Evidence map›Paper›PMID 37510183›Full record

ReviewDiagnostics (Basel, Switzerland)2023

Medical Radiology: Current Progress.

Alessia Pepe, Filippo Crimì, Federica Vernuccio, Giulio Cabrelle, Amalia Lupi, Chiara Zanon, Sebastiano Gambato, Anna Perazzolo, Emilio Quaia

Open access · goldAbstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2023. 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
3.9field-weighted citation impact, top 6% 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, 17 citations in OpenAlex.

  1. Pooled it
  2. Review
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  4. Article
  5. Article
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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

9 authors at 2 institutions in 1 country.

Alessia PepeInstitute of Radiology, University Hospital of Padua-DIMED, Padua University Hospital, University of Padua, 35122 Padua, Italy.ORCID 0000-0001-6401-3829
Filippo CrimìInstitute of Radiology, University Hospital of Padua-DIMED, Padua University Hospital, University of Padua, 35122 Padua, Italy.ORCID 0000-0001-6822-1430
Federica VernuccioDepartment of Radiology, University Hospital of Padua, 35128 Padua, Italy.ORCID 0000-0003-0350-1794
Giulio CabrelleDepartment of Radiology, University Hospital of Padua, 35128 Padua, Italy.ORCID 0000-0002-9430-1036
Amalia LupiInstitute of Radiology, University Hospital of Padua-DIMED, Padua University Hospital, University of Padua, 35122 Padua, Italy.ORCID 0000-0002-0743-9214
Chiara ZanonInstitute of Radiology, University Hospital of Padua-DIMED, Padua University Hospital, University of Padua, 35122 Padua, Italy.ORCID 0000-0002-7917-5027
Sebastiano GambatoInstitute of Radiology, University Hospital of Padua-DIMED, Padua University Hospital, University of Padua, 35122 Padua, Italy.
Anna PerazzoloInstitute of Radiology, University Hospital of Padua-DIMED, Padua University Hospital, University of Padua, 35122 Padua, Italy.
Emilio QuaiaInstitute of Radiology, University Hospital of Padua-DIMED, Padua University Hospital, University of Padua, 35122 Padua, Italy.ORCID 0000-0003-2020-9365
University of Padua · ITUniversity of Udine · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, medical radiology has undergone significant improvements in patient management due to advancements in image acquisition by the last generation of machines, data processing, and the integration of artificial intelligence. In this way, cardiovascular imaging is one of the fastest-growing radiological subspecialties. In this study, a compressive review was focused on addressing how and why CT and MR have gained a I class indication in most cardiovascular diseases, and the potential impact of tissue and functional characterization by CT photon counting, quantitative MR mapping, and 4-D flow. Regarding rectal imaging, advances in cancer imaging using diffusion-weighted MRI sequences for identifying residual disease after neoadjuvant chemoradiotherapy and [18F] FDG PET/MRI were provided for high-resolution anatomical and functional data in oncological patients. The results present a large overview of the approach to the imaging of diffuse and focal liver diseases by US elastography, contrast-enhanced US, quantitative MRI, and CT for patient risk stratification. Italy is currently riding the wave of these improvements. The development of large networks will be crucial to create high-quality databases for patient-centered precision medicine using artificial intelligence. Dedicated radiologists with specific training and a close relationship with the referring clinicians will be essential human factors.

Indexed as

cardiovascular imagingcomputed tomographyliver imagingmagnetic resonance imagingrectal imagingultrasound

Identifiers

PMID37510183
PMCPMC10378672
OpenAlexW4385202595

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.