ArticleCureus2025
A Quality Control Procedure for Single Fiducial Tracking of Lung Lesions.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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0 citing papers in PubMed.
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Real-time adaptive motion management enables the synchronization of radiation delivery with the patient's breathing motion, thus reducing target margins and normal tissue exposure. The respiratory model is created by correlating the position of external markers placed on the patient's chest with the internal target position extracted from planar X-ray images. While a fiducial-less tracking algorithm is available for lung lesions with high radiographic contrast, many patients require the implantation of radio-opaque markers for localization. To limit the incidence of complications from the implantation procedure, a single fiducial marker may be implanted. As fiducials can migrate following implantation, it is important to verify the relationship between the tumor and the fiducial prior to treatment. The goal of this technical report is to provide a quality control (QC) procedure to assess the possibility of fiducial migration in lung patients treated on the robotic radiosurgery platform.
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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.