Radiotherapy practices have changed significantly over recent decades with the introduction of increasingly personalised approaches to preparation and treatment and the use of a wider range of imaging technology, treatment techniques and software such as Artificial Intelligence (AI). The lack of development of the radiotherapy tariff, which remunerates services for radiotherapy delivery, has contributed to poor adoption rates and inequitable access for patients to new advanced treatment technologies and software across England. The radiotherapy tariff has a potential to be a lever to drive innovation across the system, if it is routinely updated to respond to latest clinical consensus. The commissioning of radiotherapy services is being transferred from NHS England to Integrated Care Boards (ICBs), in their emerging role as 'strategic commissioners'. Along with wider reform to funding mechanisms set out in the 10 Year Health Plan, this presents an opportunity to reshape the commissioning and tariff structures for radiotherapy services to better reflect contemporary radiotherapy practice. This paper explores the limitations of current funding arrangements for radiotherapy. It proposes recommendations to ensure that providers are supported to deliver more productive, innovative and value-based radiotherapy.

PURPOSE:Sparing pharyngeal constrictor muscles (PCMs) during radiotherapy improves patient-reported swallowing function. This study aimed to explore the feasibility of integrating knowledge-based planning (KBP) with multicriteria optimization (MCO) in Eclipse v18.0 to selectively spare PCM, quantify the required trade-off in prophylactic planning target volume (PTV54) coverage, and to evaluate MCO performance. METHOD:Ten patients previously planned with KBP for oropharyngeal cancer (65, 60, and 54 Gy in 30 fractions) were retrospectively re-planned. Clinical plans were further optimized using trade-off exploration in MCO, with a priority order: spinal cord and brainstem sparing, high-dose and intermediate-dose target coverage, PCM sparing, low-dose target coverage, parotids sparing, remaining organs at risk (OAR). Plans were evaluated based on planning target volumes dose metrics (D50%, D98%, and D2%), homogeneity index (HI), conformity index (CI), and maximum and mean doses to OARs, and paired t-tests were performed. Differences between navigated and deliverable plans were analyzed. One patient underwent 10 identical repeat plan generations. RESULTS:MCO reduced the average mean dose to the superior and middle PCM, inferior PCM, contralateral parotid, and larynx by 2.0, 3.4, 2.6, and 3.9 Gy, respectively (p < 0.05) but at the expense of HI and CI. No difference was observed in average PTV54 D98% between techniques; however, all clinical plans and seven MCO plans achieved D98% ≥ 95%, with three MCO plans modestly compromised (D98% 93.7%-94.6%). Dose metrics between navigated and deliverable plans differed by ≤0.7 Gy for mean doses and ≤1.8 Gy for maximum doses. Pareto surface generation was not repeatable. CONCLUSION:MCO effectively balances the trade-off between PCM sparing and low-dose target coverage. It may be a valuable tool in the context of personalized care.

BackgroundWith the introduction of a new multi-leaf collimator (MLC) enhanced leaf model (ELM) in the Varian Eclipse (TM) treatment planning system, there is currently limited data regarding the dosimetric sensitivity to real-world variation in the ELM parameters, and its clinical relevance.PurposeTo characterize the variation in ELM parameters across a large department with ten linear accelerators and investigate the feasibility of using a single machine-averaged ELM for treatment planning. This could achieve time and resource savings from reduced quality assurance, while allowing easy transfer of patients between machines.MethodsClinical plans of a range of sites (head and neck, prostate, breast, lung, and brain), techniques (VMAT, IMRT, SBRT, and SRS), and energies (6 MV, 6 MV FFF, 10 MV, and 10 MV FFF) were recalculated on Varian TrueBeam (TM) (120 MLC) and Varian EDGE (TM) (HD120 MLC), with machine-specific ELM beam models, an averaged machine and an outlier machine model. A range of clinically relevant metrics relating to target coverage (e.g. PTV D98%, D50%, D2%) and OAR doses (dosimetric, volumetric, conformity, and gradient indices) were evaluated.ResultsFor the target metrics, the maximum percentage deviation from the mean was 0.422%, 0.157%, and 1.956% for the cases of the individual machines, the averaged machine and the outlier machine correspondingly, while the maximum absolute dose differences were 0.28 Gy, 0.07 Gy, and 0.38 Gy. For the OAR metrics, the maximum deviation from the mean was 1.833%, 0.204%, and 5.722% for the individual, averaged, and outlier machines, while the maximum absolute dose differences were 0.41 Gy, 0.10 Gy, and 0.97 Gy.ConclusionsFor machines that are well matched in terms of dosimetry for transmission and sweeping gap fields, the use of an averaged machine model is unlikely to introduce clinically significant dosimetric differences to treatment plans.

