Evidence map›Paper›PMID 27648373›Full record

ArticleAmerican journal of nuclear medicine and molecular imaging2016

The benefit of personalized hybrid SPECT/CT pulmonary imaging.

Milan Simanek, Pavel Koranda

Open access · greenAbstract read
In one paragraph

Article in American journal of nuclear medicine and molecular imaging, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 18% 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

3 citing papers in PubMed, 15 citations in OpenAlex.

  1. Article
  2. Review
  3. 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

2 authors at 2 institutions in 1 country.

Milan SimanekDepartment of Nuclear Medicine, Regional Hospital Pelhrimov Czech Republic.
Pavel KorandaDepartment of Nuclear Medicine, University Hospital OlomoucCzech Republic; Faculty of Medicine and Dentistry, Palacky University OlomoucCzech Republic.
University Hospital Olomouc · CZZZN Pelhřimov (Czechia) · CZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hybrid pulmonary imaging in the present day has seen a fusion of various uses of CT scans, including angiography (CTAG), diagnostic CT, low dose CT (LDCT), and perfusion or ventilation scintigraphy in tomographic or planar imaging. Determining the most effective individualized test for the complete diagnostics of patients with pulmonary symptoms for various groups of patients is a major issue. The aim of the present study was to assess the effectiveness of the implementation of hybrid imaging in current methods of nuclear medicine in differential diagnostics of pulmonary embolism (PE). 326 patients were examined for symptomatology of PE. Patients were initially examined with SPECT perfusion scintigraphy. SPECT finding without sub-segmental or segmental defects was considered unproven PE but the finding of more segments or sub-segments in various lung parts was considered nearly proven PE. In the case of unclear findings, LDCT was added and in the case of a higher suspicion of PE, a ventilation examination was applied. It was possible to determine 83% of patients with the occurrence or exclusion of PE only on the basis of the perfusion SPECT examination and an X-ray or LDCT. LDCT was determined with 26% of the patients. With 41% of them, the use of LDCT resulted in an alternative diagnosis, explaining perfusion abnormalities. The research proved that use of SPECT/LDCT for differential diagnosis of lung symptoms brings about improvement in the diagnosis of pulmonary embolism or the identification of other lung diseases when lung perfusion abnormalities are recorded.

Indexed as

hybrid imagingPulmonary embolismSPECT/CTventilation-perfusion scan

Identifiers

PMID27648373
PMCPMC5004063
OpenAlexW2521965146

What OpenQuestion holds

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Registered trials

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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.