Evidence map›Paper›PMID 42767974›Full record

ArticleJournal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine2026

A Standardized Technique for Ultrasound-MRI Fusion Imaging of the Carotid Artery for Vascular Assessment.

Maxwell J Kiernan, Rashid Al Mukaddim, Yurim Lee, Yimeng Dou, Zhiwei Zhang, Carol C Mitchell, Kevin Johnson, Laura Eisenmenger, Robert J Dempsey, Matthew H Lee and 1 more

Abstract read
In one paragraph

Article in Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Maxwell J KiernanDepartment of Medical Physics, University of Wisconsin School of Medicine and Public health (UW-SMPH), Madison, Wisconsin, USA.ORCID https://orcid.org/0009-0007-7897-1201
Rashid Al MukaddimDepartment of Medical Physics, University of Wisconsin School of Medicine and Public health (UW-SMPH), Madison, Wisconsin, USA.
Yurim LeeDepartment of Medical Physics, University of Wisconsin School of Medicine and Public health (UW-SMPH), Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0002-8362-4227
Yimeng DouDepartment of Medical Physics, University of Wisconsin School of Medicine and Public health (UW-SMPH), Madison, Wisconsin, USA.
Zhiwei ZhangDepartment of Medical Physics, University of Wisconsin School of Medicine and Public health (UW-SMPH), Madison, Wisconsin, USA.
Carol C MitchellDepartment of Medicine, University of Wisconsin School of Medicine and Public health (UW-SMPH), Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0001-6445-3306
Kevin JohnsonDepartment of Medical Physics, University of Wisconsin School of Medicine and Public health (UW-SMPH), Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0002-8660-0853
Laura EisenmengerDepartment of Radiology, University of Wisconsin School of Medicine and Public health (UW-SMPH), Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0001-6764-4239
Robert J DempseyDepartment of Neurological Surgery, University of Wisconsin School of Medicine and Public health (UW-SMPH), Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0002-1636-5456
Matthew H LeeDepartment of Radiology, University of Wisconsin School of Medicine and Public health (UW-SMPH), Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0001-8500-0306
Tomy VargheseDepartment of Medical Physics, University of Wisconsin School of Medicine and Public health (UW-SMPH), Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0003-3299-9130

Funding

Training Program in Translational Cardiovascular Science (TPTCS)T32HL007936 · NHLBI · UNIVERSITY OF WISCONSIN-MADISON · PI Lee Lochbaum Eckhardt, Gail A Robertson · 2001 to 2026
$11.6M
Early Detection of Vascular Dysfunction Using Biomarkers from Lagrangian Carotid Strain ImagingR01HL147866 · NHLBI · UNIVERSITY OF WISCONSIN-MADISON · PI VARGHESE, TOMY · 2020 to 2023
$2.9M
NHLBI NIH HHS 1R01HL147866NHLBI NIH HHS R01 HL147866NHLBI NIH HHS T32 HL007936NHLBI NIH HHS T32HL007936
6 · The paper itself

Abstract

purposeTo describe a reproducible ultrasound-magnetic resonance imaging (MRI) fusion imaging technique developed for quantitative assessment of carotid wall strain and plaque morphology.

methodsMRI volumes (Oblique T2 Cube) were imported into the Sequoia ultrasound system equipped with an electromagnetic tracking module. The fusion workflow aligned ultrasound and MRI coordinate spaces through anatomical landmark registration of the internal and external carotid arteries. Real-time B-mode and strain imaging were performed with a 10L4 transducer. The fused MRI volume provided spatial context for localization of plaque and intima-media regions. Following alignment, additional B-mode, color Doppler, and radiofrequency (RF) data were acquired on a Siemens S2000/S3000 system to match the imaging plane used during fusion.

resultsThis workflow enabled consistent cross-modality localization of vascular features between MRI and ultrasound, improving repeatability of acquisitions. The S2000 acquisition step ensured that color Doppler and RF data corresponded to the same anatomical orientation defined during fusion.

conclusionThis technique offers a practical framework for ultrasound-MRI fusion in carotid imaging and facilitates direct localization of similar structures across 2 imaging modalities. This approach also enables visualization across different systems with manual visual corroborations that, in this case, enabled standardized RF data collection for quantitative elastography research.

Identifiers

PMID42767974
PMCPMC13637720

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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.