Radiotherapy providers are dependent on capital investment in equipment, which makes up 62% of the cost of delivering radiotherapy. The commissioning of radiotherapy services and duty to replace equipment is currently held by NHS England, but this responsibility and funding will be delegated to all Integrated Care Boards (ICBs). With constraints in national health capital spend over the past decade leaving radiotherapy infrastructure depleted, ICBs are set to inherit an expensive task of updating and replacing radiotherapy equipment. The upcoming National Cancer Plan presents the opportunity for a long-term solution to the renewal and investment in radiotherapy equipment, through rolling ringfenced funding from Government.This paper is part of a series of three papers, on (1) radiotherapy tariff, (2) radiotherapy capital spending and (3) holistic aspects of radiotherapy funding, which together consider what a sustainable, innovative and person centred radiotherapy funding model looks like as specialised services are delegated to Integrated Care Boards.

Radiotherapy treatment can have transformative effects on a patient's overall health and wellbeing, yet current funding models are constrained to curative and palliative aspects of treatment delivery. This therapeutic focus, obscures wider costs associated with radiotherapy, both at a service level and for individual patients and their families. It is essential that policy and services consider quality of life after treatment, including identification and management of long-term side effects. Currently, a lack of service provision means that many patients have no access to services equipped to manage late toxicity or are utilising inappropriate services for their needs which could also be more costly for commissioners. As Integrated Care Boards (ICBs) take greater responsibility for the whole cancer pathway there are potential patient and cost benefits of rolling out more supportive oncology and late effects services. This should be supported with better data, including Patient Reported Data (PRD) and research on the level of need for broader aspects of radiotherapy and post treatment aspects of patient experience.

INTRODUCTION:Shared decision-making (SDM) is on the NHS policy agenda, and the preferred model for preference-sensitive decisions. This study establishes baseline patient-perceived SDM in a radical head and neck cohort, and explores patients' views on SDM in a large, specialist trust. METHODS:An SDM questionnaire was distributed to all radical head and neck radiotherapy patients (N = 165), June-December 2023. This combined a well-validated instrument for measuring SDM from the patient perspective, SDM-Q-9, with additional questions exploring patient views. Thematic analysis was used to construct and interpret themes. RESULTS:65/165 (39%) questionnaires were returned. SDM-Q-9 mean standardised score was 78.6 (SD 26.3). There was a moderate ceiling effect (26%). Scores were not sensitive to sex (p = 0.64) or age (ρ = 0.1). Higher levels of SDM were perceived by participants who stated SDM was very important (51/65, 79%) than somewhat or not at all important (82.4 vs. 62.7; p = 0.02; Cohen d = 0.75). Individuals who discussed their personal priorities with the clinician (46/65, 70.8%), were more likely to be very satisfied with their involvement in SDM (89.1% vs. 52.9%). Thematic analysis generated three themes: Control, Desire for Transparency and Understanding, and Doctor as the Expert. CONCLUSION:Patient-perceived SDM levels are high for head and neck patients. Participants who value SDM also perceive higher levels of SDM. Patient satisfaction increases when individuals discuss their personal priorities. The modest response rate and self-selection bias affect the generalisability of the results. Only radiotherapy patients were included; those who chose alternative treatment may perceive different levels of SDM. The moderate ceiling effect may limit the use of SDM-Q-9 to measure impact of future interventions to improve SDM. IMPLICATIONS FOR PRACTICE:SDM-Q-9 should be combined with an objective, observer measure of SDM.

