Deformable image registration based automatic CT‐to‐CT contour propagation for head and neck adaptive radiotherapy in the routine clinical setting

Kumarasiri, Akila; Siddiqui, Farzan; Liu, Chang; Yechieli, Raphael; Shah, Mira; Pradhan, Deepak; Zhong, Hualiang; Chetty, Indrin J.; Kim, Jinkoo

doi:10.1118/1.4901409

Cited by 81 publications

(83 citation statements)

References 37 publications

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“…Much of the existing literature uses the latter method [28][29][30], however, the former method is a more accurate reflection of our daily clinical workflow, i.e. radiation oncology specialist reviewing and correcting the work of a resident.…”

Section: Discussionmentioning

confidence: 99%

Accuracy of software-assisted contour propagation from planning CT to cone beam CT in head and neck radiotherapy

et al. 2016

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Background: Autocontouring improves workflow in computed tomography (CT)-based dose planning, but could also potentially play a role for optimal use of daily cone beam CT (CBCT) in adaptive radiotherapy. This study aims to determine the accuracy of a deformable image registration (DIR) algorithm for organs at risk (OAR) in the neck region, when applied to CBCT. Material and methods: For 30 head and neck cancer (HNC) patients 14 OARs including parotid glands, swallowing structures and spinal cord were delineated. Contours were propagated by DIR from CT to the CBCTs of the first and last treatment fraction. An indirect approach, propagating contours to the first CBCT and from there to the last CBCT was also tested. Propagated contours were compared to manually corrected contours by Dice similarity coefficient (DSC) and Hausdorff distance (HD). Dose was recalculated on CBCTs and dosimetric consequences of uncertainties in DIR were reviewed. Results: Mean DSC values of !0.8 were considered adequate and were achieved in tongue base (0.91), esophagus (0.85), glottic (0.81) and supraglottic larynx (0.83), inferior pharyngeal constrictor muscle (0.84), spinal cord (0.89) and all salivary glands in the first CBCT. For the last CBCT by direct propagation, adequate DSC values were achieved for tongue base (0.85), esophagus (0.84), spinal cord (0.87) and all salivary glands. Using indirect propagation only tongue base (0.80) and parotid glands (0.87) were !0.8. Mean relative dose difference between automated and corrected contours was within ±2.5% of planed dose except for esophagus inlet (-4.5%) and esophagus (5.0%) for the last CBCT using indirect propagation. Conclusion: Compared to manually corrected contours, the DIR algorithm was accurate for use in CBCT images of HNC patients and the minor inaccuracies had little consequence for mean dose in most clinically relevant OAR. The method can thus enable a more automated segmentation of CBCT for use in adaptive radiotherapy.

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Section: Discussionmentioning

confidence: 99%

Accuracy of software-assisted contour propagation from planning CT to cone beam CT in head and neck radiotherapy

et al. 2016

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“…As such, for the first question of “how to evaluate,” assessment of both capacities, contour propagating and dose tracking, should be included. The current techniques for DIR evaluation generally fell into three categories: contour comparison, 21 , 22 , 23 , 24 , 25 landmark tracking, 5 , 23 and voxel‐based analysis 7 , 8 , 9 , 10 , 12 , 13 . Both the contour‐ and landmark‐based analyses can yield a skewed view of the overall registration accuracy, as they only test spatial accuracy in limited regions.…”

Section: Discussionmentioning

confidence: 99%

Performance variations among clinically available deformable image registration tools in adaptive radiotherapy — how should we evaluate and interpret the result?

Nie

Pouliot

Smith

et al. 2016

J Applied Clin Med Phys

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The purpose of this study is to evaluate the performance variations in commercial deformable image registration (DIR) tools for adaptive radiation therapy and further to interpret the differences using clinically available terms. Three clinical examples (prostate, head and neck (HN), and cranial spinal irradiation (CSI) with L‐spine boost) were evaluated in this study. Firstly, computerized deformed CT images were generated using simulation QA software with virtual deformations of bladder filling (prostate), neck flexion/bite‐block repositioning/tumor shrinkage (HN), and vertebral body rotation (CSI). The corresponding transformation matrices served as a “reference” for the following comparisons. Three commercialized DIR algorithms: the free‐form deformation from MIMVista 5.5 and the RegRefine from MIMMaestro 6.0, the multipass B‐spline from VelocityAI v3.0.1, and the adaptive demons from OnQ rts 2.1.15, were applied between the initial images and the deformed CT sets. The generated adaptive contours and dose distributions were compared with the “reference” and among each other. The performance in transferring contours was comparable among all three tools with an average Dice similarity coefficient of 0.81 for all the organs. However, the dose warping accuracy appeared to rely on the evaluation end points and methodologies. Point‐dose differences could show a difference of up to 23.3 Gy inside the PTVs and to overestimate up to 13.2 Gy for OARs, which was substantial for a 72 Gy prescription dose. Dosevolume histogram‐based evaluation might not be sensitive enough to illustrate all the detailed variations, while isodose assessment on a slice‐by‐slice basis could be tedious. We further explored the possibility of using 3D gamma index analysis for warping dose variation assessment, and observed differences in dose warping using different DIR tools. Overall, our results demonstrated that evaluation based only on the performance of contour transformation could not guarantee the accuracy in dose warping, while dose‐transferring validation strongly relied on the evaluation endpoint. As dose‐transferring errors could cause misinterpretations when attempting to accumulate dose for adaptive radiation therapy and more DIR tools are available for clinical use, a standard and clinically meaningful quality assurance criterion should be established for DIR QA in the near future.PACS number(s): 87.57

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“…Third, deformable registration was not used in this study. Deformable registration is being increasingly used in ART research, not only in anatomical registration but also in dose calculation [21,30,[34][35][36]. We are developing home-made deformable registration software and will compare its results with those from this study.…”

Section: Discussionmentioning

confidence: 99%

Replanning Criteria and Timing Definition for Parotid Protection-Based Adaptive Radiation Therapy in Nasopharyngeal Carcinoma

Yao

et al. 2014

International Journal of Radiation Oncology*Biology*Physics

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Deformable image registration based automatic CT‐to‐CT contour propagation for head and neck adaptive radiotherapy in the routine clinical setting

Abstract: Use of DIR-based contour propagation in the routine clinical setting is expected to increase the efficiency of H&N replanning, reducing the amount of time needed for manual target and organ delineations.

Cited by 81 publications

References 37 publications

Accuracy of software-assisted contour propagation from planning CT to cone beam CT in head and neck radiotherapy

Accuracy of software-assisted contour propagation from planning CT to cone beam CT in head and neck radiotherapy

Performance variations among clinically available deformable image registration tools in adaptive radiotherapy — how should we evaluate and interpret the result?

Replanning Criteria and Timing Definition for Parotid Protection-Based Adaptive Radiation Therapy in Nasopharyngeal Carcinoma

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