Evidence map›Paper›PMID 29021531›Full record

ArticleScientific reports2017

Correlation of X-ray diffraction signatures of breast tissue and their histopathological classification.

Robert M Moss, Amany S Amin, Chiaki Crews, Colin A Purdie, Lee B Jordan, Francesco Iacoviello, Andrew Evans, Robert D Speller, Sarah J Vinnicombe

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

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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.

Robert M MossDepartment of Medical Physics and Biomedical Engineering, University College London, Gower Street, London, WC1E 6BT, UK. robert.moss@ucl.ac.uk.
Amany S AminRoyal London Hospital, Barts Health NHS Trust, Whitechapel Road, London, E1 1BB, UK.
Chiaki CrewsDepartment of Medical Physics and Biomedical Engineering, University College London, Gower Street, London, WC1E 6BT, UK.
Colin A PurdieNHS Tayside Pathology Department, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK.
Lee B JordanNHS Tayside Pathology Department, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK.
Francesco IacovielloDepartment of Chemical Engineering, University College London, Gower Street, London, WC1E 6BT, UK.ORCID 0000-0003-3564-2380
Andrew EvansDivision of Cancer Research, University of Dundee, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK.
Robert D SpellerDepartment of Medical Physics and Biomedical Engineering, University College London, Gower Street, London, WC1E 6BT, UK.
Sarah J VinnicombeDivision of Cancer Research, University of Dundee, Ninewells Hospital and Medical School, Dundee, DD1 9SY, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This pilot study examines the correlation of X-ray diffraction (XRD) measurements with the histopathological analysis of breast tissue. Eight breast cancer samples were investigated. Each sample contained a mixture of normal and cancerous tissues. In total, 522 separate XRD measurements were made at different locations across the samples (8 in total). The resulting XRD spectra were subjected to principal component analysis (PCA) in order to determine if there were any distinguishing features that could be used to identify different tissue components. 99.0% of the variation between the spectra were described by the first two principal components (PC). Comparing the location of points in PC space with the classification determined by histopathology indicated correlation between the shape/magnitude of the XRD spectra and the tissue type. These results are encouraging and suggest that XRD could be used for the intraoperative or postoperative classification of bulk tissue samples.

Indexed as

BreastFemaleHumansPrincipal Component AnalysisX-Ray DiffractionX-Ray Microtomography

Identifiers

PMID29021531
PMCPMC5636903

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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.