Correlation of contouring variation with modeled outcome for conformal non-small cell lung cancer radiotherapy

Impact of a contouring atlas on radiographer inter-observer variation in male pelvis radiotherapy

PURPOSE/OBJECTIVE

To determine the impact of a MR-based contouring atlas for male pelvis radiotherapy delineation on inter-observer variation to support radiographer led real-time magnetic resonance image guided adaptive radiotherapy (MRgART).

MATERIAL/METHODS

Eight RTTs contoured 25 MR images in the Monaco treatment planning system (Monaco 5.40.01), from 5 patients. The prostate, seminal vesicles, bladder, and rectum were delineated before and after the introduction of an atlas developed through multi-disciplinary consensus. Inter-observer contour variations (volume), time to contour and observer contouring confidence were determined at both time-points using a 5-point Likert scale. Descriptive statistics were used to analyse both continuous and categorical variables. Dice similarity coefficient (DSC), Dice-Jaccard coefficient (DJC) and Hausdorff distance were used to calculate similarity between observers.

RESULTS

Although variation in volume definition decreased for all structures among all observers post intervention, the change was not statistically significant. DSC and DJC measurements remained consistent following the introduction of the atlas for all observers. The highest similarity was found in the bladder and prostate whilst the lowest was the seminal vesicles. The mean contouring time for all observers was reduced by 50% following the introduction of the atlas (53 to 27 minutes, p=0.01). For all structures across all observers, the mean contouring confidence increased significantly from 2.3 to 3.5 out of 5 (p=0.02).

CONCLUSION

Although no significant improvements were observed in contour variation amongst observers, the introduction of the consensus-based contouring atlas improved contouring confidence and speed; key factors for a real-time RTT-led MRgART.

Evaluating the relationship between contouring variability and modelled treatment outcome for prostate bed radiotherapy

Objectives.Contouring similarity metrics are often used in studies of inter-observer variation and automatic segmentation but do not provide an assessment of clinical impact. This study focused on post-prostatectomy radiotherapy and aimed to (1) identify if there is a relationship between variations in commonly used contouring similarity metrics and resulting dosimetry and (2) identify the variation in clinical target volume (CTV) contouring that significantly impacts dosimetry.Approach.The study retrospectively analysed CT scans of 10 patients from the TROG 08.03 RAVES trial. The CTV, rectum, and bladder were contoured independently by three experienced observers. Using these contours reference simultaneous truth and performance level estimation (STAPLE) volumes were established. Additional CTVs were generated using an atlas algorithm based on a single benchmark case with 42 manual contours. Volumetric-modulated arc therapy (VMAT) treatment plans were generated for the observer, atlas, and reference volumes. The dosimetry was evaluated using radiobiological metrics. Correlations between contouring similarity and dosimetry metrics were calculated using Spearman coefficient (Γ). To access impact of variations in planning target volume (PTV) margin, the STAPLE PTV was uniformly contracted and expanded, with plans created for each PTV volume. STAPLE dose-volume histograms (DVHs) were exported for plans generated based on the contracted/expanded volumes, and dose-volume metrics assessed.Mainresults. The study found no strong correlations between the considered similarity metrics and modelled outcomes. Moderate correlations (0.5 <Γ< 0.7) were observed for Dice similarity coefficient, Jaccard, and mean distance to agreement metrics and rectum toxicities. The observations of this study indicate a tendency for variations in CTV contraction/expansion below 5 mm to result in minor dosimetric impacts.Significance. Contouring similarity metrics must be used with caution when interpreting them as indicators of treatment plan variation. For post-prostatectomy VMAT patients, this work showed variations in contours with an expansion/contraction of less than 5 mm did not lead to notable dosimetric differences, this should be explored in a larger dataset to assess generalisability.

Automated Contouring and Planning in Radiation Therapy: What Is 'Clinically Acceptable'?

Developers and users of artificial-intelligence-based tools for automatic contouring and treatment planning in radiotherapy are expected to assess clinical acceptability of these tools. However, what is 'clinical acceptability'? Quantitative and qualitative approaches have been used to assess this ill-defined concept, all of which have advantages and disadvantages or limitations. The approach chosen may depend on the goal of the study as well as on available resources. In this paper, we discuss various aspects of 'clinical acceptability' and how they can move us toward a standard for defining clinical acceptability of new autocontouring and planning tools.

