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Quantifying day-to-day variations in 4DCBCT-based PCA motion models.

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Lung cancer radiotherapy motion models show stable early components across treatment days. This suggests pre-treatment motion models may remain valid throughout SBRT, reducing the need for daily recalibration.

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Area of Science:

  • Medical Physics
  • Radiotherapy
  • Image Analysis

Background:

  • Accurate tumor targeting in lung cancer stereotactic body radiotherapy (SBRT) requires accounting for respiratory motion.
  • Four-dimensional cone-beam CT (4DCBCT) provides image data for motion modeling during treatment.

Purpose of the Study:

  • To quantify day-to-day variations in respiratory motion models derived from pre-treatment 4DCBCT fractions in lung cancer SBRT.
  • To assess the stability of motion model components across multiple treatment fractions.

Main Methods:

  • Deformable image registration (DIR) was applied to daily 4DCBCT images to generate displacement vector fields (DVFs).
  • Principal component analysis (PCA) was used on DVFs to create motion models.
  • Variations were quantified using root mean squared (RMS) difference, directional similarity, and Euclidean Model Norm (EMN) comparing daily models to a reference.

Main Results:

  • The first two principal component eigenvectors demonstrated significantly higher stability across fractions (lower RMS, higher directional similarity, and higher EMN) compared to subsequent eigenvectors.
  • RMS difference was 0.00017 for the first two eigenvectors versus 0.00025 for the last three.
  • Directional similarity was 0.528 for the first two versus 0.041 for the last three, and EMN was 0.678 versus 0.212, respectively.

Conclusions:

  • While motion model eigenvectors exhibit day-to-day variations, the initial components remain relatively stable throughout the SBRT treatment course.
  • A pre-treatment motion model based on early PCA eigenvectors may be applicable for the entire treatment duration.
  • Further research is needed to determine the impact of these variations on motion reconstruction accuracy for clinical tasks.