Software-based fusion of PET and CT images for suspected recurrent lung cancer.
OBJECTIVE
The purpose of this study was to compare the diagnostic performance of the manual fusion of positron emission tomography (PET) and computed tomography (CT) images with that of CT alone and that of side-by-side PET and CT (PET/CT) in patients with suspected recurrent lung cancer.


METHODS
Fifty-three patients who had previously had surgery for lung cancer underwent a whole-body 2-deoxy-2-[F-18]fluoro-D-glucose (FDG)-PET scan, followed by a diagnostic CT scan. The PET and CT images were fused on a workstation. CT alone, PET/CT, and fused images were evaluated separately using a five-point grading scale (0=definitely negative, 1=probably negative, 2=equivocal, 3=probably positive, and 4=definitely positive). Lesions of grade 3 or 4 were considered positive, and diagnostic accuracy and certainty were evaluated.


RESULTS
Overall, 67 lesions in 33 patients were considered true positive pathologically or clinically. Of these 67 lesions, the evaluation of CT, PET/CT, and fused images detected 46, 55, and 66 lesions, respectively, with the number of grade 4 lesions detected being 38, 50, and 63, respectively. The diagnostic accuracy of CT, PET/CT, and fused images according to patients was 75%, 79%, and 87%, respectively.


CONCLUSIONS
These results suggest that interpreting fused images increased diagnostic certainty for detecting recurrence and provided more accurate diagnoses.
Nakamoto
Yuji
Y
Department of Diagnostic Radiology, Kyoto University Hospital, Kyoto, Japan. ynakamo1@kuhp.kyoto-u.ac.jp
Senda
Michio
M
Okada
Tomohisa
T
Sakamoto
Setsu
S
Saga
Tsuneo
T
Higashi
Tatsuya
T
Togashi
Kaori
K
D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006801:Humans; D008175:Lung Neoplasms / Q000175:diagnosis*; D008297:Male; D008875:Middle Aged; D009364:Neoplasm Recurrence, Local / Q000175:diagnosis*; D049268:Positron-Emission Tomography / Q000379:methods*; D012680:Sensitivity and Specificity; D012984:Software; D014057:Tomography, X-Ray Computed / Q000379:methods*