Evidence map›Paper›PMID 35265467›Full record

ArticleJournal of medical signals and sensors

Image Quality and Pulmonary Nodule Detectability at Low-dose Computed Tomography (low kVp and mAs): A phantom study.

Sepideh Iranmakani, Amir Reza Jahanshahi, Parinaz Mehnati, Tohid Mortezazadeh, Davood Khezerloo

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Article in Journal of medical signals and sensors. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

5 authors.

Sepideh IranmakaniDepartment of Radiology, Faculty of Allied Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran.
Amir Reza JahanshahiDepartment of Radiology, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
Parinaz MehnatiDepartment of Medical Physics, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
Tohid MortezazadehDepartment of Medical Physics, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
Davood KhezerlooDepartment of Radiology, Faculty of Allied Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Nowadays, there has been a growing demand for low-dose computed tomography (LDCT) protocols. CT has a critical role in the management of the diagnosis chain of pulmonary disease, especially in lung cancer screening. There have been introduced several dose reduction methods, however, most of them are time-consuming, intricate, and vendor-based strategies that are hardly used in clinics routinely. This study aims to evaluate the image quality and pulmonary nodule detectability of LDCT protocols that are feasible and easy implemented. Image quality was analyzed in a general quality control phantom (Gammex) and then in a manmade lung phantom with nodules-equivalent objects. Methods: This study was designed in a two steps, in the first step, a feasible low-dose lung CT protocol was selected with quality assessment of accreditation phantom image. In the second step, the selected low-dose protocol with an appropriate image quality was performed on a manmade lung phantom in which there were objects equivalent to the pulmonary nodule. Finally, image quality parameters of the phantom at the appropriate scan protocol were compared with the standard protocol. Results: A reduction of about 17% of kVp and 46% in tube current leads to dose reduction by about 70%. The contrast-to-noise ratio in the low-dose protocol remained almost unchanged. The signal-to-noise ratio in the low-dose protocol decreased by approximately 32%, and the noise level has increased by about 1.5 times. However, this reduction method hardly affected the detectability of nodules in man-made pulmonary phantom. Conclusions: Here, we demonstrated that the LDCT scan has an insignificant effect on the perception of lung nodules. In this study, patient dose in lung CT was reduced by modifying of kVp and mAs about approximately 70%. Hence, to step in toward low-dose strategies in medical imaging clinics, using easy-implemented and feasible low-dose strategies may be helpful.

Indexed as

Computed tomographyimage qualitylow-dose radiationlung cancer screening

Identifiers

PMID35265467
PMCPMC8804592

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