Impact of metal artifact reduction algorithm on gross tumor volume delineation in tonsillar cancer: reducing the interobserver variation.

Background: Patients with tonsillar cancer (TC) often have dental fillings that can significantly degrade the quality of computed tomography (CT) simulator images due to metal artifacts. We evaluated whether the use of the metal artifact reduction (MAR) algorithm reduced the interobserver variation in delineating gross tumor volume (GTV) of TC.

Methods: Eighteen patients with TC with dental fillings were enrolled in this study. Contrast-enhanced CT simulator images were reconstructed using the conventional (CT) and MAR algorithm (CT). Four board-certified radiation oncologists delineated the GTV of primary tumors using routine clinical data first on CT image datasets (GTV), followed by CT and CT fused image datasets (GTV) at least 2 weeks apart. Intermodality differences in GTV values and Dice similarity coefficient (DSC) were compared using Wilcoxon's signed-rank test.

Results: GTV was significantly smaller than GTV for three observers. The other observer showed no significant difference between GTV and GTV values. For all four observers, the mean GTV and GTV values were 14.0 (standard deviation [SD]: 7.4) cm and 12.1 (SD: 6.4) cm, respectively, with the latter significantly lower than the former (p < 0.001). The mean DSC of GTV and GTV was 0.74 (SD: 0.10) and 0.77 (SD: 0.10), respectively, with the latter significantly higher than that of the former (p < 0.001).

Conclusions: The use of the MAR algorithm led to the delineation of smaller GTVs and reduced interobserver variations in delineating GTV of the primary tumors in patients with TC.