Interobserver Variability Prediction of Primary Gross Tumor in a Patient with Non-Small Cell Lung Cancer

This research addresses the problem of interobserver variability (IOV), in which different oncologists manually delineate varying primary gross tumor volume (pGTV) contours, adding risk to targeted radiation treatments. Thus, a method of IOV reduction is urgently needed. Hypothesizing that the radiation oncologist’s IOV may shrink with the aid of IOV maps, we propose IOV prediction network (IOV-Net), a deep-learning model that uses the fuzzy membership function to produce high-quality maps based on computed tomography (CT) images. To test the prediction accuracy, a ground-truth pGTV IOV map was created using the manual contour delineations of radiation therapy structures provided by five expert oncologists. Then, we tasked IOV-Net with producing a map of its own. The mean squared error (prediction vs. ground truth) and its standard deviation were 0.0038 and 0.0005, respectively. To test the clinical feasibility of our method, CT images were divided into two groups, and oncologists from our institution created manual contours with and without IOV map guidance. The Dice similarity coefficient and Jaccard index increased by ~6 and 7%, respectively, and the Hausdorff distance decreased by 2.5 mm, indicating a statistically significant IOV reduction (p < 0.05). Hence, IOV-net and its resultant IOV maps have the potential to improve radiation therapy efficacy worldwide.

Comparative evaluation of a prototype deep learning algorithm for autosegmentation of normal tissues in head and neck radiotherapy

PURPOSE

To introduce and validate a newly developed deep-learning (DL) auto-segmentation algorithm for head and neck (HN) organs at risk (OARs) and to compare its performance with a published commercial algorithm.

METHODS

A total of 864 HN cancer cases were available to train and evaluate a prototype algorithm. The algorithm is based on a fully convolutional network with combined U-Net and V-net. A Dice loss plus Cross-Entropy Loss function with Adam optimizer was used in training. For 75 validation cases, OAR sets were generated with three DL-based models (A: the prototype model trained with gold data, B: a commercial software trained with the same data, and C: the same software trained with data from another institution). The auto-segmented structures were evaluated with Dice similarity coefficient (DSC), Hausdorff distance (HD), voxel-penalty metric (VPM) and DSC of area under dose-volume histograms. A subjective qualitative evaluation was performed on 20 random cases.

RESULTS

Overall trend was for the prototype algorithm to be the closest to the gold data by all five metrics. The average DSC/VPM/HD for algorithms A, B, and C were 0.81/84.1/1.6 mm, 0.74/62.8/3.2 mm, and 0.66/46.8/3.3 mm, respectively. 93% of model A structures were evaluated to be clinically useful.

CONCLUSION

The superior performance of the prototype was validated, even when trained with the same data. In addition to the challenges of perfecting the algorithms, the auto-segmentation results can differ when the same algorithm is trained at different institutions.

Validation of an established deep learning auto-segmentation tool for cardiac substructures in 4D radiotherapy planning scans

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Cardiotoxicity is a common complication of lung cancer radiotherapy.

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Segmentation of cardiac substructures is time-consuming and challenging.

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Deep learning segmentation tools can perform this task in 3D and 4D scans.

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Performance is high when assessed geometrically, dosimetrically and clinically.

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Auto-segmentation tools may accelerate clinical workflows and enable research.

Background

Emerging data suggest that dose-sparing several key cardiac regions is prognostically beneficial in lung cancer radiotherapy. The cardiac substructures are challenging to contour due to their complex geometry, poor soft tissue definition on computed tomography (CT) and cardiorespiratory motion artefact. A neural network was previously trained to generate the cardiac substructures using three-dimensional radiotherapy planning CT scans (3D-CT). In this study, the performance of that tool on the average intensity projection from four-dimensional (4D) CT scans (4D-AVE), now commonly used in lung radiotherapy, was evaluated.

Materials and Methods

The 4D-AVE of n=20 patients completing radiotherapy for lung cancer 2015–2020 underwent manual and automated cardiac substructure segmentation. Manual and automated substructures were compared geometrically and dosimetrically. Two senior clinicians also qualitatively assessed the auto-segmentation tool’s output.

Results

Geometric comparison of the automated and manual segmentations exhibited high levels of similarity across parameters, including volume difference (11.8% overall) and Dice similarity coefficient (0.85 overall), and were consistent with 3D-CT performance. Differences in mean (median 0.2 Gy, range −1.6–0.3 Gy) and maximum (median 0.4 Gy, range −2.2–0.9 Gy) doses to substructures were generally small. Nearly all structures (99.5 %) were deemed to be appropriate for clinical use without further editing.

Conclusions

Cardiac substructure auto-segmentation using a deep learning-based tool trained on a 3D-CT dataset was feasible on the 4D-AVE scan, meaning this tool is suitable for use on 4D-CT radiotherapy planning scans. Application of this tool would increase the practicality of routine clinical cardiac substructure delineation, and enable further cardiac radiation effects research.

