Image subtraction facilitates assessment of volume and density change in ground-glass opacities in chest CT.
OBJECTIVE
To study the impact of image subtraction of registered images on the detection of change in pulmonary ground-glass nodules identified on chest CT.


METHODS
A cohort of 33 individuals (25 men, 8 women; age range 51-75 years) with 37 focal ground-glass opacities (GGO) were recruited from a lung cancer screening trial. For every participant, 1 to 3 follow-up scans were available (total number of pairs, 84). Pairs of scans of the same nodule were registered nonrigidly and then subtracted to enhance differences in size and density. Four observers rated size and density change of the GGO between pairs of scans by visual comparison alone and with additional availability of a subtraction image and indicated their confidence. An independent experienced chest radiologist served as an arbiter having all reader data, clinical data, and follow-up examinations available. Nodule pairs for which the arbiter could not establish definite progression, regression, or stability were excluded from further evaluation. This left 59 and 58 pairs for evaluation of size and density change, respectively. Weighted kappa statistics (kappa w) were used to assess interobserver agreement and agreement with the arbiter. Statistical significance was tested with a kappa z-test.


RESULTS
When the subtraction image was available, the average interobserver kappa w improved from 0.52 to 0.66 for size change and from 0.47 to 0.57 for density change. Average agreement with the arbiter improved from 0.61 to 0.76 for size change and from 0.53 to 0.64 for density change. The effect was more pronounced when observer confidence without the subtraction image was low: agreement improved from 0.26 to 0.57 and from 0.19 to 0.47 in those cases.


CONCLUSIONS
Image subtraction improves the evaluation of subtle changes in pulmonary ground-glass opacities and decreases interobserver variability.
Staring
Marius
M
Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands. m.staring@lumc.nl
Pluim
Josien P W
JP
de Hoop
Bartjan
B
Klein
Stefan
S
van Ginneken
Bram
B
Gietema
Hester
H
Nossent
George
G
Schaefer-Prokop
Cornelia
C
van de Vorst
Saskia
S
Prokop
Mathias
M
D015502:Absorptiometry, Photon / Q000379:methods; D000368:Aged; D000465:Algorithms; D015331:Cohort Studies; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D055613:Multiple Pulmonary Nodules / Q000000981:diagnostic imaging*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D013902:Radiography, Thoracic / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014057:Tomography, X-Ray Computed / Q000379:methods*