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Translating Live EPID based Inspiration Level Assessment (LEILA) into clinical practice.

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Summary
This summary is machine-generated.

The LEILA system enhances deep inspiration breath hold (DIBH) breast radiotherapy by using electronic portal imaging device (EPID) images for real-time internal anatomy monitoring. This clinic-ready application improves accuracy and reproducibility with minimal workload.

Keywords:
Breast radiotherapyDeep Inspiration Breath Hold (DIBH)Electronic Portal Imaging Device (EPID)Motion managementReal-time patient monitoring

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Image-Guided Therapy

Background:

  • Deep inspiration breath hold (DIBH) is crucial for minimizing patient motion and reducing radiation exposure to organs at risk during breast radiotherapy.
  • Effective DIBH relies on consistent patient breathing patterns, typically monitored using external surrogates.
  • Real-time verification of internal anatomy during DIBH is essential for accurate treatment delivery.

Purpose of the Study:

  • To describe the development and implementation of the LEILA system, a real-time verification tool for DIBH breast radiotherapy.
  • To utilize electronic portal imaging device (EPID) images for monitoring internal anatomy during DIBH.
  • To establish LEILA as a clinic-ready application for enhanced DIBH accuracy and reproducibility.

Main Methods:

  • The LEILA system employs a fluence model to predict EPID images during treatment planning, estimating lung depths (LDs) and skin distances (SDs).
  • During treatment, EPID images are acquired, and differences in LDs and SDs are quantified in real-time.
  • A pilot study validated the LEILA system's feasibility by monitoring DIBH alongside the existing motion management strategy.

Main Results:

  • The LEILA system was successfully deployed on Varian TrueBeam linear accelerators with aS1200 EPIDs, demonstrating low latency (average image processing time of 74.0 ms).
  • Analysis of 17 monitored beams showed average differences in mid-lung depths and skin distances of -1.2 mm ± 3.1 mm and 1.5 mm ± 4.1 mm, respectively.
  • The system effectively quantifies deviations in internal anatomy during DIBH.

Conclusions:

  • The LEILA system offers a streamlined, automated workflow that meets clinical needs with minimal additional workload for healthcare professionals.
  • LEILA accurately assesses the accuracy and reproducibility of DIBH, providing immediate feedback on deviations.
  • The system offers retrospective insights that can be used to refine DIBH monitoring strategies for improved patient outcomes.