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Author Spotlight: Advancing CBCT and Digital Dental Image Integration with AI-Assisted Digitization
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Automated patient setup and gating using cone beam computed tomography projections.

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This study introduces an automated dynamic programming method for segmenting fiducial markers in radiation therapy, improving patient positioning accuracy and reducing setup time. The new approach enhances treatment delivery accuracy compared to manual methods.

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Area of Science:

  • Medical Physics
  • Radiotherapy Technology
  • Image Analysis

Background:

  • Fiducial markers are crucial for patient positioning and respiratory gating in radiation therapy.
  • Manual alignment using cone beam computed tomography (CBCT) is time-consuming and user-dependent, leading to suboptimal setups.

Purpose of the Study:

  • To develop and validate a fully automated, robust method for segmenting radiopaque fiducial markers in CBCT projection images.
  • To utilize segmented markers for automatic optimization of treatment couch position and/or gating window bounds.

Main Methods:

  • A dynamic programming (DP) algorithm was developed for segmenting fiducial markers in CBCT projection images.
  • The algorithm was tested on 87 markers across 39 patients, with intrafraction images acquired every 3 seconds.
  • Performance was evaluated against manual setup procedures in both gated and non-gated patient cohorts from two institutions.

Main Results:

  • The DP algorithm achieved a mean absolute 2D segmentation error of 1.3 ± 1.0 mm.
  • For gated patients, the DP algorithm improved delivery accuracy (96 ± 6% vs. 91 ± 11%, p < 0.01) compared to manual kV fluoroscopy setup.
  • For non-gated patients, the DP algorithm showed comparable performance to manual CBCT matching (1.5 ± 0.8 mm vs. 1.6 ± 0.9 mm, p = 0.48).

Conclusions:

  • The proposed automated patient setup algorithm is fast (1-2 seconds), requires no user intervention, and performs comparably to or better than current clinical manual setups.
  • This automated method offers a significant improvement in efficiency and accuracy for patient positioning in radiation therapy.
  • The dynamic programming approach provides a robust solution for fiducial marker segmentation in CBCT, enhancing radiotherapy delivery.