Evidence map›Paper›PMID 27663257›Full record

ReviewLung2016

Advances in Imaging and Automated Quantification of Pulmonary Diseases in Non-neoplastic Diseases.

Fernanda Balbinot, Álvaro da Costa Batista Guedes, Douglas Zaione Nascimento, Juliana Fischman Zampieri, Giordano Rafael Tronco Alves, Edson Marchiori, Adalberto Sperb Rubin, Bruno Hochhegger

Open access · greenAbstract readReview
PubMed Publisher
In one paragraph

Review in Lung, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 26% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
  2. 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

8 authors at 2 institutions in 1 country.

Fernanda BalbinotFederal University of Health Sciences of Porto Alegre, Porto Alegre, Brazil. balbinotf@gmail.com.ORCID 0000-0002-5881-5267
Álvaro da Costa Batista GuedesIrmandade Santa Casa de Misericórdia de Porto Alegre, LABIMED - Laboratório de Pesquisas em Imagens Médicas, Rua Prof. Annes Dias, 28, Centro, Porto Alegre, RS, 90020090, Brazil.
Douglas Zaione NascimentoIrmandade Santa Casa de Misericórdia de Porto Alegre, LABIMED - Laboratório de Pesquisas em Imagens Médicas, Rua Prof. Annes Dias, 28, Centro, Porto Alegre, RS, 90020090, Brazil.
Juliana Fischman ZampieriIrmandade Santa Casa de Misericórdia de Porto Alegre, LABIMED - Laboratório de Pesquisas em Imagens Médicas, Rua Prof. Annes Dias, 28, Centro, Porto Alegre, RS, 90020090, Brazil.
Giordano Rafael Tronco AlvesFederal University of Rio de Janeiro, Rua Thomaz Cameron, 43, Valparaíso, Petrópolis, RJ, 25685120, Brazil.
Edson MarchioriFederal University of Rio de Janeiro, Rua Thomaz Cameron, 43, Valparaíso, Petrópolis, RJ, 25685120, Brazil.
Adalberto Sperb RubinIrmandade Santa Casa de Misericórdia de Porto Alegre, LABIMED - Laboratório de Pesquisas em Imagens Médicas, Rua Prof. Annes Dias, 28, Centro, Porto Alegre, RS, 90020090, Brazil.
Bruno HochheggerIrmandade Santa Casa de Misericórdia de Porto Alegre, LABIMED - Laboratório de Pesquisas em Imagens Médicas, Rua Prof. Annes Dias, 28, Centro, Porto Alegre, RS, 90020090, Brazil.
Universidade Federal do Rio de Janeiro · BRUniversidade Federal de Ciências da Saúde de Porto Alegre · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Histological examination has always been the gold standard for the detection and quantification of lung remodeling. However, this method has some limitations regarding the invasiveness of tissue acquisition. Quantitative imaging methods enable the acquisition of valuable information on lung structure and function without the removal of tissue from the body; thus, they are useful for disease identification and follow-up. This article reviews the various quantitative imaging modalities used currently for the non-invasive study of chronic obstructive pulmonary disease, asthma, and interstitial lung diseases. Some promising computer-aided diagnosis methods are also described.

Indexed as

Magnetic Resonance ImagingAsthmaHumansImaging, Three-DimensionalLung Diseases, InterstitialPulmonary Disease, Chronic ObstructiveTomography, X-Ray ComputedAutomated quantificationBenign diseasePulmonary diseaseQuantitative method

Identifiers

PMID27663257
OpenAlexW2522383864

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.