Dosimetrically Triggered Adaptive Intensity Modulated Radiation Therapy for Cervical Cancer

Lim, Karen; Stewart, James; Kelly, Valerie J.; Xie, Jiawen; Brock, Kristy K.; Moseley, Joanne; Cho, Young Bin; Fyles, Anthony; Lundin, Anna; Rehbinder, H.; Löf, Johan; Jaffray, David A.; Milosevic, Michael

doi:10.1016/j.ijrobp.2014.05.039

Cited by 44 publications

(62 citation statements)

References 21 publications

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“…The effectiveness of automated re-planning to compensate for interfraction organ motion was studied by [45,[47][48][49]. Stewart et al [45] study explored the limits of a highly adaptive small margin treatment scenario to accommodate internal organ motion.…”

Section: Ctmentioning

confidence: 99%

A review of segmentation and deformable registration methods applied to adaptive cervical cancer radiation therapy treatment planning

Ghose

Holloway

Lim

et al. 2015

Artificial Intelligence in Medicine

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A c c e p t e d M a n u s c r i p t Highlights  This paper reviews the current state-of-the-art segmentation and deformable registration methods applied to cervical cancer adaptive radiation therapy planning. Strength and weaknesses of the registration and the segmentation methods are studied and analysed. Use of shape prior constraints can significantly reduce segmentation and registration errors.  Use of tissue specific classification of tumour may reduce tumour segmentation error. *Highlights (for review)Page 2 of 30 A c c e p t e d M a n u s c r i p t Abstract ObjectiveManual contouring and registration for radiotherapy treatment planning and online adaptation for cervical cancer radiation therapy in computed tomography (CT) and magnetic resonance images (MRI) is often necessary. However manual intervention is time consuming and may suffer from inter or intra rater variability. In recent years a number of computer-guided automatic or semi-automatic segmentation and registration methods have been proposed. Segmentation and registration in CT and MRI for this purpose is a challenging task due to soft tissue deformation, inter-patient shape and appearance variation and anatomical changes over the course of treatment. The objective of this work is to provide a state-of-the-art review of computer-aided methods developed for adaptive treatment planning and radiation therapy planning for cervical cancer radiation therapy. MethodsSegmentation and registration methods published with the goal of cervical cancer treatment planning and adaptation have been identified from the literature (PubMed and Google Scholar). A comprehensive description of each method is provided. Similarities and differences of these methods are highlighted and the strengths and weaknesses of these methods are discussed. A discussion about choice of an appropriate method for a given modality is provided. ResultsIn the reviewed papers a Dice similarity coefficient of around 0.85 along with mean absolute surface distance of 2-4 mm for the clinically treated volume were reported for transfer of contours from planning day to the treatment day. ConclusionsMost segmentation and non-rigid registration methods have been primarily designed for adaptive re-planning for the transfer of contours from planning day to the treatment day. The use of shape priors significantly improved segmen- 1Page 3 of 30 A c c e p t e d M a n u s c r i p t tation and registration accuracy compared to other models.

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Section: Ctmentioning

confidence: 99%

A review of segmentation and deformable registration methods applied to adaptive cervical cancer radiation therapy treatment planning

Ghose

Holloway

Lim

et al. 2015

Artificial Intelligence in Medicine

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“…However, the majority of the studies in this review adapted the treatment for all patients with only about 17% of the clinically applied ART and 18% of the in silico studies followed a workflow allowing for selective use of ART. Examples of patient selection in the reviewed workflows were, applied alone or in combination: exerting a threshold criteria on the detected motion for initiation of modifications [20,45,46,[61][62][63][64]69,72] or shrinking the PTV margins to less than the common 90% of the population and correct for dose degradation of outliers during/at the end of treatment [63,65,66,94]. As an alternative, differentiating the size of the plan library based on a criterion for large and small cervix-uterus [41] or discriminating the adaptations based on greater and smaller response to treatment as in the gynecological GEC-ESTRO recommendations has been applied clinically [42].…”

