Evidence map›Paper›PMID 40160645›Full record

ArticleQuantitative imaging in medicine and surgery2025

Prospective comparisons of three interpretation methods of fractional flow reserve derived from coronary computed tomography angiography.

Kun Xu, Lin Yang, Jingyuan Zhang, Wenhao Huang, Yumeng Hu, Xiaochang Leng, Yajun Liu, Xiaowei Liu, Hongfeng Jin, Yiming Tang and 7 more

Abstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2025. 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
–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

2 citing papers in PubMed.

  1. Article
  2. 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

17 authors.

Kun Xu *Department of Internal Medicine, Shengzhou Hospital of Traditional Chinese Medicine, Shengzhou, China.
Lin Yang *Department of Geriatrics, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Jingyuan Zhang *Department of Cardiology, Huaibei Miners Hospital, Huaibei, China.
Wenhao HuangDepartment of Medicine, The Second College of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China.
Yumeng HuArteryFlow Technology Co., Ltd., Hangzhou, China.
Xiaochang LengArteryFlow Technology Co., Ltd., Hangzhou, China.
Yajun LiuDepartment of Medicine, The Second College of Clinical Medicine, Zhejiang Chinese Medical University, Hangzhou, China.
Xiaowei LiuDepartment of Cardiology, Zhejiang Hospital, Hangzhou, China.
Hongfeng JinDepartment of Cardiology, Zhejiang Hospital, Hangzhou, China.
Yiming TangDepartment of Cardiology, Zhejiang Hospital, Hangzhou, China.
Jiangting WangDepartment of Cardiology, Zhejiang Hospital, Hangzhou, China.
Yitao GuoDepartment of Cardiology, Zhejiang Hospital, Hangzhou, China.
Chen YeDepartment of Cardiology, Zhejiang Hospital, Hangzhou, China.
Jianjun ZhangDepartment of Radiology, Zhejiang Hospital, Hangzhou, China.
Jianping XiangArteryFlow Technology Co., Ltd., Hangzhou, China.
Lijiang TangDepartment of Cardiology, Zhejiang Hospital, Hangzhou, China.
Changqing DuDepartment of Cardiology, Zhejiang Hospital, Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The selection of fractional flow reserve derived from computed tomography (CT-FFR) calculation locations is of particular importance when determining ischemic lesions for guiding therapeutic strategies. However, to date, there has been no prospective research comparing different measured locations of CT-FFR. The study aimed to prospectively compare the diagnostic efficiency of three interpretation methods of CT-FFR, using invasive fractional flow reserve (FFR) as the reference standard. Methods: Patients with stable coronary heart disease (CHD) who underwent coronary computed tomography angiography (CCTA) examination and met the inclusion criteria at Zhejiang Hospital from January 2019 to June 2021 were prospectively enrolled. All patients underwent invasive coronary angiography and FFR within 60 days after the CCTA examination. The CT-FFR values were computed using the novel computational fluid dynamics (CFD)-based model, AccuFFRct. Diagnostic performance of vessel-level CT-FFR, lesion-specific CT-FFR, and ΔCT-FFR were evaluated with invasive FFR ≤0.8 as the reference standard and multivariate logistic regression was used to further analyze the influencing factors of their inconsistency with FFR. Results: In total, 124 patients with 143 vessels were included in this prospective study. On a per-vessel basis, vessel-level AccuFFRct and lesion-specific AccuFFRct had good correlation with invasive FFR (r=0.70 and r=0.66, respectively). With invasive FFR ≤0.8 as the reference standard for the diagnosis of myocardial ischemia, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), diagnostic accuracy, and area under the curve (AUC) values of CCTA, vessel-level AccuFFRct, lesion-specific AccuFFRct, and ΔAccuFFRct in the diagnosis of myocardial ischemia were 82.0%, 40.2%, 50.5%, 75.0%, 58.0%, 0.611; 93.4%, 89.0%, 86.4%, 94.8%, 90.9%, 0.937; 62.3%, 92.7%, 86.4%, 76.8%, 79.7%, 0.880 and 62.3%, 92.7%, 86.4%, 76.8%, 79.7%, and 0.854, respectively. Conclusions: Vessel-level AccuFFRct, lesion-specific AccuFFRct, and ΔAccuFFRct provided better diagnostic performance compared with CCTA, with vessel-level AccuFFRct being superior in predicting myocardial ischemia, whereas lesion-specific AccuFFRct and ΔAccuFFRct had higher specificity than vessel-level AccuFFRct.

Indexed as

computational fluid dynamics (CFD)coronary computed tomography angiography (CCTA)Coronary heart disease (CHD)fractional flow reserve (FFR)myocardial ischemia

Identifiers

PMID40160645
PMCPMC11948430

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.