Quality management in radiotherapy treatment delivery

Kron, Tomas; Fox, C.; Ebert, Martin A.; Thwaites, David

doi:10.1111/1754-9485.13348

Cited by 16 publications

(15 citation statements)

References 86 publications

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“…If a plan is too complex, not modelled precisely, or utilises beam arrangements that are not robust to changes in patient anatomy or other parameters, then the delivered dose will not match the initial clinically accepted treatment plan. The issue of delivering the planned dose accurately is a separate, but intrinsically inter‐linked topic 95 . However, some points are worth mentioning.…”

Section: Treatment Plan Evaluation Methods and Toolsmentioning

confidence: 99%

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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: Treatment Plan Evaluation Methods and Toolsmentioning

confidence: 99%

“…The issue of delivering the planned dose accurately is a separate, but intrinsically inter-linked topic. 95 However, some points are worth mentioning.…”

Section: Treatment Plan Reportingmentioning

confidence: 99%

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

et al. 2022

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“…Radiotherapy (RT) is one of the main treatment modalities for neoplastic lesions. The goal of RT is to deliver a prescribed radiation dose (which is the energy deposited in matter by ionizing radiation per unit mass) to a tumor site meanwhile minimizing the damage to healthy tissue . The validation and radiation process control depends on the measurement of the absorbed dose, usually obtained with the use of dosimetric systems.…”

Section: Introductionmentioning

confidence: 99%

Dosimetric Double Network Hydrogel Based on Poly(vinyl-alcohol)/Phenylalanine-Derivatives with Enhanced Mechanical Properties

Locarno

Gallo

Arosio

et al. 2023

ACS Appl. Polym. Mater.

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An innovative double network hydrogel based on poly(vinyl-alcohol) (PVA) cross-linked with glutaraldehyde (GTA) was obtained by the addition of self-assembling phenylalanine (Phe) derivatives with the aim to achieve improved mechanical-elastic properties exploitable to produce 3D dosimeters. The self-assembling ability in fibrous structures of Phe derivatives (FmocPhe-OH, A; FmocPhe-Phe-OMe, P) even within the PVA gel was proved by AFM and SEM imaging. The proposed matrices containing A and P were completely characterized from the physical-chemical point of view in order to deeply understand how the two molecules influenced the hydrogel properties. Mechanical tests proved that the addition of the Phe derivatives produce higher stiffness, toughness, and stretchability of the hydrogels. In particular, these properties appear in the peptide P matrix and could be appropriately tailored by regulating the concentration of the added molecule. Preliminary dosimetric studies were also performed by infusing the studied hydrogels with Fricke solution. The P type has been demonstrated to be suitable for dosimetric applications by avoiding any effect on the dose response of the hydrogel. This work presents an unconventional material that is able to provide clinicians and medical physicists with effective and reliable 3D dosimetric measurements for the development of anthropomorphic phantoms that mimic mechanical properties and the radiological response of human tissues.

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“…In this step, the patient's treatment is conducted as a dry run before the patient's actual treatment. This process is performed with the help of computers to simulate the patient's anatomy and cancer location, for both practice and quality assurance purposes [11]. A study conducted in 2018 confirmed that this process resulted in reduction in the rate of incidents during treatment and anxiety levels of both patients and staff during treatment [12].…”

Section: The Radiotherapy Chainmentioning

confidence: 99%

Learning the Treatment Process in Radiotherapy Using an Artificial Intelligence–Assisted Chatbot: Development Study

Rebelo¹,

Sanders²,

Li³

et al. 2022

JMIR Form Res

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Background In knowledge transfer for educational purposes, most cancer hospital or center websites have existing information on cancer health. However, such information is usually a list of topics that are neither interactive nor customized to offer any personal touches to people facing dire health crisis and to attempt to understand the concerns of the users. Patients with cancer, their families, and the general public accessing the information are often in challenging, stressful situations, wanting to access accurate information as efficiently as possible. In addition, there is seldom any comprehensive information specifically on radiotherapy, despite the large number of older patients with cancer, to go through the treatment process. Therefore, having someone with professional knowledge who can listen to them and provide the medical information with good will and encouragement would help patients and families struggling with critical illness, particularly during the lingering pandemic. Objective This study created a novel virtual assistant, a chatbot that can explain the radiation treatment process to stakeholders comprehensively and accurately, in the absence of any similar software. This chatbot was created using the IBM Watson Assistant with artificial intelligence and machine learning features. The chatbot or bot was incorporated into a resource that can be easily accessed by the general public. Methods The radiation treatment process in a cancer hospital or center was described by the radiotherapy process: patient diagnosis, consultation, and prescription; patient positioning, immobilization, and simulation; 3D-imaging for treatment planning; target and organ contouring; radiation treatment planning; patient setup and plan verification; and treatment delivery. The bot was created using IBM Watson (IBM Corp) assistant. The natural language processing feature in the Watson platform allowed the bot to flow through a given conversation structure and recognize how the user responds based on recognition of similar given examples, referred to as intents during development. Therefore, the bot can be trained using the responses received, by recognizing similar responses from the user and analyzing using Watson natural language processing. Results The bot is hosted on a website by the Watson application programming interface. It is capable of guiding the user through the conversation structure and can respond to simple questions and provide resources for requests for information that was not directly programmed into the bot. The bot was tested by potential users, and the overall averages of the identified metrics are excellent. The bot can also acquire users’ feedback for further improvements in the routine update. Conclusions An artificial intelligence–assisted chatbot was created for knowledge transfer regarding radiation treatment process to the patients with cancer, their families, and the general public. The bot that is supported by machine learning was tested, and it was found that the bot can provide information about radiotherapy effectively.

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Quality management in radiotherapy treatment delivery

Cited by 16 publications

References 86 publications

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

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

Dosimetric Double Network Hydrogel Based on Poly(vinyl-alcohol)/Phenylalanine-Derivatives with Enhanced Mechanical Properties

Learning the Treatment Process in Radiotherapy Using an Artificial Intelligence–Assisted Chatbot: Development Study

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