Evidence map›Paper›PMID 41150023›Full record

ArticleJournal of imaging2025

Effects of Motion in Ultrashort Echo Time Quantitative Susceptibility Mapping for Musculoskeletal Imaging.

Sam Sedaghat, Jinil Park, Eddie Fu, Fang Liu, Youngkyoo Jung, Hyungseok Jang

Abstract read
In one paragraph

Article in Journal of imaging, 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. Article
  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

6 authors.

Sam SedaghatDepartment of Diagnostic and Interventional Radiology, University Hospital Heidelberg, 69120 Heidelberg, Germany.ORCID 0000-0003-2804-3718
Jinil ParkDepartment of Radiology, University of California, Davis, Sacramento, CA 95817, USA.
Eddie FuDepartment of Radiology, University of California, Davis, Sacramento, CA 95817, USA.
Fang LiuAthinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Charlestown, MA 02129, USA.
Youngkyoo JungDepartment of Radiology, University of California, Davis, Sacramento, CA 95817, USA.
Hyungseok JangDepartment of Radiology, University of California, Davis, Sacramento, CA 95817, USA.ORCID 0000-0002-3597-9525

Funding

Ultrashort Echo Time Magnetic Resonance Imaging of Hemophilic ArthropathyR01AR078877 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JANG, HYUNGSEOK · 2021 to 2025
$2.4M
Deep Learning Technology for Rapid Morphological and Quantitative Imaging of Knee PathologyR01AR079442 · NIAMS · MASSACHUSETTS GENERAL HOSPITAL · PI Fang Liu · 2022 to 2026
$2.2M
Rapid Three-dimensional Simultaneous Knee Multi-Relaxation MappingR01AR081344 · NIAMS · MASSACHUSETTS GENERAL HOSPITAL · PI Fang Liu · 2022 to 2026
$2.0M
Deep Learning Reconstruction for Rapid Multi-Component RelaxometryR21EB031185 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI LIU, FANG · 2022 to 2024
$690k
Ultra-Fast High-Resolution Multi-Parametric MRI for Characterizing Cartilage Extracellular MatrixR56AR081017 · NIAMS · MASSACHUSETTS GENERAL HOSPITAL · PI LIU, FANG · 2023 to 2023
$643k
DFG SE 3272/1-1, SE 3272/6-1NIAMS NIH HHS R01 AR078877NIAMS NIH HHS R01 AR079442NIAMS NIH HHS R01 AR081344NIAMS NIH HHS R56 AR081017NIBIB NIH HHS R21 EB031185NIH HHS R01AR078877, R21EB031185, R01AR081344, R01AR079442, R56AR081017
6 · The paper itself

Abstract

Quantitative susceptibility mapping (QSM) is a powerful magnetic resonance imaging (MRI) technique for assessing tissue composition in the human body. For imaging short-T2 tissues in the musculoskeletal (MSK) system, ultrashort echo time (UTE) imaging plays a key role. However, UTE-based QSM (UTE-QSM) often involves repeated acquisitions, making it vulnerable to inter-scan motion. In this study, we investigate the effects of motion on UTE-QSM and introduce strategies to reduce motion-induced artifacts. Eight healthy male volunteers underwent UTE-QSM imaging of the knee joint, while an additional seven participated in imaging of the ankle joint. UTE-QSM was conducted using multiple echo acquisitions, including both UTE and gradient-recalled echoes, and processed using the iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) and morphology-enabled dipole inversion (MEDI) algorithms. To assess the impact of motion, datasets were reconstructed both with and without motion correction. Furthermore, we evaluated a two-step UTE-QSM approach that incorporates tissue boundary information. This method applies edge detection, excludes pixels near detected edges, and performs a two-step QSM reconstruction to reduce motion-induced streaking artifacts. In participants exhibiting substantial inter-scan motion, prominent streaking artifacts were evident. Applying motion registration markedly reduced these artifacts in both knee and ankle UTE-QSM. Additionally, the two-step UTE-QSM approach, which integrates tissue boundary information, further enhanced image quality by mitigating residual streaking artifacts. These results indicate that motion-induced errors near tissue boundaries play a key role in generating streaking artifacts in UTE-QSM. Inter-scan motion poses a fundamental challenge in UTE-QSM due to the need for multiple acquisitions. However, applying motion registration along with a two-step QSM approach that excludes tissue boundaries can effectively suppress motion-induced streaking artifacts, thereby improving the accuracy of musculoskeletal tissue characterization.

Indexed as

magnetic resonance imaging (MRI)motion artifactsmusculoskeletal (MSK) imagingquantitative susceptibility mapping (QSM)ultrashort echo time (UTE)

Identifiers

PMID41150023
PMCPMC12565248

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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.