Adaptive iterative dose reduction 3D (AIDR 3D) vs. filtered back projection: radiation dose reduction capabilities of wide volume and helical scanning techniques on area-detector CT in a chest phantom study.
BACKGROUND
Computed tomography (CT) has important roles for lung cancer screening, and therefore radiation dose reduction by using iterative reconstruction technique and scanning methods receive widespread attention.


OBJECTIVE
To evaluate the effect of two reconstruction techniques (filtered back projection [FBP] and adaptive iterative dose reduction using three-dimensional processing [AIDR 3D]) and two acquisition techniques (wide-volume scan [WVS] and helical scan as 64-detector-row CT [64HS]) on the lung nodule identifications of using a chest phantom.


METHODS
A chest CT phantom including lung nodules was scanned using WVS and 64HS at nine different tube currents (TCs; range, 270-10 mA). All CT datasets were reconstructed with AIDR 3D and FBP. Standard deviation (SD) measurements by region of interest placement and qualitative nodule identifications were statistically compared. 64HS and WVS were evaluated separately, and FBP images acquired with 270 mA was defined as the standard reference.


RESULTS
SDs of all datasets with AIDR 3D showed no significant differences (P > 0.05) with standard reference. When comparing nodule identifications, area under the curve on WVS with AIDR 3D with TC <30 mA, on 64HS with AIDR 3D with TC <40 mA, and on reconstructions with FBP and each scan method with TC <60 mA was significantly lower than with standard reference (P < 0.05). With the same TC and reconstruction, SDs and nodule identifications of WVS were not significantly different from 64HS (P > 0.05).


CONCLUSIONS
In term of SD of lung parenchyma and nodule identification, AIDR 3D can achieve more radiation dose reduction than FBP and there is no significant different between WVS and 64HS.
Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan.
Shinichiro
S
Seki
Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan hkoyama@med.kobe-u.ac.jp.
Hisanobu
H
Koyama
Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Kobe, Japan Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan.
Yoshiharu
Y
Ohno
Advanced Biomedical Imaging Research Center, Kobe University Graduate School of Medicine, Kobe, Japan Division of Functional and Diagnostic Imaging Research, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan.
Sumiaki
S
Matsumoto
Toshiba Medical Systems Corporations, Otawara, Japan.
Hiroyasu
H
Inokawa
Toshiba Medical Systems Corporations, Otawara, Japan.
Naoki
N
Sugihara
Division of Radiology, Department of Radiology, Kobe University Graduate School of Medicine, Kobe, Japan.
Kazuro
K
Sugimura
D006801:Humans; D021621:Imaging, Three-Dimensional; D008168:Lung / Q000000981:diagnostic imaging; D019047:Phantoms, Imaging; D011829:Radiation Dosage; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed
Lung; computed tomography (CT); iterative reconstruction technique; radiation dose