An analytical model for the upper bound estimation of respiratory motion-induced dose uncertainty in spot-scanning proton beam therapy

Developing an accurate model of spot-scanning treatment delivery time and sequence for a compact superconducting synchrocyclotron proton therapy system

BACKGROUND

A new compact superconducting synchrocyclotron single-room proton solution delivers pulsed proton beams to each spot through several irradiation bursts calculated by an iterative layer delivery algorithm. Such a mechanism results in a new beam parameter, burst switching time (BST) in the total beam delivery time (BDT) which has never been studied before. In this study, we propose an experimental approach to build an accurate BDT and sequence prediction model for this new proton solution.

METHODS

Test fields and clinical treatment plans were used to investigate each beam delivery parameter that impacted BDT. The machine delivery log files were retrospectively analyzed to quantitatively model energy layer switching time (ELST), spot switching time (SSWT), spot spill time (SSPT), and BST. A total of 102 clinical IMPT treatment fields' log files were processed to validate the accuracy of the BDT prediction model in comparison with the result from the current commercial system. Interplay effect is also investigated as a clinical application by comparing this new delivery system model with a conventional cyclotron accelerator model.

RESULTS

The study finds that BST depends on the amount of data to be transmitted between two sequential radiation bursts, including a machine irradiation log file of the previous burst and a command file to instruct the proton system to deliver the next burst. The 102 clinical treatment fields showed that the accuracy of each component of the BDT matches well between machine log files and BDT prediction model. More specifically, the difference of ELST, SSWT, SSPT, and BST were (- 3.1 ± 5.7)%, (5.9 ± 3.9)%, (2.6 ± 8.7)%, and (- 2.3 ± 5.3)%, respectively. The average total BDT was about (2.1 ± 3.0)% difference compared to the treatment log files, which was significantly improved from the current commercial proton system prediction (58 ± 15)%. Compared to the conventional cyclotron system, the burst technique from synchrocyclotron effectively reduced the interplay effect in mobile tumor treatment.

CONCLUSION

An accurate BDT and sequence prediction model was established for this new clinical compact superconducting synchrocyclotron single-room proton solution. Its application could help users of similar facilities better assess the interplay effect and estimate daily patient treatment throughput.

Injection of hydrogel spacer increased maximal intrafractional prostate motion in anterior and superior directions during volumetric modulated arc therapy-stereotactic body radiation therapy for prostate cancer

Background

The aim of this study was to clarify the association between intrafractional prostate shift and hydrogel spacer.

Methods

Thirty-eight patients who received definitive volumetric modulated arc therapy (VMAT)-stereotactic body radiation therapy (SBRT) for prostate cancer with prostate motion monitoring in our institution in 2018–2019 were retrospectively evaluated. In order to move the rectum away from the prostate, hydrogel spacer (SpaceOAR system, Boston Scientific, Marlborough, the United States) injection was proposed to the patients as an option in case of meeting the indication of use. We monitored intrafractional prostate motion by using a 4-dimensional (4D) transperineal ultrasound device: the Clarity 4D ultrasound system (Elekta AB). The deviation of the prostate was monitored in each direction: superior-inferior, left–right, and anterior–posterior. We also calculated the vector length. The maximum intrafractional displacement (MID) per fraction for each direction was detected and mean of MIDs was calculated per patient. The MIDs in the non-spacer group and the spacer group were compared using the unpaired t-test.

Results

We reviewed 33 fractions in eight patients as the spacer group and 148 fractions in 30 patients as the non-spacer group. The superior MID was 0.47 ± 0.07 (mean ± SE) mm versus 0.97 ± 0.24 mm (P = 0.014), the inferior MID was 1.07 ± 0.11 mm versus 1.03 ± 0.25 mm (P = 0.88), the left MID was 0.74 ± 0.08 mm versus 0.87 ± 0.27 mm (P = 0.55), the right MID was 0.67 ± 0.08 mm versus 0.92 ± 0.21 mm (P = 0.17), the anterior MID was 0.45 ± 0.06 mm versus 1.16 ± 0.35 mm (P = 0.0023), and the posterior MID was 1.57 ± 0.17 mm versus 1.37 ± 0.22 mm (P = 0.56) in the non-spacer group and the spacer group, respectively. The max of VL was 2.24 ± 0.19 mm versus 2.89 ± 0.62 mm (P = 0.19), respectively.

Conclusions

Our findings suggest that maximum intrafractional prostate motion during VMAT-SBRT was larger in patients with hydrogel spacer injection in the superior and anterior directions. Since this difference seemed not to disturb the dosimetric advantage of the hydrogel spacer, we do not recommend routine avoidance of the hydrogel spacer use.

Report of AAPM Task Group 290: Respiratory motion management for particle therapy

Dose uncertainty induced by respiratory motion remains a major concern for treating thoracic and abdominal lesions using particle beams. This Task Group report reviews the impact of tumor motion and dosimetric considerations in particle radiotherapy, current motion‐management techniques, and limitations for different particle‐beam delivery modes (i.e., passive scattering, uniform scanning, and pencil‐beam scanning). Furthermore, the report provides guidance and risk analysis for quality assurance of the motion‐management procedures to ensure consistency and accuracy, and discusses future development and emerging motion‐management strategies. This report supplements previously published AAPM report TG76, and considers aspects of motion management that are crucial to the accurate and safe delivery of particle‐beam therapy. To that end, this report produces general recommendations for commissioning and facility‐specific dosimetric characterization, motion assessment, treatment planning, active and passive motion‐management techniques, image guidance and related decision‐making, monitoring throughout therapy, and recommendations for vendors. Key among these recommendations are that: (1) facilities should perform thorough planning studies (using retrospective data) and develop standard operating procedures that address all aspects of therapy for any treatment site involving respiratory motion; (2) a risk‐based methodology should be adopted for quality management and ongoing process improvement.

Building a precise machine-specific time structure of the spot and energy delivery model for a cyclotron-based proton therapy system

OBJECTIVE

We proposed an experimental approach to build a precise machine-specific beam delivery time (BDT) prediction and delivery sequence model for standard, volumetric, and layer repainting delivery based on a cyclotron accelerator system. Approach Test fields and clinical treatment plans' log files were used to experimentally derive three main beam delivery parameters that impacted BDT: energy layer switching time (ELST), spot switching time (SSWT), and spot drill time (SDT). This derived machine-specific model includes standard, volumetric, and layer repainting delivery sequences. A total of 103 clinical treatment fields were used to validate the model.

MAIN RESULTS

The study found that ELST is not stochastic in this specific machine. Instead, it is actually the data transmission time or energy selection time, whichever takes longer. The validation showed that the accuracy of each component of the BDT matches well between machine log files and the model's prediction. The average total BDT was about (-0.74±3.33)% difference compared to the actual treatment log files, which is improved from the current commercial proton therapy system's prediction (67.22%±26.19%).

SIGNIFICANCE

An accurate BDT prediction and delivery sequence model was established for an cyclotron-based proton therapy system IBA ProteusPLUS®. Most institutions could adopt this method to build a machine-specific model for their own proton system.