Evidence map›Paper›PMID 30058079›Full record

ArticleMagnetic resonance in medicine2019

Rapid dynamic contrast-enhanced MRI for small animals at 7T using 3D ultra-short echo time and golden-angle radial sparse parallel MRI.

Jin Zhang, Li Feng, Ricardo Otazo, Sungheon Gene Kim

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. FastMagnetic resonance letters · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Review
  16. [Elimination of Gibbs artifact based on local subpixel shift and interlaced local variation].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2019
    Article
  17. Article
  18. Feasibility of measuring blood-brain barrier permeability using ultra-short echo time radial magnetic resonance imaging.Journal of neuroimaging : official journal of the American Society of Neuroimaging
    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

4 authors.

Jin ZhangCenter for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, New York.
Li FengCenter for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, New York.
Ricardo OtazoCenter for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, New York.
Sungheon Gene KimCenter for Biomedical Imaging (CBI), Center for Advanced Imaging Innovation and Research (CAI2R), Department of Radiology, New York University School of Medicine, New York, New York.

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Nicholas D Socci · 1985 to 2026
$347.4M
Vaccine FacilityP30CA016087 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ADRIANA HEGUY · 1985 to 2026
$83.1M
TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Hersh Chandarana · 2014 to 2026
$19.3M
DCE MRI Study for Breast Cancer.R01CA160620 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI KIM, SUNGHEON GENE · 2012 to 2023
$5.4M
NCI NIH HHS P30 CA008748NCI NIH HHS P30 CA016087NCI NIH HHS R01 CA160620NIBIB NIH HHS P41 EB017183NIH HHS 5P30CA016087NIH HHS P41EB017183NIH HHS R01CA160620
6 · The paper itself

Abstract

purposeTo develop a rapid dynamic contrast-enhanced MRI method with high spatial and temporal resolution for small-animal imaging at 7 Tesla.

methodsAn ultra-short echo time (UTE) pulse sequence using a 3D golden-angle radial sampling was implemented to achieve isotropic spatial resolution with flexible temporal resolution. Continuously acquired radial spokes were grouped into subsets for image reconstruction using a multicoil compressed sensing approach (Golden-angle RAdial Sparse Parallel; GRASP). The proposed 3D-UTE-GRASP method with high temporal and spatial resolutions was tested using 7 mice with GL261 intracranial glioma models.

resultsIterative reconstruction with different temporal resolutions and regularization factors λ showed that, in all cases, the cost function decreased to less than 2.5% of its starting value within 20 iterations. The difference between the time-intensity curves of 3D-UTE-GRASP and nonuniform fast Fourier transform (NUFFT) images was minimal when λ was 1% of the maximum signal intensity of the initial NUFFT images. The 3D isotropic images were used to generate pharmacokinetic parameter maps to show the detailed images of the tumor characteristics in 3D and also to show longitudinal changes during tumor growth.

conclusionThis feasibility study demonstrated that the proposed 3D-UTE-GRASP method can be used for effective measurement of the 3D spatial heterogeneity of tumor pharmacokinetic parameters.

Indexed as

Imaging, Three-DimensionalMagnetic Resonance ImagingAlgorithmsAnimalsBrain NeoplasmsCell Line, TumorContrast MediaData CompressionFeasibility StudiesImage EnhancementImage Interpretation, Computer-AssistedImage Processing, Computer-AssistedKineticsMiceMice, Inbred C57BLMicrocirculationContrast Media3D golden angle radial samplingcompressed sensingDCE-MRIGRASPparallel imagingUTE

Identifiers

PMID30058079
PMCPMC6258350

What OpenQuestion holds

Textmetadata
LicenceTDM
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.