The dosimetric impact of axillary nodes contouring variability in breast cancer radiotherapy: an AIRO multi-institutional study

AIM

To quantify the dosimetric impact of contouring variability of axillary lymph nodes (L2, L3, L4) in breast cancer (BC) locoregional radiotherapy (RT).

MATERIALS AND METHODS

18 RT centres were asked to plan a locoregional treatment on their own planning target volume (single centre, SC-PTV) which was created by applying their institutional margins to the clinical target volume of the axillary nodes of three BC patients (P1, P2, P3) previously delineated (SC-CTV). The gold standard CTVs (GS-CTVs) of P1, P2 and P3 were developed by BC experts' consensus and validated with STAPLE algorithm. For each participating centre, the GS-PTV of each patient was created by applying the same margins as those used for the SC-CTV to SC-PTV expansion and replaced the SC-PTV in the treatment plan. Datasets were imported into MIM v6.1.7 [MIM Software Inc.], where dose-volume histograms (DVHs) were extracted and differences were analysed.

RESULTS

17/18 centres used intensity-modulated RT (IMRT). The CTV to PTV margins ranged from 0 to 10 mm (median 5 mm). No correlation was observed between GS-CTV coverage by 95% isodose and GS-PTV margins width. Doses delivered to 98% (D98) and 95% (D95) of GS-CTVs were significantly lower than those delivered to the SC-CTVs. No significant difference between SC-CTV and GS-CTV was observed in maximum dose (D2), always under 110%. Mean dose ≥ 99% of the SC-CTVs and GS-CTVs was satisfied in 84% and 50%, respectively. In less than one half of plans, GS-CTV V95% was above 90%. Breaking down the GS-CTV into the three nodal levels (L2, L3 and L4), L4 had the lowest probability to be covered by the 95% isodose.

CONCLUSIONS

Overall, GS-CTV resulted worse coverage, especially for L4. IMRT was largely used and CTV-to-PTV margins did not compensate for contouring issues. The results highlighted the need for delineation training and standardization.

ProCaLung - Peer review in stage III, mediastinal node-positive, non-small-cell lung cancer: How to benchmark clinical practice of nodal target volume definition and delineation in Belgium☆

BACKGROUND AND PURPOSE

The Quality Assurance project for stage III non-small cell lung cancer radiotherapy ProCaLung performed a multicentric two-step exercise evaluating mediastinal nodal Target Volume Definition and Delineation (TVD) variability and the opportunity for standardization. The TVD variability before and after providing detailed guidelines and the value of qualitative contour reviewing before applying quantitative measures were investigated.

MATERIALS AND METHODS

The case of a patient with stage III NSCLC and involved mediastinal lymph nodes was used as a basis for this study. Twenty-two radiation oncologists from nineteen centers in Belgium and Luxembourg participated in at least one of two phases of the project (before and after introduction of ProCaLung contouring guidelines). The resulting thirty-three mediastinal nodal GTV and CTV contours were then evaluated using a qualitative-before-quantitative (QBQ) approach. First, a qualitative analysis was performed, evaluating adherence to most recent guidelines. From this, a list of observed deviations was created and these were used to evaluate contour conformity. The second analysis was quantitative, using overlap and surface distance measures to compare contours within qualitative groups and between phases. A 'most robust' reference volume for these analyses was created using the STAPLE-algorithm and an averaging method.

RESULTS

Five GTV and seven CTV qualitative groups were identified. Second step contours were more often in higher-conformity groups (p = 0.012 for GTV and p = 0.024 for CTV). Median Residual Mean Square Distances improved from 2.34 mm to 1.36 mm for GTV (p = 0.01) and from 4.53 mm to 1.58 mm for CTV (p < 0.0001). Median Dice coefficients increased from 0.81 to 0.84 for GTV (p = 0.07) and from 0.82 to 0.89 for CTV (p ≤ 0.001). Using HC-contours only to generate references translated in more robust quantitative evaluations.

CONCLUSION

Variability of mediastinal nodal TVD was reduced after providing the ProCaLung consensus guidelines. A qualitative review was essential for providing meaningful quantitative measures.

Challenges in the target volume definition of lung cancer radiotherapy

Radiotherapy, with or without systemic treatment has an important role in the management of lung cancer. In order to deliver the treatment accurately, the clinician must precisely outline the gross tumour volume (GTV), mostly on computed tomography (CT) images. However, due to the limited contrast between tumour and non-malignant changes in the lung tissue, it can be difficult to distinguish the tumour boundaries on CT images leading to large interobserver variation and differences in interpretation. Therefore the definition of the GTV has often been described as the weakest link in radiotherapy with its inaccuracy potentially leading to missing the tumour or unnecessarily irradiating normal tissue. In this article, we review the various techniques that can be used to reduce delineation uncertainties in lung cancer.

