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Artificial intelligence for treatment delivery: image-guided radiotherapy.

Moritz Rabe1, Christopher Kurz1, Adrian Thummerer1

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Strahlentherapie Und Onkologie : Organ Der Deutschen Rontgengesellschaft ... [Et Al]
|August 14, 2024
PubMed
Summary

Artificial intelligence (AI) is revolutionizing radiation therapy (RT) automation, especially in image-guided RT (IGRT) and online adaptive RT (ART) workflows. AI enhances imaging accuracy and efficiency for improved patient treatment outcomes.

Keywords:
Automatic segmentationDeep learningMotion managementOnline adaptive radiation therapySynthetic computed tomography

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Area of Science:

  • Medical Physics
  • Radiotherapy
  • Artificial Intelligence

Background:

  • Radiation therapy (RT) is a computationally intensive field with significant automation potential.
  • Image-guided RT (IGRT) and online adaptive RT (ART) workflows, particularly with magnetic resonance (MR) and cone-beam computed tomography (CBCT) linacs, increasingly require automation.

Purpose of the Study:

  • To review the current state and future potential of artificial intelligence (AI) in modern image-guided radiation therapy (IGRT).
  • To explore AI applications in enhancing online adaptive RT (ART) workflows.

Main Methods:

  • Review of modern IGRT and online ART workflows.
  • Analysis of AI applications in CBCT and MRI correction for dose calculation.
  • Examination of AI for auto-segmentation, motion management, and response assessment using in-room imaging.

Main Results:

  • AI shows significant promise for automating critical aspects of IGRT and ART.
  • Applications include improving dose calculation accuracy, streamlining segmentation, enhancing motion management, and enabling precise response assessment.
  • AI integration is crucial for advancing the efficiency and effectiveness of online adaptive radiotherapy.

Conclusions:

  • AI is poised to drive major advancements in image-guided radiation therapy.
  • The integration of AI in IGRT and ART workflows is essential for future developments in radiotherapy.
  • AI applications discussed are key to optimizing automated imaging corrections and treatment delivery.