The emerging role of radiation therapists in the contouring of organs at risk in radiotherapy: analysis of inter-observer variability with radiation oncologists for the chest and upper abdomen

Correlation between rCBV Delineation Similarity and Overall Survival in a Prospective Cohort of High-Grade Gliomas Patients: The Hidden Value of Multimodal MRI?

PURPOSE

The accuracy of target delineation in radiation treatment planning of high-grade gliomas (HGGs) is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Magnetic resonance imaging (MRI) represents the standard imaging modality for delineation of gliomas with inherent limitations in accurately determining the microscopic extent of tumors. The purpose of this study was to assess the survival impact of multi-observer delineation variability of multiparametric MRI (mpMRI) and [18F]-FET PET/CT.

MATERIALS AND METHODS

Thirty prospectively included patients with histologically confirmed HGGs underwent a PET/CT and mpMRI including diffusion-weighted imaging (DWI: b0, b1000, ADC), contrast-enhanced T1-weighted imaging (T1-Gado), T2-weighted fluid-attenuated inversion recovery (T2Flair), and perfusion-weighted imaging with computation of relative cerebral blood volume (rCBV) and K2 maps. Nine radiation oncologists delineated the PET/CT and MRI sequences. Spatial similarity (Dice similarity coefficient: DSC) was calculated between the readers for each sequence. Impact of the DSC on progression-free survival (PFS) and overall survival (OS) was assessed using Kaplan-Meier curves and the log-rank test.

RESULTS

The highest DSC mean values were reached for morphological sequences, ranging from 0.71 +/- 0.18 to 0.84 +/- 0.09 for T2Flair and T1Gado, respectively, while metabolic volumes defined by PET/CT achieved a mean DSC of 0.75 +/- 0.11. rCBV variability (mean DSC0.32 +/- 0.20) significantly impacted PFS (p = 0.02) and OS (p = 0.002).

CONCLUSIONS

Our data suggest that the T1-Gado and T2Flair sequences were the most reproducible sequences, followed by PET/CT. Reproducibility for functional sequences was low, but rCBV inter-reader similarity significantly impacted PFS and OS.

Deep learning application for abdominal organs segmentation on 0.35 T MR-Linac images

Introduction

Linear accelerator (linac) incorporating a magnetic resonance (MR) imaging device providing enhanced soft tissue contrast is particularly suited for abdominal radiation therapy. In particular, accurate segmentation for abdominal tumors and organs at risk (OARs) required for the treatment planning is becoming possible. Currently, this segmentation is performed manually by radiation oncologists. This process is very time consuming and subject to inter and intra operator variabilities. In this work, deep learning based automatic segmentation solutions were investigated for abdominal OARs on 0.35 T MR-images.

Methods

One hundred and twenty one sets of abdominal MR images and their corresponding ground truth segmentations were collected and used for this work. The OARs of interest included the liver, the kidneys, the spinal cord, the stomach and the duodenum. Several UNet based models have been trained in 2D (the Classical UNet, the ResAttention UNet, the EfficientNet UNet, and the nnUNet). The best model was then trained with a 3D strategy in order to investigate possible improvements. Geometrical metrics such as Dice Similarity Coefficient (DSC), Intersection over Union (IoU), Hausdorff Distance (HD) and analysis of the calculated volumes (thanks to Bland-Altman plot) were performed to evaluate the results.

Results

The nnUNet trained in 3D mode achieved the best performance, with DSC scores for the liver, the kidneys, the spinal cord, the stomach, and the duodenum of 0.96 ± 0.01, 0.91 ± 0.02, 0.91 ± 0.01, 0.83 ± 0.10, and 0.69 ± 0.15, respectively. The matching IoU scores were 0.92 ± 0.01, 0.84 ± 0.04, 0.84 ± 0.02, 0.54 ± 0.16 and 0.72 ± 0.13. The corresponding HD scores were 13.0 ± 6.0 mm, 16.0 ± 6.6 mm, 3.3 ± 0.7 mm, 35.0 ± 33.0 mm, and 42.0 ± 24.0 mm. The analysis of the calculated volumes followed the same behavior.

Discussion

Although the segmentation results for the duodenum were not optimal, these findings imply a potential clinical application of the 3D nnUNet model for the segmentation of abdominal OARs for images from 0.35 T MR-Linac.

