Evidence map›Paper›PMID 35681237›Full record

ReviewInfectious agents and cancer2022

Diffusion weighted imaging and diffusion kurtosis imaging in abdominal oncological setting: why and when.

Vincenza Granata, Roberta Fusco, Andrea Belli, Ginevra Danti, Eleonora Bicci, Carmen Cutolo, Antonella Petrillo, Francesco Izzo

Open access · goldAbstract readReview
In one paragraph

Review in Infectious agents and cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

20 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
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  9. Article
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  13. Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response.International journal of molecular sciences · 2023
    Review
  14. Review
  15. Review
  16. Immunotherapy Assessment: A New Paradigm for Radiologists.Diagnostics (Basel, Switzerland) · 2023
    Review
  17. Review
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  19. Article
  20. Review
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 at 3 institutions in 1 country.

Vincenza GranataDivision of Radiology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli", I-80131, Naples, Italy. v.granata@istitutotumori.na.it.
Roberta FuscoMedical Oncology Division, Igea Spa, Naples, Italy.
Andrea BelliDivision of Hepatobiliary Surgical Oncology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli", I-80131, Naples, Italy.
Ginevra DantiDepartment of Radiology, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy.
Eleonora BicciDepartment of Radiology, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy.
Carmen CutoloDepartment of Medicine, Surgery and Dentistry, University of Salerno, Salerno, Italy.
Antonella PetrilloDivision of Radiology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli", I-80131, Naples, Italy.
Francesco IzzoDivision of Hepatobiliary Surgical Oncology, "Istituto Nazionale Tumori IRCCS Fondazione Pascale - IRCCS di Napoli", I-80131, Naples, Italy.
Istituto Nazionale Tumori IRCCS "Fondazione G. Pascale" · ITAzienda Ospedaliero-Universitaria Careggi · ITUniversity of Salerno · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This article provides an overview of diffusion kurtosis (DKI) imaging in abdominal oncology. DKI allows for more data on tissue structures than the conventional diffusion model (DWI). However, DKI requires high quality images at b-values greater than 1000 s/mm

Indexed as

DKIDWIMagnetic resonance imagingOncological setting

Identifiers

PMID35681237
PMCPMC9185934
OpenAlexW4282941202

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.