Quality assurance assessment of diagnostic and radiation therapy-simulation CT image registration for head and neck radiation therapy: anatomic region of interest-based comparison of rigid and deformable algorithms.

PURPOSE: To develop a quality assurance (QA) workflow by using a robust, curated, manually segmented anatomic region-of-interest (ROI) library as a benchmark for quantitative assessment of different image registration techniques used for head and neck radiation therapy-simulation computed tomography (CT) with diagnostic CT coregistration. MATERIALS AND METHODS: Radiation therapy-simulation CT images and diagnostic CT images in 20 patients with head and neck squamous cell carcinoma treated with curative-intent intensity-modulated radiation therapy between August 2011 and May 2012 were retrospectively retrieved with institutional review board approval. Sixty-eight reference anatomic ROIs with gross tumor and nodal targets were then manually contoured on images from each examination. Diagnostic CT images were registered with simulation CT images rigidly and by using four deformable image registration (DIR) algorithms: atlas based, B-spline, demons, and optical flow. The resultant deformed ROIs were compared with manually contoured reference ROIs by using similarity coefficient metrics (ie, Dice similarity coefficient) and surface distance metrics (ie, 95% maximum Hausdorff distance). The nonparametric Steel test with control was used to compare different DIR algorithms with rigid image registration (RIR) by using the post hoc Wilcoxon signed-rank test for stratified metric comparison. RESULTS: A total of 2720 anatomic and 50 tumor and nodal ROIs were delineated. All DIR algorithms showed improved performance over RIR for anatomic and target ROI conformance, as shown for most comparison metrics (Steel test, P < .008 after Bonferroni correction). The performance of different algorithms varied substantially with stratification by specific anatomic structures or category and simulation CT section thickness. CONCLUSION: Development of a formal ROI-based QA workflow for registration assessment demonstrated improved performance with DIR techniques over RIR. After QA, DIR implementation should be the standard for head and neck diagnostic CT and simulation CT allineation, especially for target delineation.

Beam path toxicity in candidate organs-at-risk: assessment of radiation emetogenesis for patients receiving head and neck intensity modulated radiotherapy.

BACKGROUND: To investigate potential dose-response relationship between radiation-associated nausea and vomiting (RANV) reported during radiotherapy and candidate nausea/vomiting-associated regions of interest (CNV-ROIs) in head and neck (HNC) squamous cell carcinomas. METHODS AND MATERIAL: A total of 130 patients treated with IMRT with squamous cell carcinomas of head and neck were evaluated. For each patient, CNV-ROIs were segmented manually on planning CT images. Clinical on-treatment RANV data were reconstructed by a review of the records for all patients. Dosimetric data parameters were recorded from dose-volume histograms. Nausea and vomiting reports were concatenated as a single binary "Any N/V" variable, and as a "CTC-V2+" variable. RESULTS: The mean dose to CNV-ROIs was higher for patients experiencing RANV events. For patients receiving IMRT alone, a dose-response effect was observed with varying degrees of magnitude, at a statistically significant level for the area postrema, brainstem, dorsal vagal complex, medulla oblongata, solitary nucleus, oropharyngeal mucosa and whole brain CNV-ROIs. CONCLUSION: RANV is a common therapy-related morbidity facing patients receiving HNC radiotherapy, and, for those receiving radiotherapy-alone, is associated with modifiable dose to specific CNS structures.