Reduction of inter-observer contouring variability in daily clinical practice through a retrospective, evidence-based intervention

BACKGROUND

Inter-observer variations (IOVs) arising during contouring can potentially impact plan quality and patient outcomes. Regular assessment of contouring IOV is not commonly performed in clinical practice due to the large time commitment required of clinicians from conventional methods. This work uses retrospective information from past treatment plans to facilitate a time-efficient, evidence-based intervention to reduce contouring IOV.

METHODS

The contours of 492 prostate cancer treatment plans created by four radiation oncologists were analyzed in this study. Structure volumes, lengths, and DVHs were extracted from the treatment planning system and stratified based on primary oncologist and inclusion of a pelvic lymph node (PLN) target. Inter-observer variations and their dosimetric consequences were assessed using Student's t-tests. Results of this analysis were presented at an intervention meeting, where new consensus contour definitions were agreed upon. The impact of the intervention was assessed one-year later by repeating the analysis on 152 new plans.

RESULTS

Significant IOV in prostate and PLN target delineation existed pre-intervention between oncologists, impacting dose to nearby OARs. IOV was also present for rectum and penile-bulb structures. Post-intervention, IOV decreased for all previously discordant structures. Dosimetric variations were also reduced. Although target contouring concordance increased significantly, some variations still persisted for PLN structures, highlighting remaining areas for improvement.

CONCLUSION

We detected significant contouring IOV in routine practice using easily accessible retrospective data and successfully decreased IOV in our clinic through a reflective intervention. Continued application of this approach may aid improvements in practice standardization and enhance quality of care.

Proposal for the delineation of neoadjuvant target volumes in oesophageal cancer

PURPOSE

To define instructions for delineation of target volumes in the neoadjuvant setting in oesophageal cancer.

MATERIALS AND METHODS

Radiation oncologists of five European centres participated in the following consensus process: [1] revision of published (MEDLINE) and national/institutional delineation guidelines; [2] first delineation round of five cases (patient 1-5) according to national/institutional guidelines; [3] consensus meeting to discuss the results of step 1 and 2, followed by a target volume delineation proposal; [4] circulation of proposed instructions for target volume delineation and atlas for feedback; [5] second delineation round of five new cases (patient 6-10) to peer review and validate (two additional centres) the agreed delineation guidelines and atlas; [6] final consensus on the delineation guidelines depicted in an atlas. Target volumes of the delineation rounds were compared between centres by Dice similarity coefficient (DSC) and maximum/mean undirected Hausdorff distances (H_max/H_mean).

RESULTS

In the first delineation round, the consistency between centres was moderate (CTVtotal: DSC = 0.59-0.88; H_mean = 0.2-0.4 cm). Delineations in the second round were much more consistent. Lowest variability was obtained between centres participating in the consensus meeting (CTVtotal: DSC: p < 0.050 between rounds for patients 6/7/8/10; H_mean: p < 0.050 for patients 7/8/10), compared to validation centres (CTVtotal: DSC: p < 0.050 between validation and consensus meeting centres for patients 6/7/8; H_mean: p < 0.050 for patients 7/10). A proposal for delineation of target volumes and an atlas were generated.

CONCLUSION

We proposed instructions for target volume delineation and an atlas for the neoadjuvant radiation treatment in oesophageal cancer. These will enable a more uniform delineation of patients in clinical practice and clinical trials.

Impact of dosimetric differences between CT and MRI derived target volumes for external beam cervical cancer radiotherapy

OBJECTIVES

The use of MRI is becoming more prevalent in cervical cancer external beam radiotherapy (RT). The aim of this study was to investigate the impact of dosimetric differences between CT and MRI-derived target volumes for cervical cancer external beam RT.

METHODS

An automated planning technique for volumetric modulated arc therapy was developed. Two automated planning plans were generated for 18 cervical cancer patients where planning target volumes (PTVs) were generated based on CT or MRI data alone. Dose metrics for planning target volumes and organs at risk (OARs) were compared to analyse any differences based on imaging modality.

RESULTS

All treatment plans were clinically acceptable. Bladder doses (V40) were lower in MRI-based plans (p = 0.04, 53.6 ± 17.2 % vs 60.3 ± 13.1 % for MRI vs CT, respectively). The maximum dose for left iliac crest showed lower doses in CT-based plans (p = 0.02, 47.8 ± 0.7 Gy vs 47.4 ± 0.4 Gy MRI vs CT, respectively). No significant differences were seen for other OARs.

CONCLUSIONS

The dosimetric differences of CT- and MRI-based contouring variability for this study was small. CT remains the standard imaging modality for volume delineation for these patients.

