1. Quasi-breath-hold technique using personalized audio-visual biofeedback for respiratory motion management in radiotherapy
- Author
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Kunwoo Lee, Sung-Joon Ye, Yang Kyun Park, Ii Han Kim, Hwi Young Kim, and Simon P. Kim
- Subjects
Motion compensation ,Stereo cameras ,business.industry ,Computer science ,medicine.medical_treatment ,General Medicine ,Biofeedback ,Duty cycle ,Histogram ,Respiration ,Medical imaging ,medicine ,Computer vision ,Artificial intelligence ,business - Abstract
Purpose: To introduce a respiratory motion management technique, so called quasi-breath-hold (QBH) technique and evaluate its feasibility. As a hybrid technique combining free-breathing-based gating (denoted as gating for convenience) and breath-hold (BH), the QBH is designed to overcome typical limitations existing in either one such as phase-shift, residual motion, complexity, and discomfort. Methods: The QBH is realized using an audio-visual biofeedback system (AVBFS) and a respiratory motion management program (RMMP). The AVBFS, consisting of two infra-red stereo cameras and a head mounted display, monitors respiratory motion and provides dynamic feedback to patients. The RMMP establishes a personalized respiration model based on deep free breathing. The model is further processed to generate a QBH model by inserting a short breath-hold period into the end point of the-end-of-expiration phase. Then the patient is guided to follow the QBH model through the AVBFS. A simulation study with ten volunteers was performed to evaluate the feasibility of the proposed technique. In the simulation, an in-house developed macro program automatically controlled the QBH procedure to virtually deliver an intensity modulated radiation therapy(IMRT) plan. For each volunteer subject, three QBH maneuvers with different breath-hold times of 3, 5, and 7s (denoted as QBH3s, QBH5s, and QBH7s, respectively) and a conventional gating maneuver with 30% duty cycle (for comparison purpose) were applied. External respiration motion signals obtained during the gating window were analyzed to obtain mean absolute error (MAE) between the measured and guiding curve, mean absolute deviation (MAD) of the measured curve, and an inverse uncertainty time histogram (IUTH). Results: Every volunteer successfully performed all of the four maneuvers (1 gating and 3 QBH patterns). The average treatment times were 466.8, 452.3, and 430.8 s for the QBH3s, QBH5s, and QBH7s, respectively, compared to 530.4 s for the gating technique. The mean absolute errors between measured and guiding curve during the gating window were 0.9 ± 0.7, 0.8 ± 0.6, 0.7 ± 0.6, and 0.6 ± 0.7 mm for the gating, QBH3s, QBH5s, and QBH7s, respectively. The mean absolute deviations of the measured curve during the gating window were 0.7 ± 0.7, 0.5 ± 0.5, 0.5 ± 0.4, and 0.5 ± 0.6 mm for the gating, QBH3s, QBH5s, and QBH7s, respectively. In the analysis of the IUTH during the gating window, the QBH simulations showed similar (QBH3s) or less (QBH5s and QBH7s) motion uncertainties compared to the gating simulation. Conclusions: The proposed QBH technique with personalized audio-visual biofeedback was feasible for respiratory motion management. It showed equivalent or less motion uncertainty and shorter treatment time than the conventional free-breathing-based gating technique did. The technique is expected to optimally compromise between patient comfort and treatment efficiency.
- Published
- 2011