RESUMEN
INTRODUCTION: Accurate segmentation of tumors and quantification of tumor features are important for cancer detection, diagnosis, monitoring, and planning therapeutic intervention. Due to inherent noise components in multi-parametric imaging and inter-observer and intra-observer variations, it is common that various segmentation methods may produce large segmentation errors in tumor volumes and their associated radiomic features. The purpose of this study is to carry out the stability analysis for radiomic features with respect to segmentation variation in oropharyngeal cancer (OPC). METHODS: In this study, 436 contrast-enhanced computed tomography (CT) axial images were collected from patients with OPC. In order to derive various segmentations of tumor volumes, two additional segmentations were obtained via resizing the original segmented regions of interest (ROIs) based on their geometric information on the boundary. For three ROI image groups, we calculated 109 radiomic features. Then, a logistic regression model was built to investigate the correlation between the radiomic features extracted from GTVp and the response to chemotherapy and radiation in terms of overall survival (OS). Finally, in order to evaluate the stability of each feature with respect to segmentation results, based on the prediction probabilities, we assessed the inter-rater reliability and reproducibility by calculating the intra-class correlation coefficients (ICC) and concordance correlation coefficients (CCC). RESULTS: Most radiomic features in this study varied a lot when the ROIs were not well segmented. For both the representation agreement and predictive agreement, the ICC and CCC were below 0.5 for all the features. We still found some robust features with relatively high ICC and CCC compared to most features. For example, 25percentile (ICC = 0.38, CCC = 0.37 in representation agreement and ICC = CCC = 0.27 in predictive agreement) is a quantile based feature, which is robust to the extremely high or low values; and Hu_1_std (ICC = 0.31, CCC = 0.31 in representation agreement) is a feature calculated based on the first Hu moment, which is invariant to the transformation of ROIs. CONCLUSION: In OPC studies, the tumor segmentation variation affects the radiomic features from CT images in terms of both representation and prediction. Some features that are robust to the extreme values or invariant to the transformation of ROIs may be treated as radiomic markers to assist with OPC treatment monitoring and prognostic prediction.
RESUMEN
PURPOSE: We compared mandibular doses and osteoradionecrosis in patients with oropharyngeal cancer after intensity-modulated radiation therapy (IMRT) or intensity-modulated proton therapy (IMPT). METHODS AND MATERIALS: We identified 584 patients who received definitive radiotherapy for oropharyngeal cancer from January 2011 through June 2014 at MD Anderson Cancer Center (534 IMRT and 50 IMPT). The dosimetric variables and osteoradionecrosis were compared with Chi-square test or Fisher's exact test. RESULTS: Median follow-up time for all patients (534 IMRT and IMPT) was 33.8months (33.8months IMRT vs. 34.6months IMPT, P=0.854), and median time to osteoradionecrosis was 11.4months (range 6.74-16.1months). Mandibular doses were lower for patients treated with IMPT (minimum 0.8 vs. 7.3Gy; mean 25.6 vs. 41.2Gy; P<0.001), and osteoradionecrosis rates were lower as well: 2% IMPT (1 grade 1), 7.7% IMRT (12 grade 4, 5 grade 3, 1 grade 2 and 23 grade 1). Osteoradionecrosis location depended on the primary tumor site and high-dose field in the mandible. CONCLUSIONS: Osteoradionecrosis events were significantly associated with higher dose irradiation to mandibular. Use of IMPT minimized excess irradiation of the mandible and consequently reduced the risk of osteoradionecrosis for oropharyngeal cancer.