Evaluation of the 4D <scp>RADPOS</scp> dosimetry system for dose and position quality assurance of CyberKnife

Marants, R; Vandervoort, Eric; Cygler, Joanna

doi:10.1002/mp.13102

Cited by 9 publications

(26 citation statements)

References 51 publications

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“…Several studies have investigated the motion-tracking accuracy of the SRTS using phantom measurements 13,14,16,24 or log files. 9,11,15 Inoue et al reported that the accuracy for probability> 95% was 1.5 mm (range, 1.0-3.5).…”

Section: Discussionmentioning

confidence: 99%

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Impacts of respiratory phase shifts on motion‐tracking accuracy of the CyberKnife Synchrony™ Respiratory Tracking System

et al. 2019

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Purpose The SynchronyTM Respiratory Tracking System (SRTS) component of the CyberKnife® Robotic Radiosurgery System (Accuray, Inc., Sunnyvale CA) enables real‐time tracking of moving targets by modeling the correlation between the targets and external surrogate light‐emitting diode (LED) markers placed on the patient’s chest. Previous studies reported some cases with respiratory phase shifts between lung tumor and chest wall motions. In this study, the impacts of respiratory phase shifts on the motion‐tracking accuracy of the SRTS were investigated. Methods A plastic scintillator was used to detect the position of the x‐ray beams. The scintillation light was recorded using a camera in a dark room. A moving phantom moved a U‐shaped frame on the scintillator with a 4th power of sinusoidal functions. Three metallic markers for motion tracking and four fluorescent tapes were attached to the frame. The fluorescent tapes were used to identify phantom position and respiratory phase for each video frame. The beam positions collected, when considered relative to the phantom motion, represent the degree of tracking error. Beam position was calculated by adding error value to phantom position. Motions with respiratory phase shifts between the target and an extra stage mimicking chest wall motion were also tested for LED markers. Log files of the SRTS were analyzed to evaluate correlation errors. Results When target and LED marker motions were synchronized with a respiratory cycle of 4 s, the maximum tracking errors for 90% and 95% of beam‐on time were 1.0 mm and 1.2 mm, respectively. The frequency of tracking errors increased when LED marker motion phase preceded target motion. Tracking errors that corresponded to 90% beam‐on time were within 2.4 mm for 5–15% of phase shifts. In contrast, the tracking errors were very large when the LED marker delayed to the target motions; the maximum errors of 90% beam‐on time were 3.0, 3.8, and 7.5 mm for 5%, 10%, and 15% of phase shifts, respectively. The patterns of the tracking errors derived from the scintillation light were very similar to those of the correlation data of the SRTS derived from the log files, indicating that the tracking errors caused mainly due to the errors in modeling the correlation data. With long respiratory cycle of 6 s, the tracking errors were significantly decreased; the maximum tracking errors for 95% beam‐on time were 1.6 mm and 2.2 mm for early and delayed LED motion. Conclusion We have investigated the motion‐tracking accuracy of the CyberKnife SRTS for cases with the respiratory phase shift between the target and the LED marker. The maximum tracking errors for 90% probability were within 2.4 mm when the target delays to the LED markers. When LED marker delays, however, very large tracking errors were observed. With a long respiratory cycle, the tracking errors were greatly improved to less than 2.2 mm. Coaching slow breathing will be useful for accurate motion tracking radiotherapy.

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Section: Discussionmentioning

confidence: 99%

“…9,23 However, few studies have investigated respiratory phase shifts. Marants et al 24 used two motion phantoms to generate phase shifts between the lung tumor phantom and LED markers. The authors then compared the target positions identified by the electromagnetic positioning sensor and the Synchrony correlation log files.…”

Section: Discussionmentioning

confidence: 99%

Impacts of respiratory phase shifts on motion‐tracking accuracy of the CyberKnife Synchrony™ Respiratory Tracking System

et al. 2019

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“…The same tendency was reported by Marants et al, and they mentioned that this tendencywas not because of the dose calculation algorithms, but because of the tumor-tracking error. 34 The gamma passing rates were lower in the P1 plan than in the P2 and P3 plans. The respiratory cycle and amplitude was shorter in the P1 plan.…”

Section: Discussionmentioning

confidence: 86%

“…The same tendency was reported by Marants et al . , and they mentioned that this tendencywas not because of the dose calculation algorithms, but because of the tumor‐tracking error …”

Section: Discussionmentioning

confidence: 99%

Evaluation of newly implemented dose calculation algorithms for multileaf collimator‐based CyberKnife tumor‐tracking radiotherapy

