ArticleCureus2025
Artificial Intelligence (AI)-Driven Adaptive Motion Management in Helical and Robotic Radiotherapy: Innovations, Challenges, and Future Directions.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- AI-driven robotic surgery in oncology: advancing precision, personalization, and patient outcomes.Journal of robotic surgery · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Artificial intelligence (AI) has revolutionized motion-adaptive radiotherapy (ART) by enhancing tumor-tracking accuracy and optimizing radiation dosage delivery. Traditional motion management techniques, such as respiratory gating and internal target volume (ITV) expansion, often result in increased treatment margins and unintended radiation exposure. AI-powered real-time motion tracking, deformable image registration (DIR), and ART offer superior tumor localization, automated dose modulation, and real-time imaging integration. This study examined AI-based motion guidance technologies in helical tomotherapy (HT) and CyberKnife (Accuray, Madison, WI) robotic radiosurgery, highlighting technical innovations, engineering challenges, and clinical applications. HT employs megavoltage computed tomography (MVCT) for intra-fractional motion monitoring, whereas CyberKnife utilizes x-ray-based beam correction via a robotic arm to achieve submillimeter precision. Despite advancements, challenges such as AI processing latency, tumor motion variability, and multimodal imaging integration persist. Future research should focus on improving the AI response times, enhancing motion prediction algorithms, and developing fully automated AI-based radiation delivery systems.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.