Purpose: In radiation therapy, head and neck (H&N) supports and thermoplastic masks are used to reproduce the setup of patients for H&N treatment. Individualized supports that include the... Show morePurpose: In radiation therapy, head and neck (H&N) supports and thermoplastic masks are used to reproduce the setup of patients for H&N treatment. Individualized supports that include the shoulders may improve the immobilization of the upper thorax region. The purpose of this study was to compare the local misalignment of the supraclavicular region using a vacuum cushion H&N support to a more simple in-house modified, clinically standard H&N support.Methods and materials: Two groups of 15 patients were evaluated: the first group of patients was positioned using a vacuum cushion as an individual head support and the second group with a modified Posifix headrest (MPH). A total of 316 cone beam computed tomography (CBCTs; similar to 10 scans per patient) were evaluated using a multiple region of interest registration protocol. Local setup errors were measured using chamfer matching on the CBCT scan to the planning CT scan for 9 bony structures (cervical vertebrae 1, 3, 5, and 7 [C7], lower jaw, hyoid bone, larynx, skull, and jugular notch). In this study, we compared the local residual misalignments of the bony structures and in particular those of the jugular notch and C7 as surrogates of the shoulders and thorax region. The workload was qualitatively evaluated on the basis of open interviews.Results: The significant differences in group mean, systematic error, and random error of the local residual misalignments between the 2 groups for jugular notch and C7 were equal or smaller than 0.5 mm and 0.1 degrees, and for the other 7 bony structures were equal to or smaller than 0.6 mm and 1.2 degrees (larynx). There were no large differences in workload.Conclusions: No clinically relevant differences were found between a modified Posifix headrest and an individual vacuum cushion for H&N cancer patients in local posture change at the level of the clavicle and upper thorax. (C) 2014 American Society for Radiation Oncology. Published by Elsevier Inc. All rights reserved. Show less
Mencarelli, A.; Kranen, S.R. van; Hamming-Vrieze, O.; Beek, S. van; Rasch, C.R.N.; Herk, M. van; Sonke, J.J. 2014
Purpose: To compare deformable image registration (DIR) accuracy and precision for normal and tumor tissues in head and neck cancer patients during the course of radiation therapy (RT).Methods and... Show morePurpose: To compare deformable image registration (DIR) accuracy and precision for normal and tumor tissues in head and neck cancer patients during the course of radiation therapy (RT).Methods and Materials: Thirteen patients with oropharyngeal tumors, who underwent submucosal implantation of small gold markers (average 6, range 4-10) around the tumor and were treated with RT were retrospectively selected. Two observers identified 15 anatomical features (landmarks) representative of normal tissues in the planning computed tomography (pCT) scan and in weekly cone beam CTs (CBCTs). Gold markers were digitally removed after semiautomatic identification in pCTs and CBCTs. Subsequently, landmarks and gold markers on pCT were propagated to CBCTs, using a b-spline-based DIR and, for comparison, rigid registration (RR). To account for observer variability, the pair-wise difference analysis of variance method was applied. DIR accuracy (systematic error) and precision (random error) for landmarks and gold markers were quantified. Time trend of the precisions for RR and DIR over the weekly CBCTs were evaluated.Results: DIR accuracies were submillimeter and similar for normal and tumor tissue. DIR precision (1 SD) on the other hand was significantly different (P<.01), with 2.2 mm vector length in normal tissue versus 3.3 mm in tumor tissue. No significant time trend in DIR precision was found for normal tissue, whereas in tumor, DIR precision was significantly (P<.009) degraded during the course of treatment by 0.21 mm/week.Conclusions: DIR for tumor registration proved to be less precise than that for normal tissues due to limited contrast and complex non-elastic tumor response. Caution should therefore be exercised when applying DIR for tumor changes in adaptive procedures. (C) 2014 Elsevier Inc. Show less
Mencarelli, A.; Beek, S. van; Zijp, L.J.; Rasch, C.; Herk, M. van; Sonke, J.J. 2014
Despite immobilization of head and neck (H and N) cancer patients, considerable posture changes occur over the course of radiotherapy (RT). To account for the posture changes, we previously... Show moreDespite immobilization of head and neck (H and N) cancer patients, considerable posture changes occur over the course of radiotherapy (RT). To account for the posture changes, we previously implemented a multiple regions of interest (mROIs) registration system tailored to the H and N region for image-guided RT correction strategies. This paper is focused on the automatic segmentation of the ROIs in the H and N region. We developed a fast and robust automatic detection system suitable for an online image-guided application and quantified its performance. The system was developed to segment nine high contrast structures from the planning CT including cervical vertebrae, mandible, hyoid, manubrium of sternum, larynx and occipital bone. It generates nine 3D rectangular-shaped ROIs and informs the user in case of ambiguities. Two observers evaluated the robustness of the segmentation on 188 H and N cancer patients. Bland-Altman analysis was applied to a sub-group of 50 patients to compare the registration results using only the automatically generated ROIs and those manually set by two independent experts. Finally the time performance and workload were evaluated. Automatic detection of individual anatomical ROIs had a success rate of 97%/53% with/without user notifications respectively. Following the notifications, for 38% of the patients one or more structures were manually adjusted. The processing time was on average 5 s. The limits of agreement between the local registrations of manually and automatically set ROIs was comprised between +/- 1.4 mm, except for the manubrium of sternum (-1.71 mm and 1.67 mm), and were similar to the limits agreement between the two experts. The workload to place the nine ROIs was reduced from 141 s (+/- 20 s) by the manual procedure to 59 s (+/- 17 s) using the automatic method. An efficient detection system to segment multiple ROIs was developed for Cone-Beam CT image-guided applications in the H and N region and is clinically implemented in our department. Show less
