Evidence map›Paper›PMID 41155117›Full record

ArticleBioengineering (Basel, Switzerland)2025

Design and Performance Assessment of a High-Resolution Small-Animal PET System.

Wei Liu, Peng Xi, Jiguo Liu, Xilong Xu, Zhaoheng Xie, Yanye Lu, Xiangxi Meng, Qiushi Ren

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2025. 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

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

1 citing paper in PubMed.

  1. 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

8 authors.

Wei LiuCollege of Future Technology, Peking University, Beijing 100871, China.ORCID 0009-0009-5891-6189
Peng XiCollege of Future Technology, Peking University, Beijing 100871, China.
Jiguo LiuShandong Madic Technology Co., Ltd., Linyi 276100, China.
Xilong XuShandong Madic Technology Co., Ltd., Linyi 276100, China.
Zhaoheng XieInstitute of Medical Technology, Peking University Health Science Center, Peking University, Beijing 100191, China.
Yanye LuInstitute of Medical Technology, Peking University Health Science Center, Peking University, Beijing 100191, China.
Xiangxi MengDepartment of Nuclear Medicine, Peking University Cancer Hospital, Beijing 100142, China.ORCID 0000-0002-6590-011X
Qiushi RenCollege of Future Technology, Peking University, Beijing 100871, China.

Funding

National Development and Reform Commission [2019]877
6 · The paper itself

Abstract

This work reports the performance evaluation of a newly developed small-animal positron emission tomography (PET) system based on lutetium-yttrium oxyorthosilicate (LYSO) crystals and multi-pixel photon counter (MPPC). Performance was evaluated, including spatial resolution, system sensitivity, energy resolution, scatter fraction (SF), noise-equivalent count rate (NECR), micro-Derenzo phantom imaging, and in vivo imaging of mice and rats. The system achieved a tangential spatial resolution of 0.9 mm in the axial direction at a quarter axial offset using the three-dimensional ordered-subsets expectation maximization (3D OSEM) reconstruction algorithm. The peak sensitivity was 8.74% within a 200-750 keV energy window, with an average energy resolution of 12.5%. Scatter fractions were 12.9% and 30.0% for mouse- and rat-like phantoms, respectively. The NECR reached 878.7 kcps at 57.6 MBq for the mouse phantom and 421.4 kcps at 63.2 MBq for the rat phantom. High-resolution phantom and in vivo images confirmed the system's capability for quantitative, high-sensitivity small-animal imaging, demonstrating its potential for preclinical molecular imaging studies.

Indexed as

LYSOperformance evaluationSiPMsmall-animal PET

Identifiers

PMID41155117
PMCPMC12561788

What OpenQuestion holds

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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.