Evidence map›Paper›PMID 29172671›Full record

ReviewThe British journal of radiology2018

Pulmonary quantitative CT imaging in focal and diffuse disease: current research and clinical applications.

Mario Silva, Gianluca Milanese, Valeria Seletti, Alarico Ariani, Nicola Sverzellati

Open access · hybridAbstract readReview
In one paragraph

Review in The British journal of radiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
5.0field-weighted citation impact, top 4% 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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 49 citations in OpenAlex.

  1. Quantitative computed tomography and predictive modelling for COPD exacerbations.European respiratory review : an official journal of the European Respiratory Society · 2025
    Pooled it
  2. Article
  3. Observational
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  19. Solid Indeterminate Pulmonary Nodules of Less Than 300 mmDiagnostics (Basel, Switzerland) · 2019
    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

5 authors at 1 institution in 1 country.

Mario Silva1 Department of Medicine and Surgery (DiMeC), Section of Radiology, Unit of Surgical Sciences, University of Parma , Parma , Italy.ORCID http://orcid.org/0000-0002-2538-7032
Gianluca Milanese1 Department of Medicine and Surgery (DiMeC), Section of Radiology, Unit of Surgical Sciences, University of Parma , Parma , Italy.
Valeria Seletti1 Department of Medicine and Surgery (DiMeC), Section of Radiology, Unit of Surgical Sciences, University of Parma , Parma , Italy.
Alarico Ariani2 Department of Medicine, Internal Medicine and Rheumatology Unit, University Hospital of Parma , Parma , Italy.
Nicola Sverzellati1 Department of Medicine and Surgery (DiMeC), Section of Radiology, Unit of Surgical Sciences, University of Parma , Parma , Italy.
University of Parma · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The frenetic development of imaging technology-both hardware and software-provides exceptional potential for investigation of the lung. In the last two decades, CT was exploited for detailed characterization of pulmonary structures and description of respiratory disease. The introduction of volumetric acquisition allowed increasingly sophisticated analysis of CT data by means of computerized algorithm, namely quantitative CT (QCT). Hundreds of thousands of CTs have been analysed for characterization of focal and diffuse disease of the lung. Several QCT metrics were developed and tested against clinical, functional and prognostic descriptors. Computer-aided detection of nodules, textural analysis of focal lesions, densitometric analysis and airway segmentation in obstructive pulmonary disease and textural analysis in interstitial lung disease are the major chapters of this discipline. The validation of QCT metrics for specific clinical and investigational needs prompted the translation of such metrics from research field to patient care. The present review summarizes the state of the art of QCT in both focal and diffuse lung disease, including a dedicated discussion about application of QCT metrics as parameters for clinical care and outcomes in clinical trials.

Indexed as

AlgorithmsDiagnosis, Computer-AssistedHumansLung DiseasesTomography, X-Ray Computed

Identifiers

PMID29172671
PMCPMC5965469
OpenAlexW2768452128

What OpenQuestion holds

Textmetadata
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.