Evidence map›Paper›PMID 28342101›Full record

ArticleEuropean radiology2017

Myocardial segmentation based on coronary anatomy using coronary computed tomography angiography: Development and validation in a pig model.

Mi Sun Chung, Dong Hyun Yang, Young-Hak Kim, Soo-Jin Kang, Joonho Jung, Namkug Kim, Seung-Ho Heo, Seunghee Baek, Joon Beom Seo, Byoung Wook Choi and 2 more

Abstract read
PubMed Publisher
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 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
  2. Article
  3. 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

12 authors.

Mi Sun ChungDepartment of Radiology, Chung-Ang University Hospital, Chung-Ang University College of Medicine, 102, Heukseok-ro, Dongjakgu, Seoul, 06973, South Korea.
Dong Hyun YangDepartment of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Asanbyeongwon-gil 86, Seoul, 138-736, South Korea. donghyun.yang@gmail.com.
Young-Hak KimHeart Institute, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Soo-Jin KangHeart Institute, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Joonho JungHeart Institute, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Namkug KimDepartment of Convergence Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Seung-Ho HeoAsan institute for Life Science, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Seunghee BaekDepartment of Clinical Epidemiology and Biostatistics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Joon Beom SeoDepartment of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Asanbyeongwon-gil 86, Seoul, 138-736, South Korea.
Byoung Wook ChoiDepartment of Diagnostic Radiology, College of Medicine, Yonsei University, Seoul, South Korea.
Joon-Won KangDepartment of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Asanbyeongwon-gil 86, Seoul, 138-736, South Korea.
Tae-Hwan LimDepartment of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Asanbyeongwon-gil 86, Seoul, 138-736, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo validate a method for performing myocardial segmentation based on coronary anatomy using coronary CT angiography (CCTA).

methodsCoronary artery-based myocardial segmentation (CAMS) was developed for use with CCTA. To validate and compare this method with the conventional American Heart Association (AHA) classification, a single coronary occlusion model was prepared and validated using six pigs. The unstained occluded coronary territories of the specimens and corresponding arterial territories from CAMS and AHA segmentations were compared using slice-by-slice matching and 100 virtual myocardial columns.

resultsCAMS more precisely predicted ischaemic area than the AHA method, as indicated by 95% versus 76% (p < 0.001) of the percentage of matched columns (defined as percentage of matched columns of segmentation method divided by number of unstained columns in the specimen). According to the subgroup analyses, CAMS demonstrated a higher percentage of matched columns than the AHA method in the left anterior descending artery (100% vs. 77%; p < 0.001) and mid- (99% vs. 83%; p = 0.046) and apical-level territories of the left ventricle (90% vs. 52%; p = 0.011).

conclusionsCAMS is a feasible method for identifying the corresponding myocardial territories of the coronary arteries using CCTA. KEY POINTS: • CAMS is a feasible method for identifying corresponding coronary territory using CTA • CAMS is more accurate in predicting coronary territory than the AHA method • The AHA method may underestimate the ischaemic territory of LAD stenosis.

Indexed as

Computed Tomography AngiographyAnimalsCoronary AngiographyCoronary Artery DiseaseCoronary VesselsDisease Models, AnimalHeartMyocardiumSwineAnimal experimentationComputed tomographyCoronary artery diseaseMyocardial ischaemiaSoftware validation

Identifiers

PMID28342101

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.