BACKGROUND AND PURPOSE: Head and neck cancer can cause substantial morbidity and mortality. Our aim was to evaluate the potential usefulness of a computerized system for segmenting lesions in head and neck CT scans and for estimation of volume change of head and neck malignant tumors in response to treatment. MATERIALS AND METHODS: CT scans from a pretreatment examination and a post 1-cycle chemotherapy examination of 34 patients with 34 head and neck primary-site cancers were collected. The computerized system was developed in our laboratory. It performs 3D segmentation on the basis of a level-set model and uses as input an approximate bounding box for the lesion of interest. The 34 tumors included tongue, tonsil, vallecula, supraglottic, epiglottic, and hard palate carcinomas. As a reference standard, 1 radiologist outlined full 3D contours for each of the 34 primary tumors for both the pre- and posttreatment scans and a second radiologist verified the contours. RESULTS: The correlation between the automatic and manual estimates for both the pre- to post-treatment volume change and the percentage volume change for the 34 primary-site tumors was 0.95, with an average error of -2.4 ± 8.5% by automatic segmentation. There was no substantial difference and specific trend in the automatic segmentation accuracy for the different types of primary head and neck tumors, indicating that the computerized segmentation performs relatively robustly for this application. CONCLUSIONS: The tumor size change in response to treatment can be accurately estimated by the computerized segmentation system relative to radiologists' manual estimations for different types of head and neck tumors.
|Original language||English (US)|
|Number of pages||8|
|Journal||American Journal of Neuroradiology|
|State||Published - Oct 2010|
ASJC Scopus subject areas
- Radiology Nuclear Medicine and imaging
- Clinical Neurology