Abstract Book

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two weeks of treatment for day 21 (p=0.01, HR=0.10), and day 28 (p=0.02, HR=0.12).

after radiotherapy (Xer 12m the prediction of Xer 12m . The predictive IBMs indicated heterogeneity and metabolic functionality, subsequently leading to the hypothesis that the fat to functional parenchymal parotid tissue ratio is an important pre- treatment marker in developing Xer 12m . In this study, we tested the hypothesis that the ratio of fat to parenchymal parotid tissue is associated with the development of xerostomia Xer 12m with MR-image biomarkers (MR-IBMs). In addition, we investigated whether prediction of Xer 12m could be improved by adding MR-IBMs to the reference model based on parotid gland dose and baseline xerostomia. Material and Methods Parotid gland MR-IBMs were extracted from pre- treatment T1-weighted MR images of 68 head and neck cancer patients treated at Center A. Patient-rated toxicity was prospectively collected (EORTC QLQ-H&N35). The reference model with mean doses to the parotid glands and baseline xerostomia was fitted to the dataset. Bootstrapped forward selection was performed to select IBMs as additional predictive variables. The performance of the resulting multivariable model was compared with that of the reference model. Ultimately, the performance was explored by externally validating the MR-IBM models in a cohort of 25 patients from Center B. Results High intensity MR-IBM P90 (90 th intensity percentile of parotid histograms in normalized MRI-units) values were significantly associated with a higher risk of Xer 12m . Due to the short T1 relaxation of fat, higher P90 values relate to higher fat concentrations in the parotid glands. MR-IBM significantly added to the reference model in predicting Xer 12m (likelihood-ratio test; p=0.002). The reference model AUC increased from 0.83 to 0.88 (reference model and P90), and this predictor was consistently selected on bootstrap replicates (17.5%). In the external dataset, the MR-IBM model was good (AUC external.val. =0.83), especially compared to the performance of the reference model (AUC external.val. =0.65). Conclusion The results support the hypothesis that the amount of predisposed fat within the parotid glands is associated with Xer 12m . Moreover, pre-treatment MR-IBMs substantially improved prediction accuracy of radiation- induced xerostomia compared to the reference model based on dose and clinical parameters only. ), and significantly improved

Conclusion The study found FDG PET metrics of tumors to have high correlation coefficients over four weeks of imaging with the median tumor slope of TLG being associated with overall survival. In addition, the study demonstrated that differences in overall survival may be found after two weeks of treatment. These results may be useful for future studies when selecting imaging time points and PET metrics for association with outcome in NSCLC patients. OC-0180 Parotid gland fat related Magnetic Resonance Image biomarkers improve prediction of late xerostomia L.V. Van Dijk 1 , M. Thor 2 , R.J.H.M. Steenbakkers 1 , A. Apte 2 , T. Zhai 1 , R. Borra 3 , N. Lee 4 , J.A. Langendijk 1 , J.O. Deasy 2 , N.M. Sijtsema 1 1 University Medical Center Groningen, Radiation oncology, Groningen, The Netherlands 2 Memorial Sloan Kettering Cancer Center, Department of Medical Physics, New York, USA 3 University Medical Center Groningen, Department of Radiology, Groningen, The Netherlands 4 Memorial Sloan Kettering Cancer Center, Department of Radiation Oncology, New York, USA Purpose or Objective Our previous studies showed that image biomarkers (IBMs) of the parotid gland from CT and PET images were associated with a higher risk of xerostomia 12 months