The suitability of common metrics for assessing parotid and larynx autosegmentation accuracy

Beasley, William; McWilliam, A.; Aitkenhead, A.; Mackay, Ranald I; Rowbottom, C.

doi:10.1120/jacmp.v17i2.5889

Cited by 19 publications

(26 citation statements)

References 29 publications

(33 reference statements)

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“…Development of NTCP models can be facilitated by generating agreement in dose constraint parameters, facilitated by a greater consistency in contouring the muscles of mastication. The reduction in variability in contouring the muscles of mastication may translate into a reduction in variability in reported dose to these structures [30]. It is beyond the scope of the present study however to determine the dosimetric effects of reduced clinician interobserver variation.…”

Section: Discussionmentioning

confidence: 92%

Use of a novel atlas for muscles of mastication to reduce inter observer variability in head and neck radiotherapy contouring

Hague

Beasley

Dixon

et al. 2019

Radiotherapy and Oncology

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Trismus is caused by injury to the masticatory muscles resulting from cancer or its treatment. Contouring these muscles to reduce dose and radiation related trismus can be problematic due to interobserver variability. This study aimed to evaluate the reduction in interobserver variability achievable with a new contouring atlas. Materials/methods: The atlas included: medial and lateral pterygoids (MP, LP), masseter (M) and temporalis (T) muscles, and the temporo-mandibular joint (TMJ). Seven clinicians delineated five paired structures on CT scans from 5 patients without the atlas. After 5 weeks, contouring was repeated using the atlas. Using contours generated by the clinicians on the same 5 CT scans as reference, dice similarity coefficient (DSC), mean distance-to-agreement (DTA) and centre of mass (COM) difference were compared with and without the atlas. Comparison was also performed split by training grade. Mean and standard deviation (SD) values were measured. Results: The atlas reduced interobserver variability for all structures. Mean DTA significantly improved for MP (p = 0.01), M (p < 0.01), T (p < 0.01) and TMJ (p < 0.01). Mean DTA improved using the atlas for the trainees across all muscles, with the largest reduction in variability observed for the T (4.3 ± 7.1 v 1.2 ± 0.4 mm, p = 0.06) and TMJ (2.1 ± 0.7 v 0.8 ± 0.3 mm, p < 0.01). Distance between the COM and interobserver variability reduced in all directions for MP and T. Conclusion: A new atlas for contouring masticatory muscles during radiotherapy planning for head and neck cancer reduces interobserver variability and could be used as an educational tool.

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Section: Discussionmentioning

confidence: 92%

Use of a novel atlas for muscles of mastication to reduce inter observer variability in head and neck radiotherapy contouring

Hague

Beasley

Dixon

et al. 2019

Radiotherapy and Oncology

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“…As stated by Vinod et al, an assessment of contouring variation based solely on geometry may have little to no clinical significance, especially where no correlations between contouring metrics and dosimetry have been performed. Additionally, commonly cited spatial overlap metrics conformity index and DSC have been shown to display only minimal to no significant correlations with dosimetry for non-small cell lung cancers (Jameson et al, 2014) and head and neck cancers (Beasley et al, 2016) respectively. As no study correlating contouring similarity metrics and dosimetry had been performed for prostate radiotherapy, this study was undertaken to bring clinical relevancy and allow insights into target volume and organ-at-risk dosimetry to other inter-observer contouring variation studies.…”

Section: Discussionmentioning

confidence: 99%

“…A combination of boundary and volume metrics is recommended (Fotina et al, 2012), however these metric choices may have little to no correlation with dosimetry. Studies investigating non-small cell lung cancers (Jameson et al, 2014) and head and neck cancers (Beasley et al, 2016) found that commonly utilised overlap metrics conformity index and DSC displayed weak or no correlations with simulated treatment outcome respectively. The aim of this study was to evaluate correlations between contouring similarity metrics and dosimetry for prostate cancer planned for VMAT radiotherapy.…”

Section: Introductionmentioning

confidence: 99%

Correlations between contouring similarity metrics and simulated treatment outcome for prostate radiotherapy

Roach¹,

Jameson²,

Dowling³

et al. 2018

Phys. Med. Biol.

