Setup Uncertainties of Anatomical Sub-Regions in Head-and-Neck Cancer Patients After Offline CBCT Guidance

Kranen, S. Van; Beek, S. van; Rasch, Coen R. N.; Herk, Marcel van; Sonke, Jan‐Jakob

doi:10.1016/j.ijrobp.2008.11.035

Cited by 156 publications

(150 citation statements)

References 15 publications

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“…Numerous publications have suggested appropriate PTV and PRV margins for three‐dimensional conformal and intensity‐modulated radiation therapy, ranging from 2‐5 mm for head and neck, depending on immobilization and frequency of image guidance 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 and 3‐10 mm for prostate depending on frequency of image guidance 33 , 34 , 35 . Some authors have suggested the conventional 5 mm margin for head and neck is conservative and margin reduction may be possible, 24 , 25 , 27 , 29 but others have reported local setup uncertainties meet or exceed 5 mm 26 , 28 , 36 …”

Section: Discussionmentioning

confidence: 99%

“…Some authors have suggested the conventional 5 mm margin for head and neck is conservative and margin reduction may be possible, 24 , 25 , 27 , 29 but others have reported local setup uncertainties meet or exceed 5 mm 26 , 28 , 36 …”

Section: Discussionmentioning

confidence: 99%

“…Assuming that appropriate PRV margins can be conservatively extrapolated from PTV margin data, the combination of 2‐3 mm reported setup uncertainty for head and neck, interobserver variation, and DIR error in quadrature would yield margins less than 5 mm for all but the anterior oral cavity, suggesting that conventional margins may be sufficient to cover the additional uncertainty of interobserver variation. This assumes, of course, the lower estimates for setup uncertainty, which may not be valid for anatomical subregions within the head and neck 26 , 28 , 36 . For prostate, the quadrature sum including interobserver variation and DIR would only be covered by a 5 mm margin for the lower reported setup uncertainty of 3 mm.…”

Section: Discussionmentioning

confidence: 99%

See 2 more Smart Citations

Deformable image registration and interobserver variation in contour propagation for radiation therapy planning

Riegel

Antone

Zhang

et al. 2016

J Applied Clin Med Phys

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Deformable image registration (DIR) and interobserver variation inevitably introduce uncertainty into the treatment planning process. The purpose of the current work was to measure deformable image registration (DIR) errors and interobserver variability for regions of interest (ROIs) in the head and neck and pelvic regions. Measured uncertainties were combined to examine planning margin adequacy for contours propagated for adaptive therapy and to assess the trade‐off of DIR and interobserver uncertainty in atlas‐based automatic segmentation. Two experienced dosimetrists retrospectively contoured brainstem, spinal cord, anterior oral cavity, larynx, right and left parotids, optic nerves, and eyes on the planning CT (CT1) and attenuation‐correction CT of diagnostic PET/CT (CT2) for 30 patients who received radiation therapy for head and neck cancer. Two senior radiation oncology residents retrospectively contoured prostate, bladder, and rectum on the postseed‐implant CT (CT1) and planning CT (CT2) for 20 patients who received radiation therapy for prostate cancer. Interobserver variation was measured by calculating mean Hausdorff distances between the two observers' contours. CT2 was deformably registered to CT1 via commercially available multipass B‐spline DIR. CT2 contours were propagated and compared with CT1 contours via mean Hausdorff distances. These values were summed in quadrature with interobserver variation for margin analysis and compared with interobserver variation for statistical significance using two‐tailed t‐tests for independent samples (α=0.05). Combined uncertainty ranged from 1.5‐5.8 mm for head and neck structures and 3.1‐3.7 mm for pelvic structures. Conventional 5 mm margins may not be adequate to cover this additional uncertainty. DIR uncertainty was significantly less than interobserver variation for four head and neck and one pelvic ROI. DIR uncertainty was not significantly different than interobserver variation for four head and neck and one pelvic ROI. DIR uncertainty was significantly greater than interobserver variation for two head and neck and one pelvic ROI. The introduction of DIR errors may offset any reduction in interobserver variation by using atlas‐based automatic segmentation.PACS number(s): 87.57.nj, 87.55.D‐

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Deformable image registration and interobserver variation in contour propagation for radiation therapy planning

