Evidence map›Paper›PMID 41505274›Full record

ArticleMagnetic resonance in medicine2026

Strong-Gradient Diffusion-Weighted Imaging of Prostate Cancer Using an Inside-Out Nonlinear Gradient Coil.

Horace Z Zhang, Nahla M H Elsaid, Terence W Nixon, Andrew Dewdney, Dana C Peters, Jeffrey C Weinreb, Preston C Sprenkle, R Todd Constable, Gigi Galiana

Abstract read
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In one paragraph

Article in Magnetic resonance in medicine, 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

9 authors.

Horace Z ZhangDepartment of Biomedical Engineering, Yale University, New Haven, Connecticut, USA.ORCID 0009-0001-1416-2380
Nahla M H ElsaidDepartment of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut, USA.
Terence W NixonDepartment of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut, USA.
Andrew DewdneySiemens Healthineers AG, Erlangen, Germany.
Dana C PetersDepartment of Biomedical Engineering, Yale University, New Haven, Connecticut, USA.ORCID 0000-0001-7556-4642
Jeffrey C WeinrebDepartment of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut, USA.
Preston C SprenkleDepartment of Urology, Yale University, New Haven, Connecticut, USA.
R Todd ConstableDepartment of Biomedical Engineering, Yale University, New Haven, Connecticut, USA.
Gigi GalianaDepartment of Biomedical Engineering, Yale University, New Haven, Connecticut, USA.

Funding

NIH HHS CA264851
6 · The paper itself

Abstract

purposeTo demonstrate improved image quality and lesion conspicuity in prostate diffusion-weighted imaging (DWI) using an inside-out nonlinear gradient coil that provides locally strong gradients (200-500 500 mT/m) at typical prostate positions. THEORY AND

methodsBefore applying the nonlinear gradient coil to DWI with Echo Planar Imaging (EPI) readout, we investigated geometric distortion and eddy currents, and proposed necessary corrections. We then developed two DWI protocols (b

resultsCorrections effectively reduced nonlinear-gradient DWI artifacts. ADC maps from linear- and nonlinear-gradient-encoded studies agreed well, with a normalized root-mean-square-error of ∼10%, a common level of ADC variation. TE was significantly reduced from 57 to 42-47 ms for moderate b-values (≤ 1000 s/mm

conclusionThe inside-out nonlinear gradient coil enhances prostate DWI.

Indexed as

Diffusion Magnetic Resonance ImagingProstatic NeoplasmsEquipment DesignHumansImage EnhancementMaleReproducibility of ResultsSensitivity and SpecificitySignal-To-Noise Ratiodiffusion MRIgradientprostate

Identifiers

PMID41505274
PMCPMC12962214

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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.