PurposeArtificial intelligence (AI) based commercial software can be used to automatically delineate organs at risk (OAR), with potential for efficiency savings in the radiotherapy treatment planning pathway, and reduction of inter- and intra-observer variability. There has been little research investigating gross failure rates and failure modes of such systems.Method50 head and neck (H&N) patient data sets with "gold standard" contours were compared to AI-generated contours to produce expected mean and standard deviation values for the Dice Similarity Coefficient (DSC), for four common H&N OARs (brainstem, mandible, left and right parotid). An AI-based commercial system was applied to 500 H&N patients. AI-generated contours were compared to manual contours, outlined by an expert human, and a gross failure was set at three standard deviations below the expected mean DSC. Failures were inspected to assess reason for failure of the AI-based system with failures relating to suboptimal manual contouring censored. True failures were classified into 4 sub-types (setup position, anatomy, image artefacts and unknown).ResultsThere were 24 true failures of the AI-based commercial software, a gross failure rate of 1.2%. Fifteen failures were due to patient anatomy, four were due to dental image artefacts, three were due to patient position and two were unknown. True failure rates by OAR were 0.4% (brainstem), 2.2% (mandible), 1.4% (left parotid) and 0.8% (right parotid).ConclusionTrue failures of the AI-based system were predominantly associated with a non-standard element within the CT scan. It is likely that these non-standard elements were the reason for the gross failure, and suggests that patient datasets used to train the AI model did not contain sufficient heterogeneity of data. Regardless of the reasons for failure, the true failure rate for the AI-based system in the H&N region for the OARs investigated was low (similar to 1%).

PurposeIn radiotherapy of the head and neck (H&N) it is common for the clinical target volume (CTV) to extend to the patient's skin. Adding a margin for set-up uncertainty and delivery creates a planning target volume (PTV) that extends beyond the patient surface. This can result in excessive fluence being delivered to the build-up region and therefore the skin. This study evaluates four different planning methods used when inverse-planning H&N radiotherapy treatments with CTV extending to the skin. The aim of the study was to determine which planning method gives superior plan quality.MethodTen H&N cancer patients with a CTV contoured to the skin were inverse-planned using four planning methods. The planning methods compared were: cropping the optimization PTV back from the skin surface by 5.0, 3.0, and 0.0 mm and a virtual bolus method. For each planning method, the increased fluence at the skin surface was analyzed. The CTV coverage and skin doses were compared. Plan robustness was evaluated by applying an isocenter shift of +/- 3.0 mm in the major axes.ResultsThe planning method cropping the PTV 0.0 mm from the skin surface results in an increased fluence in the build-up region. The average volume of CTV receiving 98% of the prescription dose was 89.6% +/- 3.4%, 91.6% +/- 2.4%, and 93.5% +/- 1.7% when cropped 5.0, 3.0, and 0.0 mm, respectively, and 93.4% +/- 2.1% for the virtual bolus method. Introducing plan uncertainty affects CTV coverage the most when cropping 5.0 mm. When plan uncertainties are considered the methods of cropping 5.0, 3.0 mm, and the virtual bolus method have the same average skin dose within +/- 0.3%.ConclusionThis study shows that a virtual bolus planning method results in no increased fluence at the patient's surface, improves CTV coverage, and is the most robust to changes in setup and patient anatomy.

Radiotherapy is needed by half of all patients with cancer. The Lancet Oncology Commission 1 Atun R Jaffray DA Barton MB et al. Expanding global access to radiotherapy. Lancet Oncol. 2015; 16: 1153-1186 Summary Full Text Full Text PDF PubMed Scopus (660) Google Scholar on expanding global access to radiotherapy in 2015 reported that, with relatively modest investment, radiotherapy could treat large numbers of patients with cancer and save lives. International efforts are underway to ensure equal access to radiotherapy through effective implementation of national cancer control plans (NCCPs) with adequate, sustainable financing mechanisms and strong political commitment. The Global Coalition for Radiotherapy has recommended radiotherapy essential standards 2 International Cancer Control PartnershipRadiotherapy essential standards. https://www.iccp-portal.org/news/radiotherapy-essential-standardsDate: 2023 Date accessed: February 12, 2024 Google Scholar for inclusion in NCCPs, and work has begun with the US National Institutes of Health on the worldwide implementation of radiotherapy services.

Purpose/objective: To date there has been limited research looking at patient views on the imple-mentation of artificial intelligence (AI) in radiotherapy. The aim of this study is to adapt and utilise a validated patient questionnaire to develop an understanding of current patient views on the use of AI in radiotherapy. Materials/methods: An existing questionnaire, developed to assess understanding of patients' views on the implementation of AI in radiology, was adapted to the field of radiotherapy. The questionnaire was distributed to cancer patients receiving radiotherapy treatment between November 2021 and March 2022. Completed questionnaires were analysed to assess patient levels of positivity or negativity towards AI. Results were grouped into five factors, representing underlying patient perspectives, and correlation of factors with demographic variables was assessed. Results: In total, 95 patients participated. Overall, there was a moderately negative patient view towards the use of AI in radiotherapy. Certain factors drew a more negative response than others, for example patients desire significant personal interaction with healthcare professionals during the course of their treatment. No significant correlation was found between the demographics of age and gender and the strength of views towards the use of AI in radiotherapy. Conclusion: This study has found that there are clear patient concerns around the use of AI in radio-therapy. As the use of AI in this field increases in future years, it will therefore be extremely important to educate and involve patients in the future direction of this technology. (c) 2023 The Authors. Published by Elsevier Ltd on behalf of The College of Radiographers. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

