Evidence map›Paper›PMID 28830200›Full record

ArticleThe British journal of radiology2017

Assessment of structural similarity in CT using filtered backprojection and iterative reconstruction: a phantom study with 3D printed lung vessels.

Raoul M S Joemai, Jacob Geleijns

Abstract readComparative Study
In one paragraph

Article 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 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  17. PixelPrint: Three-dimensional printing of realistic patient-specific lung phantoms for CT imaging.Proceedings of SPIE--the International Society for Optical Engineering
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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

2 authors.

Raoul M S JoemaiDepartment of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
Jacob GeleijnsDepartment of Radiology, Leiden University Medical Center, Leiden, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo compare the performance of three generations of CT reconstruction techniques using structural similarity (SSIM) as a measure of image quality for CT scans of a chest phantom with 3D printed lung vessels.

methodsCT images of the chest phantom were acquired at seven dose levels by changing the tube current while other acquisition parameters were kept constant. Three CT reconstruction techniques were applied on each acquisition. The first technique was filtered backprojection (FBP), the second technique was FBP with iterative filtering (adaptive iteration dose reduction in 3 dimensions (AIDR 3D)) and the third technique was model-based iterative reconstruction (Forward projected model-based Iterative Reconstruction SoluTion (FIRST)). Image quality of the CT data was quantified in terms of SSIM. The SSIM index was used for image quality comparison between the dose levels and different reconstruction techniques. The SSIM index gives a value between 0 and 1, with 0 as the lowest image quality and 1 as an excellent image quality.

resultsThe lowest SSIM index was observed for FBP at all dose levels. The reconstruction technique with the highest SSIM depends on the dose level. For tube currents higher than 80 mA, AIDR 3D showed the highest SSIM index, and for tube currents lower or equal to 80 mA FIRST showed the highest SSIM index.

conclusionSSIM index is a robust quantity and is correlated to the image quality as perceived by the humans. Advanced CT reconstruction techniques provide better image quality in all conditions compared to FBP. Advances in knowledge: SSIM is a robust measure to compare CT image quality for advanced reconstruction techniques relative to a reference. The 3D print technology is an useful method for the development of dedicated phantoms for CT image quality evaluation.

Indexed as

Printing, Three-DimensionalHumansImage Processing, Computer-AssistedImaging, Three-DimensionalLungModels, AnatomicPhantoms, ImagingRadiographic Image EnhancementSignal-To-Noise RatioTomography, X-Ray Computed

Identifiers

PMID28830200
PMCPMC5963378

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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.