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Many similarity metrics exist for inter-observer contouring variation studies, however no correlation between metric choice and prostate cancer radiotherapy dosimetry has been explored. These correlations were investigated in this study. Two separate trials were undertaken, the first a thirty-five patient cohort with three observers, the second a five patient dataset with ten observers. Clinical and planning target volumes (CTV and PTV), rectum, and bladder were independently contoured by all observers in each trial. Structures were contoured on T2-weighted MRI and transferred onto CT following rigid registration for treatment planning in the first trial. Structures were contoured directly on CT in the second trial. STAPLE and majority voting volumes were generated as reference gold standard volumes for each structure for the two trials respectively. VMAT treatment plans (78 Gy to PTV) were simulated for observer and gold standard volumes, and dosimetry assessed using multiple radiobiological metrics. Correlations between contouring similarity metrics and dosimetry were calculated using Spearman's rank correlation coefficient. No correlations were observed between contouring similarity metrics and dosimetry for CTV within either trial. Volume similarity correlated most strongly with radiobiological metrics for PTV in both trials, including TCP (ρ = 0.57, 0.65), TCP (ρ = 0.39, 0.62), and EUD (ρ = 0.43, 0.61) for each respective trial. Rectum and bladder metric correlations displayed no consistency for the two trials. PTV volume similarity was found to significantly correlate with rectum normal tissue complication probability (ρ = 0.33, 0.48). Minimal to no correlations with dosimetry were observed for overlap or boundary contouring metrics. Future inter-observer contouring variation studies for prostate cancer should incorporate volume similarity to provide additional insights into dosimetry during analysis.

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“…Beasley et al [30] also reported that when measured with a suitable spatial metric, the higher the geometric accuracy of the contour, the smaller the dose difference should therefore be reflected, and vice versa. Our research showed that when the geometric index was within the acceptable threshold range, the corresponding dose difference can be clinically unacceptable, or when the geometric index was beyond the acceptable threshold range, the corresponding dose difference can be clinically Ex-D2% = D2% for expansion transformations; Re-D2% = D98% for reduction transformations; Sin-D2% = D2% for sine function transformations.…”

Section: Discussionmentioning

confidence: 99%

Clinically oriented contour evaluation using geometric and dosimetric indices based on geometric transformation

Xian

Xiao

et al. 2020

Preprint

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Background : In radiotherapy, geometric indices are often used to evaluate the accuracy of contouring; However, the ability of geometric indices to identify the error of contouring results is limited, and there is lack of clinical background. Based on the reference contouring, we systematically introduced geometric errors to study the relationship between geometric and dosimetric indices and evaluated the clinical feasibility of assessing the accuracy of contouring based on geometric indices alone. Materials and Methods: A C-shaped target, organ at risk (Core), and intensity-modulated radiotherapy (IMRT) plan outlined in the American Association of Physicists in Medicine (AAPM) TG-119 report (The report of Task Group 119 of the AAPM) were used as references. Translation, scaling, rotation (except for the Core), and sine function transformation were performed to simulate the contouring results. The corresponding dosimetric indices were obtained from the original dose distribution of the radiotherapy plan, and correlations (R²) between geometric indices and dosimetric indices were quantified through linear regression. The clinical applicability of the threshold for geometric indices was analyzed by combining the geometric indices and dose difference diagram. Results: The correlations between the geometric and dosimetric indices were different and inconsistent for the contouring of the target and Core after the geometric transformation simulation. Except for the sine function transformation (R²: 0.04–0.023, p > 0.05), the other three geometric indices of the planning target volume (PTV) had strong correlations with the dosimetric indices D98% and D mean (R²: 0.689–0.988), 80% of which were strongly correlated with a p < 0.001. The correlation results for the other geometric transformations in the Core were similar to those in the PTV except for the down shift transformation. Conclusions: The dosimetric indices are heavily influenced by the contour differences, thus highlighting their importance in the evaluation process. Clinically, an assessment of the contour accuracy of the region of interest is not feasible based on geometric indices alone, and should be combined with dosimetric indices. Keywords: Contour evaluation, Geometric indices, Dosimetric indices, Geometric transformation simulation

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The suitability of common metrics for assessing parotid and larynx autosegmentation accuracy

Cited by 19 publications

References 29 publications

Use of a novel atlas for muscles of mastication to reduce inter observer variability in head and neck radiotherapy contouring

Use of a novel atlas for muscles of mastication to reduce inter observer variability in head and neck radiotherapy contouring

Correlations between contouring similarity metrics and simulated treatment outcome for prostate radiotherapy

Clinically oriented contour evaluation using geometric and dosimetric indices based on geometric transformation

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