Evidence map›Paper›PMID 40384724›Full record

ArticleQuantitative imaging in medicine and surgery2025

Novel fat suppression technique for ultrashort echo time MRI using single-point Dixon phase modeling.

Nathan Newbury, Sam Sedaghat, Jiyo S Athertya, Soo Hyun Shin, Yajun Ma, Saeed Jerban, Michael Carl, Melissa Lou Silva, Eric Y Chang, Jiang Du and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

11 authors.

Nathan Newbury *Department of Radiology, University of California, San Diego, San Diego, CA, USA.
Sam Sedaghat *Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany.
Jiyo S AthertyaDepartment of Radiology, University of California, San Diego, San Diego, CA, USA.
Soo Hyun ShinDepartment of Radiology, University of California, San Diego, San Diego, CA, USA.
Yajun MaDepartment of Radiology, University of California, San Diego, San Diego, CA, USA.
Saeed JerbanDepartment of Radiology, University of California, San Diego, San Diego, CA, USA.
Michael CarlGE Healthcare, San Diego, CA, USA.
Melissa Lou SilvaDepartment of Radiology, University of California, San Diego, San Diego, CA, USA.
Eric Y ChangDepartment of Radiology, University of California, San Diego, San Diego, CA, USA.
Jiang DuDepartment of Radiology, University of California, San Diego, San Diego, CA, USA.
Hyungseok JangDepartment of Radiology, University of California, Davis, Sacramento, CA, USA.

Funding

Ultrashort Echo Time (UTE) Magnetic Resonance Imaging of BoneR01AR068987 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DU, JIANG · 2015 to 2024
$4.9M
Quantitative UTE MR Imaging: Sensitive Biomarkers for OsteoarthritisR01AR062581 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DU, JIANG · 2013 to 2022
$4.1M
Ultrashort Echo Time Magnetic Resonance Imaging of the Lumbar Intervertebral Disc.R01AR079484 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Yajun Ma · 2022 to 2026
$2.7M
Ultrashort Echo Time Magnetic Resonance Imaging of Hemophilic ArthropathyR01AR078877 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JANG, HYUNGSEOK · 2021 to 2025
$2.4M
Quantitative UTE MR Imaging of Myelin: Novel Biomarkers for Alzheimer's DiseaseRF1AG075717 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DU, JIANG · 2022 to 2022
$2.3M
Three-dimensional Ultrashort Echo Time Magnetic Resonance Imaging of EnthesesR01AR075825 · NIAMS · VETERANS MEDICAL RESEARCH FDN/SAN DIEGO · PI CHANG, ERIC Y · 2019 to 2023
$1.8M
Quantitative UTE MR Imaging of Myelin: Novel Biomarkers for Alzheimer's DiseaseR01AG075717 · NIA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Jiang Du · 2025 to 2026
$1.3M
Knee evaluation under mechanical loading by cones ultrashort echo time MR imagingK01AR080257 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI saeed jerban · 2022 to 2026
$602k
CSRD VA I01 CX001388CSRD VA I01 CX002211NIAMS NIH HHS K01 AR080257NIAMS NIH HHS R01 AR062581NIAMS NIH HHS R01 AR068987NIAMS NIH HHS R01 AR075825NIAMS NIH HHS R01 AR078877NIAMS NIH HHS R01 AR079484NIA NIH HHS R01 AG075717NIA NIH HHS RF1 AG075717RRD VA I01 RX002604
6 · The paper itself

Abstract

Background: Fat suppression plays a vital role in numerous magnetic resonance imaging (MRI) examinations, particularly in the musculoskeletal (MSK) system. However, current fat suppression methods are not fully optimized for ultrashort echo time (UTE) imaging, despite being essential for many advanced UTE-based imaging applications. This study aimed to investigate a novel fat suppression technique for UTE MRI using a single-point Dixon (1p-Dixon) approach through phase modeling. Methods: In this study, four cadaveric human knee joints, and six healthy volunteers were included. A 1p-Dixon-based fat suppression method was developed, which utilizes intrinsic information from complex UTE signals. Additionally, a data-driven approach based on the phase distribution was used for the decomposition of water and fat signals in short T2 tissues. The feasibility of the proposed method was evaluated in a fat-water phantom first and validated in Results: In the phantom experiment, there was a significant correlation between the estimated fat fraction and the actual fat fraction (R>0.98; P<0.05). The Conclusions: Our novel fat suppression technique has been shown to provide a fast, time-saving, and robust fat suppression for UTE imaging without the need for additional scans.

Indexed as

Dixonfat suppressionkneemusculoskeletal (MSK)Ultrashort echo time (UTE)

Identifiers

PMID40384724
PMCPMC12082590

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.