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Retrospective Analysis of 1118 Outpatient Chest CT Scans to Determine Factors Associated with Excess Scan Length

Overview
Journal Clin Imaging
Publisher Elsevier
Specialty Radiology
Date 2020 Mar 23
PMID 32200203
Citations 4
Authors
Affiliations
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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.

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References
1.
Kalra M, Maher M, Toth T, Hamberg L, Blake M, Shepard J . Strategies for CT radiation dose optimization. Radiology. 2004; 230(3):619-28. DOI: 10.1148/radiol.2303021726. View

2.
Brenner D, Doll R, Goodhead D, Hall E, Land C, Little J . Cancer risks attributable to low doses of ionizing radiation: assessing what we really know. Proc Natl Acad Sci U S A. 2003; 100(24):13761-6. PMC: 283495. DOI: 10.1073/pnas.2235592100. View

3.
Mascalchi M, Sali L . Lung cancer screening with low dose CT and radiation harm-from prediction models to cancer incidence data. Ann Transl Med. 2017; 5(17):360. PMC: 5599275. DOI: 10.21037/atm.2017.06.41. View

4.
Cardis E, Vrijheid M, Blettner M, Gilbert E, Hakama M, Hill C . The 15-Country Collaborative Study of Cancer Risk among Radiation Workers in the Nuclear Industry: estimates of radiation-related cancer risks. Radiat Res. 2007; 167(4):396-416. DOI: 10.1667/RR0553.1. View

5.
. The ALARA (as low as reasonably achievable) concept in pediatric CT intelligent dose reduction. Multidisciplinary conference organized by the Society of Pediatric Radiology. August 18-19, 2001. Pediatr Radiol. 2002; 32(4):217-313. DOI: 10.1007/s00247-002-0665-z. View