Evidence map›Paper›PMID 36929293›Full record

ArticleJournal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology2023

Comparison of 2D-QCA, 3D-QCA and coronary angiography derived FFR in predicting myocardial ischemia assessed by CZT-SPECT MPI.

Xianglin Tang, Neng Dai, BuChun Zhang, Haidong Cai, Yanlei Huo, Mengdie Yang, Yongji Jiang, Shaofeng Duan, Jianying Shen, Mengyun Zhu and 2 more

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In one paragraph

Article in Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Deep learning to automate SPECT MPI myocardial reorientation.Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology · 2023
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors at 6 institutions in 2 countries.

Xianglin Tang *Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
Neng Dai *Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Xuhui District, Shanghai, 200032, China.
BuChun Zhang *Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China.
Haidong CaiDepartment of Nuclear Medicine, Shanghai Tenth People's Hospital, Shanghai, China.
Yanlei HuoDepartment of Nuclear Medicine, Shanghai Tenth People's Hospital, Shanghai, China.
Mengdie YangDepartment of Nuclear Medicine, Shanghai Tenth People's Hospital, Shanghai, China.
Yongji JiangDepartment of Nuclear Medicine, Shanghai Tenth People's Hospital, Shanghai, China.
Shaofeng DuanGE Healthcare China, Shanghai, China.
Jianying ShenCardiology Department, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China.
Mengyun ZhuCardiology Department, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China.
Yawei XuCardiology Department, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 301 Yanchang Road, Shanghai, 200072, China. xuyawei@tongji.edu.cn.
Junbo GeDepartment of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, 180 Fenglin Road, Xuhui District, Shanghai, 200032, China. jbge@zs-hospital.sh.cn.
Shanghai Tenth People's Hospital · CNFudan University · CNTongji University · CNUnited Imaging Healthcare (China) · CNUniversity of Science and Technology of China · CNZhongshan Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAngiography derived fractional flow reserve (angio-FFR) has been proposed. This study aimed to assess its diagnostic performance with cadmium-zinc-telluride single emission computed tomography (CZT-SPECT) as reference. METHODS AND

resultsPatients underwent CZT-SPECT within 3 months of coronary angiography were included. Angio-FFR computation was performed using computational fluid dynamics. Percent diameter (%DS) and area stenosis (%AS) were measured by quantitative coronary angiography. Myocardial ischemia was defined as a summed difference score ≥ 2 in a vascular territory. Angio-FFR ≤ 0.80 was considered abnormal. 282 coronary arteries in 131 patients were analyzed. Overall accuracy of angio-FFR to detect ischemia on CZT-SPECT was 90.43%, with a sensitivity of 62.50% and a specificity of 98.62%. The diagnostic performance (= area under ROC = AUC) of angio-FFR [AUC = 0.91, 95% confidence intervals (CI) 0.86-0.95] was similar as those of %DS (AUC = 0.88, 95% CI 0.84-0.93, p = 0.326) and %AS (AUC = 0.88, 95% CI 0.84-0.93 p = 0.241) by 3D-QCA, but significantly higher than those of %DS (AUC = 0.59, 95% CI 0.51-0.67, p < 0.001) and %AS (AUC = 0.59, 95% CI 0.51-0.67, p < 0.001) by 2D-QCA. However, in vessels with 50-70% stenoses, AUC of angio-FFR was significantly higher than those of %DS (0.80 vs. 0.47, p < 0.001) and %AS (0.80 vs. 0.46, p < 0.001) by 3D-QCA and %DS (0.80 vs. 0.66, p = 0.036) and %AS (0.80 vs. 0.66, p = 0.034) by 2D-QCA.

conclusionAngio-FFR had a high accuracy in predicting myocardial ischemia assessed by CZT-SPECT, which is similar as 3D-QCA but significantly higher than 2D-QCA. While in intermediate lesions, angio-FFR is better than 3D-QCA and 2D-QCA in assessing myocardial ischemia.

Indexed as

Coronary Artery DiseaseCoronary StenosisFractional Flow Reserve, MyocardialMyocardial IschemiaConstriction, PathologicCoronary AngiographyHumansPredictive Value of TestsSeverity of Illness IndexTomography, Emission-Computed, Single-Photonangiography-derived fractional flow reserveComputational fluid dynamicsCoronary artery diseaseCZT-SPECTmyocardial perfusion imaging

Identifiers

PMID36929293
OpenAlexW4327555425

What Socratic 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 Socratic graph.