Kranen, S. van; Mencarelli, A.; Beek, S. van; Rasch, C.; Herk, M. van; Sonke, J.J. 2013
Background and purpose: To develop and validate an adaptive intervention strategy for radiotherapy of head-and-neck cancer that accounts for systematic deformations by modifying the planning-CT ... Show moreBackground and purpose: To develop and validate an adaptive intervention strategy for radiotherapy of head-and-neck cancer that accounts for systematic deformations by modifying the planning-CT (pCT) to the average misalignments in daily cone beam CT (CBCT) measured with deformable registration (DR). Methods and materials: Daily CBCT scans (808 scans) for 25 patients were retrospectively registered to the pCT with B-spline DR. The average deformation vector field (< DVF >) was used to deform the pCT for adaptive intervention. Two strategies were simulated: single intervention after 10 fractions and weekly intervention with an < DVF > from the previous week.Methods and materials: The model was geometrically validated with the residual misalignment of anatomical landmarks both on bony-anatomy (BA; automatically generated) and soft-tissue (ST; manually identified).Results: Systematic deformations were 2.5/3.4 mm vector length (BA/ST). Single intervention reduced deformations to 1.5/2.7 mm (BA/ST). Weekly intervention resulted in 1.0/2.2 mm (BA/ST) and accounted better for progressive changes. 15 patients had average systematic deformations >2 mm (BA): reductions were 1.1/1.9 mm (single/weekly BA). ST improvements were underestimated due to observer and registration variability.Conclusions: Adaptive intervention with a pCT modified to the average anatomy during treatment successfully reduces systematic deformations. The improved accuracy could possibly be exploited in margin reduction and/or dose escalation. (C) 2013 Elsevier Ireland Ltd. All rights reserved. Show less
Mencarelli, A.; Beek, S. van; Kranen, S. van; Rasch, C.; Herk, M. van; Sonke, J.J. 2012
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... Show morePurpose: 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-of-interest (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. c 2012 American Association of Physicists in Medicine. [http://dx.doi.org/10.1118/1.4760990] Show less
Kranen, S. van; Beek, S. van; Mencarelli, A.; Rasch, C.; Herk, M. van; Sonke, J.J. 2010
Background and purpose: To optimize couch shifts based on multiple region-of-interest (ROI) registrations and derive criteria for adaptive replanning for management of deformations in head-and-neck... Show moreBackground and purpose: To optimize couch shifts based on multiple region-of-interest (ROI) registrations and derive criteria for adaptive replanning for management of deformations in head-and-neck (H&N) cancer patients.Materials and methods: Eight ROIs containing bony structures were defined on the planning-CT and individually registered to daily cone-beam CTs for 19 H&N cancer patients. Online couch shifts were retrospectively optimized to correct the mean setup error over all ROIs (mean correction) or to minimize the maximum error (MiniMax correction). Residual error distributions were analyzed for both methods. The number of measurements before adaptive-intervention and corresponding action-level were optimized.Results: Overall residual setup errors were smallest for the mean corrections, while MiniMax corrections reduced the largest errors. The percentage of fractions with residual errors >5 mm was 38% versus 19%. Reduction of deformations by single plan adaptation was most effective after eight fractions: systematic deformations reduced from 1.7 to 0.9 mm. Fifty percent of this reduction can already be achieved by replanning 1/3 of the patients.Conclusion: Two correction methods based on multiple ROI registration were introduced to manage setup errors from deformations that either minimize overall geometrical uncertainties or maximum errors. Moreover, the registrations could be used to select patient with large deformations for replanning. (C) 2009 Elsevier Ireland Ltd. All rights reserved. Radiotherapy and Oncology 94 (2010) 199-205 Show less
Beek, S. van; Kranen, S. van; Mencarelli, A.; Remeijer, P.; Rasch, C.; Herk, M. van; Sonke, J.J. 2010
Purpose: To discuss the first clinical experience with a multiple region of interest (mROI) registration and correction method for high-precision radiotherapy of head-and-neck cancer patients... Show morePurpose: To discuss the first clinical experience with a multiple region of interest (mROI) registration and correction method for high-precision radiotherapy of head-and-neck cancer patients.Materials and methods: 12-13 3D rectangular-shaped ROIs were automatically placed around bony structures on the planning CT scans (n = 50 patients) which were individually registered to subsequent CBCT scans. mROI registration was used to quantify global and local setup errors. The time required to perform the mROI registration was compared with that of a previously used single-ROI method. The number of scans with residual local setup error exceeding 5 mm/5 degrees (warnings) was scored together with the frequency ROIs exceeding these limits for three or more consecutive imaging fractions (systematic errors).Results: In 40% of the CBCT scans, one or more ROI-registrations exceeded the 5 mm/5 degrees. Most warnings were seen in ROI "hyoid", 31% of the rotation warnings and 14% of the translation warnings. Systematic errors lead to 52 consults of the treating physician. The preparation and registration time was similar for both registration methods.Conclusions: The mROI registration method is easy to use with little extra workload, provides additional information on local setup errors, and helps to select patients for re-planning. (C) 2009 Elsevier Ireland Ltd. All rights reserved. Radiotherapy and Oncology 94 (2010) 213-217 Show less