Estimating how contouring differences affect normal tissue complication probability modelling

Background and purpose

Normal tissue complication probability (NTCP) models are developed from large retrospective datasets where automatic contouring is often used to contour the organs at risk. This study proposes a methodology to estimate how discrepancies between two sets of contours are reflected on NTCP model performance. We apply this methodology to heart contours within a dataset of non-small cell lung cancer (NSCLC) patients.

Materials and methods

One of the contour sets is designated the ground truth and a dosimetric parameter derived from it is used to simulate outcomes via a predefined NTCP relationship. For each simulated outcome, the selected dosimetric parameters associated with each contour set are individually used to fit a toxicity model and their performance is compared. Our dataset comprised 605 stage IIA-IIIB NSCLC patients. Manual, deep learning, and atlas-based heart contours were available.

Results

How contour differences were reflected in NTCP model performance depended on the slope of the predefined model, the dosimetric parameter utilized, and the size of the cohort. The impact of contour differences on NTCP model performance increased with steeper NTCP curves. In our dataset, parameters on the low range of the dose-volume histogram were more robust to contour differences.

Conclusions

Our methodology can be used to estimate whether a given contouring model is fit for NTCP model development. For the heart in comparable datasets, average Dice should be at least as high as between our manual and deep learning contours for shallow NTCP relationships (88.5 ± 4.5 %) and higher for steep relationships.

Interpretable Machine Learning for Choosing Radiation Dose-volume Constraints on Cardio-pulmonary Substructures Associated with Overall Survival in NRG Oncology RTOG 0617

PURPOSE

Our objective was to use interpretable machine learning for choosing dose-volume constraints on cardiopulmonary substructures (CPSs) associated with overall survival (OS) in radiation therapy for locally advanced non-small cell lung cancer.

METHODS AND MATERIALS

A total of 428 patients with non-small cell lung cancer were randomly divided into training/validation/test subsets (n = 230/149/49) in Radiation Therapy Oncology Group 0617. Manual or automated contouring was performed to segment CPSs, including heart, atria, ventricles, aorta, left/right ventricle/atrium (LV+RV+LA+RA), inferior/superior vena cava, pulmonary artery, and pericardium. Peri (pericardium-heart), rest (heart-[LV+RV+LA+RA]), clinical target volume (CTV), and lungs-CTV contours were also obtained. Dose-volume histogram features were extracted, including minimum/mean dose to the hottest x% volume (Dx%[Gy]/MOHx%[Gy]), minimum/mean/maximum dose, percent volume receiving at least xGy (VxGy[%]), and overlapping volume of each CPS with planning target volume (PTV_Voverlap[%]). Clinical parameters were collected from the National Clinical Trials Network/Community oncology research program data archive. Feature selection was performed using a series of multiblock sparse partial least squares regression, stability selection supervised principal component analysis, and Boruta. Explainable boosting machine (EBM) was trained using a conditional survival distribution-based approach for imputing censored data, treating survival analysis as a regression problem. Harrell's C-index was used to evaluate OS discrimination performance of EBM, Cox proportional hazards (CPH), random survival forest, extreme gradient boosting survival embeddings, and CPH deep neural network (DeepSurv) models in the test set. Dose-volume constraints were selected using the binary change point detection algorithm in Shapley additive explanations-based partial dependence functions.

RESULTS

Selected features included LA_V60Gy(%), pericardium_D30%(Gy), lungs-CTV_PTV_Voverlap(%), RA_V55Gy(%), and received_cons_chemo. All models ranked LA_V60Gy(%) as the most important feature. EBM achieved the best performance for predicting OS, followed by extreme gradient boosting survival embeddings, random survival forest, DeepSurv, and CPH (C-index = 0.653, 0.646, 0.642, 0.638, and 0.632). EBM global explanations suggested that LA_V60Gy(%) < 25.6, lungs-CTV_PTV_Voverlap(%) < 1.1, pericardium_D30%(Gy) < 18.9, RA_V55Gy(%) < 19.5, and received_cons_chemo = 'Yes' for improved OS.

CONCLUSIONS

EBM can be used to discriminate OS while also guiding dose-volume constraint selection for optimal management of cardiac toxicity in lung cancer radiation therapy.

[Survey by SFRO, SNRO and AFPPE about the evolution of the radiation therapist profession in France]

PURPOSE

As part of the multidisciplinary team, radiation therapists are in charge of elements of treatment preparation and delivery of radiotherapy to cancer patients. Helping scientific and technological improvements, more and more patients with cancer were treated with radiotherapy including hypofractionnated radiotherapy, that explain the increase of demands on services. The professional impacted by this increase of demands are radiation oncologists and medical physicists. The opportunity to push forward the radiation therapist's competencies appears with the possibility to shift them some tasks. In this context, a first work was performed with objectives to have an overview of the tasks shifted to radiation therapists in France, the tasks that they could perform but also to evaluate some criteria of job satisfaction.

