Evidence map›Paper›PMID 37854546›Full record

ArticleBiomedical optics express2023

Liver injury monitoring using dynamic fluorescence molecular tomography based on a time-energy difference strategy.

Yizhe Zhao, Shuangchen Li, Xuelei He, Jingjing Yu, Lizhi Zhang, Heng Zhang, De Wei, Beilei Wang, Jintao Li, Hongbo Guo and 1 more

Abstract read
In one paragraph

Article in Biomedical optics express, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Yizhe ZhaoThe Xi'an Key Laboratory of Radiomics and Intelligent Perception, Xi'an, China.
Shuangchen LiThe Xi'an Key Laboratory of Radiomics and Intelligent Perception, Xi'an, China.ORCID https://orcid.org/0000-0002-0021-6907
Xuelei HeThe Xi'an Key Laboratory of Radiomics and Intelligent Perception, Xi'an, China.
Jingjing YuSchool of Physics and Information Technology, Shaanxi Normal University, Xi'an, 710062, China.ORCID https://orcid.org/0000-0003-4580-7898
Lizhi ZhangThe Xi'an Key Laboratory of Radiomics and Intelligent Perception, Xi'an, China.
Heng ZhangThe Xi'an Key Laboratory of Radiomics and Intelligent Perception, Xi'an, China.
De WeiThe Xi'an Key Laboratory of Radiomics and Intelligent Perception, Xi'an, China.
Beilei WangThe Xi'an Key Laboratory of Radiomics and Intelligent Perception, Xi'an, China.
Jintao LiThe Xi'an Key Laboratory of Radiomics and Intelligent Perception, Xi'an, China.
Hongbo GuoThe Xi'an Key Laboratory of Radiomics and Intelligent Perception, Xi'an, China.ORCID https://orcid.org/0000-0003-2035-874X
Xiaowei HeThe Xi'an Key Laboratory of Radiomics and Intelligent Perception, Xi'an, China.ORCID https://orcid.org/0000-0003-2126-178X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dynamic fluorescence molecular tomography (DFMT) is a promising molecular imaging technique that offers the potential to monitor fast kinetic behaviors within small animals in three dimensions. Early monitoring of liver disease requires the ability to distinguish and analyze normal and injured liver tissues. However, the inherent ill-posed nature of the problem and energy signal interference between the normal and injured liver regions limit the practical application of liver injury monitoring. In this study, we propose a novel strategy based on time and energy, leveraging the temporal correlation in fluorescence molecular imaging (FMI) sequences and the metabolic differences between normal and injured liver tissue. Additionally, considering fluorescence signal distribution disparity between the injured and normal regions, we designed a universal Golden Ratio Primal-Dual Algorithm (GRPDA) to reconstruct both the normal and injured liver regions. Numerical simulation and

Identifiers

PMID37854546
PMCPMC10581805

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Registered trials

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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.