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Interobserver and intermodality variability in GTV delineation on simulation CT, FDG-PET, and MR Images of Head and
Carryn M Anderson1, Wenqing Sun2, John M Buatti3
1Department of Radiation Oncology, University of Iowa Hospitals and Clinics, Iowa City, Iowa, USA.
Purpose:
To compare the interobserver and intermodality differences in image-based identification of head and neck primary site gross tumor volumes (GTV). Modalities compared include: contrast-enhanced CT, F-18 fluorodeoxyglucose positron emission tomography (PET/CT) and contrast-enhanced MRI.
Methods And Materials:
Fourteen patients were simulated after immobilization for all 3 imaging modalities (CT, PET/CT, MRI). Three radiation oncologists (RO) contoured GTVs as seen on each modality. The GTV was contoured first on the contrast-enhanced CT (considered the standard), then on PET/CT, and finally on post-contrast T1 MRI. Interobserver and intermodality variability were analyzed by volume, intersection, union, and volume overlap ratio (VOR).
Results:
Analysis of RO contours revealed the average volume for CT-, PET/CT-, and MRI-derived GTVs were 45cc, 35cc and 49cc, respectively. In 93% of cases PET/CT-derived GTVs had the smallest volume and in 57% of cases MRI-derived GTVs had the largest volume. CT showed the largest variation in target definition (standard deviation amongst observers 35%) compared to PET/CT (28%) and MRI (27%). The VOR was largest (indicating greatest interobserver agreement) in PET/CT (46%), followed by MRI (36%), followed by CT (34%). For each observer, the least agreement in GTV definition occurred between MRI & PET/CT (average VOR = 41%), compared to CT & PET/CT (48%) and CT & MRI (47%).
Conclusions:
A nonsignificant interobserver difference in GTVs for each modality was seen. Among three modalities, CT was least consistent, while PET/CT-derived GTVs had the smallest volumes and were most consistent. MRI combined with PET/CT provided the least agreement in GTVs generated. The significance of these differences for head & neck cancer is important to explore as we move to volume-based treatment planning based on multi-modality imaging as a standard method for treatment delivery.
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