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Dynamic Lung Tumor Tracking for Stereotactic Ablative Body Radiation Therapy
Published on: June 7, 2015
Predictive uncertainty in infrared marker-based dynamic tumor tracking with Vero4DRT
Mami Akimoto1, Mitsuhiro Nakamura, Nobutaka Mukumoto
1Department of Radiation Oncology and Image-applied Therapy, Graduate School of Medicine, Kyoto University, Kyoto 606-8507, Japan.
Medical Physics
|September 7, 2013
Summary
Infrared (IR) marker-based lung cancer treatment significantly reduced motion errors. However, baseline drift occasionally caused >3 mm intrafractional errors, necessitating frequent model updates for accurate tumor tracking.
Area of Science:
- Medical Physics
- Radiation Oncology
- Image-Guided Therapy
Background:
- Dynamic tumor tracking irradiation (IR Tracking) utilizes infrared markers for real-time tumor localization.
- Accurate tumor tracking is crucial for minimizing geometric errors in lung cancer radiotherapy.
- Predictive modeling aims to anticipate tumor motion for continuous beam targeting.
Purpose of the Study:
- To quantify predictive uncertainty in IR marker-based dynamic tumor tracking for lung cancer.
- To evaluate the accuracy of a four-dimensional (4D) model in predicting tumor position during treatment.
- To analyze intrafractional errors arising from baseline drift in IR Tracking.
Main Methods:
- Analysis of 110 logfiles from 10 lung cancer patients undergoing IR Tracking with Vero4DRT.
- Development of a 4D model correlating IR marker positions (PIR) with implanted gold marker tumor positions (Pdetect).
- Evaluation of predictive errors in 4D modeling (E4DM) and baseline drift errors (EBD) during treatment sessions.
Main Results:
- Mean predictive error in 4D modeling (E4DM) was minimal (0.0 mm), with standard deviations up to 1.6 mm across directions.
- Baseline drift errors (EBD) ranged from -2.1 to 3.5 mm, showing strong correlations with drift in IR marker and detected positions.
- Untreated baseline drift led to systematic deviations between predicted and detected target positions.
Conclusions:
- IR Tracking effectively reduces respiratory motion-induced geometric errors in lung cancer radiotherapy.
- Occasional intrafractional errors exceeding 3 mm due to baseline drift were observed.
- Continuous monitoring of target/marker positions and frequent 4D model updates are recommended to compensate for baseline drift errors.
