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Textural feature calculated from segmental fluences as a modulation index for VMAT.

So-Yeon Park1, Jong Min Park2, Jung-In Kim2

  • 1Department of Radiation Oncology, Seoul National University Hospital, Seoul, Republic of Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Republic of Korea; Biomedical Research Institute, Seoul National University College of Medicine, Seoul, Republic of Korea; Interdisciplinary Program in Radiation Applied Life Science, Seoul National University College of Medicine, Seoul, Republic of Korea.

Physica Medica : PM : an International Journal Devoted to the Applications of Physics to Medicine and Biology : Official Journal of the Italian Association of Biomedical Physics (AIFB)
|September 23, 2015
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Summary

Textural features, specifically contrast with 10 segments, effectively predict volumetric modulated arc therapy (VMAT) delivery accuracy. This method shows higher correlation than traditional modulation indices for improved radiotherapy precision.

Keywords:
Degree of modulationFluenceTexture analysisVolumetric modulated arc therapy

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Area of Science:

  • Medical Physics
  • Radiation Oncology

Background:

  • Volumetric Modulated Arc Therapy (VMAT) is a complex radiotherapy technique.
  • Ensuring accurate VMAT plan delivery is crucial for effective cancer treatment.
  • Predictive models for VMAT delivery accuracy are needed to optimize treatment outcomes.

Purpose of the Study:

  • To optimize textural features from VMAT plans to predict delivery accuracy.
  • To evaluate the correlation between specific textural features and VMAT delivery errors.
  • To compare the predictive performance of textural features against conventional modulation indices.

Main Methods:

  • Retrospective analysis of 20 prostate and 20 head and neck VMAT plans.
  • Generation of fluences by summing segments at sequential control points (5 to 356 segments).
  • Calculation of 6 textural features (e.g., contrast, entropy) at displacement distances of 1, 5, and 10.
  • Spearman's rank correlation coefficients (rs) computed between textural features and VMAT delivery accuracy metrics.

Main Results:

  • Contrast (d=10) with 10 segments showed significant correlation (rs=0.666) with global gamma passing rates (2%/2mm).
  • This feature also correlated strongly with multi-leaf collimator positional errors (rs=-0.895) and gantry angle errors (rs=0.727).
  • 14 out of 35 dose-volumetric parameters showed statistically significant correlations with delivery accuracy changes.

Conclusions:

  • Contrast (d=10) derived from 10 segments demonstrates superior predictive capability for VMAT delivery accuracy.
  • This textural feature outperforms conventional modulation indices in predicting radiotherapy delivery precision.
  • The findings suggest a novel approach for quality assurance in VMAT planning and delivery.