Evidence map›Paper›PMID 33780445›Full record

ArticlePLoS computational biology2021

A prediction tool for plaque progression based on patient-specific multi-physical modeling.

Jichao Pan, Yan Cai, Liang Wang, Akiko Maehara, Gary S Mintz, Dalin Tang, Zhiyong Li

Erratum issuedAbstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Jichao PanSchool of Biological Sciences and Medical Engineering, Southeast University, Nanjing Jiangsu, China.
Yan CaiSchool of Biological Sciences and Medical Engineering, Southeast University, Nanjing Jiangsu, China.
Liang WangSchool of Biological Sciences and Medical Engineering, Southeast University, Nanjing Jiangsu, China.
Akiko MaeharaThe Cardiovascular Research Foundation, New York, New York, United States of America.
Gary S MintzThe Cardiovascular Research Foundation, New York, New York, United States of America.ORCID 0000-0003-3296-8705
Dalin TangSchool of Biological Sciences and Medical Engineering, Southeast University, Nanjing Jiangsu, China.ORCID 0000-0002-6965-6417
Zhiyong LiSchool of Biological Sciences and Medical Engineering, Southeast University, Nanjing Jiangsu, China.ORCID 0000-0002-6814-9165

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Atherosclerotic plaque rupture is responsible for a majority of acute vascular syndromes and this study aims to develop a prediction tool for plaque progression and rupture. Based on the follow-up coronary intravascular ultrasound imaging data, we performed patient-specific multi-physical modeling study on four patients to obtain the evolutional processes of the microenvironment during plaque progression. Four main pathophysiological processes, i.e., lipid deposition, inflammatory response, migration and proliferation of smooth muscle cells (SMCs), and neovascularization were coupled based on the interactions demonstrated by experimental and clinical observations. A scoring table integrating the dynamic microenvironmental indicators with the classical risk index was proposed to differentiate their progression to stable and unstable plaques. The heterogeneity of plaque microenvironment for each patient was demonstrated by the growth curves of the main microenvironmental factors. The possible plaque developments were predicted by incorporating the systematic index with microenvironmental indicators. Five microenvironmental factors (LDL, ox-LDL, MCP-1, SMC, and foam cell) showed significant differences between stable and unstable group (p < 0.01). The inflammatory microenvironments (monocyte and macrophage) had negative correlations with the necrotic core (NC) expansion in the stable group, while very strong positive correlations in unstable group. The inflammatory microenvironment is strongly correlated to the NC expansion in unstable plaques, suggesting that the inflammatory factors may play an important role in the formation of a vulnerable plaque. This prediction tool will improve our understanding of the mechanism of plaque progression and provide a new strategy for early detection and prediction of high-risk plaques.

Indexed as

Models, BiologicalDisease ProgressionHumansInflammationNeovascularization, PathologicPlaque, Atherosclerotic

Identifiers

PMID33780445
PMCPMC8057612

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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.