Clinical Accuracy Analysis and Error Modeling in the CyberKnife System; A Comparative Study

Document Type : Original Paper

Authors

Department of Energy Engineering and Physics, Medical Radiation Engineering Group, Amirkabir University of Technology, Tehran, Iran.

10.22038/ijmp.2024.80469.2411

Abstract

Introduction: This study conducted a clinical accuracy analysis of Synchrony Respiratory Tracking System across different CyberKnife generations (G3, G4, VSI, and M6) to provide comprehensive comparing across different generations. Additionally, appropriate regression models were developed to explain the behavior of standard deviation (SD) of the errors (correlation and prediction) and tumor motion in each region.
Material and Methods: The clinical log data was analyzed to assess the correlation and prediction errors. A retrospective analysis was conducted on 46 patients with thoracic or abdominal cancers treated using the CyberKnife G3. Furthermore, the F-test, P-value, and R2 analysis were applied to model the SD of correlation and prediction errors as a function of tumor displacements across five lung regions and two abdomen regions.
Results: Using a systematic approach, linear, quadratic, cubic, or piecewise regression models were proposed for SD of the errors across tumor displacement. The estimated radial Synchrony error (mean±SD) for the CyberKnife G3, G4, VSI, and M6 was 2.60±0.93 mm, 2.00±0.60 mm, 1.79±1.16 mm, and 0.66±0.23 mm, respectively.
Conclusion: The results indicate that correlation error remains predominant in both lung and abdominal regions across all CyberKnife generations. However, prediction error has been significantly reduced in the G4, VSI, and M6 systems. This improvement is attributed to the newer generations incorporating a combination of historical pattern-matching filters and least-mean-square filters. Error modeling based on tumor motion in different regions reveals a linear relationship between errors and target amplitude in the lung region, while the liver and pancreas regions exhibit non-linear relationships.

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Main Subjects

References

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Iranian Journal of Medical Physics
Volume 22, Issue 1
January and February 2025
Pages 36-43

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History

  • Receive Date: 12 June 2024
  • Revise Date: 19 October 2024
  • Accept Date: 09 April 2025

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