Evidence map›Paper›PMID 21964707›Full record

ReviewFrontiers of medicine2011

Multislice computed tomography angiography in the diagnosis of cardiovascular disease: 3D visualizations.

Zhonghua Sun

Abstract readReview
PubMed Publisher
In one paragraph

Review in Frontiers of medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 16 citations in OpenAlex.

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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

1 author at 1 institution in 1 country.

Zhonghua SunDiscipline of Medical Imaging, Department of Imaging and Applied Physics, Curtin University, Perth, Western Australia, Australia. z.sun@curtin.edu.au
Curtin University · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multislice computed tomography (CT) has been widely used in clinical practice for the diagnosis of cardiovascular disease due to its reduced invasiveness and high spatial and temporal resolution. As a reliable alternative to conventional angiography, multislice CT angiography has been recognized as the method of choice for detecting and diagnosing head and neck vascular disease, abdominal aortic aneurysm, aortic dissection, and pulmonary embolism. In patients with suspected coronary artery disease, although invasive coronary angiography still remains as the gold standard technique, multislice CT angiography demonstrates high diagnostic accuracy; in selected patients, it is considered as the first-line technique. The imaging diagnosis of cardiovascular disease is based on a combination of two-dimensional (2D) and three-dimensional (3D) visualization tools to enhance the diagnostic value. This is facilitated by reconstructed visualizations which provide additional information about the extent of the disease, an accurate assessment of the spatial relationship between normal structures and pathological changes, and pre-operative planning and post-procedure follow-up. The aim of the present article is to present an overview of the diagnostic performance of various 2D and 3D CT visualizations in cardiovascular disease, including multiplanar reformation, maximum intensity projection, volume rendering, and virtual intravascular endoscopy. The recognition of the potential value of these visualizations will assist clinicians in efficiently using the multislice CT imaging modality for the diagnostic management of patients with cardiovascular disease.

Indexed as

AngiographyCardiovascular DiseasesHumansImaging, Three-DimensionalMultidetector Computed Tomography

Identifiers

PMID21964707
OpenAlexW1975194302

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.