Optimal threshold of a control parameter for tomotherapy respiratory tracking: A phantom study

Abstract

Background: Radixact Synchrony^® , a real-time motion tracking and compensating modality, is used for helical tomotherapy. Control parameters are used for the accurate application of irradiation. Radixact Synchrony^® uses the potential difference, which is an index of the accuracy of the prediction model of target motion and is represented by a statistical prediction of the 3D distance error. Although there are several reports on Radixact Synchrony^® , few have reported the appropriate settings of the potential difference threshold.

Purpose: This study aims to determine the optimal threshold of the potential difference of Radixact Synchrony^® during respiratory tumor-motion-tracking irradiation.

Methods: The relationship among the dosimetric accuracy, motion tracking accuracy, and control parameter was evaluated using a moving platform, a phantom with a basic respiratory model (the fourth power of a sinusoidal wave), and several irregular respiratory model waveforms. The dosimetric accuracy was evaluated by gamma analysis (3%, 1 mm, 10% dose threshold). The tracking accuracy was measured by the distance error of the difference between the tracked and driven positions of the phantom. The largest potential difference for 95% of treatment time was evaluated, and its correlation with the gamma-pass ratio and distance error was investigated. The optimal threshold of the potential difference was determined by receiver operating characteristic (ROC) analysis.

Results: A linear correlation was identified between the potential difference and the gamma-pass ratio (R = -0.704). A linear correlation was also identified between the potential difference and distance error (R = 0.827). However, as the potential difference increased, it tended to underestimate the distance error. The ROC analysis revealed that the appropriate cutoff value of the potential difference was 3.05 mm.

Conclusion: The irradiation accuracy with motion tracking by Radixact Synchrony^® could be predicted from the potential difference, and the threshold of the potential difference should be set to ∼3 mm.

Keywords: dosimetric accuracy; respiratory tracking; tomotherapy.

FIGURE 1

Phantom setup and irradiation plan. (a) Phantom and two‐dimensional (2D) detector were placed on the moving platform: The LED marker was placed on the surrogate stage. The 2D detector, LED marker, surrogate stage, and moving platform were indicated by black arrow, white arrow, black arrowhead, and white arrowhead, respectively. Dose distribution for the (b) transverse section on the isocenter axis and (c) coronal section on the isocenter axis. The marker used for tracking is shown in the pink ROI (indicated by an arrow).

FIGURE 2

Example of a respiratory waveform input to the moving platform. (a) Basic waveform: modeled as the fourth power of a sinusoidal wave. (b) Baseline shift waveform: baseline shifting at a constant speed (at a shift speed of 3 mm/s). (c) Irregular‐amplitude waveform: amplitude of the basic waveform randomly varies every cycle (with a maximum amplitude variation of 40%). (d) Phase shift waveform: same waveform as the basic waveform, albeit with a shift in the respiration phase between the LED marker and the target (with a 10% phase shift).

FIGURE 3

Dosimetric analyses for each respiratory waveform. Dosimetric analysis for (a) baseline shift waveform and (b) irregular amplitude respiratory waveform. LED marker motion with synchronization (LED sync.) and without synchronization (LED without sync.) are represented by red and blue lines, respectively. Statistical analysis is used to compare each condition with a stable waveform. (c) Dosimetric analysis for the phase shift waveform. Phase shift is defined as positive when the LED marker moves ahead of the platform and negative when it moves behind it. Statistical analysis is compared with no phase shift (0%) and each condition. p‐value is Student's t‐test. *p < 0.05.

FIGURE 4

Relationship between gamma‐pass ratio and δ₉₅ . The linear correlation exists between δ₉₅ and the gamma‐pass ratio. In each respiratory waveform, the phantom and LED markers moving with the same waveform input and those moving with different inputs are represented as circles and triangles, respectively.

FIGURE 5

(a) Relationship between maximum Potential diff for 95% (PD₉₅ ) and gamma‐pass ratio. PD₉₅ and gamma‐pass ratio are linearly correlated. In each respiratory waveform, the phantom and LED markers moving with the same waveform input and those moving with different inputs are indicated by circles and triangles, respectively. (b) Receiver operating characteristic (ROC) curve analysis with PD₉₅ as the predictor variable. Sensitivity is used to measure the percentage of true positive failed measurements. The area under the curve for this model is 0.951. The optimal cutoff value of the potential difference is 3.05 mm, according to Youden's index.

FIGURE 6

Maximum Potential diff for 95% (PD₉₅ ) versus maximum 3D distance errors for 95% (δ₉₅ ). The correlation is approximately linear and shows good agreement (ICC 0.763; 95% CI 0.632–0.845). In each respiratory waveform, the phantom and LED marker moving with the same waveform input are indicated by circles, and those moving with different inputs by triangles.