Evidence map›Paper›PMID 33052465›Full record

ArticleEuropean radiology2021

Histological validation of simultaneous non-contrast angiography and intraplaque hemorrhage imaging (SNAP) for characterizing carotid intraplaque hemorrhage.

Dongye Li, Huiyu Qiao, Yongjun Han, Hualu Han, Dandan Yang, Jingli Cao, Huimin Xu, Tao Wang, Yajie Wang, Jun Shen and 1 more

Abstract read
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In one paragraph

Article in European radiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 16% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

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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

11 authors at 4 institutions in 1 country.

Dongye LiDepartment of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, China.
Huiyu QiaoCenter for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Haidian District, Beijing, 100084, China.
Yongjun HanCenter for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Haidian District, Beijing, 100084, China.
Hualu HanCenter for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Haidian District, Beijing, 100084, China.
Dandan YangCenter for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Haidian District, Beijing, 100084, China.
Jingli CaoChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Huimin XuDepartment of Radiology, Peking University Third Hospital, Beijing, China.
Tao WangDepartment of Neurosurgery, Peking University Third Hospital, Beijing, China.
Yajie WangDepartment of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing, China.
Jun Shen *Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, China. shenjun@mail.sysu.edu.cn.
Xihai Zhao *Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University School of Medicine, Haidian District, Beijing, 100084, China. xihaizhao@tsinghua.edu.cn.ORCID http://orcid.org/0000-0001-8953-0566
Capital Medical University · CNTsinghua University · CNPeking University · CNSun Yat-sen University · CN

Funding

Beijing Municipal Science and Technology Commission D171100003017003Guangdong Province Universities and Colleges Pearl River Scholar Funded Scheme 2017Ministry of Science and Technology of the People's Republic of China 2017YFC1307904National Natural Science Foundation of China 81771825National Natural Science Foundation of China U1801681the Key Areas Research and Development Program of Guangdong 2019B020235001
6 · The paper itself

Abstract

objectivesThis study sought to validate the performance of simultaneous non-contrast angiography and intraplaque hemorrhage (SNAP) imaging in characterizing carotid IPH by histology.

methodsThirty-five patients with carotid atherosclerotic disease (symptomatic 50-70% stenosis or > 70% stenosis) scheduled for carotid endarterectomy underwent 3.0-T carotid MR imaging by acquiring SNAP and magnetization-prepared rapid acquisition gradient-echo (MP-RAGE) sequences. Presence and area of IPH were separately evaluated on SNAP and MP-RAGE images. Presence and area of IPH were also assessed on histology. Agreement between SNAP/MP-RAGE and histology was determined in identify and quantify IPH using Cohen kappa, Spearman correlation, and Bland-Altman analyses.

resultsOf all 35 patients (mean age: 63.1 ± 8.8 years; 27 males), 128 slices with successful registration were eligible for analysis. The accuracy, sensitivity, specificity, and positive and negative predictive values were 86.7%, 85%, 89.6%, 93.2%, and 78.2% for SNAP, and 76.6%, 75%, 79.2%, 85.7%, and 65.5% for MP-RAGE in identification of IPH, respectively. In identification of IPH, the kappa value between SNAP and histology and between MP-RAGE and histology was 0.725 and 0.520, respectively. The correlation between SNAP and histology (r = 0.805, p < 0.001) was stronger than that between MP-RAGE and histology (r = 0.637, p < 0.001) in measuring IPH area. Bland-Altman analysis showed that, in measuring IPH area, the bias of SNAP (1.4 mm

conclusionsThis validation study by histology demonstrates that SNAP sequence better identifies and quantifies carotid intraplaque hemorrhage compared with traditional MP-RAGE sequence. KEY POINTS: • SNAP imaging showed better agreement with histology compared with MP-RAGE imaging, especially for the IPHs with small size. • SNAP sequence is a more effective tool to identify and quantify carotid IPH than traditional sequence of MP-RAGE that can help clinicians to optimizing the treatment strategy. • The plaque components of rich lipid pools or loose matrix and chronic/old IPH (cholesterol crystals) can lead to false positive and false negative results in SNAP and MP-RAGE imaging for identifying IPH.

Indexed as

Carotid Artery DiseasesCarotid StenosisPlaque, AtheroscleroticAgedAngiographyCarotid ArteriesHemorrhageHumansMagnetic Resonance ImagingMaleMiddle AgedReproducibility of ResultsAtherosclerotic plaqueCarotid arteryMagnetic resonance imaging

Identifiers

PMID33052465
OpenAlexW3092283147

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.