Evidence map›Paper›PMID 36924807›Full record

ArticleMagnetic resonance imaging2023

Characterization of motion dependent magnetic field inhomogeneity for DWI in the kidneys.

Nima Gilani, Artem Mikheev, Inge M Brinkmann, Dibash Basukala, Thomas Benkert, Malika Kumbella, James S Babb, Hersh Chandarana, Eric E Sigmund

Open access · greenAbstract read
In one paragraph

Article in Magnetic resonance imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.7field-weighted citation impact, top 7% 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

14 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Motion Mitigation Techniques for Abdominal and Cardiac MR Imaging.Journal of magnetic resonance imaging : JMRI · 2026
    Review
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  10. Development of modified multi-parametric CT algorithms for diagnosing clear-cell renal cell carcinoma in small solid renal masses.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025
    Article
  11. Review
  12. Article
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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

9 authors at 1 institution in 1 country.

Nima GilaniCenter for Advanced Imaging and Innovation (CAI(2)R), Center for Biomedical Imaging, Department of Radiology, NYU Langone Health, New York, USA. Electronic address: nima.gilani@nyulangone.org.
Artem MikheevCenter for Advanced Imaging and Innovation (CAI(2)R), Center for Biomedical Imaging, Department of Radiology, NYU Langone Health, New York, USA.
Inge M BrinkmannSiemens Medical Solutions USA Inc., Malvern, PA, USA.
Dibash BasukalaCenter for Advanced Imaging and Innovation (CAI(2)R), Center for Biomedical Imaging, Department of Radiology, NYU Langone Health, New York, USA.
Thomas BenkertSiemens Healthcare GmbH, Erlangen, Germany.
Malika KumbellaCenter for Advanced Imaging and Innovation (CAI(2)R), Center for Biomedical Imaging, Department of Radiology, NYU Langone Health, New York, USA.
James S BabbCenter for Advanced Imaging and Innovation (CAI(2)R), Center for Biomedical Imaging, Department of Radiology, NYU Langone Health, New York, USA.
Hersh ChandaranaCenter for Advanced Imaging and Innovation (CAI(2)R), Center for Biomedical Imaging, Department of Radiology, NYU Langone Health, New York, USA.
Eric E SigmundCenter for Advanced Imaging and Innovation (CAI(2)R), Center for Biomedical Imaging, Department of Radiology, NYU Langone Health, New York, USA. Electronic address: Eric.Sigmund@nyulangone.org.
Siemens Healthcare (Germany) · DE

Funding

TR&D 4: Revealing Microstructure: Biophysical modeling and validation for discovery and clinical careP41EB017183 · NIBIB · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI Daniel K Sodickson · 2014 to 2026
$19.3M
Advanced Diffusion Imaging for Management of Renal Cancer: Oncologic Control and Renal Functional Reserve - Resubmission - 1R01CA245671 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI CHANDARANA, HERSH, SIGMUND, ERIC EDWARD · 2020 to 2025
$3.0M
NCI NIH HHS R01 CA245671NIBIB NIH HHS P41 EB017183
6 · The paper itself

Abstract

purposeDiffusion-weighted imaging (DWI) of the abdomen has increased dramatically for both research and clinical purposes. Motion and static field inhomogeneity related challenges limit image quality of abdominopelvic imaging with the most conventional echo-planar imaging (EPI) pulse sequence. While reversed phase encoded imaging is increasingly used to facilitate distortion correction, it typically assumes one motion independent magnetic field distribution. In this study, we describe a more generalized workflow for the case of kidney DWI in which the field inhomogeneity at multiple respiratory phases is mapped and used to correct all images in a multi-contrast DWI series.

methodsIn this HIPAA-compliant and IRB-approved prospective study, 8 volunteers (6 M, ages 28-51) had abdominal imaging performed in a 3 T MRI system (MAGNETOM Prisma; Siemens Healthcare, Erlangen, Germany) with ECG gating. Coronal oblique T2-weighted HASTE images were collected for anatomical reference. Sagittal phase-contrast (PC) MRI images through the left renal artery were collected to determine systolic and diastolic phases. Cardiac triggered oblique coronal DWI were collected at 10 b-values between 0 and 800 s/mm2 and 12 directions. DWI series were distortion corrected using field maps generated by forward and reversed phase encoded b = 0 images collected over the full respiratory cycle and matched by respiratory phase. Morphologic accuracy, intraseries spatial variability, and diffusion tensor imaging (DTI) metrics mean diffusivity (MD) and fractional anisotropy (FA) were compared for results generated with no distortion correction, correction with only one respiratory bin, and correction with multiple respiratory bins across the breathing cycle.

resultsComputed field maps showed significant variation in static field with kidney laterality, region, and respiratory phase. Distortion corrected images showed significantly better registration to morphologic images than uncorrected images; for the left kidney, the multiple bin correction outperformed one bin correction. Line profile analysis showed significantly reduced spatial variation with multiple bins than one bin correction. DTI metrics were mostly similar between correction methods, with some differences observed in MD between uncorrected and corrected datasets.

conclusionsOur results indicate improved morphology of kidney DWI and derived parametric maps as well as reduced variability over the full image series using the motion-resolved distortion correction. This work highlights some morphologic and quantitative metric improvements can be obtained for kidney DWI when distortion correction is performed in a respiratory-resolved manner.

Indexed as

Diffusion Magnetic Resonance ImagingDiffusion Tensor ImagingAdultEcho-Planar ImagingHumansKidneyMagnetic Resonance ImagingMiddle AgedMotionProspective StudiesDistortion correctionDTIDWIKidneyMagnetic field inhomogeneityMotion correctionRenal

Identifiers

PMID36924807
PMCPMC10108090
OpenAlexW4324195433

What OpenQuestion holds

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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.