ADVANCES IN KNOWLEDGE

This is the first study to evaluate the dosimetric implications of imaging modality on target and OAR doses in cervical cancer external beam RT.

Dose planning variations related to delineation variations in MRI-guided brachytherapy for locally advanced cervical cancer

PURPOSE

To examine the variability in prescribed dose due to contouring variations in intracavitary image-guided adaptive brachytherapy for cervical cancer. To identify correlations between dosimetric outcomes and delineation uncertainty metrics.

METHODS AND MATERIALS

A data set from an EMBRACE sub-study on contouring uncertainties was used, consisting of magnetic resonance images of six patients with cervical cancer delineated by 10 experienced observers (target volumes and organs at risk). Two gold standard contours were generated, an expert consensus and the simultaneous truth and performance level estimation. Plans were individually optimised to all of the contour sets (12 in total). Plans were applied to the gold standard contour sets, and dose volume histogram parameters including D₉₀, D₉₈ and D_2cm³ were determined. The variability between plans was assessed. Dose volume histogram parameters and delineation uncertainty metrics were correlated using the Spearman's non-parametric rank correlation.

RESULTS

There is a dosimetric variability between observers, patients and the gold standard contour used for analysis. Approximately 3 Gy D₉₀ EQD2₁₀ variability (SD) was observed for the CTVHR and 1.2-3.6 Gy D_2cm³ EQD2₃ for the organs at risk. The maximum geometric dimensions of the delineations are most commonly correlated with dosimetry changes. Although the correlations are similar across gold standards, the direction of these correlations differs, indicating that the dosimetric outcomes are dependent on the contour that the plan is optimised to.

CONCLUSION

This study highlights the dosimetric differences interobserver uncertainty in contouring can have for cervical cancer brachytherapy. The importance of carefully choosing a gold standard from which to benchmark is reiterated.

Impact of Peer Review in the Radiation Treatment Planning Process: Experience of a Tertiary Care University Hospital in Pakistan

PURPOSE

To evaluate and report the frequency of changes in radiation therapy treatment plans after peer review in a simulation review meeting once a week.

MATERIALS AND METHODS

Between July 1 and August 31, 2016, the radiation plans of 116 patients were discussed in departmental simulation review meetings. All plans were finalized by the primary radiation oncologist before presenting them in the meeting. A team of radiation oncologists reviewed each plan, and their suggestions were documented as no change, major change, minor change, or missing contour. Changes were further classified as changes in clinical target volume, treatment field, or dose. All recommendations were stratified on the basis of treatment intent, site, and technique. Data were analyzed by Statistical Package for the Social Sciences and are presented descriptively.

RESULTS

Out of 116 plans, 26 (22.4%) were recommended for changes. Minor changes were suggested in 15 treatment plans (12.9%) and a major change in 10 (8.6%), and only one plan was suggested for missing contour. The frequency of change recommendations was greater in radical radiation plans than in palliative plans (92.3% v 7.7%). The head and neck was the most common treatment site recommended for any changes (42.3%). Most of the changes were recommended in the technique planned with three-dimensional conformal radiation therapy (50%). Clinical target volume (73.1%) was identified as the most frequent parameter suggested for any change, followed by treatment field (19.2%) and dose (0.08%).

CONCLUSION

Peer review is an important tool that can be used to overcome deficiencies in radiation treatment plans, with a goal of improved and individualized patient care. Our study reports changes in up to a quarter of radiotherapy plans.

Introducing FDG PET/CT-guided chemoradiotherapy for stage III NSCLC in low- and middle-income countries: preliminary results from the IAEA PERTAIN trial

Purpose

Patients with stage III non-small-cell lung cancer (NSCLC) treated with chemoradiotherapy (CRT) in low- and middle-income countries (LMIC) continue to have a poor prognosis. It is known that FDG PET/CT improves staging, treatment selection and target volume delineation (TVD), and although its use has grown rapidly, it is still not widely available in LMIC. CRT is often used as sequential treatment, but is known to be more effective when given concurrently. The aim of the PERTAIN study was to assess the impact of introducing FDG PET/CT-guided concurrent CRT, supported by training and quality control (QC), on the overall survival (OS) and progression-free survival (PFS) of patients with stage III NSCLC.

Methods

The study included patients with stage III NSCLC from nine medical centres in seven countries. A retrospective cohort was managed according to local practices between January 2010 and July 2014, which involved only optional diagnostic FDG PET/CT for staging (not for TVD), followed by sequential or concurrent CRT. A prospective cohort between August 2015 and October 2018 was treated according to the study protocol including FDG PET/CT in treatment position for staging and multimodal TVD followed by concurrent CRT by specialists trained in protocol-specific TVD and with TVD QC. Kaplan–Meier analysis was used to assess OS and PFS in the retrospective and prospective cohorts.

