Evidence map›Paper›PMID 30820822›Full record

ArticleJapanese journal of radiology2019

Airway quantification using adaptive statistical iterative reconstruction-V on wide-detector low-dose CT: a validation study on lung specimen.

Lin Zhang, Zhengyu Li, Jie Meng, Xueqian Xie, Hao Zhang

Abstract readValidation Study
PubMed Publisher
In one paragraph

Article in Japanese journal of radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
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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

5 authors.

Lin ZhangDepartment of Radiology, Shanghai General Hospital of Nanjing Medical University, No. 100 Haining Road, Shanghai, 200080, People's Republic of China.
Zhengyu LiDepartment of Radiology, Shanghai General Hospital of Nanjing Medical University, No. 100 Haining Road, Shanghai, 200080, People's Republic of China.
Jie MengDepartment of Radiology, Shanghai General Hospital of Nanjing Medical University, No. 100 Haining Road, Shanghai, 200080, People's Republic of China.
Xueqian XieDepartment of Radiology, Shanghai General Hospital of Nanjing Medical University, No. 100 Haining Road, Shanghai, 200080, People's Republic of China. adrianxie@163.com.
Hao ZhangDepartment of Radiology, Shanghai General Hospital of Nanjing Medical University, No. 100 Haining Road, Shanghai, 200080, People's Republic of China. drzhang021@163.com.

Funding

Ministry of Science and Technology 2016YFE0103000National Natural Science Foundation of China 81471662Science and Technology Commission of Shanghai Municipality 16410722300Science and Technology Commission of Shanghai Municipality 16411968500
6 · The paper itself

Abstract

purposeTo evaluate the accuracy of airway quantification of adaptive statistical iterative reconstruction (ASIR)-V on low-dose CT using a human lung specimen.

methodA lung specimen was scanned on Revolution CT with low-dose settings (20 mAs, 40 mAs and 60 mAs/100 kV) and standard-dose setting (100 mAs/120 kV). CT images were reconstructed using lung kernel with eleven ASIR-V levels from 0 to 100% with 10% interval. ASIR-V level from 0 to 100% with 10% interval was reconstructed on lung kernel. Wall area percentage (%WA) and wall thickness (WT) were measured.

resultsRadiation dose of 20 mAs, 40 mAs and 60 mAs low-dose settings reduced by 87.6%, 75.2% and 62.8% compared to that on standard dose, respectively. Low-dose settings significantly decreased image SNR (p < 0.05) and increased noise (p < 0.001). ASIR-V level exponentially improved image SNR and linearly decreased image noise (all p < 0.001). The mean airway measurement ratios of low-dose to standard-dose were within 2% variation for %WA and within 3% variation for WT. Most %WA and WT values showed no obvious correlation with ASIR-V levels.

conclusionASIR-V showed to improve image quality in low radiation dose. However, low-dose settings and ASIR-V strength did not significantly influence airway quantification values, although variation in measurements slightly increased with dose reduction.

Indexed as

CadaverHumansImage Processing, Computer-AssistedLungMaleRadiation DosageRadiographic Image Interpretation, Computer-AssistedReproducibility of ResultsTomography, X-Ray ComputedAirway quantificationIterative reconstructionLow dosePhantomTomographyx-ray computed

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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.