Evidence map›Paper›PMID 28000292›Full record

ArticleNMR in biomedicine2017

Microstructural models for diffusion MRI in breast cancer and surrounding stroma: an ex vivo study.

Colleen Bailey, Bernard Siow, Eleftheria Panagiotaki, John H Hipwell, Thomy Mertzanidou, Julie Owen, Patrycja Gazinska, Sarah E Pinder, Daniel C Alexander, David J Hawkes

Open access · hybridAbstract read
In one paragraph

Article in NMR in biomedicine, 2017. 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
2.8field-weighted citation impact, top 10% 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

17 citing papers in PubMed, 32 citations in OpenAlex.

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  5. Ex-vivo 1.5T MR Imaging versus CT in Estimating the Size of the Pathologically Invasive Component of Lung Adenocarcinoma Spectrum Lesions.Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024
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  15. Journal of medical imaging (Bellingham, Wash.) · 2017
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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 2 countries.

Colleen BaileyUniversity College London, Centre for Medical Image Computing, London, UK.
Bernard SiowUniversity College London, Centre for Advanced Biomedical Imaging, London, UK.
Eleftheria PanagiotakiUniversity College London, Centre for Medical Image Computing, London, UK.
John H HipwellUniversity College London, Centre for Medical Image Computing, London, UK.
Thomy MertzanidouUniversity College London, Centre for Medical Image Computing, London, UK.
Julie OwenKing's College London, Guy's Hospital, Breast Research, Pathology, London, UK.
Patrycja GazinskaKing's College London, Guy's Hospital, Breast Research, Pathology, London, UK.
Sarah E PinderKing's College London, Guy's Hospital, Breast Research, Pathology, London, UK.
Daniel C AlexanderUniversity College London, Centre for Medical Image Computing, London, UK.
David J HawkesUniversity College London, Centre for Medical Image Computing, London, UK.
University College London · GBBreast Cancer Now · GBKing's College London · GB

Funding

Cancer Research UK 16463
6 · The paper itself

Abstract

The diffusion signal in breast tissue has primarily been modelled using apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) and diffusion tensor (DT) models, which may be too simplistic to describe the underlying tissue microstructure. Formalin-fixed breast cancer samples were scanned using a wide range of gradient strengths, durations, separations and orientations. A variety of one- and two-compartment models were tested to determine which best described the data. Models with restricted diffusion components and anisotropy were selected in most cancerous regions and there were no regions in which conventional ADC or DT models were selected. Maps of ADC generally related to cellularity on histology, but maps of parameters from more complex models suggest that both overall cell volume fraction and individual cell size can contribute to the diffusion signal, affecting the specificity of ADC to the tissue microstructure. The areas of coherence in diffusion anisotropy images were small, approximately 1 mm, but the orientation corresponded to stromal orientation patterns on histology.

Indexed as

Models, BiologicalBreast NeoplasmsComputer SimulationConnective TissueDiffusion Tensor ImagingFemaleHumansImage Interpretation, Computer-AssistedMagnetic Resonance ImagingReproducibility of ResultsSensitivity and SpecificityTumor Cells, Culturedanisotropybreast cancerdiffusionDTIex vivoMRIrestriction

Identifiers

PMID28000292
PMCPMC5244665
OpenAlexW2563263983

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.