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Purpose: To externally validate the previously published pre-treatment prediction models for lymph nodes failure after definitive radiotherapy in head and neck squamous cell carcinoma (HNSCC) patients., Materials and Methods: This external validation cohort consisted of 143 node positive HNSCC patients treated between July 2007 and June 2016 by curative radiotherapy with or without either cisplatin or cetuximab. Imaging and pathology reports during follow-up were analyzed to indicate persisting or recurring nodes. The previously established clinical, radiomic and combined models were validated on this cohort by assessing the concordance index (c-index) and model calibration., Results: Overall 113 patients with 374 pLNs were suitable for final analysis. There were 20 (5.3%) nodal failures from 15 patients after a median follow-up of 36.1 months. Baseline characteristics and radiomic features were comparable to the training cohort. Both the radiomic model (Least-axis-length of lymph node (LALLN) and correlation of gray level co-occurrence matrix (Corre-GLCM)) and the combined model (T stage, gender, WHO performance score, LALLN and Corre-GLCM) showed good agreement between predicted and observed nodal control probabilities. The radiomic (c-index: 0.71; 95% confidence interval (CI): 0.59-0.84) and combined (c-index: 0.71; 95% CI: 0.59-0.82) models performed better than the clinical model (c-index: 0.57; 95% CI: 0.47-0.68) on this cohort, with a significant difference between the combined and clinical models (z-score test: p = 0.005)., Conclusion: The combined model including clinical and radiomic features was externally validated and proved useful to predict nodal failures and could be helpful to guide treatment choices before and after curative radiation treatment for node positive HNSCC patients., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background and Purpose: To develop and validate a pre-treatment radiomics-based prediction model to identify pathological lymph nodes (pLNs) at risk of failures after definitive radiotherapy in head and neck squamous cell carcinoma patients., Materials and Methods: Training and validation cohorts consisted of 165 patients with 558 pLNs and 112 patients with 467 pLNs, respectively. All patients were primarily treated with definitive radiotherapy, with or without systemic treatment. The endpoint was the cumulative incidence of nodal failure. For each pLN, 82 pre-treatment CT radiomic features and 7 clinical features were included in the Cox proportional-hazard analysis., Results: There were 68 and 23 nodal failures in the training and validation cohorts, respectively. Multivariable analysis revealed three clinical features (T-stage, gender and WHO Performance-status) and two radiomic features (Least-axis-length representing nodal size and gray level co-occurrence matrix based - Correlation representing nodal heterogeneity) as independent prognostic factors. The model showed good discrimination with a c-index of 0.80 (0.69-0.91) in the validation cohort, significantly better than models based on clinical features (p < 0.001) or radiomics (p = 0.003) alone. High- and low-risk groups were defined by using thresholds of estimated nodal failure risks at 2-year of 60% and 10%, resulting in positive and negative predictive values of 94.4% and 98.7%, respectively., Conclusion: A pre-treatment prediction model was developed and validated, integrating the quantitative radiomic features of individual lymph nodes with generally used clinical features. Using this prediction model, lymph nodes with a high failure risk can be identified prior to treatment, which might be used to select patients for intensified treatment strategies targeted on individual lymph nodes., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Purpose To develop and validate prediction models of overall survival (OS) for head and neck cancer (HNC) patients based on image biomarkers (IBMs) of the primary tumor and positive lymph nodes (Ln) in combination with clinical parameters. Material and methods The study cohort was composed of 289 nasopharyngeal cancer (NPC) patients from China and 298 HNC patients from the Netherlands. Multivariable Cox-regression analysis was performed to select clinical parameters from the NPC and HNC datasets, and IBMs from the NPC dataset. Final prediction models were based on both IBMs and clinical parameters. Results Multivariable Cox-regression analysis identified three independent IBMs (tumor Volume-density, Run Length Non-uniformity and Ln Major-axis-length). This IBM model showed a concordance(c)-index of 0.72 (95%CI: 0.65–0.79) for the NPC dataset, which performed reasonably with a c-index of 0.67 (95%CI: 0.62–0.72) in the external validation HNC dataset. When IBMs were added in clinical models, the c-index of the NPC and HNC datasets improved to 0.75 (95%CI: 0.68–0.82; p = 0.019) and 0.75 (95%CI: 0.70–0.81; p < 0.001), respectively. Conclusion The addition of IBMs from the primary tumor and Ln improved the prognostic performance of the models containing clinical factors only. These combined models may improve pre-treatment individualized prediction of OS for HNC patients. [ABSTRACT FROM AUTHOR]

Purpose: To study the dosimetric difference between fixed-jaw volumetric modulated radiotherapy (FJ-VMAT) and large-field volumetric modulated radiotherapy (LF-VMAT) for nasopharyngeal carcinoma (NPC) with cervical lymph node metastasis. Methods: Computed tomography (CT) datasets of 10 NPC patients undergoing chemoradiotherapy were used to generate LF-VMAT and FJ-VMAT plans in the Eclipse version 10.0 treatment planning system. These two kinds of plans were then compared with respect to planning-target-volume (PTV) coverage, conformity index (CI), homogeneity index (HI), organ-at-risk sparing, monitor units (MUs) and treatment time (TT). Results: The FJ-VMAT plans provided lower D2% of PGTVnd (PTV of lymph nodes), PTV1 (high-risk PTV) and PTV2 (low-risk PTV) than did the LF-VMAT plans, whereas no significant differences were observed in PGTVnx (PTV of primary nasopharyngeal tumor). The FJ-VMAT plans provided lower doses delivered to the planning organ at risk (OAR) volumes (PRVs) of both brainstem and spinal cord, both parotid glands and normal tissue than did the LF-VMAT plans, whereas no significant differences were observed with respect to the oral cavity and larynx. The MUs of the FJ-VMAT plans (683 ± 87) were increased by 22% ± 12% compared with the LF-VMAT plans (559 ± 62). In terms of the TT, no significant difference was found between the two kinds of plans. Conclusions: FJ-VMAT was similar or slightly superior to LF-VMAT in terms of PTV coverage and was significantly superior in terms of OAR sparing, at the expense of increased MUs. [ABSTRACT FROM AUTHOR]