Riegel

Antone

Zhang

et al. 2016

J Applied Clin Med Phys

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“…CBCT scans were registered to pCT scans using multiple region-of-interest registration 14 (mROI), Fig. 2.…”

Section: Iia2 Multiple Region-of-interest Registrationmentioning

confidence: 99%

Validation of deformable registration in head and neck cancer using analysis of variance

et al. 2012

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Purpose: Deformable image registration (DIR) is often validated based on a distance-to-agreement (DTA) criterion of automatically propagated anatomical landmarks that were manually identified. Due to human observer variability, however, the performance of the registration method is diluted. The purpose of this study was to evaluate an analysis of variance (ANOVA) based validation to account for such observer variation. Methods: Weekly cone beam CTs (CBCTs) of ten head and neck cancer patients undergoing five weeks of radiotherapy were used. An expert identified 23 anatomical features (landmarks) on the planning CT. The landmarks were automatically propagated to the CBCT using multiregion-ofinterest (mROI) registration. Additionally, two human observers independently localized these landmarks on the CBCTs. Subsequently, ANOVA was used to compute the variance of each observer on the pairwise distance (PWD).Results: ANOVA based analysis demonstrated that a classical DTA approach underestimated the precision for the mROI due to human observer variation by about 25%. The systematic error (accuracy) of mROI ranged from 0.13 to 0.17 mm; the variability (1 SD) (precision) ranged from 1.3 to 1.5 mm demonstrating that its performance is dominated by the precision. Conclusions:The PWD-ANOVA method accounts for human observer variation allowing a better estimation of the of DIR errors.

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“…In addition, it is common for some patients to experience tumor regression or weight loss during treatment, which may result in anatomical changes that can affect dose delivery to the tumor and organs at risk 1. Such changes may require the patient to have a repeat CT (re‐CT) simulation with the possibility of generating a revised treatment plan based on the changes in anatomy 2, 3, 4, 5. At our institution, radiation therapists are responsible for documenting changes in patient anatomy as treatment progresses.…”

Section: Introductionmentioning

confidence: 99%

Using gamma index to flag changes in anatomy during image‐guided radiation therapy of head and neck cancer

Schaly

Kempe²,

Venkatesan

et al. 2017

J Applied Clin Med Phys

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During radiation therapy of head and neck cancer, the decision to consider replanning a treatment because of anatomical changes has significant resource implications. We developed an algorithm that compares cone‐beam computed tomography (CBCT) image pairs and provides an automatic alert as to when remedial action may be required. Retrospective CBCT data from ten head and neck cancer patients that were replanned during their treatment was used to train the algorithm on when to recommend a repeat CT simulation (re‐CT). An additional 20 patients (replanned and not replanned) were used to validate the predictive power of the algorithm. CBCT images were compared in 3D using the gamma index, combining Hounsfield Unit (HU) difference with distance‐to‐agreement (DTA), where the CBCT study acquired on the first fraction is used as the reference. We defined the match quality parameter (MQP x) as a difference between the x th percentiles of the failed‐pixel histograms calculated from the reference gamma comparison and subsequent comparisons, where the reference gamma comparison is taken from the first two CBCT images acquired during treatment. The decision to consider re‐CT was based on three consecutive MQP values being less than or equal to a threshold value, such that re‐CT recommendations were within ±3 fractions of the actual re‐CT order date for the training cases. Receiver‐operator characteristic analysis showed that the best trade‐off in sensitivity and specificity was achieved using gamma criteria of 3 mm DTA and 30 HU difference, and the 80th percentile of the failed‐pixel histogram. A sensitivity of 82% and 100% was achieved in the training and validation cases, respectively, with a false positive rate of ~30%. We have demonstrated that gamma analysis of CBCT‐acquired anatomy can be used to flag patients for possible replanning in a manner consistent with local clinical practice guidelines.

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Setup Uncertainties of Anatomical Sub-Regions in Head-and-Neck Cancer Patients After Offline CBCT Guidance

Cited by 156 publications

References 15 publications

Deformable image registration and interobserver variation in contour propagation for radiation therapy planning

Deformable image registration and interobserver variation in contour propagation for radiation therapy planning

Validation of deformable registration in head and neck cancer using analysis of variance

Using gamma index to flag changes in anatomy during image‐guided radiation therapy of head and neck cancer

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