PURPOSE:We have experimentally and computationally characterized the PTW microSilicon 60023-type diode's performance in 6 and 15 MV photon fields ≥5 × 5 mm2 projected to isocenter. We tested the detector on- and off-axis at 5 and 15 cm depths in water, and investigated whether its response could be improved by including within it a thin airgap. METHODS:Experimentally, detector readings were taken in fields generated by a Varian TrueBeam linac and compared with doses-to-water measured using Gafchromic film and ionization chambers. An unmodified 60023-type diode was tested along with detectors modified to include 0.6, 0.8, and 1.0 mm thick airgaps. Computationally, doses absorbed by water and detectors' sensitive volumes were calculated using the EGSnrc/BEAMnrc Monte Carlo radiation transport code. Detector response was characterized using k Q c l i n , 4 cm f c l i n , 4 cm , a factor that corrects for differences in the ratio of dose-to-water to detector reading between small fields and the reference condition, in this study 5 cm deep on-axis in a 4 × 4 cm2 field. RESULTS:The greatest errors in measurements of small field doses made using uncorrected readings from the unmodified 60023-type detector were over-responses of 2.6% ± 0.5% and 5.3% ± 2.0% determined computationally and experimentally, relative to the reading-per-dose in the reference field. Corresponding largest errors for the earlier 60017-type detector were 11.9% ± 0.6% and 11.7% ± 1.4% over-responses. Adding even the thinnest, 0.6 mm, airgap to the 60023-type detector over-corrected it, leading to under-responses of up to 4.8% ± 0.6% and 5.0% ± 1.8% determined computationally and experimentally. Further, Monte Carlo calculations indicate that a detector with a 0.3 mm airgap would read correctly to within 1.3% on-axis. The ratio of doses at 15 and 5 cm depths in water in a 6 MV 4 × 4 cm2 field was measured more accurately using the unmodified 60023-type detector than using the 60017-type detector, and was within 0.3% of the ratio measured using an ion chamber. The 60023-type diode's sensitivity also varied negligibly as dose-rate was reduced from 13 to 4 Gy min-1 by decreasing the linac pulse repetition frequency, whereas the sensitivity of the 60017-type detector fell by 1.5%. CONCLUSIONS:The 60023-type detector performed well in small fields across a wide range of beam energies, field sizes, depths, and off-axis positions. Its response can potentially be further improved by adding a thin, 0.3 mm, airgap.

AbstractPurposeExplore the feasibility of adopting failure modes and effects analysis (FMEA) for risk assessment of a high volume clinical service at a UK radiotherapy center. Compare hypothetical failure modes to locally reported incidents.MethodAn FMEA for a lung radiotherapy service was conducted at a hospital that treats ~ 350 lung cancer patients annually with radical radiotherapy. A multidisciplinary team of seven people was identified including a nominated facilitator. A process map was agreed and failure modes identified and scored independently, final failure modes and scores were then agreed at a face‐to‐face meeting. Risk stratification methods were explored and staff effort recorded. Radiation incidents related to lung radiotherapy reported locally in a 2‐year period were analyzed to determine their relation to the identified failure modes. The final FMEA was therefore a combination of prospective evaluation and retrospective analysis from an incident learning system.ResultsThirty‐six failure modes were identified for the pre‐existing clinical service. The top failure modes varied according to the ranking method chosen. The process required 30 h of combined staff time. Over the 2‐year period chosen, 38 voluntarily reported incidents were identified as relating to lung radiotherapy. Of these, 13 were not predicted by the identified failure modes, with six relating to delays in the process, three issues with appointment times, one communication error, two instances of a failure to image, and one technical fault deemed unpredictable by the manufacturer. Four additional failure modes were added to the FMEA following the incident analysis.ConclusionFMEA can be effectively applied to an established high volume service as a risk assessment method. Facilitation by an individual familiar with the FMEA process can reduce resource requirement. Prospective evaluation of risks should be combined with an incident reporting and learning system to produce a more comprehensive analysis of risk.

