Evidence map›Paper›PMID 36119736›Full record

ArticleFrontiers in cardiovascular medicine2022

A stable and quantitative method for dimensionality reduction of aortic centerline.

Tao Peng, Hongji Pu, Peng Qiu, Han Yang, Ziyue Ju, Hui Ma, Juanlin Zhang, Kexin Chen, Yanqing Zhan, Rui Sheng and 6 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

16 authors.

Tao PengSchool of Biomedical Engineering, Anhui Medical University, Hefei, China.
Hongji PuDepartment of Vascular Surgery, Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Peng QiuDepartment of Vascular Surgery, Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Han YangSchool of Biomedical Engineering, Anhui Medical University, Hefei, China.
Ziyue JuSchool of Biomedical Engineering, Anhui Medical University, Hefei, China.
Hui MaSchool of Biomedical Engineering, Anhui Medical University, Hefei, China.
Juanlin ZhangSchool of Biomedical Engineering, Anhui Medical University, Hefei, China.
Kexin ChenSchool of Biomedical Engineering, Anhui Medical University, Hefei, China.
Yanqing ZhanThe Fourth Affiliated Hospital of Anhui Medical University, Hefei, China.
Rui ShengChaohu Clinical Medical College, Anhui Medical University, Hefei, China.
Yi WangSchool of Biomedical Engineering, Anhui Medical University, Hefei, China.
Binshan ZhaDepartment of Vascular and Thyroid Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Yang YangDepartment of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China.
Shu FangSchool of Biomedical Engineering, Anhui Medical University, Hefei, China.
Xinwu LuDepartment of Vascular Surgery, Shanghai Ninth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Jinhua ZhouSchool of Biomedical Engineering, Anhui Medical University, Hefei, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aortic dissection (AD) is a fatal aortic disease with high mortality. Assessing the morphology of the aorta is critical for diagnostic and surgical decisions. Aortic centerline projection methods have been used to evaluate the morphology of the aorta. However, there is a big difference between the current model of primary plane projection (PPP) and the actual shape of individuals, which is not conducive to morphological statistical analysis. Finding a method to compress the three-dimensional information of the aorta into two dimensions is helpful to clinical decision-making. In this paper, the evaluation parameters, including contour length (CL), enclosure area, and the sum of absolute residuals (SAR), were introduced to objectively evaluate the optimal projection plane rather than artificial subjective judgment. Our results showed that the optimal projection plane could be objectively characterized by the three evaluation parameters. As the morphological criterion, SAR is optimal among the three parameters. Compared to the optimal projection plane selected by traditional PPP, our method has better AD discrimination in the analysis of aortic tortuosity, and is conducive to the clinical operation of AD. Thus, it has application prospects for the preprocessing techniques for the geometric morphology analysis of AD.

Indexed as

aortic dissectioncenterline modelinggeometric plane projectionmorphological analysisthree-dimensional coordinate transformation

Identifiers

PMID36119736
PMCPMC9473432

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