Results

Guidelines for FDG PET/CT image acquisition and TVD were developed and published. All specialists involved in the PERTAIN study received training between June 2014 and May 2016. The PET/CT scanners used received EARL accreditation. In November 2018 a planned interim analysis was performed including 230 patients in the retrospective cohort with a median follow-up of 14 months and 128 patients in the prospective cohort, of whom 69 had a follow-up of at least 1 year. Using the Kaplan–Meier method, OS was significantly longer in the prospective cohort than in the retrospective cohort (23 vs. 14 months, p = 0.012). In addition, median PFS was significantly longer in the prospective cohort than in the retrospective cohort (17 vs. 11 months, p = 0.012).

Conclusion

In the PERTAIN study, the preliminary results indicate that introducing FDG PET/CT-guided concurrent CRT for patients with stage III NSCLC in LMIC resulted in a significant improvement in OS and PFS. The final study results based on complete data are expected in 2020.

Electronic supplementary material

The online version of this article (10.1007/s00259-019-04421-5) contains supplementary material, which is available to authorized users.

The impact of training and professional collaboration on the interobserver variation of lung cancer delineations: a multi-institutional study

BACKGROUND

To assess the impact of training and interprofessional collaboration on the interobserver variation in the delineation of the lung gross tumor volume (GTVp) and lymph node (GTVln).

MATERIAL AND METHODS

Eight target volume delineations courses were organized between 2008 and 2013. Specialists and trainees in radiation oncology were asked to delineate the GTVp and GTVln on four representative CT images of a patient diagnosed with lung cancer individually prior each course (baseline), together as group (interprofessional collaboration) and post-training. The mean delineated volume and local standard deviation (local SD) between the contours for each course group were calculated and compared with the expert delineations.

RESULTS

A total 410 delineations were evaluated. The average local SD was lowest for the interprofessional collaboration (GTVp = 0.194 cm, GTVln = 0.371 cm) followed by the post-training (GTVp = 0.244 cm, GTVln = 0.607 cm) and baseline delineations (GTVp = 0.274 cm, GTVln: 0.718 cm). The mean delineated volume was smallest for the interprofessional (GTVp = 4.93 cm³, GTVln = 4.34 cm³) followed by the post-training (GTVp = 5.68 cm³, GTVln = 5.47 cm³) and baseline delineations (GTVp = 6.65 cm³, GTVln = 6.93 cm³). All delineations were larger than the expert for both GTVp and GTVln (p < .001).

CONCLUSION

Our findings indicate that image interpretational differences can lead to large interobserver variation particularly when delineating the GTVln. Interprofessional collaboration was found to have the greatest impact on reducing interobserver variation in the delineation of the GTVln. This highlights the need to develop a clinical workflow so as to ensure that difficult cases are reviewed routinely by a second radiation oncologist or radiologist so as to minimize the risk of geographical tumor miss and unnecessary irradiation to normal tissue.

Multi-observer contouring of male pelvic anatomy: Highly variable agreement across conventional and emerging structures of interest

INTRODUCTION

This study quantified inter-observer contouring variations for multiple male pelvic structures, many of which are of emerging relevance for prostate cancer radiotherapy progression and toxicity response studies.

METHODS

Five prostate cancer patient datasets (CT and T2-weighted MR) were distributed to 13 observers for contouring. CT structures contoured included the clinical target volume (CTV), seminal vesicles, rectum, colon, bowel bag, bladder and peri-rectal space (PRS). MR contours included CTV, trigone, membranous urethra, penile bulb, neurovascular bundle and multiple pelvic floor muscles. Contouring variations were assessed using the intraclass correlation coefficient (ICC), Dice similarity coefficient (DSC), and multiple additional metrics.

RESULTS

Clinical target volume (CT and MR), bladder, rectum and PRS contours showed excellent inter-observer agreement (median ICC = 0.97; 0.99; 1.00; 0.95; 0.90, DSC = 0.83 ± 0.05; 0.88 ± 0.05; 0.93 ± 0.03; 0.81 ± 0.07; 0.80 ± 0.06, respectively). Seminal vesicle contours were more variable (ICC = 0.75, DSC = 0.73 ± 0.14), while colon and bowel bag contoured volumes were consistent (ICC = 0.97; 0.97), but displayed poor overlap (DSC = 0.58 ± 0.22; 0.67 ± 0.21). Smaller MR structures showed significant inter-observer variations, with poor overlap for trigone, membranous urethra, penile bulb, and left and right neurovascular bundles (DSC = 0.44 ± 0.22; 0.41 ± 0.21; 0.66 ± 0.21; 0.16 ± 0.17; 0.15 ± 0.15). Pelvic floor muscles recorded moderate to strong inter-observer agreement (ICC = 0.50-0.97), although large outlier variations were observed.

