Evidence map›Paper›PMID 39457847›Full record

ArticleAnimals : an open access journal from MDPI2024

Use of 18-Fluorodeoxyglucose Positron Emission Tomography and Near-Infrared Fluorescence-Guided Imaging Surgery in the Treatment of a Gastric Tumor in a Dog.

Su-Hyeon Kim, Yeon Chae, Byeong-Teck Kang, Sungin Lee

Abstract readCase Reports
In one paragraph

Article in Animals : an open access journal from MDPI, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

4 authors.

Su-Hyeon KimDepartment of Veterinary Surgery, College of Veterinary Medicine, Chungbuk National University, Cheongju 28644, Republic of Korea.
Yeon ChaeLaboratory of Veterinary Internal Medicine, College of Veterinary Medicine, Chungbuk National University, Cheongju 28644, Republic of Korea.
Byeong-Teck KangLaboratory of Veterinary Internal Medicine, College of Veterinary Medicine, Chungbuk National University, Cheongju 28644, Republic of Korea.
Sungin LeeDepartment of Veterinary Surgery, College of Veterinary Medicine, Chungbuk National University, Cheongju 28644, Republic of Korea.ORCID 0000-0003-4976-7467

Funding

National Research Foundation of Korea RS-2023-00253736, 2021RIS-001
6 · The paper itself

Abstract

A 13-year-old Maltese dog with an abdominal mass underwent 18F-FDG PET/computed tomography (CT) for tumor localization and metastatic evaluation. PET/CT scans revealed a gastric mass near the esophagogastric junction and demonstrated mean and maximum standardized uptake values (SUVs) of 4.596 and 6.234, respectively, for the abdominal mass. Subsequent surgery incorporated ICG for NIR fluorescence-guided imaging, aiding in precise tumor localization and margin assessment. The excised mass was identified as a low-grade leiomyosarcoma on histopathology. The dog underwent PET/CT imaging six months postoperatively following the excision of the mass, which confirmed the absence of recurrence or residual lesions during follow-up. NIR fluorescence imaging using ICG demonstrated efficacy in real-time tumor visualization and margin assessment, a technique not previously reported in veterinary literature. The PET/CT findings complemented the diagnosis and provided valuable insights into metastasis. The absence of recurrence or complications in postoperative follow-up underscores the potential of these imaging modalities in enhancing surgical precision and improving prognosis in canine gastric tumors.

Indexed as

caninedogfluorodeoxyglucosegastric tumorindocyanine greenleiomyosarcomanear-infraredpositron emission tomography/computed tomography

Identifiers

PMID39457847
PMCPMC11503833

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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.