Evidence map›Paper›PMID 25605346›Full record

ArticleThe British journal of radiology2015

Model-based vs hybrid iterative reconstruction technique in ultralow-dose submillisievert CT colonography.

L Lambert, P Ourednicek, J Jahoda, A Lambertova, J Danes

Abstract readComparative Study
In one paragraph

Article in The British journal of radiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Impact of CT reconstruction algorithm on auto-segmentation performance.Journal of applied clinical medical physics · 2019
    Article
  4. Article
  5. Article
  6. Computed Tomography Colonography Phantom: Construction, Validation and Literature Review.Iranian journal of radiology : a quarterly journal published by the Iranian Radiological Society · 2016
    Article
  7. Article
  8. Article
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.

L Lambert1 Department of Radiology, First Faculty of Medicine of Charles University in Prague, Prague, Czech Republic.
P Ourednicek
J Jahoda
A Lambertova
J Danes

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo compare image quality of different reconstruction techniques in submillisievert ultralow-dose CT colonography (CTC) and to correlate colonic findings with subsequent optical colonoscopy.

methods58 patients underwent ultralow-dose CTC. The images were reconstructed with filtered back projection (FBP), hybrid iterative reconstruction (HIR) or model-based iterative reconstruction (MBIR) techniques. In each segment, endoluminal noise (expressed as standard deviation of endoluminal density) was measured and image quality was rated on a five-point Likert scale by two independent readers. Colonic lesions were evaluated in consensus and correlated with subsequent optical colonoscopy where possible.

resultsThe estimated radiation dose was 0.41 ± 0.05 mSv for the supine and 0.42 ± 0.04 mSv for the prone acquisitions. In the endoluminal view, the image quality was rated better in HIR, whereas better scores were obtained in MBIR in the cross-sectional view, where the endoluminal noise was the lowest (p < 0.0001). Five (26%) polyps were not identified using both computer-aided detection and endoluminal inspection in FBP images vs only one (5%) in MBIR and none in HIR images.

conclusionThis study showed that in submillisievert ultralow-dose CTC, the image quality for the endoluminal view is better when HIR is used, whereas MBIR yields superior images for the cross-sectional view. The inferior quality of images reconstructed with FBP may result in decreased detection of colonic lesions. ADVANCES IN KNOWLEDGE: Radiation dose from CTC can be safely reduced <1 mSv for both positions when iterative reconstruction is used. MBIR provides better image quality in the cross-sectional view and HIR in the endoluminal view.

Indexed as

AgedColonography, Computed TomographicFemaleHumansMaleMiddle AgedModels, TheoreticalRadiation DosageRadiographic Image Interpretation, Computer-Assisted

Identifiers

PMID25605346
PMCPMC4651260

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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.