Iterative active deformational methodology for tumor delineation: Evaluation across radiation treatment stage and volume.
OBJECTIVE
To introduce, implement, and assess an iterative modification to the active deformational image segmentation method as applied to cervical cancer tumors.


METHODS
A comparison by Jaccard similarity (JS) between this active deformational method and manual segmentation was performed on tumors of various sizes across preradiation, 3 weeks postradiation, and 6 weeks postradiation using a General Linear Mixed Model across 121 studies from 52 patients with Stage IIB-IV cervical cancers.


RESULTS
The deformable segmentation method produced promising levels of agreement including JS factors of 0.71+/-0.11 in the preradiation studies. The analysis illustrated a rate of improvement in JS with increasing tumor volume that differed between the preradiation and 6 weeks postradiation stage (P=0.0474). In the large preradiated tumors each additional cm3 of volume was associated with an increase or improvement in JS of 0.0008 (95% confidence interval [CI]: 0.0003, 0.0014). In the smaller postradiation tumors, each additional cm3 of volume was associated with a more robust improvement in JS of 0.0046 (95% CI: 0.0009, 0.0082).


CONCLUSIONS
Agreement was strongly affected by tumor volume, and its performance was most impacted across volume in the later stages of radiation therapy. The deformation-based segmentation method appears to demonstrate utility for delineating cervical cancer tumors, particularly in the earliest stages of radiation treatment, where agreement is greatest.
Wu
D H
DH
Department of Radiological Sciences, Oklahoma University Health Science Center, Oklahoma City, Oklahoma 73104, USA. dee-wu@ouhsc.edu
Shaffer
A D
AD
Thompson
D M
DM
Yang
Z
Z
Magnotta
V A
VA
Alam
R
R
Suri
J
J
Yuh
W T C
WT
Mayr
N A
NA
D000465:Algorithms; D001185:Artificial Intelligence; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008875:Middle Aged; D009367:Neoplasm Staging; D010363:Pattern Recognition, Automated / Q000379:methods*; D011881:Radiotherapy, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016896:Treatment Outcome; D002583:Uterine Cervical Neoplasms / Q000175:diagnosis* / Q000532:radiotherapy*