CONCLUSIONS

Inter-observer contouring variation was significant for multiple pelvic structures contoured on MR.

Challenges for Quality Assurance of Target Volume Delineation in Clinical Trials

In recent years, new radiotherapy techniques have emerged that aim to improve treatment outcome and reduce toxicity. The standard method of evaluating such techniques is to conduct large scale multicenter clinical trials, often across continents. A major challenge for such trials is quality assurance to ensure consistency of treatment across all participating centers. Analyses from previous studies have shown that poor compliance and protocol violation have a significant adverse effect on treatment outcomes. The results of the clinical trials may, therefore, be confounded by poor quality radiotherapy. Target volume delineation (TVD) is one of the most critical steps in the radiotherapy process. Many studies have shown large inter-observer variations in contouring, both within and outside of clinical trials. High precision techniques, such as intensity-modulated radiotherapy, image-guided brachytherapy, and stereotactic radiotherapy have steep dose gradients, and errors in contouring may lead to inadequate dose to the tumor and consequently, reduce the chance of cure. Similarly, variation in organ at risk delineation will make it difficult to evaluate dose response for toxicity. This article reviews the literature on TVD variability and its impact on dosimetry and clinical outcomes. The implications for quality assurance in clinical trials are discussed.

ACTIVE MEAN FIELDS FOR PROBABILISTIC IMAGE SEGMENTATION: CONNECTIONS WITH CHAN-VESE AND RUDIN-OSHER-FATEMI MODELS

Segmentation is a fundamental task for extracting semantically meaningful regions from an image. The goal of segmentation algorithms is to accurately assign object labels to each image location. However, image-noise, shortcomings of algorithms, and image ambiguities cause uncertainty in label assignment. Estimating the uncertainty in label assignment is important in multiple application domains, such as segmenting tumors from medical images for radiation treatment planning. One way to estimate these uncertainties is through the computation of posteriors of Bayesian models, which is computationally prohibitive for many practical applications. On the other hand, most computationally efficient methods fail to estimate label uncertainty. We therefore propose in this paper the Active Mean Fields (AMF) approach, a technique based on Bayesian modeling that uses a mean-field approximation to efficiently compute a segmentation and its corresponding uncertainty. Based on a variational formulation, the resulting convex model combines any label-likelihood measure with a prior on the length of the segmentation boundary. A specific implementation of that model is the Chan-Vese segmentation model (CV), in which the binary segmentation task is defined by a Gaussian likelihood and a prior regularizing the length of the segmentation boundary. Furthermore, the Euler-Lagrange equations derived from the AMF model are equivalent to those of the popular Rudin-Osher-Fatemi (ROF) model for image denoising. Solutions to the AMF model can thus be implemented by directly utilizing highly-efficient ROF solvers on log-likelihood ratio fields. We qualitatively assess the approach on synthetic data as well as on real natural and medical images. For a quantitative evaluation, we apply our approach to the icgbench dataset.

Defining and assessing an anisotropic delineation margin for modern radiotherapy

PURPOSE

Uncertainty in target volume delineation for modern radiotherapy impacts dosimetry and patient outcomes. Delineation uncertainty is generally overlooked in practice as a source of error, potentially since historically, other uncertainties have been the main focus. This work defined and assessed an anisotropic delineation margin in both polar and spherical coordinate systems in order to account for the spatially varying nature of this uncertainty using a whole breast radiotherapy cohort as a proof of concept.

METHODS

A cohort of 21 whole breast radiotherapy patient datasets with clinical target volumes delineated by eight independent observers was utilized. Patients were divided into categories based on target volume and laterality. An anisotropic delineation margin for each category was determined by multiplying the average standard deviation in observer contours in each category by a factor of two. Standard deviation was determined in both polar and spherical coordinates at angular increments. This anisotropic approach was compared to a conventional clinical approach, where the delineation margin was applied in the cardinal directions only. The assessment of the delineation margin was undertaken by comparing the encompassment of the observer volumes by the target volume with added margin. The extra, presumed healthy tissue included in the margin and the malignant tissue missed by the margin were determined.

RESULTS

The proposed delineation margin is effective at accounting for inter-observer variation, producing >95% coverage of all CTVs for polar, spherical, and Cartesian margins in 82%, 79%, and 92% of cases, respectively. Additionally, <1% malignant tissue was missed for 65%, 70%, and 91% of cases and <37% healthy tissue was included in 95%, 89%, and 97% of cases. A conventional delineation margin approach is most appropriate for small and gold standard target volumes. However, for large target volumes, an anisotropic margin is necessary, producing significantly greater coverage of CTVs, including significantly less presumed healthy tissue and missing significantly less malignant tissue.

