Evidence map›Paper›PMID 38184772›Full record

ReviewKorean journal of radiology2024

Imaging Evaluation of Peritoneal Metastasis: Current and Promising Techniques.

Chen Fu, Bangxing Zhang, Tiankang Guo, Junliang Li

Open access · hybridAbstract readReview
In one paragraph

Review in Korean journal of radiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
11.5field-weighted citation impact, top 1% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.

  1. Guideline
  2. Article
  3. Article
  4. Article
  5. Effect of neoadjuvant chemotherapy on [European journal of nuclear medicine and molecular imaging · 2026
    Article
  6. Review
  7. Article
  8. Review
  9. Comparison between [EJNMMI research · 2026
    Article
  10. Diagnostic Efficacy of FAPI-PET/CT Versus [Diagnostics (Basel, Switzerland) · 2026
    Review
  11. Review
  12. Review
  13. Review
  14. Article
  15. Article
  16. Article
  17. Review
  18. Characteristics ofCancer imaging : the official publication of the International Cancer Imaging Society · 2025
    Article
  19. Article
  20. 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 3 institutions in 1 country.

Chen FuThe First School of Clinical Medical, Gansu University of Chinese Medicine, Lanzhou, Gansu, China.ORCID 0000-0001-8442-7500
Bangxing ZhangSchool of Clinical Medicine, Ningxia Medical University, Yinchuan, Ningxia, China.ORCID 0009-0006-0520-9438
Tiankang GuoDepartment of General Surgery, Gansu Provincial Hospital, Lanzhou, Gansu, China.ORCID 0000-0001-8556-3870
Junliang LiThe First School of Clinical Medical, Gansu University of Chinese Medicine, Lanzhou, Gansu, China.ORCID 0000-0002-3076-9115
Gansu University of Traditional Chinese Medicine · CNGansu Provincial Hospital · CNNingxia Medical University · CN

Funding

CAMS 2019PT320005CAMS NHCDP2022028Education Science of Gansu Province GHB1859GUCM 2020KCYB-7Key Laboratory of Molecular Diagnostics and Precision Medicine for Surgical Oncology in Gansu Province 2020GSZDSYS02Longyuan Youth Innovation and Entrepreneurship Talent Project 111266548053Research Fund project of Gansu Provincial Hospital 22GSSYB-14Research Fund project of Gansu Provincial Hospital 22GSSYC-1Teaching Research and Reform comprehensive project of Gansu University of Traditional Chinese Medicin ZHXM-202207
6 · The paper itself

Abstract

Early diagnosis, accurate assessment, and localization of peritoneal metastasis (PM) are essential for the selection of appropriate treatments and surgical guidance. However, available imaging modalities (computed tomography [CT], conventional magnetic resonance imaging [MRI], and 18fluorodeoxyglucose positron emission tomography [PET]/CT) have limitations. The advent of new imaging techniques and novel molecular imaging agents have revealed molecular processes in the tumor microenvironment as an application for the early diagnosis and assessment of PM as well as real-time guided surgical resection, which has changed clinical management. In contrast to clinical imaging, which is purely qualitative and subjective for interpreting macroscopic structures, radiomics and artificial intelligence (AI) capitalize on high-dimensional numerical data from images that may reflect tumor pathophysiology. A predictive model can be used to predict the occurrence, recurrence, and prognosis of PM, thereby avoiding unnecessary exploratory surgeries. This review summarizes the role and status of different imaging techniques, especially new imaging strategies such as spectral photon-counting CT, fibroblast activation protein inhibitor (FAPI) PET/CT, near-infrared fluorescence imaging, and PET/MRI, for early diagnosis, assessment of surgical indications, and recurrence monitoring in patients with PM. The clinical applications, limitations, and solutions for fluorescence imaging, radiomics, and AI are also discussed.

Indexed as

Artificial IntelligencePeritoneal NeoplasmsHumansOptical ImagingPositron Emission Tomography Computed TomographyTomography, X-Ray ComputedTumor MicroenvironmentArtificial intelligenceDeep learningDiagnostic imagingMachine learningMolecular imagingOptical imagingPeritoneal neoplasmsRadiomics

Identifiers

PMID38184772
PMCPMC10788608
OpenAlexW4390487034

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

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.