MATERIAL AND METHODS

The committee of "new status and value of status" including six radiation oncologists (the French society of radiation oncology [SFRO] et national union of radiation oncologists [SNRO]) and six radiation therapists committee members of the French association of radiation therapists (AFPPE), built a questionnaire including three parts: demographic characteristics, tasks shifted and job satisfaction criteria. In total, the questionnaire included 19 questions and 24 items assessed with a four point-Likert scale (ranging from "completely disagree" to "completely agree"). This survey, formatting with google form, was tested by the committee members and the final version was sent to the SFRO, AFPPE and SNRO members, before being disseminated on the social networks.

RESULTS

From November 18th 2022 to December 31st 2022, 492 responses were received (response rate=18.3%): 55 % of the respondents had at least 11 years of experience in radiotherapy. The respondents worked in different type of health facilities (36 % in specialized cancer centres, 19.5 % in private centers, 17.5% in university and general hospital, 10.2% in general hospital). More than ¼ of the respondents had a teaching lecturer activity, 20% had a management team activity and a research activity for 18%. Less than 10% of the respondents had another degree than that of radiation therapist: university degree (n=27), degree in dosimetry (n=11) and master (n=3). More than 76% would like to be trained and to have access to the advanced practice, more than 50% would like expend competencies with a university degree, 30% with a master and 67% would like to participate in research. Forty-two percent of the respondents were involved in a task shifting (excluding decree relating to acts and activities carried out by radiation therapists) and among the radiation therapists non-involved, 63% would be interested in being. Regarding job satisfaction, 53% of the respondents were satisfied with their job and their salary and 68% believed that their job occupation is in line with their professional aspirations. More than 2/3 of the respondents described a significant workload and mental load, 53% thought to have time for their patient care and 70% felt some organisational difficulties.

CONCLUSION

This survey shows: (i) A significant involvement of radiation therapists in the task shifting; (ii) A very strong demand for career development, in particular with existing degrees or to be created degree such as advanced practice; and (iii) The need to reinforce a job satisfaction for almost the half of the respondents, linked to a workload, a mental load and some organisational difficulties.

[Radiation therapists shortage in France: Organizational consequences and difficulties in deploying new missions and/or tasks delegation]

PURPOSE

Radiation therapists shortage has been evaluated at national level in France, specifically in oncology radiotherapy, in terms of: (i) organizational adaptations, (ii) impact on patients care, and (iii) difficulties in deploying new missions and/or tasks delegation.

MATERIALS AND METHODS

French professional organisations representing radiation therapists - SFRO, SNRO and AFPPE - sent their members a national survey (ten questions on 32 items).

RESULTS

From 18 November 2022 to 31 December 2022, 55 responses were received (response rate: 31%) from radiotherapy managers or department heads; 51% had a structure comprising three to five treatment rooms (receiving 500 to 1000 patients per year [36%], or 1500 to 2000 patients per year [33%]). Activities performed were intensity-modulated radiotherapy (100%), stereotaxic radiotherapy (85%), brachytherapy (40%), adaptive radiotherapy (34%). These structures described consequences in closing machine time for 25% of them (reduction of the hourly volume greater than 10% in 57%) with the following consequences in the last 6 months: (i) an extension of the period of medical care (78%), a closing of one or more accelerators (50%) and the development of moderate hypofractionation scheme or extreme hypofractionation (50%). In current functioning, linear accelerators can deliver treatments with a team of two radiation therapists per room for a short day (43%) or two to four radiation therapists per room teams for a long day (40%). During the last 6 months, there has been a 10% increase in linear accelerators operating with a single team. (ii) regarding treatment planning: 16.4% reported a decrease in the opening amplitude (less than 20% in 44% of cases, from 20 to 50% in 33 % of cases). The initial scheduling of appointments for radiotherapy sessions was carried out by radiation therapists in 84% of the departments in current functioning (0.1 to 1 FTE dedicated to this activity in 62% of the departments). Over the last 6 months, there has been a clear reduction in the number of dedicated FTEs: [FTE=0.1 to 1]=-8%; [FTE=0]=+7%. (ii) Regarding tasks delegation (excluding the decree on acts and activities carried out by the radiation therapist): organ at risk delineation is partially performed by radiation therapist in 26% of the centres; caregiver support time in 78% (56% totally or 22% partially). This activity has been reduced by 42%. Seventy-five percent of departments want to develop new techniques, patient-centered approaches (44%), implement task delegation (organ at risk delineation: 58%; weekly consultations: 67%; positioning imaging validation: 71%), and 78% of departments are interested in developing advanced radiotherapy practice. However, the number of radiation therapists is considered insufficient in their implementation in 76% of cases (one to two FTE missing for 72% of structures).

