Evidence map›Paper›PMID 33552601›Full record

ArticleRadiology research and practice2021

Dosimetry and Comparison between Different CT Protocols (Low Dose, Ultralow Dose, and Conventional CT) for Lung Nodules' Detection in a Phantom.

Cleverson Alex Leitão, Gabriel Lucca de Oliveira Salvador, Priscilla Tazoniero, Danny Warszawiak, Cristian Saievicz, Rosangela Requi Jakubiak, Dante Luiz Escuissato

Abstract read
In one paragraph

Article in Radiology research and practice, 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
–field-weighted citation impact
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.

  1. Article
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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

7 authors.

Cleverson Alex LeitãoDepartment of Radiology, Universidade Federal do Paraná, Curitiba, Paraná, Brazil.
Gabriel Lucca de Oliveira SalvadorDepartment of Radiology, Universidade Federal do Paraná, Curitiba, Paraná, Brazil.ORCID https://orcid.org/0000-0001-9776-6851
Priscilla TazonieroDepartment of Radiology, Universidade Federal do Paraná, Curitiba, Paraná, Brazil.
Danny WarszawiakDepartment of Radiology, Universidade Federal do Paraná, Curitiba, Paraná, Brazil.
Cristian SaieviczDepartment of Radiology, Universidade Federal do Paraná, Curitiba, Paraná, Brazil.
Rosangela Requi JakubiakUniversidade Tecnológica Federal do Paraná, Curitiba, Paraná, Brazil.
Dante Luiz EscuissatoDepartment of Radiology, Universidade Federal do Paraná, Curitiba, Paraná, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe effects of dose reduction in lung nodule detection need better understanding. PURPOSE: To compare the detection rate of simulated lung nodules in a chest phantom using different computed tomography protocols, low dose (LD), ultralow dose (ULD), and conventional (CCT), and to quantify their respective amount of radiation. MATERIALS AND

methodsA chest phantom containing 93 simulated lung nodules was scanned using five different protocols: ULD (80 kVp/30 mA), LD A (120 kVp/20 mA), LD B (100 kVp/30 mA), LD C (120 kVp/30 mA), and CCT (120 kVp/automatic mA). Four chest radiologists analyzed a selected image from each protocol and registered in diagrams the nodules they detected. Kruskal-Wallis and McNemar's tests were performed to determine the difference in nodule detection. Equivalent doses were estimated by placing thermoluminescent dosimeters on the surface and inside the phantom.

resultsThere was no significant difference in lung nodules' detection when comparing ULD and LD protocols (

conclusionThere is no significant difference in simulated lung nodules' detection when comparing ULD and LD protocols, but both differ from CCT, especially when considering lower-attenuating nodules.

Identifiers

PMID33552601
PMCPMC7847358

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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.