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Related Experiment Video

Updated: May 4, 2026

Dynamic Lung Tumor Tracking for Stereotactic Ablative Body Radiation Therapy
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Tumor tracking method based on a deformable 4D CT breathing motion model driven by an external surface surrogate.

Aurora Fassi1, Joël Schaerer2, Mathieu Fernandes2

  • 1Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milano, Italy.

International Journal of Radiation Oncology, Biology, Physics
|December 17, 2013
PubMed
Summary

This study presents a novel tumor tracking method using a surrogate-driven motion model for precise radiation therapy. The technique accurately estimates tumor motion from external surface imaging, reducing the need for invasive tracking during treatment.

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Image-guided therapy

Background:

  • Respiration-induced motion causes significant intrafraction uncertainties in extracranial radiation therapy.
  • Accurate real-time tumor localization is crucial for high-precision radiotherapy to minimize radiation dose to healthy tissues.

Purpose of the Study:

  • To develop and evaluate a noninvasive tumor tracking method using a surrogate-driven motion model for dynamic localization of extracranial targets.
  • To compensate for respiration-induced intrafraction motion in high-precision radiation therapy.

Main Methods:

  • A patient-specific breathing motion model was derived from 4-dimensional planning CT (4D CT) scans.
  • Respiratory parameters were updated using in-room radiography and optical surface imaging, with baseline adapted from daily cone-beam CT (CBCT).
  • Tumor motion was estimated from external breathing surrogates derived from thoracoabdominal surface displacement.

Main Results:

  • The developed method achieved tumor motion estimation with absolute differences ranging from 0.7 to 2.4 mm compared to CBCT reference trajectories.
  • Phase shifts between reference and estimated tumor motion did not exceed 7% of the breathing cycle.
  • Simultaneous acquisition of CBCT and optical surface images allowed for robust validation on 7 lung cancer patients.

Conclusions:

  • The proposed tumor tracking method integrates 4D CT motion information with real-time surface imaging, offering an alternative to traditional correlation models.
  • This technique reduces reliance on invasive imaging and continuous correlation parameter updates.
  • It provides a promising approach for noninvasive, dynamic intrafraction motion management in radiation therapy.