et al. 2020

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Purpose In the previous treatment planning system (TPS) for CyberKnife (CK), multileaf collimator (MLC)‐based treatment plans could be created only by using the finite‐size pencil beam (FSPB) algorithm. Recently, a new TPS, including the FSPB with lateral scaling option (FSPB+) and Monte Carlo (MC) algorithms, was developed. In this study, we performed basic and clinical end‐to‐end evaluations for MLC‐based CK tumor‐tracking radiotherapy using the MC, FSPB+, and FSPB. Methods Water‐ and lung‐equivalent slab phantoms were combined to obtain the percentage depth dose (PDD) and off‐center ratio (OCR). The CK M6 system and Precision TPS were employed, and PDDs and OCRs calculated by the MC, FSPB+, and FSPB were compared with the measured doses obtained for 30.8 × 30.8 mm2 and 60.0 × 61.6 mm2 fields. A lung motion phantom was used for clinical evaluation and MLC‐based treatment plans were created using the MC. The doses were subsequently recalculated using the FSPB+ and FSPB, while maintaining the irradiation parameters. The calculated doses were compared with the doses measured using a microchamber (for target doses) or a radiochromic film (for dose profiles). The dose volume histogram (DVH) indices were compared for all plans. Results In homogeneous and inhomogeneous phantom geometries, the PDDs calculated by the MC and FSPB+ agreed with the measurements within ±2.0% for the region between the surface and a depth of 250 mm, whereas the doses calculated by the FSPB in the lung‐equivalent phantom region were noticeably higher than the measurements, and the maximum dose differences were 6.1% and 4.4% for the 30.8 × 30.8 mm2 and 60.0 × 61.6 mm2 fields, respectively. The maximum distance to agreement values of the MC, FSPB+, and FSPB at the penumbra regions of OCRs were 1.0, 0.6, and 1.1 mm, respectively, but the best agreement was obtained between the MC‐calculated curve and measurements at the boundary of the water‐ and lung‐equivalent slabs, compared with those of the FSPB+ and FSPB. For clinical evaluations using the lung motion phantom, under the static motion condition, the dose errors measured by the microchamber were −1.0%, −1.9%, and 8.8% for MC, FSPB+, and FSPB, respectively; their gamma pass rates for the 3%/2 mm criterion comparing to film measurement were 98.4%, 87.6%, and 31.4% respectively. Under respiratory motion conditions, there was no noticeable decline in the gamma pass rates. In the DVH indices, for most of the gross tumor volume and planning target volume, significant differences were observed between the MC and FSPB, and between the FSPB+ and FSPB. Furthermore, significant differences were observed for lung Dmean, V15 Gy, and V20 Gy between the MC, FSPB+, and FSPB. Conclusions The results indicate that the doses calculated using the MC and FSPB+ differed remarkably in inhomogeneous regions, compared with the FSPB. Because the MC was the most consistent with the measurements, it is recommended for final dose calculations in inhomogeneous regions such as the lung. Furthermore, the sufficient accurac...

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“…It also does not explicitly model the dosimetric impact of tracking errors, including the synchronization of the sign of the motion tracking error with respiratory phase 25,27 which can lead to decreased target dose due to penumbral broadening. 47 As shown in Fig. 7, if we reduce the PTV margin semicontinuously using predicted errors determined by a regression model, at least 140 of 148 cases could have PTV margins reduced.…”

Section: D Early Warning Systemmentioning

confidence: 98%

Patient‐specific PTV margins for liver stereotactic body radiation therapy determined using support vector classification with an early warning system for margin adaptation

2020

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Purpose: An adaptive planning target volume (PTV) margin strategy incorporating a volumetric tracking error assessment after each fraction is proposed for robotic stereotactic body radiation therapy (SBRT) liver treatments. Methods and materials: A supervised machine learning algorithm employing retrospective data, which emulates a dry-run session prior to planning, is used to investigate if motion tracking errors are <2 mm, and consequently, planning target volume (PTV) margins can be reduced. A fraction of data collected during the beginning of a treatment course emulates a dry-run session (mock) before planning. Twenty features are calculated using mock data and used for support vector classification (SVC). A treatment course is labeled as Class 1 if the maximum root-mean-square radial tracking error for all remaining fractions is below 2 mm, or Class 2 otherwise. We evaluate the classification using fivefold cross-validation, leave-one-out cross-validation, 500 repeated random subsampling cross-validation, and the receiver operating characteristic (ROC) metric. The classification is independently cross-validated on a cohort of 48 treatment plans for other anatomical sites. A per fraction assessment of volumetric tracking errors is performed for the standard 5 mm PTV margin (PTV std) for courses predicted as Class 2; or for a margin reduced by 2 mm (PTV std-2mm) for those predicted as Class 1. We perturb the gross tumor volume (GTV) by the tracking errors for each x-ray image acquisition and calculate the fractional GTV voxel occupancy probability (P i) inside the PTV for each treatment fraction i. For treatment courses classified as Class 1, an early warning system flags treatment courses having any P i < 0.99, and the subsequent treatments are proposed to be replanned using PTV std. Results: The classification accuracies are 0.84 AE 0.06 using fivefold cross-validation, and 0.77 when validated using an independent testing set (other anatomical sites). Eighty percent of treatment courses are correctly classified using leave-one-out cross-validation. The sensitivity, precision, specificity, F1 score, and accuracy are 0.81 AE 0.09, 0.85 AE 0.08, 0.80 AE 0.11, 0.83 AE 0.06, and 0.80 AE 0.07, respectively, using 500 repeated random subsampling cross-validation. The area under the curve for the ROC metric is 0.87 AE 0.05. The four most important features for classification are related to standard deviations of motion tracking errors, the linearity between the target location and external LED marker positions, and marker radial motion amplitudes. Eleven of 64 cases predicted to be of Class 1 have 0.96 < P i < 0.99 for each treatment fraction, and require replanning using PTV std. In comparison, the PTV std always covers the perturbed GTVs with P i > 0.99 for all patients. Conclusions: Support vector classification is proposed for the classification of different motion tracking errors for patient courses based on a mock session before planning for SBRT liver treatments. It is feasible to implement patient-specific P...

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Evaluation of the 4D RADPOS dosimetry system for dose and position quality assurance of CyberKnife

Abstract: RADPOS is an accurate and precise QA tool for dose and position measurements for CyberKnife deliveries with respiratory motion compensation.

Cited by 9 publications

References 51 publications

Impacts of respiratory phase shifts on motion‐tracking accuracy of the CyberKnife Synchrony™ Respiratory Tracking System

Impacts of respiratory phase shifts on motion‐tracking accuracy of the CyberKnife Synchrony™ Respiratory Tracking System

Evaluation of newly implemented dose calculation algorithms for multileaf collimator‐based CyberKnife tumor‐tracking radiotherapy

Patient‐specific PTV margins for liver stereotactic body radiation therapy determined using support vector classification with an early warning system for margin adaptation

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