Evidence map›Paper›PMID 42175722›Full record

ArticleJournal of magnetic resonance imaging : JMRI2026

Comparison of Retrospective Motion Compensation Techniques for Pulmonary Dynamic Ultrashort Time to Echo MRI in Suspected Idiopathic Pulmonary Fibrosis.

Abhilash S Kizhakke Puliyakote, Luis A Torres, Aiah AlAtoum, Natally AlArab, Kevin M Johnson, Rodrigo M Bello, Bryan O'Sullivan-Murphy, Joseph G Mammarappallil, Andrew D Hahn, Sean B Fain

Abstract readComparative Study
In one paragraph

Article in Journal of magnetic resonance imaging : JMRI, 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

10 authors.

Abhilash S Kizhakke PuliyakoteDepartment of Radiology, University of Iowa HealthCare, Iowa City, Iowa, USA.ORCID https://orcid.org/0000-0003-4541-0786
Luis A TorresDepartment of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0003-1948-3500
Aiah AlAtoumRoy J. Carver Department of Biomedical Engineering, University of Iowa, Iowa City, Iowa, USA.
Natally AlArabDepartment of Radiology, University of Iowa HealthCare, Iowa City, Iowa, USA.
Kevin M JohnsonDepartment of Medical Physics, University of Wisconsin-Madison, Madison, Wisconsin, USA.ORCID https://orcid.org/0000-0002-8660-0853
Rodrigo M BelloDepartment of Radiology, University of Iowa HealthCare, Iowa City, Iowa, USA.
Bryan O'Sullivan-MurphyDepartment of Radiology, Duke University School of Medicine, Durham, North Carolina, USA.ORCID https://orcid.org/0000-0002-1426-5013
Joseph G MammarappallilDepartment of Radiology, Duke University School of Medicine, Durham, North Carolina, USA.
Andrew D HahnDepartment of Radiology, University of Iowa HealthCare, Iowa City, Iowa, USA.ORCID https://orcid.org/0000-0002-0246-2108
Sean B FainDepartment of Radiology, University of Iowa HealthCare, Iowa City, Iowa, USA.ORCID https://orcid.org/0000-0001-5461-0646

Funding

Institutional Clinical and Translational Science AwardUL1TR000427 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2012 to 2016
$32.2M
University of Iowa Institute for Clinical and Translational ScienceUM1TR004403 · NCATS · UNIVERSITY OF IOWA · PI Marlan R Hansen, Patricia Winokur · 2023 to 2026
$16.1M
Using MRI To Visualize Regional Therapy Response In Idiopathic Pulmonary FibrosisR01HL126771 · NHLBI · DUKE UNIVERSITY · PI Bastiaan Driehuys · 2015 to 2026
$6.6M
MANIPULATING IKS AS A THERAPEUTIC APPROACH TO CARDIAC ARRHYTHMIASR01HL126774 · NHLBI · WASHINGTON UNIVERSITY · PI CUI, JIANMIN · 2015 to 2018
$3.1M
Dynamic Imaging of Lung Ventilation and Perfusion Using CT and MRIR01HL169765 · NHLBI · UNIVERSITY OF IOWA · PI Sean Bedilion Fain · 2023 to 2026
$2.9M
MRI methods for high resolution imaging of the lungR01HL136965 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI JOHNSON, KEVIN MICHAEL, LARSON, PEDER ERIC ZUFALL · 2018 to 2021
$2.7M
University of Iowa - Research 3T MRI Connectome UpgradeS10OD025025 · OD · UNIVERSITY OF IOWA · PI MAGNOTTA, VINCENT A · 2018 to 2018
$1.9M
NCATS NIH HHS UL1 TR000427NCATS NIH HHS UM1 TR004403NHLBI NIH HHS HL126771NHLBI NIH HHS HL126774NHLBI NIH HHS HL136965NHLBI NIH HHS HL169765NHLBI NIH HHS R01 HL126771NHLBI NIH HHS R01 HL126774NHLBI NIH HHS R01 HL136965NHLBI NIH HHS R01 HL169765NIH HHS S10 OD025025NIH HHS UL1TR000427NIH HHS UM1TR004403NIH/NCATS S10OD025025
6 · The paper itself

Abstract

backgroundMotion can degrade image quality during Ultrashort Time-to-Echo (UTE) pulmonary MRI and is particularly prevalent in patients with lung disease. Comprehensive assessment of the impact of motion compensation techniques on image quality and clinical interpretation is needed. PURPOSE/HYPOTHESIS: To compare the impact of retrospective motion compensation schemes on image quality and clinical interpretation of pulmonary UTE MRI in idiopathic pulmonary fibrosis (IPF). STUDY TYPE: Prospective. POPULATION: 21 (male = 18; mean age, 69.9 ± 8.1 years) participants with suspected IPF. FIELD STRENGTH/SEQUENCE: 1.5 T/3 T, 3D center-out radial (gradient-echo) UTE sequence with 2× radial oversampling, while free-breathing. ASSESSMENT: Images were reconstructed to 1.25 mm isotropic resolution using five retrospective schemes: no gating, hard-gating, soft-gating, motion-resolved (XD-GRASP), and an iterative approach (iMoCo). Signal-to-noise ratios (SNR) were estimated within the lung parenchyma, airways, aorta, muscles, and liver. Contrast-to-noise ratios (CNR) were estimated using the mean airway signal as reference. Image sharpness was estimated using the maximum derivative of a line profile across the diaphragm and a wavelet-based autofocus measure. Three radiologists evaluated image quality, motion artifacts on a 5-point Likert scale, and diagnostic classification of usual interstitial pneumonia (UIP). STATISTICAL TESTS: The Kruskal-Wallis non-parametric test was used for qualitative reader scores and one-way ANOVA for the quantitative metrics, with p < 0.05 as the threshold for significance.

resultsCNR was highest using the iMoCo reconstructions (lung parenchyma: 1.64 ± 1.41 vs. 0.88 ± 0.81 via XD-GRASP). Image sharpness was significantly improved using compressed sensing (CS)-based techniques (XD-GRASP and iMoCo), compared to the other methods, using both diaphragm profile (CS: 6.28 ± 3.70 vs. non-CS: 3.73 ± 2.06) and wavelet metrics (CS: 2.33 ± 0.42 vs. non-CS: 2.05 ± 0.35). CS methods also demonstrated greatest image quality based on reader scores.

conclusionMotion compensation using compressed sensing methods can improve image quality and clinical utility of UTE-MRI in the identification and diagnostic classification of typical parenchymal fibrotic patterns. EVIDENCE LEVEL: Level 2-Prospective study, with a reference standard determined during the course of the study (CT imaging). TECHNICAL EFFICACY: Stage 1.

Indexed as

Idiopathic Pulmonary FibrosisImage Processing, Computer-AssistedLungMagnetic Resonance ImagingAgedAlgorithmsArtifactsFemaleHumansImage Interpretation, Computer-AssistedMaleMiddle AgedMotionProspective StudiesReproducibility of ResultsRespirationfree‐breathingIPFpulmonary MRIrespiratory motion compensationretrospective gatingUTE‐MRI

Identifiers

PMID42175722
PMCPMC13466589

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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.