Rafael Jiménez; Núria Antón; Miguel Prieto; Francesco Amorelli; Palmira Foro; Manuel Algara; Xavier Sanz; Ismael Membrive; Ana Reig; Jaume Quera; Enric Fernández-Velilla; Oscar Pera
Journal:  Clin Transl Oncol       Date:  2022-10-04       Impact factor: 3.340

2.  Effect of plan complexity on the dosimetry, delivery accuracy, and interplay effect in lung VMAT SBRT with 6 MV FFF beam.

Authors:  Chao Ge; Huidong Wang; Kunzhi Chen; Wuji Sun; Huicheng Li; Yinghua Shi
Journal:  Strahlenther Onkol       Date:  2022-04-29       Impact factor: 4.033

3.  Optimization of collimator angles in dual-arc volumetric modulated arc therapy planning for whole-brain radiotherapy with hippocampus and inner ear sparing.

Authors:  Wuji Sun; Kunzhi Chen; Yu Li; Wenming Xia; Lihua Dong; Yinghua Shi; Chao Ge; Xu Yang; Libo Wang; Huidong Wang
Journal:  Sci Rep       Date:  2021-09-24       Impact factor: 4.379

4.  Treatment plan quality assessment for radiotherapy of rectal cancer patients using prediction of organ-at-risk dose metrics.

Authors:  Ana Vaniqui; Richard Canters; Femke Vaassen; Colien Hazelaar; Indra Lubken; Kirsten Kremer; Cecile Wolfs; Wouter van Elmpt
Journal:  Phys Imaging Radiat Oncol       Date:  2020-10-19

5.  Evaluation of plan robustness on the dosimetry of volumetric arc radiotherapy (VMAT) with set-up uncertainty in Nasopharyngeal carcinoma (NPC) radiotherapy.

Authors:  Zhen Ding; Xiaoyong Xiang; Qi Zeng; Jun Ma; Zhitao Dai; Kailian Kang; Suyan Bi
Journal:  Radiat Oncol       Date:  2022-01-03       Impact factor: 3.481

6.  The impact of different optimization strategies on the agreement between planned and delivered doses during volumetric modulated arc therapy for total marrow irradiation.

Authors:  Joanna Litoborska; Tomasz Piotrowski; Marta Kruszyna-Mochalska; Julian Malicki
Journal:  Contemp Oncol (Pozn)       Date:  2021-07-01

7.  Selection Strategy of Jaw Tracking in VMAT Planning for Lung SBRT.

Authors:  Wuji Sun; Yinghua Shi; Yu Li; Chao Ge; Xu Yang; Wenming Xia; Kunzhi Chen; Libo Wang; Lihua Dong; Huidong Wang
Journal:  Front Oncol       Date:  2022-02-08       Impact factor: 6.244

8.  Evaluation of Plan Robustness Using Hybrid Intensity-Modulated Radiotherapy (IMRT) and Volumetric Arc Modulation Radiotherapy (VMAT) for Left-Sided Breast Cancer.

Authors:  Zhen Ding; Qi Zeng; Kailian Kang; Meiling Xu; Xiaoyong Xiang; Chenbin Liu
Journal:  Bioengineering (Basel)       Date:  2022-03-24

9.  Dosimetric Comparison of Ultra-Hypofractionated and Conventionally Fractionated Radiation Therapy Boosts for Patients with High-Risk Prostate Cancer.

Authors:  Tomasz Piotrowski; Slav Yartsev; Jaroslaw Krawczyk; Marta Adamczyk; Agata Jodda; Julian Malicki; Piotr Milecki
Journal:  Life (Basel)       Date:  2022-03-09

10.  Forecasting of the composite dose for organs at risk and solid targets with random movements during different image-guided scenarios of the photon radiation therapy. Solution for the Varian therapeutic line.

Authors:  Adam Ryczkowski; Tomasz Piotrowski
Journal:  Rep Pract Oncol Radiother       Date:  2021-06-09
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