Evidence map›Paper›PMID 34856926›Full record

ArticleBMC cancer2021

Reduction of metal artifacts from knee tumor prostheses on CT images: value of the single energy metal artifact reduction (SEMAR) algorithm.

Fang-Ling Zhang, Ruo-Cheng Li, Xiao-Ling Zhang, Zhao-Hui Zhang, Ling Ma, Lei Ding

Open access · goldAbstract read
In one paragraph

Article in BMC cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.5field-weighted citation impact, top 19% 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

2 citing papers in PubMed, 19 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

6 authors at 2 institutions in 1 country.

Fang-Ling Zhang *Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, 58# Zhongshan Er Road, 510080, Guangzhou, Guangdong Province, People's Republic of China.
Ruo-Cheng Li *Department of Radiology, The First Affiliated Hospital, Sun Yat-sen University, 58# Zhongshan Er Road, 510080, Guangzhou, Guangdong Province, People's Republic of China.
Xiao-Ling ZhangDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, 58# Zhongshan Er Road, 510080, Guangzhou, Guangdong Province, People's Republic of China.
Zhao-Hui ZhangDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, 58# Zhongshan Er Road, 510080, Guangzhou, Guangdong Province, People's Republic of China.
Ling MaDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, 58# Zhongshan Er Road, 510080, Guangzhou, Guangdong Province, People's Republic of China. mling@mail.sysu.edu.cn.
Lei DingDepartment of Radiology, The First Affiliated Hospital, Sun Yat-sen University, 58# Zhongshan Er Road, 510080, Guangzhou, Guangdong Province, People's Republic of China. dinglei3@mail.sysu.edu.cn.
Sun Yat-sen University · CNThe First Affiliated Hospital, Sun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo evaluate the effect of the single energy metal artifact reduction (SEMAR) algorithm with a multidetector CT (MDCT) for knee tumor prostheses.

methodsFirst, a phantom of knee tumor prosthesis underwent a MDCT scan. The raw data was reconstructed by iterative reconstruction (IR) alone and IR plus SEMAR. The mean value of the CT number and the image noise were measured around the prosthesis at the stem level and articular level. Second, 95 consecutive patients with knee tumor prostheses underwent MDCT scans. The raw data were also reconstructed by the two methods. Periprosthetic structures were selected at the similar two levels. Four radiologists visually graded the image quality on a scale from 0 to 5. Additionally, the readers also assessed the presence of prosthetic complication and tumor recurrence on a same scale.

resultsIn the phantom, when the SEMAR was used, the CT numbers were closer to normal value and the noise of images using soft and sharper kernel were respectively reduced by up to 77.1% and 43.4% at the stem level, and by up to 82.2% and 64.5% at the articular level. The subjective scores increased 1 ~ 3 points and 1 ~ 4 points at the two levels, respectively. Prosthetic complications and tumor recurrence were diagnosed in 66 patients. And the SEMAR increased the diagnostic confidence of prosthetic complications and tumor recurrence (4 ~ 5 vs. 1 ~ 1.5).

conclusionsThe SEMAR algorithm can significantly reduce the metal artifacts and increase diagnostic confidence of prosthetic complications and tumor recurrence in patients with knee tumor prostheses.

Indexed as

AlgorithmsArtifactsKnee ProsthesisMetalsAdolescentAdultBone NeoplasmsChildFemaleFemoral NeoplasmsFemurHumansImage Processing, Computer-AssistedMaleMiddle AgedMultidetector Computed TomographyMetalsComputed tomographyImage qualityKneeMetal artifact reductionTumor prosthesis

Identifiers

PMID34856926
PMCPMC8638139
OpenAlexW3217124112

What OpenQuestion holds

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LicenceCC BY
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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.