Development and validation of a prototypal neural networks-based tumor tracking method

Area of Science:

• Medical Physics
• Radiotherapy
• Artificial Intelligence

Background:

• Intra-fractional organ motion causes significant uncertainties in radiotherapy target localization, compromising dose delivery accuracy.
• This inaccuracy is particularly critical in particle therapy, potentially leading to severe side effects and suboptimal tumor control.
• Current clinical tumor tracking solutions are limited to photon radiotherapy (e.g., CyberKnife), with no established methods for particle therapy.

Purpose of the Study:

• To develop a prototype neural network-based tumor tracking algorithm specifically designed for particle therapy.
• To address the limitations of current tumor tracking technologies in the context of particle beam treatments.
• To evaluate the efficacy of artificial neural networks in real-time target motion mitigation for particle therapy.

Main Methods:

• Developed a novel algorithm utilizing three independent neural networks to estimate internal target position from external surrogate signals.
• Employed a benchmark dataset from 20 patients treated with the CyberKnife system for performance evaluation.
• Focused on real-time dynamic steering of the radiation beam to match the moving target's position.

Main Results:

• The developed neural network-based algorithm demonstrated superior targeting error reduction compared to the CyberKnife system benchmark.
• The findings indicate significant potential for artificial neural networks in enhancing tumor tracking accuracy.
• The prototypal algorithm shows promise for clinical implementation in particle therapy settings.

Conclusions:

• Artificial neural networks offer a viable and powerful approach for developing advanced tumor tracking methodologies in particle therapy.
• The developed algorithm represents a significant step towards overcoming motion-related uncertainties in particle radiotherapy.
• This research paves the way for more precise and effective cancer treatments using particle beams.