Evidence map›Paper›PMID 39446304›Full record

ArticlePhysical and engineering sciences in medicine2024

Investigating 4D respiratory cone-beam CT imaging for thoracic interventions on robotic C-arm systems: a deformable phantom study.

Tess Reynolds, Owen Dillon, Yiqun Ma, Nicholas Hindley, J Webster Stayman, Magdalena Bazalova-Carter

Abstract read
In one paragraph

Article in Physical and engineering sciences in medicine, 2024. 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. Review
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

6 authors.

Tess ReynoldsUniversity of Sydney, Sydney, NSW, Australia. tess.reynolds@sydney.edu.au.ORCID https://orcid.org/0000-0003-0543-9170
Owen DillonUniversity of Sydney, Sydney, NSW, Australia.ORCID https://orcid.org/0000-0002-3002-384X
Yiqun MaJohns Hopkins University, Baltimore, MD, USA.ORCID https://orcid.org/0000-0002-5941-0739
Nicholas HindleyUniversity of Sydney, Sydney, NSW, Australia.ORCID https://orcid.org/0000-0003-0162-8716
J Webster StaymanJohns Hopkins University, Baltimore, MD, USA.ORCID https://orcid.org/0000-0003-4358-378X
Magdalena Bazalova-CarterUniversity of Victoria, Victoria, BC, Canada.ORCID https://orcid.org/0000-0002-9365-2889

Funding

Task-Driven 3D Interventional ImagingR01EB027127 · NIBIB · JOHNS HOPKINS UNIVERSITY · PI STAYMAN, JOSEPH WEBSTER · 2019 to 2022
$1.8M
NIBIB NIH HHS R01 EB027127
6 · The paper itself

Abstract

Increasingly, interventional thoracic workflows utilize cone-beam CT (CBCT) to improve navigational and diagnostic yield. Here, we investigate the feasibility of implementing free-breathing 4D respiratory CBCT for motion mitigated imaging in patients unable to perform a breath-hold or without suspending mechanical ventilation during thoracic interventions. Circular 4D respiratory CBCT imaging trajectories were implemented on a clinical robotic CBCT system using additional real-time control hardware. The circular trajectories consisted of 1 × 360° circle at 0° tilt with fixed gantry velocities of 2°/s, 10°/s, and 20°/s. The imaging target was an in-house developed anthropomorphic breathing thorax phantom with deformable lungs and 3D-printed imaging targets. The phantom was programmed to reproduce 3 patient-measured breathing traces. Following image acquisition, projections were retrospectively binned into ten respiratory phases and reconstructed using filtered back projection, model-based, and iterative motion compensated algorithms. A conventional circular acquisition on the system of the free-breathing phantom was used as comparator. Edge Response Width (ERW) of the imaging target boundaries and Contrast-to-Noise Ratio (CNR) were used for image quality quantification. All acquisitions across all traces considered displayed visual evidence of motion blurring, and this was reflected in the quantitative measurements. Additionally, all the 4D respiratory acquisitions displayed a lower contrast compared to the conventional acquisitions for all three traces considered. Overall, the current implementation of 4D respiratory CBCT explored in this study with various gantry velocities combined with motion compensated algorithms improved image sharpness for the slower gantry rotations considered (2°/s and 10°/s) compared to conventional acquisitions over a variety of patient traces.

Indexed as

Cone-Beam Computed TomographyFour-Dimensional Computed TomographyPhantoms, ImagingRespirationAlgorithmsHumansImage Processing, Computer-AssistedRoboticsThorax4DCBCTCone-beam CTInterventional imagingRespiratory

Identifiers

PMID39446304
PMCPMC11666758

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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.