Interobserver-variability of lung nodule volumetry considering different segmentation algorithms and observer training levels.
OBJECTIVE
The aim of this study was to investigate the interobserver variability of CT based diameter and volumetric measurements of artificial pulmonary nodules. A special interest was the consideration of different measurement methods, observer experience and training levels.


METHODS
For this purpose 46 artificial small solid nodules were examined in a dedicated ex-vivo chest phantom with multislice-spiral CT (20 mAs, 120 kV, collimation 16 mm x 0.75 mm, table feed 15 mm, reconstructed slice thickness 1mm, reconstruction increment 0.7 mm, intermediate reconstruction kernel). Two observer groups of different radiologic experience (0 and more than 5 years of training, 3 observers each) analysed all lesions with digital callipers and 2 volumetry software packages (click-point depending and robust volumetry) in a semi-automatic and manually corrected mode. For data analysis the variation coefficient (VC) was calculated in per cent for each group and a Wilcoxon test was used for analytic statistics.


RESULTS
Click-point robust volumetry showed with a VC of <0.01% in both groups the smallest interobserver variability. Between experienced and un-experienced observers interobserver variability was significantly different for diameter measurements (p=0.023) but not for semi-automatic and manual corrected volumetry. A significant training effect was revealed for diameter measurements (p=0.003) and semi-automatic measurements of click-point depending volumetry (p=0.007) in the un-experienced observer group.


CONCLUSIONS
Compared to diameter measurements volumetry achieves a significantly smaller interobserver variance and advanced volumetry algorithms are independent of observer experience.
Bolte
H
H
Department of Diagnostic Radiology, University Hospital Schleswig-Holstein Campus Kiel, Arnold-Heller Strasse 9, 24105 Kiel, Germany. hendrikbolte@rad.uni-kiel.de
Jahnke
T
T
Schäfer
F K W
FK
Wenke
R
R
Hoffmann
B
B
Freitag-Wolf
S
S
Dicken
V
V
Kuhnigk
J M
JM
Lohmann
J
J
Voss
S
S
Knöss
N
N
Heller
M
M
Biederer
J
J
D000465:Algorithms; D000818:Animals; D002138:Calibration; D004195:Disease Models, Animal; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008171:Lung Diseases / Q000000981:diagnostic imaging*; D015588:Observer Variation; D011871:Radiology / Q000193:education*; D011873:Radiology Information Systems; D012984:Software; D013552:Swine; D036542:Tomography, Spiral Computed / Q000379:methods / Q000706:statistics & numerical data*