Literature DB >> 32200203

Retrospective analysis of 1118 outpatient chest CT scans to determine factors associated with excess scan length.

Stuart L Cohen1, Thomas J Ward2, Alex Makhnevich3, Safiya Richardson3, Matthew D Cham4.   

Abstract

RATIONALE
OBJECTIVES: Excess z-axis scanning continues as an unnecessary source of radiation. This study seeks to determine patient, technologist and CT factors that affect excess scan length for chest CT.
MATERIALS AND METHODS: Retrospective evaluation of 1118 consecutive noncontrast chest CT scans, over twelve consecutive months, was performed for evaluation of scan length above and below the lung parenchyma. Scan length >2 cm was considered excessive. Bivariate analysis for mean excess scan length and presence of excess scan length analyzed technologist's exam volume during the study period, patient age, patient gender, day of week, and time of day as categorical variables. Technologists performing >100 chest CT scans during the study period were considered high-volume while all others were considered low-volume.
RESULTS: Mean excess scan length was 5 mm, 29 mm, and 33 mm above the lungs, below the lungs, and total. 81% and 95% of studies had excess scanning above the lungs and below the lungs respectively. Multivariable analysis showed that high volume technologists, male patients, and patients younger than 65 had a greater amount of excess scan length and presence of excessive scanning above the lungs; high volume technologists and male patients had a greater amount of excess scan length below the lungs, and high volume technologists and patients older than 65 had greater presence of excessive scanning below the lungs, each p < 0.001.
CONCLUSIONS: Excess scanning on chest CT is common, varies by patient age and gender and was significantly greater for high volume technologists.
Copyright © 2020 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Chest CT; Excess scanning; Radiation dose; Technologist

Year:  2020        PMID: 32200203     DOI: 10.1016/j.clinimag.2019.11.020

Source DB:  PubMed          Journal:  Clin Imaging        ISSN: 0899-7071            Impact factor:   1.605


  2 in total

1.  Development of deep learning-assisted overscan decision algorithm in low-dose chest CT: Application to lung cancer screening in Korean National CT accreditation program.

Authors:  Sihwan Kim; Woo Kyoung Jeong; Jin Hwa Choi; Jong Hyo Kim; Minsoo Chun
Journal:  PLoS One       Date:  2022-09-29       Impact factor: 3.752

2.  Automatic Scan Range Delimitation in Chest CT Using Deep Learning.

Authors:  Aydin Demircioğlu; Moon-Sung Kim; Magdalena Charis Stein; Nika Guberina; Lale Umutlu; Kai Nassenstein
Journal:  Radiol Artif Intell       Date:  2021-02-10
  2 in total

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