Evidence map›Paper›PMID 40660872›Full record

ArticleJournal of applied clinical medical physics2025

Geometric characterization of an electromagnetic surface tracking system in a radiation therapy environment.

Mumtaz Hussain Soomro, Junliang Xu, Jie Ding, Jochen Cammin, Narottam Lamichhane, Alex Van Slyke, Xiao Liang, Steve Roys, Jiachen Zhuo, Thomas Ernst and 3 more

Abstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Mumtaz Hussain SoomroDepartment of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Junliang XuDepartment of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA.ORCID https://orcid.org/0000-0002-8276-2601
Jie DingDepartment of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Jochen CamminDepartment of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Narottam LamichhaneDepartment of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Alex Van SlykeDepartment of Radiation Oncology, Yale New Haven Hospital, Trumbull, Connecticut, USA.
Xiao LiangDiagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Steve RoysDiagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Jiachen ZhuoDiagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Thomas ErnstDiagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Rao P GullapalliDiagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA.
Erez NevoRobin Medical Inc., Baltimore, Maryland, USA.
Amit SawantDepartment of Radiation Oncology, University of Maryland School of Medicine, Baltimore, Maryland, USA.ORCID https://orcid.org/0000-0002-3901-5774

Funding

Personalized Motion Management for Truly 4D Lung RadiotherapyR01CA262017 · NCI · UNIVERSITY OF MARYLAND BALTIMORE · PI ERNST, THOMAS M, SAWANT, AMIT · 2021 to 2025
$3.1M
NCI NIH HHS R01 CA262017NIH HHS R01 CA 262017
6 · The paper itself

Abstract

backgroundDespite advances in image-guided radiation therapy (IGRT), real-time, soft-tissue-based, volumetric motion monitoring remains unsolved. Integrated MRI+Linac systems are a solution, but are costly and complex. X-ray and optical photogrammetry-based systems have their limitations. Surrogate-based motion models, which use external signals to estimate internal motion, offer an alternative. We explore the feasibility of an electromagnetic (EM) fiducial-based device integrated with a surrogate-based motion model for real-time in-room volumetric motion monitoring. PURPOSE: To assess the feasibility of an EM-tracking system in the linac room, with an eventual goal of integrating it into an MRI-compatible system for real-time volumetric motion monitoring.

methodsWe empirically assessed the impact of gantry rotation and the radiation beam on EM-tracking accuracy using a sinusoidal motion trajectory (2 cm peak-to-peak, 5 s per cycle) programmed into a 2D motion platform. Four EM-tracking sensors were affixed to the platform, and their recorded trajectories were compared to the programmed motion under various conditions, including static and dynamic gantry positions, with and without radiation beams, and during CBCT acquisition.

resultsThe EM-tracking system faithfully reproduced the programmed sinusoidal motion during treatment beam (MV) and CBCT acquisition (kV + gantry rotation). With the beam off and static gantry and static motion platform at 0°, the average point-wise tracking difference was < 0.5 mm compared to gantry angles of 90°, 180°, and 270°. Similarly, with a moving platform, the sensors achieved a < 1 mm difference at the same angles. Additionally, the gantry's clockwise and anticlockwise rotations caused a < 0.5 mm difference on average at all angles during beam-off.

conclusionPreliminary results show the EM-tracking system operates with sub-millimeter accuracy in the linac room, with minimal effects from the radiation beam, gantry motion, or CBCT acquisition, supporting its feasibility for real-time volumetric motion monitoring during IGRT.

Indexed as

Electromagnetic PhenomenaFiducial MarkersNeoplasmsParticle AcceleratorsPhantoms, ImagingRadiotherapy, Image-GuidedRadiotherapy Planning, Computer-AssistedCone-Beam Computed TomographyHumansImage Processing, Computer-AssistedMagnetic Resonance ImagingRadiotherapy DosageRadiotherapy, Intensity-Modulated4D imagingelectromagnetic (EM) trackingLinacreal‐time trackingvolumetric motion models

Identifiers

PMID40660872
PMCPMC12260265

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.