CONCLUSIONS

All delineation margin methods that account for target volume and laterality proved to be adequate, with appropriate encompassment of interobserver variation and minimal inclusion of extra excess healthy tissue and exclusion of possible malignant tissue. The anisotropic approach was found to be superior to a conventional approach for target volumes >1400 cm³ only with significantly greater encompassment of interobserver variation, less missed malignant tissue and less included healthy tissue. This methodology has been validated for a whole breast radiotherapy cohort as a proof of concept, however could be applied to other anatomical sites.

Uncertainties in volume delineation in radiation oncology: A systematic review and recommendations for future studies

BACKGROUND AND PURPOSE

Volume delineation is a well-recognised potential source of error in radiotherapy. Whilst it is important to quantify the degree of interobserver variability (IOV) in volume delineation, the resulting impact on dosimetry and clinical outcomes is a more relevant endpoint. We performed a literature review of studies evaluating IOV in target volume and organ-at-risk (OAR) delineation in order to analyse these with respect to the metrics used, reporting of dosimetric consequences, and use of statistical tests.

METHODS AND MATERIALS

Medline and Pubmed databases were queried for relevant articles using keywords. We included studies published in English between 2000 and 2014 with more than two observers.

RESULTS

119 studies were identified covering all major tumour sites. CTV (n=47) and GTV (n=38) were most commonly contoured. Median number of participants and data sets were 7 (3-50) and 9 (1-132) respectively. There was considerable heterogeneity in the use of metrics and methods of analysis. Statistical analysis of results was reported in 68% (n=81) and dosimetric consequences in 21% (n=25) of studies.

CONCLUSION

There is a lack of consistency in conducting and reporting analyses from IOV studies. We suggest a framework to use for future studies evaluating IOV.

The dosimetric impact of target volume delineation variation for cervical cancer radiotherapy

BACKGROUND

Cervical cancer inter-observer delineation variation has been demonstrated. This article addresses its dosimetric impact.

METHODS

21 centres outlined two INTERLACE trial quality assurance test cases. A gold standard clinical target volume (GSCTV) was created from a consensus and STAPLE outline. RapidArc plans were created for all centres' planning target volumes (PTVs; PTV1+2). Gold standard PTVs (GSPTVs) were created for each plan by applying each centre's CTV-PTV margins to GSCTV. DVH parameters including D95% and Dmean for each PTV1+2 and GSPTV were compared, representing planned versus GSPTV delivered dose. PTV1+2 and GSPTV V95% was also calculated.

RESULTS

Reviewing all parameters, no plans achieved acceptable GSPTV coverage. GSPTV V95%⩾95% was not achieved for any plan. GSPTV V95%<90% in 15/21 (case 1) and 14/22 (case 2) and <80% in 2 plans from both cases. GSPTV V95% is on average 10-15% lower than planned and GSPTV D95% is 10-20% lower than planned. Most common GSCTV anatomical areas not receiving 95% dose were vagina, obturator and external iliac nodes and, in case 1, the superior nodal aspect.

CONCLUSION

Cervical cancer CTV delineation variation leads to significant reductions in dose delivered to GSPTV. This highlights the ongoing importance of standardising delineation in the IMRT era.

Results of the Australasian (Trans-Tasman Oncology Group) radiotherapy benchmarking exercise in preparation for participation in the PORTEC-3 trial

INTRODUCTION

Protocol deviations in Randomised Controlled Trials have been found to result in a significant decrease in survival and local control. In some cases, the magnitude of the detrimental effect can be larger than the anticipated benefits of the interventions involved. The implementation of appropriate quality assurance of radiotherapy measures for clinical trials has been found to result in fewer deviations from protocol. This paper reports on a benchmarking study conducted in preparation for the PORTEC-3 trial in Australasia.

METHODS

A benchmarking CT dataset was sent to each of the Australasian investigators, it was requested they contour and plan the case according to trial protocol using local treatment planning systems. These data was then sent back to Trans-Tasman Oncology Group for collation and analysis.

RESULTS

Thirty three investigators from eighteen institutions across Australia and New Zealand took part in the study. The mean clinical target volume (CTV) volume was 383.4 (228.5-497.8) cm(3) and the mean dose to a reference gold standard CTV was 48.8 (46.4-50.3) Gy.

CONCLUSIONS

Although there were some large differences in the contouring of the CTV and its constituent parts, these did not translate into large variations in dosimetry. Where individual investigators had deviations from the trial contouring protocol, feedback was provided. The results of this study will be used to compare with the international study QA for the PORTEC-3 trial.