CONCLUSION

This survey shows a significant impact of radiation therapist shortage in radiotherapy oncology care (treatment delays, access to caregiver support time, workload on treatment teams), and represents a major obstacle to the development of radiotherapy structures.

Large scale crowdsourced radiotherapy segmentations across a variety of cancer anatomic sites

Clinician generated segmentation of tumor and healthy tissue regions of interest (ROIs) on medical images is crucial for radiotherapy. However, interobserver segmentation variability has long been considered a significant detriment to the implementation of high-quality and consistent radiotherapy dose delivery. This has prompted the increasing development of automated segmentation approaches. However, extant segmentation datasets typically only provide segmentations generated by a limited number of annotators with varying, and often unspecified, levels of expertise. In this data descriptor, numerous clinician annotators manually generated segmentations for ROIs on computed tomography images across a variety of cancer sites (breast, sarcoma, head and neck, gynecologic, gastrointestinal; one patient per cancer site) for the Contouring Collaborative for Consensus in Radiation Oncology challenge. In total, over 200 annotators (experts and non-experts) contributed using a standardized annotation platform (ProKnow). Subsequently, we converted Digital Imaging and Communications in Medicine data into Neuroimaging Informatics Technology Initiative format with standardized nomenclature for ease of use. In addition, we generated consensus segmentations for experts and non-experts using the Simultaneous Truth and Performance Level Estimation method. These standardized, structured, and easily accessible data are a valuable resource for systematically studying variability in segmentation applications.

Online adaptive MR-guided radiotherapy: Conformity of contour adaptation for prostate cancer, rectal cancer and lymph node oligometastases among radiation therapists and radiation oncologists

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Contour adaptation conformity analyzed for LN-metastases, rectal- + prostate cancer.

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Contour adaptation conformity among RTTs and radiation oncologists is comparable.

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Role expansion of RTTs with daily contour adaptation impacts workflow efficiency.

Background and purpose

Online adaptive MR-guided treatment planning workflows facilitate daily contour adaptation to the actual anatomy. Allocating contour adaptation to radiation therapists (RTTs) instead of radiation oncologists (ROs) might allow for increasing workflow efficiency. This study investigates conformity of adapted target contours provided by dedicated RTTs and ROs.

Materials and methods

In a simulated online procedure, 6 RTTs and 6 ROs recontoured targets and organs at risk (OAR) in prostate cancer (n = 2), rectal cancer (n = 2) and lymph node-oligometastases (n = 2) cases. RTTs gained contouring competence beforehand by following a specific in-house training program. For all target contours and the reference delineations volumetric differences were determined and Dice similarity coefficient (DSC), conformity index (CI) and generalized CI were calculated. Delineation time and –confidence were registered for targets and OAR. Impact of contour adaptation on treatment plan quality was investigated.

Results

Delineation conformity was generally high with DSC, CI and generalized CI values in the range of 0.81–0.94, 0.87–0.95 and 0.63–0.85 for prostate cancer, rectal cancer and LN-oligometastasis, respectively. Target volumes were comparable for both, RTTs and ROs. Time needed and confidence in contour adaptation was comparable as well. Treatment plans derived with adapted contours did not violate dose volume constrains as used in clinical routine.

Conclusion

After tumor site specific training, daily contour adaptations as needed in adaptive online radiotherapy workflows can be accurately performed by RTTs. Conformity of the derived contours is high and comparable to contours as provided by ROs.

Advanced practice roles of therapeutic radiographers/radiation therapists: A systematic literature review

INTRODUCTION

Advances in Radiotherapy (RT) technology and increase of complexity in cancer care have enabled the implementation of new treatment techniques. Subsequently, a greater level of autonomy, responsibility, and accountability in the practice of Therapeutic Radiographers/Radiation Therapists (TR/RTTs) has led to Advanced Practice (AP) roles. The published evidence of this role is scattered with confusing terminology and divergence regarding the perception of whether a specific role represents AP internationally. This study aims to establish an international baseline of evidence on AP roles in RT to identify roles and activities performed by TR/RTTs at advanced level practice and to summarise the impact.

