Evidence map›Paper›PMID 27532028›Full record

ArticleFrontiers in oncology2016

Demonstration of Non-Gaussian Restricted Diffusion in Tumor Cells Using Diffusion Time-Dependent Diffusion-Weighted Magnetic Resonance Imaging Contrast.

Tuva R Hope, Nathan S White, Joshua Kuperman, Ying Chao, Ghiam Yamin, Hauke Bartch, Natalie M Schenker-Ahmed, Rebecca Rakow-Penner, Robert Bussell, Natsuko Nomura and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in oncology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing 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

17 citing papers in PubMed.

  1. Review
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  5. Multimodal apparent diffusion MRI model in noninvasive evaluation of breast cancer and Ki-67 expression.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024
    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

13 authors.

Tuva R HopeThe Interventional Centre, Oslo University Hospital, Oslo, Norway; Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway.
Nathan S WhiteDepartment of Radiology, University of California San Diego , La Jolla, CA , USA.
Joshua KupermanDepartment of Radiology, University of California San Diego , La Jolla, CA , USA.
Ying ChaoDepartment of Neurosciences, University of California San Diego , La Jolla, CA , USA.
Ghiam YaminDepartment of Radiology, University of California San Diego , La Jolla, CA , USA.
Hauke BartchDepartment of Radiology, University of California San Diego , La Jolla, CA , USA.
Natalie M Schenker-AhmedDepartment of Radiology, University of California San Diego , La Jolla, CA , USA.
Rebecca Rakow-PennerDepartment of Radiology, University of California San Diego , La Jolla, CA , USA.
Robert BussellDepartment of Radiology, University of California San Diego , La Jolla, CA , USA.
Natsuko NomuraDepartment of Neurosciences, University of California San Diego , La Jolla, CA , USA.
Santosh KesariDepartment of Neurosciences, University of California San Diego , La Jolla, CA , USA.
Atle BjørnerudThe Interventional Centre, Oslo University Hospital, Oslo, Norway; Department of Physics, University of Oslo, Oslo, Norway.
Anders M DaleDepartment of Radiology, University of California San Diego, La Jolla, CA, USA; Department of Neurosciences, University of California San Diego, La Jolla, CA, USA.

Funding

U of Calif, San Diego Neuroscience Microscopy ImagingP30NS047101 · NINDS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI GLEESON, JOSEPH G, ZHENG, BINHAI · 2003 to 2022
$9.0M
Traning Clinical Scientists in Radiological ImagingT32EB005970 · NIBIB · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Eric Y Chang, Rebecca Ann Rakow-Penner · 2007 to 2026
$3.2M
NIBIB NIH HHS T32 EB005970NINDS NIH HHS P30 NS047101
6 · The paper itself

Abstract

The diffusion-weighted magnetic resonance imaging (DWI) technique enables quantification of water mobility for probing microstructural properties of biological tissue and has become an effective tool for collecting information about the underlying pathology of cancerous tissue. Measurements using multiple b-values have indicated biexponential signal attenuation, ascribed to "fast" (high ADC) and "slow" (low ADC) diffusion components. In this empirical study, we investigate the properties of the diffusion time (Δ)-dependent components of the diffusion-weighted (DW) signal in a constant b-value experiment. A xenograft gliobastoma mouse was imaged using Δ = 11 ms, 20 ms, 40 ms, 60 ms, and b = 500-4000 s/mm(2) in intervals of 500 s/mm(2). Data were corrected for EPI distortions, and the Δ-dependence on the DW-signal was measured within three regions of interest [intermediate- and high-density tumor regions and normal-appearing brain (NAB) tissue regions]. In this study, we verify the assumption that the slow decaying component of the DW-signal is non-Gaussian and dependent on Δ, consistent with restricted diffusion of the intracellular space. As the DW-signal is a function of Δ and is specific to restricted diffusion, manipulating Δ at constant b-value (cb) provides a complementary and direct approach for separating the restricted from the hindered diffusion component. We found that Δ-dependence is specific to the tumor tissue signal. Based on an extended biexponential model, we verified the interpretation of the diffusion time-dependent contrast and successfully estimated the intracellular restricted ADC, signal volume fraction, and cell size within each ROI.

Indexed as

cancerdiffusion time-dependenceDWIglioblastoma multiformeMRIrestricted diffusionxenograft tumor model

Identifiers

PMID27532028
PMCPMC4970563

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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.