The feasibility study of atlas-based autosegmentation (ABAS) software in head-and-neck cancer / 中华放射肿瘤学杂志

ABSTRACT

Objective To test and evaluate the geometric accuracy of delineation of organs at risk ( OARs) in head and neck cancer using an atlas?based autosegmentation ( ABAS) software. Methods The atlases for the ABAS software was generated using images from 40 patients with head and neck cancer undergoing intensity?modulated radiotherapy. The software was tested in 40 new patients. Automatic delineation of OARs was carried out on computed tomography images by single?( one to one ) and multi?template ( ten to one) approaches. In order to evaluate the feasibility of the automatic delineation in clinical application, differences in volume (ΔV%), position (Δx,Δy, andΔz), conformability (sensitivity ( Se ), specificity ( Sp ) , and dice similarity coefficient ( DSC) ) , and delineation time were assessed between the automatic and manual delineation. The comparison between the two automatic delineation approaches was made by paried t test. Results For all OARs, the multi?template automatic delineation achieved a significantly smaller mean ΔV% value and a significantly larger mean DSC value than the single?template automatic delineation (-0.02%± 0?29% vs. -0.16%± 0?41%, P<0?05;0.74± 0?16 vs. 0.68± 0?20, P<0?05);the position differences between two automatic delineation approaches were less than 0?4 cm in all three directions except for the temporal lobe, lower jaw, and spinal cord;in the receiver operating characteristic curve defined by Se versus 1-Sp , the data points were all within the first quadrant except for the optic nerve and chiasm;automatic delineation saved 42%?72% of time compared with manual delineation. Conclusions The ABAS software achieves satisfactory results of automatic delineation for most of OARs in patients with head and neck cancer. The multi?template automatic delineation, particularly, has better outcomes than the single?template one. In addition, it greatly shortens the time the clinicians spend on delineation of OARs.