Evidence map›Paper›PMID 29315083›Full record

ArticleInvestigative radiology2018

CAPTURE: Consistently Acquired Projections for Tuned and Robust Estimation: A Self-Navigated Respiratory Motion Correction Approach.

Cihat Eldeniz, Tyler Fraum, Amber Salter, Yasheng Chen, H Michael Gach, Parag J Parikh, Kathryn J Fowler, Hongyu An

Abstract read
In one paragraph

Article in Investigative radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.1field-weighted citation impact, top 23% 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

5 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Real-time BMedical physics · 2022
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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.

Cihat Eldeniz
Tyler Fraum
Amber Salter
Yasheng Chen
H Michael Gach
Parag J Parikh
Kathryn J Fowler
Hongyu An
Mallinckrodt (United States) · US

Funding

Rapid, robust and non-invasive cerebral oxygenation measurements using MRIR01NS082561 · NINDS · WASHINGTON UNIVERSITY · PI AN, HONGYU · 2014 to 2018
$2.8M
NINDS CENTER CORE FOR BRAIN IMAGINGP30NS098577 · NINDS · WASHINGTON UNIVERSITY · PI HERSHEY, TAMARA G, MARCUS, DANIEL SCOTT · 2016 to 2019
$2.4M
Free-Breathing Perfusion MRI of the Abdomen with Predictive Motion CorrectionR01CA159471 · NCI · WASHINGTON UNIVERSITY · PI GACH, H MICHAEL · 2011 to 2015
$913k
NCI NIH HHS R01 CA159471NINDS NIH HHS P30 NS098577NINDS NIH HHS R01 NS082561
6 · The paper itself

Abstract

objectivesIn this study, we present a fully automated and robust self-navigated approach to obtain 4-dimensional (4-D) motion-resolved images during free breathing. MATERIALS AND

methodsThe proposed method, Consistently Acquired Projections for Tuned and Robust Estimation (CAPTURE), is a variant of the stack-of-stars gradient-echo sequence. A 1-D navigator was consistently acquired at a fixed azimuthal angle for all stacks of spokes to reduce nonphysiological signal contamination due to system imperfections. The resulting projections were then "tuned" using complex phase rotation to adapt to scan-to-scan variations, followed by the detection of the respiratory curve. Four-dimensional motion-corrected and uncorrected images were then reconstructed via respiratory and temporal binning, respectively.This Health Insurance Portability and Accountability Act-compliant study was performed with Institutional Review Board approval. A phantom experiment was performed using a custom-made deformable motion phantom with an adjustable frequency and amplitude. For in vivo experiments, 10 healthy participants and 12 liver tumor patients provided informed consent and were imaged with the CAPTURE sequence.Two radiologists, blinded to which images were motion-corrected and which were not, independently reviewed the images and scored the image quality using a 5-point Likert scale.

resultsIn the respiratory motion phantom experiment, CAPTURE reversed the effects of motion blurring and restored edge sharpness from 36% to 78% of that observed in the images from the static scan.Despite large intra- and intersubject variability in respiration patterns, CAPTURE successfully detected the respiratory motion signal in all participants and significantly improved the image quality according to the subjective radiological assessments of 2 raters (P < 0.05 for both raters) with a 1 to 2-point improvement in the median Likert scores across the whole set of participants. Small lesions (<1 cm in size) which might otherwise be missed on uncorrected images because of motion blurring were more clearly depicted on the CAPTURE images.

conclusionsCAPTURE provides a robust and fully automated solution for obtaining 4-D motion-resolved images in a free-breathing setting. With its unique tuning feature, CAPTURE can adapt to large intersubject and interscan variations. CAPTURE also enables better lesion delineation because of improved image sharpness, thereby increasing the visibility of small lesions.

Indexed as

RespirationAdultAgedFemaleHumansImage Processing, Computer-AssistedImaging, Three-DimensionalLiverLiver NeoplasmsMagnetic Resonance ImagingMaleMiddle AgedMotionPhantoms, ImagingYoung Adult

Identifiers

PMID29315083
PMCPMC5882511
OpenAlexW2784108798

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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.