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Low-dose computed tomography with 4th-generation iterative reconstruction algorithm in assessment of oncologic patients

Authors :
Alessandra Casiraghi
Sandro Sironi
Franca Meloni
Cammillo Talei Franzesi
Davide Ippolito
Davide Fior
Ippolito, D
Casiraghi, A
TALEI FRANZESI, C
Fior, D
Meloni, F
Sironi, S
Source :
World Journal of Gastrointestinal Oncology
Publication Year :
2017
Publisher :
Baishideng Publishing Group Inc, 2017.

Abstract

AIM To compare radiation dose and image quality of low-dose computed tomography (CT) protocol combined with hybrid-iterative reconstruction algorithm with standard-dose CT examinations for follow-up of oncologic patients. METHODS Fifty-one patients with known malignant diseases which underwent, during clinical follow-up, both standard-dose and low-dose whole-body CT scans were enrolled. Low-dose CT was performed on 256-row scanner, with 120 kV and automated mA modulation, and iterative reconstruction algorithm. Standard-dose CT was performed on 16-rows scanner, with 120 kV, 200-400 mAs (depending on patient weight). We evaluated density values and signal-to-noise ratio, along with image noise (SD), sharpness and diagnostic quality with 4-point scale. RESULTS Density values in liver, spleen and aorta were higher in low-dose images (liver 112.55 HU vs 103.90 HU, P < 0.001), as SD values in liver and spleen (liver 16.81 vs 14.41). Volumetric-Computed-Tomographic-Dose-Index (CTDIvol) and Dose-Length-Product (DLP) were significantly lower in low-dose CT as compared to standard-dose (DLP 1025.6 mGy*cm vs 1429.2 mGy*cm, P < 0.001) with overall dose reduction of 28.9%. Qualitative analysis did not reveal significant differences in image noise and diagnostic quality. CONCLUSION Automatic tube-current modulation combined with hybrid-iterative algorithm allows radiation dose reduction of 28.9% without loss of diagnostic quality, being useful in reducing dose exposure in oncologic patients.

Details

Language :
English
ISSN :
19485204
Volume :
9
Issue :
10
Database :
OpenAIRE
Journal :
World Journal of Gastrointestinal Oncology
Accession number :
edsair.doi.dedup.....5df50fda4200dc7845a41e320ec96482