Evidence map›Paper›PMID 27913913›Full record

ArticleEuropean radiology2017

Improved image quality in abdominal CT in patients who underwent treatment for hepatocellular carcinoma with small metal implants using a raw data-based metal artifact reduction algorithm.

Keitaro Sofue, Takeshi Yoshikawa, Yoshiharu Ohno, Noriyuki Negi, Hiroyasu Inokawa, Naoki Sugihara, Kazuro Sugimura

Abstract read
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In one paragraph

Article in European radiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.0field-weighted citation impact, top 22% 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

11 citing papers in PubMed, 15 citations in OpenAlex.

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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

7 authors at 3 institutions in 1 country.

Keitaro SofueDepartment of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, Hyogo, 650-0017, Japan. keitarosofue@gmail.com.
Takeshi YoshikawaAdvanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan.
Yoshiharu OhnoAdvanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Kobe, Hyogo, Japan.
Noriyuki NegiDivision of Radiology, Kobe University Hospital, Kobe, Hyogo, Japan.
Hiroyasu InokawaToshiba Medical Systems Corporation, Otawara, Tochigi, Japan.
Naoki SugiharaToshiba Medical Systems Corporation, Otawara, Tochigi, Japan.
Kazuro SugimuraDepartment of Radiology, Kobe University Graduate School of Medicine, 7-5-2 Kusunoki-cho, Chuo-ku, Kobe, Hyogo, 650-0017, Japan.
Kobe University · JPToshiba (Japan) · JPKobe University Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo determine the value of a raw data-based metal artifact reduction (SEMAR) algorithm for image quality improvement in abdominal CT for patients with small metal implants.

methodsFifty-eight patients with small metal implants (3-15 mm in size) who underwent treatment for hepatocellular carcinoma were imaged with CT. CT data were reconstructed by filtered back projection with and without SEMAR algorithm in axial and coronal planes. To evaluate metal artefact reduction, mean CT number (HU and SD) and artefact index (AI) values within the liver were calculated. Two readers independently evaluated image quality of the liver and pancreas and visualization of vasculature using a 5-point visual score. HU and AI values and image quality on images with and without SEMAR were compared using the paired Student's t-test and Wilcoxon signed rank test. Interobserver agreement was evaluated using linear-weighted κ test.

resultsMean HU and AI on images with SEMAR was significantly lower than those without SEMAR (P < 0.0001). Liver and pancreas image qualities and visualizations of vasculature were significantly improved on CT with SEMAR (P < 0.0001) with substantial or almost perfect agreement (0.62 ≤ κ ≤ 0.83).

conclusionsSEMAR can improve image quality in abdominal CT in patients with small metal implants by reducing metallic artefacts. KEY POINTS: • SEMAR algorithm significantly reduces metallic artefacts from small implants in abdominal CT. • SEMAR can improve image quality of the liver in dynamic CECT. • Confidence visualization of hepatic vascular anatomies can also be improved by SEMAR.

Indexed as

AlgorithmsArtifactsProstheses and ImplantsAbdomenAgedCarcinoma, HepatocellularCombined Modality TherapyFemaleHumansImage Processing, Computer-AssistedLiver NeoplasmsMaleMetalsMiddle AgedReproducibility of ResultsRetrospective StudiesMetalsAbdominalComputed tomographyHepatocellular carcinomaLiverMetal artefact reduction

Identifiers

PMID27913913
OpenAlexW2557928641

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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.