Evidence map›Paper›PMID 33807205›Full record

ArticleCancers2021

Multidimensional Diffusion Magnetic Resonance Imaging for Characterization of Tissue Microstructure in Breast Cancer Patients: A Prospective Pilot Study.

Isaac Daimiel Naranjo, Alexis Reymbaut, Patrik Brynolfsson, Roberto Lo Gullo, Karin Bryskhe, Daniel Topgaard, Dilip D Giri, Jeffrey S Reiner, Sunitha B Thakur, Katja Pinker-Domenig

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2021. 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
5.1field-weighted citation impact, top 4% 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

18 citing papers in PubMed, 42 citations in OpenAlex.

  1. Article
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  10. bioRxiv : the preprint server for biology · 2023
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  14. Nonparametric 5D D-RJournal of magnetic resonance (San Diego, Calif. : 1997) · 2022
    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

10 authors at 3 institutions in 3 countries.

Isaac Daimiel NaranjoMemorial Sloan Kettering Cancer Center, Department of Radiology, Breast Imaging Service, 300 E 66th Street, New York, NY 10065, USA.ORCID 0000-0002-4878-1710
Alexis ReymbautRandom Walk Imaging AB, SE-22002 Lund, Sweden.ORCID 0000-0002-2167-5483
Patrik BrynolfssonRandom Walk Imaging AB, SE-22002 Lund, Sweden.
Roberto Lo GulloMemorial Sloan Kettering Cancer Center, Department of Radiology, Breast Imaging Service, 300 E 66th Street, New York, NY 10065, USA.
Karin BryskheRandom Walk Imaging AB, SE-22002 Lund, Sweden.
Daniel TopgaardDepartment of Chemistry, Lund University, SE-22100 Lund, Sweden.ORCID 0000-0001-9373-6348
Dilip D GiriMemorial Sloan Kettering Cancer Center, Department of Pathology, 1275 York Ave, New York, NY 10065, USA.
Jeffrey S ReinerMemorial Sloan Kettering Cancer Center, Department of Radiology, Breast Imaging Service, 300 E 66th Street, New York, NY 10065, USA.
Sunitha B ThakurMemorial Sloan Kettering Cancer Center, Department of Radiology, Breast Imaging Service, 300 E 66th Street, New York, NY 10065, USA.ORCID 0000-0001-8090-3696
Katja Pinker-DomenigMemorial Sloan Kettering Cancer Center, Department of Radiology, Breast Imaging Service, 300 E 66th Street, New York, NY 10065, USA.ORCID 0000-0002-2722-7331
Memorial Sloan Kettering Cancer Center · USRandom Walk Imaging · SELund University · SE

Funding

X-RAY CRYSTALLOGRAPHYP30CA008748 · NCI · SLOAN-KETTERING INSTITUTE FOR CANCER RES · PI Hongbiao Carl Lekaye · 1985 to 2026
$347.4M
Breast Cancer Research Foundation NAFundación Alfonso Martín Escudero NANCI NIH HHS P30 CA008748NIH HHS P30 CA008748Susan G. Komen NA
6 · The paper itself

Abstract

Diffusion-weighted imaging is a non-invasive functional imaging modality for breast tumor characterization through apparent diffusion coefficients. Yet, it has so far been unable to intuitively inform on tissue microstructure. In this IRB-approved prospective study, we applied novel multidimensional diffusion (MDD) encoding across 16 patients with suspected breast cancer to evaluate its potential for tissue characterization in the clinical setting. Data acquired via custom MDD sequences was processed using an algorithm estimating non-parametric diffusion tensor distributions. The statistical descriptors of these distributions allow us to quantify tissue composition in terms of metrics informing on cell densities, shapes, and orientations. Additionally, signal fractions from specific cell types, such as elongated cells (bin1), isotropic cells (bin2), and free water (bin3), were teased apart. Histogram analysis in cancers and healthy breast tissue showed that cancers exhibited lower mean values of "size" (1.43 ± 0.54 × 10

Indexed as

breast cancerdiffusion-weighted imagingmagnetic resonance imagingmultidimensional diffusion MRIoscillating gradients

Identifiers

PMID33807205
PMCPMC8037718
OpenAlexW3143013739

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.