Evidence map›Paper›PMID 29785834›Full record

ArticleJournal of applied clinical medical physics2018

Development of a robust MRI fiducial system for automated fusion of MR-US abdominal images.

Christopher P Favazza, Krzysztof R Gorny, Matthew R Callstrom, Anil N Kurup, Michael Washburn, Pamela S Trester, Charles L Fowler, Nicholas J Hangiandreou

Open access · goldAbstract read
In one paragraph

Article in Journal of applied clinical medical physics, 2018. 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, top 93% of its field
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, 3 citations in OpenAlex.

  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

8 authors at 2 institutions in 1 country.

Christopher P FavazzaDepartment of Radiology, Mayo Clinic, Rochester, MN, USA.
Krzysztof R GornyDepartment of Radiology, Mayo Clinic, Rochester, MN, USA.
Matthew R CallstromDepartment of Radiology, Mayo Clinic, Rochester, MN, USA.
Anil N KurupDepartment of Radiology, Mayo Clinic, Rochester, MN, USA.
Michael WashburnGE Healthcare, Wauwatosa, WI, USA.
Pamela S TresterDepartment of Radiology, Mayo Clinic, Rochester, MN, USA.
Charles L FowlerDepartment of Radiology, Mayo Clinic, Rochester, MN, USA.
Nicholas J HangiandreouDepartment of Radiology, Mayo Clinic, Rochester, MN, USA.
Mayo Clinic in Arizona · USSiemens Healthcare (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We present the development of a two-component magnetic resonance (MR) fiducial system, that is, a fiducial marker device combined with an auto-segmentation algorithm, designed to be paired with existing ultrasound probe tracking and image fusion technology to automatically fuse MR and ultrasound (US) images. The fiducial device consisted of four ~6.4 mL cylindrical wells filled with 1 g/L copper sulfate solution. The algorithm was designed to automatically segment the device in clinical abdominal MR images. The algorithm's detection rate and repeatability were investigated through a phantom study and in human volunteers. The detection rate was 100% in all phantom and human images. The center-of-mass of the fiducial device was robustly identified with maximum variations of 2.9 mm in position and 0.9° in angular orientation. In volunteer images, average differences between algorithm-measured inter-marker spacings and actual separation distances were 0.53 ± 0.36 mm. "Proof-of-concept" automatic MR-US fusions were conducted with sets of images from both a phantom and volunteer using a commercial prototype system, which was built based on the above findings. Image fusion accuracy was measured to be within 5 mm for breath-hold scanning. These results demonstrate the capability of this approach to automatically fuse US and MR images acquired across a wide range of clinical abdominal pulse sequences.

Indexed as

Magnetic Resonance ImagingAlgorithmsFiducial MarkersHumansPhantoms, ImagingUltrasonographyauto-registrationfiducial markerimage fusionMRIultrasound

Identifiers

PMID29785834
PMCPMC6036384
OpenAlexW2804548289

What OpenQuestion holds

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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.