Evidence map›Paper›PMID 34557925›Full record

ArticleRadiation protection dosimetry2021

OPTIMIZATION OF LUNG CT PROTOCOL FOR THE DIAGNOSTIC EVALUATION OF COVID-19 LUNG DISEASE.

Seyed Mohammad Bagher Hosseini Nasab, Mohammad Reza Deevband, Roghaye Rahimi, Saeed Nasiri, Mohammad Reza Ahangaran, Mina Morshedi

Open access · bronzeAbstract read
In one paragraph

Article in Radiation protection dosimetry, 2021. 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
0.4field-weighted citation impact, top 37% 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, 3 citations in OpenAlex.

  1. Article
  2. COVID-19 pneumonia: lessons learned, challenges, and preparing for the future.Diagnostic and interventional radiology (Ankara, Turkey) · 2022
    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

6 authors at 1 institution in 1 country.

Seyed Mohammad Bagher Hosseini NasabRadiology Department, Taleghani Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.ORCID 0000-0001-7292-1499
Mohammad Reza DeevbandDepartment of Medical Physics and Biomedical engineering, Faculty of Medicine, Shahid Beheshti University of Medical Sciences and Health Services, Tehran, Iran.
Roghaye RahimiRadiology Department, Loghman Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Saeed NasiriFaculty of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Mohammad Reza AhangaranRadiology Department, Nikan Hospital, Tehran, Iran.
Mina MorshediRadiology Department, Taleghani Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Shahid Beheshti University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study intends to evaluate the different lung CT scan protocols used for the diagnostic evaluation of COVID-19-induced lung disease in Iranian imaging centers in terms of radiation dose and image quality. After data collecting, subjective image quality, radiation dose and objective image quality such as noise, SNR and CNR were assessed. Statistically significant differences in effective dose and image quality were evident among different lung CT protocols. Lowest and highest effective dose was1.31 ± 0.53 mSv related to a protocol with activated AEC (reference mAs = 20) and 6.15 ± 0.57 mSv related to a protocol with Fixed mAs (mAs = 100), respectively. A protocol with enabled tube current modulation with 70 mAs as a reference mAs, and protocol with 20 mAs and enabled AEC had the best and lowest image quality, respectively. To optimize the scan parameters, AEC must be used, and a range of tube currents (between 20 and 50 mAs) can produce acceptable images in terms of diagnostic quality and radiation dose for the diagnosis of COVID-19-induced lung disease.

Indexed as

COVID-19Lung DiseasesHumansIranLungRadiation DosageSARS-CoV-2Tomography, X-Ray Computed

Identifiers

PMID34557925
PMCPMC8500036
OpenAlexW3199702415

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.