METHODS

A systematic PRISMA review of the literature was undertaken. Thematic analysis was used to synthesise the roles and associated activities. Six RT external experts validated the list. The impact was scrutinised in terms of clinical, organisational, and professional outcomes.

RESULTS

Studies (n = 87) were included and categorised into four groups. AP roles were listed by clinical area, site-specific, and scope of practice, and advanced activities were organised into seven dimensions and 27 sub-dimensions. Three most-reported outcomes were: enhanced service capacity, higher patient satisfaction, and safety maintenance.

CONCLUSION

Evidence-based AP amongst TR/RTTs show how AP roles were conceptualised, implemented, and evaluated. Congruence studies have shown that TR/RTTs are at par with the gold-standard across the various AP roles.

IMPLICATIONS FOR PRACTICE

This is the first systematic literature review synthetisising AP roles and activities of TR/RTTs. This study also identified the main areas of AP that can be used to develop professional frameworks and education guiding policy by professional bodies, educators and other stakeholders.

Implementation of web-based open-source radiotherapy delineation software (WORDS) in organs at risk contouring training for newly qualified radiotherapists: quantitative comparison with conventional one-to-one coaching approach

BACKGROUND

Due to the role expansion of radiotherapists in dosimetric aspect, radiotherapists have taken up organs at risk (OARs) contouring work in many clinical settings. However, training of newly qualified radiotherapists in OARs contouring can be time consuming, it may also cause extra burden to experienced radiotherapists. As web-based open-source radiotherapy delineation software (WORDS) has become more readily available, it has provided a free and interactive alternative to conventional one-to-one coaching approach during OARs contouring training. The present study aims to evaluate the effectiveness of WORDS in training OARs contouring skills of newly qualified radiotherapists, compared to those trained by conventional one-to-one coaching approach.

METHODS

Nine newly qualified radiotherapists (licensed in 2017 - 2018) were enrolled to the conventional one-to-one coaching group (control group), while 11 newly qualified radiotherapists (licensed in 2019 - 2021) were assigned to WORDS training group (measured group). Ten OARs were selected to be contoured in this 3-phases quantitative study. Participants were required to undergo phase 1 OARs contouring in the beginning of the training session. Afterwards, conventional one-to-one training or WORDS training session was provided to participants according to their assigned group. Then the participants did phase 2 and 3 OARs contouring which were separated 1 week apart. Phase 1 - 3 OARs contouring aimed to demonstrate participants' pre-training OARs contouring ability, post-training OARs contouring ability and knowledge retention after one-week interval respectively using either training approach. To prevent bias, the computed tomography dataset for OARs contouring in each phase were different. Variations in the contouring scores for the selected OARs were evaluated between 3 phases using Kruskal-Wallis tests with Dunn tests for pairwise comparisons. Variations in the contouring scores between control and measured group in phase 1 - 3 contouring were analyzed using Wilcoxon signed-rank test. A p-value < 0.05 was considered to be statistically significant.

RESULTS

In both control group and measured group, significant improvement (p < 0.05) in phase 2 and 3 contouring scores have been observed comparing to phase 1 contouring scores. In comparison of contouring scores between control group and measured group, no significant differences (p > 0.05) were observed in all OARs between both groups.

CONCLUSIONS

The results in this study have demonstrated that the outcome of OARs contouring training using WORDS is comparable to the conventional training approach. In addition, WORDS can offer flexibility to newly qualified radiotherapists to practice OARs contouring at will, as well as reduce staff training burden of experienced radiotherapists.

[Cooperation protocol and advanced practice, an evolutionary perspective for the French radiation therapist]

For several years, the profession of radiographer has been unattractive and is in search of professional recognition. Increasingly complex therapeutic and diagnostic evolutions forces professionals to develop their skills to ensure quality and safe care for all patients. The primary role of the radiographer is to support patients and to accompany them during their examination or treatment, combining caregiver and technician's roles. Transversal missions and delegation of tasks are inherent to the profession but are not widely recognized. Cooperation between radiotherapy professionals is a response to offer the therapeutic radiographer/radiation therapist (RTT) opportunities in terms of attractiveness, career prospects, and increased skills. In radiotherapy, advanced practice activities already exist in some departments but require regulatory adjustments, in particular regarding the redistribution of the roles of RTT but also the status of these professionals. The formalization of these practices can be largely inspired by the many feedbacks around the world. This article aims to reflect the evolution's perspectives in the career of an RTT and on the valorisation of this profession in the current context.