Evidence map›Paper›PMID 31192940›Full record

ArticleMedicine2019

Evaluation of the depiction ability of the microanatomy of the temporal bone in quarter-detector CT: Model-based iterative reconstruction vs hybrid iterative reconstruction.

Ryo Kurokawa, Eriko Maeda, Harushi Mori, Shiori Amemiya, Jiro Sato, Kenji Ino, Rumiko Torigoe, Osamu Abe

Abstract read
In one paragraph

Article in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 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

8 authors.

Ryo KurokawaDepartment of Radiology, Graduate School of Medicine, University of Tokyo.
Eriko MaedaDepartment of Radiology, Graduate School of Medicine, University of Tokyo.
Harushi MoriDepartment of Radiology, Graduate School of Medicine, University of Tokyo.
Shiori AmemiyaDepartment of Radiology, Graduate School of Medicine, University of Tokyo.
Jiro SatoDepartment of Radiology, Graduate School of Medicine, University of Tokyo.
Kenji InoDepartment of Radiation Technology, University of Tokyo Hospital.
Rumiko TorigoeCanon Medical Systems Corporation, Japan.
Osamu AbeDepartment of Radiology, Graduate School of Medicine, University of Tokyo.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Little is known regarding differences between model-based iterative reconstruction (MBIR) and hybrid iterative reconstruction (HIR) in temporal bone computed tomography (CT). This study compared the ability to depict microstructures in temporal bone in quarter-detector CT (QDCT) between MBIR and HIR.Sixty-two temporal bones in 31 consecutive adult patients who underwent QDCT were included. Reconstruction was performed with Forward projected model-based Iterative Reconstruction SoluTion (FIRST) BONE mild mode and Adaptive Iterative Dose Reduction 3D (AIDR3D) enhanced mild mode. Imaging quality was graded for 3 microstructures (spiral osseous lamina, tympanic membrane, and singular canal).Spiral osseous lamina was significantly well-delineated in the AIDR3D enhanced group, compared with the FIRST group. In nearly all cases with FIRST, spiral osseous lamina was poorly defined. Although there was no significant difference, depiction of the tympanic membrane and singular canal tended to be better with AIDR3D enhanced mode.Routine reconstruction for preoperative temporal bone CT should be performed with HIR, rather than MBIR.

Indexed as

AdultAgedAged, 80 and overFemaleHumansMaleMiddle AgedRadiographic Image Interpretation, Computer-AssistedRetrospective StudiesSpiral LaminaTemporal BoneTomography, X-Ray Computed

Identifiers

PMID31192940
PMCPMC6587614

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Registered trials

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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.