Evidence map›Paper›PMID 36152039›Full record

ArticleEuropean radiology2023

Evaluation of fully automated commercial software for Agatston calcium scoring on non-ECG-gated low-dose chest CT with different slice thickness.

Hyun Woo Kang, Woo Jin Ahn, Ju Hyun Jeong, Young Joo Suh, Dong Hyun Yang, Hangseok Choi, Sung Ho Hwang, Hwan Seok Yong, Yu-Whan Oh, Eun-Young Kang and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
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

11 authors.

Hyun Woo KangKorea University College of Medicine, Seoul, South Korea.
Woo Jin AhnKorea University College of Medicine, Seoul, South Korea.
Ju Hyun JeongDepartment of Radiology, Ansan Hospital, Korea University College of Medicine, 123, Jeokgeum-ro, Danwon-gu, Ansan-si, Gyeonggi-do, South Korea.
Young Joo SuhDepartment of Radiology, Severance Hospital, Research Institute of Radiological Science, Center for Clinical Imaging Data Science, Yonsei University College of Medicine, Seoul, South Korea.
Dong Hyun YangDepartment of Radiology and Research Institute of Radiology, Cardiac Imaging Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Hangseok ChoiMedical Science Research Center, Korea University College of Medicine, Seoul, South Korea.
Sung Ho HwangDepartment of Radiology, Anam Hospital, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul, 02841, South Korea.
Hwan Seok YongDepartment of Radiology, Guro Hospital, Korea University College of Medicine, 148, Gurodong-ro, Guro-gu, Seoul, 08308, South Korea.
Yu-Whan OhDepartment of Radiology, Anam Hospital, Korea University College of Medicine, 73, Goryeodae-ro, Seongbuk-gu, Seoul, 02841, South Korea.
Eun-Young KangDepartment of Radiology, Guro Hospital, Korea University College of Medicine, 148, Gurodong-ro, Guro-gu, Seoul, 08308, South Korea.
Cherry KimDepartment of Radiology, Ansan Hospital, Korea University College of Medicine, 123, Jeokgeum-ro, Danwon-gu, Ansan-si, Gyeonggi-do, South Korea. cherrykim0505@gmail.com.ORCID http://orcid.org/0000-0002-3361-5496

Funding

the Ministry of Health & Welfare, Republic of Korea HI18C0022
6 · The paper itself

Abstract

objectivesTo evaluate commercial deep learning-based software for fully automated coronary artery calcium (CAC) scoring on non-electrocardiogram (ECG)-gated low-dose CT (LDCT) with different slice thicknesses compared with manual ECG-gated calcium-scoring CT (CSCT).

methodsThis retrospective study included 567 patients who underwent both LDCT and CSCT. All LDCT images were reconstructed with a 2.5-mm slice thickness (LDCT

resultsCSCT

conclusionsFully automated CAC-scoring software with both CSCT and LDCT yielded excellent reliability and agreement with CSCT KEY POINTS: • Total Agatston scores and all vessels of CSCT

Indexed as

CalciumCoronary Artery DiseaseCoronary AngiographyCoronary VesselsHumansReproducibility of ResultsRetrospective StudiesSoftwareTomography, X-Ray ComputedCalciumArtificial intelligenceCalciumCoronary arteriesSoftwareTomography, X-ray computed

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.