Evidence map›Paper›PMID 28368658›Full record

ReviewThe British journal of radiology2017

Early clinical applications for imaging at microscopic detail: microfocus computed tomography (micro-CT).

J Ciaran Hutchinson, Susan C Shelmerdine, Ian C Simcock, Neil J Sebire, Owen J Arthurs

Open access · hybridAbstract readReview
In one paragraph

Review in The British journal of radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
5.6field-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

31 citing papers in PubMed, 78 citations in OpenAlex.

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  7. The State of High-Resolution Imaging of the Human Inner Ear: A Look Into the Black Box.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
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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

5 authors at 1 institution in 1 country.

J Ciaran Hutchinson1 Department of Histopathology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.
Susan C Shelmerdine2 UCL Great Ormond Street Institute of Child Health, London, UK.
Ian C Simcock2 UCL Great Ormond Street Institute of Child Health, London, UK.
Neil J Sebire1 Department of Histopathology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK.
Owen J Arthurs2 UCL Great Ormond Street Institute of Child Health, London, UK.ORCID http://orcid.org/0000-0003-1213-3516
Great Ormond Street Hospital · GB

Funding

Department of Health NIHR-CS-012-002Medical Research Council MR/R002118/1
6 · The paper itself

Abstract

Microfocus CT (micro-CT) has traditionally been used in industry and preclinical studies, although it may find new applicability in the routine clinical setting. It can provide high-resolution three-dimensional digital imaging data sets to the same level of detail as microscopic examination without the need for tissue dissection. Micro-CT is already enabling non-invasive detailed internal assessment of various tissue specimens, particularly in breast imaging and early gestational fetal autopsy, not previously possible from more conventional modalities such as MRI or CT. In this review, we discuss the technical aspects behind micro-CT image acquisition, how early work with small animal studies have informed our knowledge of human disease and the imaging performed so far on human tissue specimens. We conclude with potential future clinical applications of this novel and emerging technique.

Indexed as

AnimalsAutopsyContrast MediaForensic MedicineHumansImaging, Three-DimensionalSensitivity and SpecificityX-Ray MicrotomographyContrast Media

Identifiers

PMID28368658
PMCPMC5594989
OpenAlexW2604221705

What OpenQuestion holds

Textmetadata
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.