Automatic volume delineation in oncological PET. Evaluation of a dedicated software tool and comparison with manual delineation in clinical data sets.
OBJECTIVE
Evaluation of a dedicated software tool for automatic delineation of 3D regions of interest in oncological PET.


METHODS
The applied procedure encompasses segmentation of user-specified subvolumes within the tomographic data set into separate 3D ROIs, automatic background determination, and local adaptive thresholding of the background corrected data. Background correction and adaptive thresholding are combined in an iterative algorithm. Nine experienced observers used this algorithm for automatic delineation of a total of 37 ROIs in 14 patients. Additionally, the observers delineated the same ROIs also manually (using a freely chosen threshold for each ROI) and the results of automatic and manual ROI delineation were compared.


RESULTS
For the investigated 37 ROIs the manual delineation shows a strong interobserver variability of (26.8±6.3)% (range: 15% to 45%) while the corresponding value for automatic delineation is (1.1±1.0)% (range: <0.1% to 3.6%). The fractional deviation of the automatic volumes from the observer-averaged manual ones is (3.7±12.7)%.


CONCLUSIONS
The evaluated software provides results in very good agreement with observer-averaged manual evaluations, facilitates and accelerates the volumetric evaluation, eliminates the problem of interobserver variability and appears to be a useful tool for volumetric evaluation of oncological PET in clinical routine.
PET Center, Institute of Radiopharmacy, Helmholtz-Zentrum Dresden-Rossendorf, Germany. hofheinz@hzdr.de
F
F
Hofheinz
C
C
Pötzsch
L
L
Oehme
B
B
Beuthien-Baumann
J
J
Steinbach
J
J
Kotzerke
J
J
van den Hoff
D000328:Adult; D000368:Aged; D000465:Algorithms; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000000981:diagnostic imaging*; D015588:Observer Variation; D010363:Pattern Recognition, Automated / Q000379:methods*; D049268:Positron-Emission Tomography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity