The impact of contour variation on tumour control probability in anal cancer

Jones, Michael P.; Martin, Jarad; Foo, Kerwyn; Estoesta, Patrick; Holloway, Lois; Jameson, Michael

doi:10.1186/s13014-018-1033-y

Cited by 4 publications

(3 citation statements)

References 34 publications

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“…Inaccurate demarcation may lead to a geographic miss of a high-risk region and hence, reduced local control and poor survival. 25 This also exposes the surrounding normal tissues to excess doses of radiation beyond their tolerance limits, resulting in higher toxicities. This severity of toxicity warrants the use of precise techniques of delivering radiation.…”

Section: Discussionmentioning

confidence: 99%

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

Qureshi

Mansha

Karim

et al. 2019

JGO

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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.

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Section: Discussionmentioning

confidence: 99%

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

Qureshi

Mansha

Karim

et al. 2019

JGO

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“…[16][17][18] Inter-observer variability in the definition of radiotherapy treatment volumes can impair disease control and treatment outcomes. 19,20 PET imaging reduces this interobserver difference, but it does not remove it entirely. 21,22 Manual definition and identification of the tumour edge is dependent on the observer's skills, experience, contouring system and window settings used.…”

Section: Introductionmentioning

confidence: 98%

Defining primary anal cancer tumour volume on FDG–PET – an initial assessment of semi–automated methods

Smith¹,

Joon²,

Schneider-Kolsky³

et al. 2021

IJRRT

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Purpose Clinician inexperience, intra–observer and inter–observer variations in tumour definition may affect staging, radiotherapy target definition, and treatment outcomes, particularly in rare cancers. The purpose of this study was to assess the correlation between semi–automated methods of primary anal cancer (AC) definition and our current clinical standard of manual clinician definition using 18F–FDG–PET imaging and to provide recommendations for clinical use. Methods All patients referred for chemoradiotherapy for AC between 2012 and 2016 were prospectively enrolled, with all 18F–FDG–PET imaging acquired within one year of chemoradiotherapy collected. Three methods of primary AC definition were performed on all PET datasets. Manual definition by an experienced radiologist was considered the clinical standard for comparison of volume and coincidence (Dice coefficient) in our study. Semi–automated techniques assessed included a gradient–based SUV (SUV–gradient) method and a SUV threshold method with a range of thresholds relative to SUVmax (40 (T40), 50 (T50) and 60% (T60)). Results Ten patients were enrolled with 33 PET study sets available for analysis. While all methods created contours on pre– and post–treatment scans, manual definition of PET–avid disease was only necessary on 11 of the 33 study sets. SUV–gradient and T40 defined contours were not statistically different in volume to the clinical standard (p = 0.83 & 0.72 respectively). The observed Dice coefficient relative to the manual clinician contours were 0.75 and 0.73 for the SUV–gradient and T40 methods respectively. Conclusions It is possible to define gross AC using SUV–based methods, with the SUV–gradient–based method followed by the T40 method most closely correlating with our current clinical standard. The SUV–gradient–based method studied is housed within a proprietary clinical system. A semi–automated approach that uses a vendor neutral T40 method and the clinician’s knowledge and skill appears optimal in defining AC. With this approach AC may be defined reliably to enhance efficiencies in radiotherapy and nuclear medicine processes, and to support clinicians in identifying and defining this rare disease. Trial registration ANZCTR, ACTRN12620000066987. Registered 28 January 2020–Retrospectively registered, https://www.anzctr.org.au/ACTRN12620000066987.aspx

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“…The requirements of fast pace and accurate planning will put the entire workflow under high pressure, thus increasing planning errors. Moreover, the planner's experience level and preferences would result in significant inter-and intra-observer variations [8,9], further introducing more uncertainties in treatment planning and dose delivery [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

A deep learning-based self-adapting ensemble method for segmentation in gynecological brachytherapy

Zhu

Zhang

et al. 2022

Radiat Oncol

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Purpose Fast and accurate outlining of the organs at risk (OARs) and high-risk clinical tumor volume (HRCTV) is especially important in high-dose-rate brachytherapy due to the highly time-intensive online treatment planning process and the high dose gradient around the HRCTV. This study aims to apply a self-configured ensemble method for fast and reproducible auto-segmentation of OARs and HRCTVs in gynecological cancer. Materials and methods We applied nnU-Net (no new U-Net), an automatically adapted deep convolutional neural network based on U-Net, to segment the bladder, rectum and HRCTV on CT images in gynecological cancer. In nnU-Net, three architectures, including 2D U-Net, 3D U-Net and 3D-Cascade U-Net, were trained and finally ensembled. 207 cases were randomly chosen for training, and 30 for testing. Quantitative evaluation used well-established image segmentation metrics, including dice similarity coefficient (DSC), 95% Hausdorff distance (HD95%), and average surface distance (ASD). Qualitative analysis of automated segmentation results was performed visually by two radiation oncologists. The dosimetric evaluation was performed by comparing the dose-volume parameters of both predicted segmentation and human contouring. Results nnU-Net obtained high qualitative and quantitative segmentation accuracy on the test dataset and performed better than previously reported methods in bladder and rectum segmentation. In quantitative evaluation, 3D-Cascade achieved the best performance in the bladder (DSC: 0.936 ± 0.051, HD95%: 3.503 ± 1.956, ASD: 0.944 ± 0.503), rectum (DSC: 0.831 ± 0.074, HD95%: 7.579 ± 5.857, ASD: 3.6 ± 3.485), and HRCTV (DSC: 0.836 ± 0.07, HD95%: 7.42 ± 5.023, ASD: 2.094 ± 1.311). According to the qualitative evaluation, over 76% of the test data set had no or minor visually detectable errors in segmentation. Conclusion This work showed nnU-Net’s superiority in segmenting OARs and HRCTV in gynecological brachytherapy cases in our center, among which 3D-Cascade shows the highest accuracy in segmentation across different applicators and patient anatomy.

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The impact of contour variation on tumour control probability in anal cancer

Cited by 4 publications

References 34 publications

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

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

Defining primary anal cancer tumour volume on FDG–PET – an initial assessment of semi–automated methods

A deep learning-based self-adapting ensemble method for segmentation in gynecological brachytherapy

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