Dynamic gating window technique for the reduction of dosimetric error in respiratory-gated spot-scanning particle therapy: An initial phantom study using patient tumor trajectory data.

Spot-scanning particle therapy possesses advantages, such as high conformity to the target and efficient energy utilization compared with those of the passive scattering irradiation technique. However, this irradiation technique is sensitive to target motion. In the current clinical situation, some motion management techniques, such as respiratory-gated irradiation, which uses an external or internal surrogate, have been clinically applied. In surrogate-based gating, the size of the gating window is fixed during the treatment in the current treatment system. In this study, we propose a dynamic gating window technique, which optimizes the size of gating window for each spot by considering a possible dosimetric error. The effectiveness of the dynamic gating window technique was evaluated by simulating irradiation using a moving target in a water phantom. In dosimetric characteristics comparison, the dynamic gating window technique exhibited better performance in all evaluation volumes with different effective depths compared with that of the fixed gate approach. The variation of dosimetric characteristics according to the target depth was small in dynamic gate compared to fixed gate. These results suggest that the dynamic gating window technique can maintain an acceptable dose distribution regardless of the target depth. The overall gating efficiency of the dynamic gate was approximately equal or greater than that of the fixed gating window. In dynamic gate, as the target depth becomes shallower, the gating efficiency will be reduced, although dosimetric characteristics will be maintained regardless of the target depth. The results of this study suggest that the proposed gating technique may potentially improve the dose distribution. However, additional evaluations should be undertaken in the future to determine clinical applicability by assuming the specifications of the treatment system and clinical situation.

Application of motion prediction based on a long short-term memory network for imaging dose reduction in real-time tumor-tracking radiation therapy.

PURPOSE: To demonstrate the possibility of using a lower imaging rate while maintaining acceptable accuracy by applying motion prediction to minimize the imaging dose in real-time image-guided radiation therapy. METHODS: Time-series of three-dimensional internal marker positions obtained from 98 patients in liver stereotactic body radiation therapy were used to train and test the long-short-term memory (LSTM) network. For real-time imaging, the root mean squared error (RMSE) of the prediction on three-dimensional marker position made by LSTM, the residual motion of the target under respiratory-gated irradiation, and irradiation efficiency were evaluated. In the evaluation of the residual motion, the system-specific latency was assumed to be 100 ms. RESULTS: Except for outliers in the superior-inferior (SI) direction, the median/maximum values of the RMSE for imaging rates of 7.5, 5.0, and 2.5 frames per second (fps) were 0.8/1.3, 0.9/1.6, and 1.2/2.4 mm, respectively. The median/maximum residual motion in the SI direction at an imaging rate of 15.0 fps without prediction of the marker position, which is a typical clinical setting, was 2.3/3.6 mm. For rates of 7.5, 5.0, and 2.5 fps with prediction, the corresponding values were 2.0/2.6, 2.2/3.3, and 2.4/3.9 mm, respectively. There was no significant difference between the irradiation efficiency with and that without prediction of the marker position. The geometrical accuracy at lower frame rates with prediction applied was superior or comparable to that at 15 fps without prediction. In comparison with the current clinical setting for real-time image-guided radiation therapy, which uses an imaging rate of 15.0 fps without prediction, it may be possible to reduce the imaging dose by half or more. CONCLUSIONS: Motion prediction can effectively lower the frame rate and minimize the imaging dose in real-time image-guided radiation therapy.