Evidence map›Paper›PMID 36236557›Full record

ArticleSensors (Basel, Switzerland)2022

Accelerated Quantitative 3D UTE-Cones Imaging Using Compressed Sensing.

Jiyo S Athertya, Yajun Ma, Amir Masoud Afsahi, Alecio F Lombardi, Dina Moazamian, Saeed Jerban, Sam Sedaghat, Hyungseok Jang

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.2field-weighted citation impact, top 8% 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

19 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Fast 3D UTE in vivo TMagnetic resonance in medicine · 2026
    Article
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  6. Brain short TNeuroImage · 2025
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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 1 institution in 1 country.

Jiyo S AthertyaDepartment of Radiology, University of California, San Diego, CA 92103, USA.ORCID 0000-0002-0866-1052
Yajun MaDepartment of Radiology, University of California, San Diego, CA 92103, USA.
Amir Masoud AfsahiDepartment of Radiology, University of California, San Diego, CA 92103, USA.ORCID 0000-0002-8906-7767
Alecio F LombardiDepartment of Radiology, University of California, San Diego, CA 92103, USA.ORCID 0000-0002-6820-1779
Dina MoazamianDepartment of Radiology, University of California, San Diego, CA 92103, USA.
Saeed JerbanDepartment of Radiology, University of California, San Diego, CA 92103, USA.
Sam SedaghatDepartment of Radiology, University of California, San Diego, CA 92103, USA.
Hyungseok JangDepartment of Radiology, University of California, San Diego, CA 92103, USA.
University of California San Diego · US

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 Hemophilic ArthropathyR01AR078877 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI JANG, HYUNGSEOK · 2021 to 2025
$2.4M
Three-Dimensional UTE Magnetic Resonance Imaging of the Osteochondral JunctionR21AR075851 · NIAMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MA, YAJUN · 2020 to 2021
$376k
Developing MRI Biomarkers of Myelin and Iron in Veterans with Traumatic Brain InjuryI01CX002211 · VA · VA SAN DIEGO HEALTHCARE SYSTEM · PI Jiang Du · 2021 to 2026
–
CSRD VA I01 CX002211NIAMS NIH HHS R01 AR062581NIAMS NIH HHS R01 AR068987NIAMS NIH HHS R01 AR078877NIAMS NIH HHS R21 AR075851NIH HHS R01AR062581, R01AR068987, R01AR075825, R01AR078877, and R21AR075851
6 · The paper itself

Abstract

In this study, the feasibility of accelerated quantitative Ultrashort Echo Time Cones (qUTE-Cones) imaging with compressed sensing (CS) reconstruction is investigated. qUTE-Cones sequences for variable flip angle-based UTE T1 mapping, UTE adiabatic T1ρ mapping, and UTE quantitative magnetization transfer modeling of macromolecular fraction (MMF) were implemented on a clinical 3T MR system. Twenty healthy volunteers were recruited and underwent whole-knee MRI using qUTE-Cones sequences. The k-space data were retrospectively undersampled with different undersampling rates. The undersampled qUTE-Cones data were reconstructed using both zero-filling and CS reconstruction. Using CS-reconstructed UTE images, various parameters were estimated in 10 different regions of interests (ROIs) in tendons, ligaments, menisci, and cartilage. Structural similarity, percentage error, and Pearson’s correlation were calculated to assess the performance. Dramatically reduced streaking artifacts and improved SSIM were observed in UTE images from CS reconstruction. A mean SSIM of ~0.90 was achieved for all CS-reconstructed images. Percentage errors between fully sampled and undersampled CS-reconstructed images were below 5% for up to 50% undersampling (i.e., 2× acceleration). High linear correlation was observed (>0.95) for all qUTE parameters estimated in all subjects. CS-based reconstruction combined with efficient Cones trajectory is expected to achieve a clinically feasible scan time for qUTE imaging.

Indexed as

Imaging, Three-DimensionalMagnetic Resonance ImagingHumansRetrospective StudiesTendonscompressed sensingimage reconstructionquantitative MRIUTE

Identifiers

PMID36236557
PMCPMC9573555
OpenAlexW4303980541

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.