Evidence map›Paper›PMID 40005897›Full record

ArticleVeterinary sciences2025

Early Enhancement in Contrast-Enhanced Computed Tomography Is an Index of

Toshiyuki Tanaka, Tomoki Motegi, Nanami Sumikawa, Misaki Mori, Shohei Kurokawa, Hideo Akiyoshi

Abstract read
In one paragraph

Article in Veterinary sciences, 2025. 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

6 authors.

Toshiyuki TanakaLaboratory of Veterinary Advanced Diagnosis and Treatment, School of Veterinary Science, Osaka Metropolitan University, Osaka 5988531, Japan.ORCID 0000-0002-7911-913X
Tomoki MotegiSection of Computational Biomedicine, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA.ORCID 0000-0002-6811-0973
Nanami SumikawaLaboratory of Veterinary Surgery, School of Veterinary Science, Osaka Metropolitan University, Osaka 5988531, Japan.
Misaki MoriLaboratory of Veterinary Surgery, School of Veterinary Science, Osaka Metropolitan University, Osaka 5988531, Japan.
Shohei KurokawaLaboratory of Veterinary Advanced Diagnosis and Treatment, School of Veterinary Science, Osaka Metropolitan University, Osaka 5988531, Japan.
Hideo AkiyoshiLaboratory of Veterinary Advanced Diagnosis and Treatment, School of Veterinary Science, Osaka Metropolitan University, Osaka 5988531, Japan.

Funding

JSPS KAKENHI 22K05991
6 · The paper itself

Abstract

Canine hepatocellular carcinoma (HCC) is characterized by distinct computed tomography (CT) findings. HCC exhibits tumor heterogeneity, with different genomic information and histopathological features within the same tumor. In human HCC, genetic alterations affect the prognosis and treatment, and research has begun to assess genetic alterations using minimally invasive and reproducible CT. However, the relationship between CT findings and the genomic information of canine HCC is unknown. Early contrast of HCC indicates increased intratumoral neovascular growth. In this study, we aimed to investigate the relationship between enhancement patterns in the arterial phase of CT imaging and gene expression in canine HCC using RNA sequencing. Based on the CT findings, three of the eight dogs studied were classified as having enhancement HCC and five as having non-enhancement HCC. RNA sequencing was performed using the mRNA extracted from the specimens. Eight differentially expressed genes met the cutoff criteria. Among these,

Indexed as

dogHCCliverradiogenomicsRNA sequence

Identifiers

PMID40005897
PMCPMC11860268

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.