Evidence map›Paper›PMID 28779403›Full record

ArticleEuropean radiology2018

CT Perfusion evaluation of gastric cancer: correlation with histologic type.

Dong Ho Lee, Se Hyung Kim, Ijin Joo, Joon Koo Han

Abstract read
PubMed Publisher
In one paragraph

Article in European radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
1.5field-weighted citation impact, top 18% of its field
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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.

  1. Pooled it
  2. Global trends in artificial intelligence applications for gastric cancer prediction, treatment, and management: a topic modeling and bibliometric analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
    Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Article
  10. Detection of gastric cancer and its histological type based on iodine concentration in spectral CT.Cancer imaging : the official publication of the International Cancer Imaging Society · 2018
    Article
  11. 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 at 2 institutions in 1 country.

Dong Ho LeeDepartment of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Korea.
Se Hyung KimDepartment of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Korea. shkim7071@gmail.com.
Ijin JooDepartment of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Korea.
Joon Koo HanDepartment of Radiology, Seoul National University Hospital, 101 Daehangno, Jongno-gu, Seoul, 110-744, Korea.
Seoul National University Hospital · KRSeoul National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo prospectively evaluate if the perfusion parameters of gastric cancer can provide information on histologic subtypes of gastric cancer.

methodsWe performed preoperative perfusion CT (PCT) and curative gastrectomy in 46 patients. PCT data were analysed using a dedicated software program. Perfusion parameters were obtained by two independent radiologists and were compared according to histologic type using Kruskal-Wallis, Mann-Whitney U test and receiver operating characteristic analysis. To assess inter-reader agreement, we used intraclass correlation coefficient (ICC).

resultsInter-reader agreement for perfusion parameters was moderate to substantial (ICC = 0.585-0.678). Permeability surface value of poorly cohesive carcinoma (PCC) was significantly higher than other histologic types (47.3 ml/100 g/min in PCC vs 26.5 ml/100 g/min in non-PCC, P < 0.001). Mean transit time (MTT) of PCC was also significantly longer than non-PCC (13.0 s in PCC vs 10.3 s in non-PCC, P = 0.032). The area under the curve to predict PCC was 0.891 (P < 0.001) for permeability surface and 0.697 (P = 0.015) for MTT.

conclusionObtaining perfusion parameters from PCT was feasible in gastric cancer patients and can aid in the preoperative imaging diagnosis of PCC-type gastric cancer as the permeability surface and MTT value of PCC type gastric cancer were significantly higher than those of non-PCC. KEY POINTS: • Obtaining perfusion parameters from PCT was feasible in patients with gastric cancer. • Permeability surface and MTT were significantly higher in poorly cohesive carcinoma (PCC). • Permeability surface, MTT can aid in the preoperative imaging diagnosis of PCC.

Indexed as

Neoplasm StagingAgedDiagnosis, DifferentialFemaleHumansMaleMiddle AgedROC CurveStomach NeoplasmsTomography, X-Ray ComputedHistologic type of gastric cancerMean transit timePerfusion CTPermeability surfacePoorly cohesive carcinoma

Identifiers

PMID28779403
OpenAlexW2742439998

What OpenQuestion holds

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Registered trials

None linked

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.