Purpose. In small megavoltage photon fields, the accuracies of an unmodified PTW 60017-type diode dosimeter and six diodes modified by adding airgaps of thickness 0.6-1.6 mm and diameter 3.6 mm have been comprehensively characterized experimentally and computationally. The optimally thick airgap for density compensation was determined, and detectors were micro-CT imaged to investigate differences between experimentally measured radiation responses and those predicted computationally.Methods. Detectors were tested on- and off-axis, at 5 and 15 cm depths in 6 and 15 MV fields >= 0.5 x 0.5 cm(2). Computational studies were carried out using the EGSnrc/BEAMnrc Monte Carlo radiation transport code. Experimentally, radiation was delivered using a Varian TrueBeam linac and doses absorbed by water were measured using Gafchromic EBT3 film and ionization chambers, and compared with diode readings. Detector response was characterized via the kQclin,Qmsrfclin,fmsr<iformalism, choosing a 4 x 4 cm(2)reference field.Results. For the unmodified 60017 diode, the maximum error in small field doses obtained from diode readings uncorrected by kQclin,Qmsrfclin,fmsr<ifactors was determined as 11.9% computationally at +0.25 mm off-axis and 5 cm depth in a 15 MV 0.5 x 0.5 cm(2)field, and 11.7% experimentally at -0.30 mm off-axis and 5 cm depth in the same field. A detector modified to include a 1.6 mm thick airgap performed best, with maximum computationally and experimentally determined errors of 2.2% and 4.1%. The 1.6 mm airgap deepened the modified dosimeter's effective point of measurement by 0.5 mm. For some detectors significant differences existed between responses in small fields determined computationally and experimentally, micro-CT imaging indicating that these differences were due to within-tolerance variations in the thickness of an epoxy resin layer.Conclusions. The dosimetric performance of a 60017 diode detector was comprehensively improved throughout 6 and 15 MV small photon fields via density compensation. For this approach to work well with good detector-to-detector reproducibility, tolerances on dense component dimensions should be reduced to limit associated variations of response in small fields, or these components should be modified to have more water-like densities.

Purpose: To analyse changes in 2-year overall survival (OS2yr) with radiotherapy (RT) dose, dose-perfraction, treatment duration and chemotherapy use, in data compiled from prospective trials of RT and chemo-RT (CRT) for locally-advanced non-small cell lung cancer (LA-NSCLC). Material and methods: OS2yr data was analysed for 6957 patients treated on 68 trial arms (21 RT-only, 27 sequential CRT, 20 concurrent CRT) delivering doses-per-fraction <= 4.0 Gy. An initial model considering dose, dose-per-fraction and RT duration was fitted using maximum-likelihood techniques. Model extensions describing chemotherapy effects and survival-limiting toxicity at high doses were assessed using likelihood-ratio testing, the Akaike Information Criterion (AIC) and cross-validation. Results: A model including chemotherapy effects and survival-limiting toxicity described the data significantly better than simpler models (p < 10(-)(14)), and had better AIC and cross-validation scores. The fitted alpha/beta ratio for LA-NSCLC was 4.0 Gy (95%CI: 2.8-6.0 Gy), repopulation negated 0.38 (95%CI: 0.31-0.47) Gy EQD2/day beyond day 12 of RT, and concurrent CRT increased the effective tumour EQD2 by 23% (95%CI: 16-31%). For schedules delivered in 2 Gy fractions over 40 days, maximum modelled OS2yr for RT was 52% and 38% for stages IIIA and IIIB NSCLC respectively, rising to 59% and 42% for CRT. These survival rates required 80 and 87 Gy (RT or sequential CRT) and 67 and 73 Gy (concurrent CRT). Modelled OS2yr rates fell at higher doses. Conclusions: Fitted dose-response curves indicate that gains of -10% in OS2yr can be made by escalating RT and sequential CRT beyond 64 Gy, with smaller gains for concurrent CRT. Schedule acceleration achieved via hypofractionation potentially offers an additional 5-10% improvement in OS2yr. Further 10-20% OS2yr gains might be made, according to the model fit, if critical normal structures in which survival-limiting toxicities arise can be identified and selectively spared. (C) 2019 Elsevier B.V. All rights reserved.

ConclusionFor cases involving higher dose effects on the evaluated structures, 4DOF registration improved plan conformity compared to 3DOF.Clinically relevant dose deviations in the CTV were not found in this patient collective.While mean dose delivery to OARs increased only slightly, up to 6 Gy in additional dose occurred for individual patient cases in this collective because of rotational errors.Safety margins for OARs could be a solution to this matter.