Section: Discussionmentioning

confidence: 99%

“…Whereas online re-planning for prostate, gynecological and bladder cancer EBRT was applied in silico, the strategy was only used clinically for gynecological cancer treated with BT ( Figure 3) [58,59,61,65-67,70-72,74,78,80,82,83,88-91,94,100, 101,103]. An ART workflow presented in the in silico studies but not in the clinical workflows was offline re-plan/re-optimization, applied during or at the end of EBRT, to correct degradation of the dose distribution from previously delivered fraction [60,63,69,75,76]. In addition to one in silico implementation of online compensation [58], these were the only studies where feedback from delivered dose triggered adaptations.…”

Section: Discussionmentioning

confidence: 99%

“…In addition to one in silico implementation of online compensation [58], these were the only studies where feedback from delivered dose triggered adaptations. Contributing to differences in applied strategies and workflows could be the additional manual contouring, which was a pre-requisite in over 70% of the simulated ART workflows [22,59,60,[62][63][64][65][66][68][69][70]72,74,78,79,[81][82][83]85,86,88,89,91,93,[95][96][97][98][100][101][102][103][104][105][106][107]. To reduce the need of manual contours, the segmentation could be propagated using deformable image registration.…”

Section: Discussionmentioning

confidence: 99%

“…Deformable registration was utilized when generating ITVs in one offline re-planning/ re-optimization and in two online plan selection workflows applied clinically [17,41,54]. Deformable image registration was more frequently applied in the in silico studies, mostly for online re-planning/re-optimization [59,61,67,71,86,87,94] and offline re-planning/re-optimization strategies [60,63,66,69,75,107] but also applied for online MLC/field adjustments [77,89]. To facilitate adaptations, especially for online execution, modifications of the planning system or automatic activation/selection of plans was applied in 50% of the in silico studies [58][59][60][61][67][68][69]71,72,[74][75][76][77][78][79][80][82][83][84][85][86][87][88][92][93][94].…”

Section: Discussionmentioning

confidence: 99%

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Adaptive radiotherapy strategies for pelvic tumors – a systematic review of clinical implementations

et al. 2016

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Influence of air mapping errors on the dosimetric accuracy of prostate CBCT‐guided online adaptive radiation therapy

Lemus

Tanny

Cummings

et al. 2023

J Applied Clin Med Phys

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PurposeCBCT‐guided online adaptive radiotherapy (oART) plans presently utilize daily synthetic CTs (sCT) that are automatically generated using deformable registration algorithms. These algorithms may have poor performance at reproducing variable volumes of gas present during treatment. Therefore, we have analyzed the air mapping error between the daily CBCTs and the corresponding sCT and explored its dosimetric effect on oART plan calculation.MethodsAbdominopelvic air volume was contoured on both the daily CBCT images and the corresponding synthetic images for 207 online adaptive pelvic treatments. Air mapping errors were tracked over all fractions. For two case studies representing worst case scenarios, dosimetric effects of air mapping errors were corrected in the sCT images using the daily CBCT air contours, then recalculating dose. Dose volume histogram statistics and 3D gamma passing rates were used to compare the original and air‐corrected sCT‐based dose calculations.ResultsAll analyzed patients showed observable air pocket contour differences between the sCT and the CBCT images. The largest air volume difference observed in daily CBCT images for a given patient was 276.3 cc, a difference of more than 386% compared to the sCT. For the two case studies, the largest observed change in DVH metrics was a 2.6% reduction in minimum PTV dose, with all other metrics varying by less than 1.5%. 3D gamma passing rates using 1%/1 mm criteria were above 90% when comparing the uncorrected and corrected dose distributions.ConclusionCurrent CBCT‐based oART workflow can lead to inaccuracies in the mapping of abdominopelvic air pockets from daily CBCT to the sCT images used for the optimization and calculation of the adaptive plan. Despite the large observed mapping errors, the dosimetric effects of such differences on the accuracy of the adapted plan dose calculation are unlikely to cause differences greater than 3% for prostate treatments.

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Dosimetrically Triggered Adaptive Intensity Modulated Radiation Therapy for Cervical Cancer

Cited by 44 publications

References 21 publications

A review of segmentation and deformable registration methods applied to adaptive cervical cancer radiation therapy treatment planning

A review of segmentation and deformable registration methods applied to adaptive cervical cancer radiation therapy treatment planning

Adaptive radiotherapy strategies for pelvic tumors – a systematic review of clinical implementations

Influence of air mapping errors on the dosimetric accuracy of prostate CBCT‐guided online adaptive radiation therapy

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