Late-xerostomia prediction model based on F-FDG PET image biomarkers of the main salivary glands.

Background And Purpose: Recently, a comprehensive xerostomia prediction model was published, based on baseline xerostomia, mean dose to parotid glands (PG) and submandibular glands (SMG). Previously, PET imaging biomarkers (IBMs) of PG were shown to improve xerostomia prediction. Therefore, this study aimed to explore the potential improvement of the additional PET-IBMs from both PG and SMG to the recent comprehensive xerostomia prediction model (i.

An efficient strategy to select head and neck cancer patients for adaptive radiotherapy.

Background And Purpose: Adaptive radiotherapy (ART) is workload intensive but only benefits a subgroup of patients. We aimed to develop an efficient strategy to select candidates for ART in the first two weeks of head and neck cancer (HNC) radiotherapy.

Materials And Methods: This study retrospectively enrolled 110 HNC patients who underwent modern photon radiotherapy with at least 5 weekly in-treatment re-scan CTs.

Validation of the F-FDG PET image biomarker model predicting late xerostomia after head and neck cancer radiotherapy.

Background And Purpose: Previously, PET image biomarkers (PET-IBMs) - the 90 percentile standardized uptake value (P90-SUV) and the Mean SUV (Mean-SUV) of the contralateral parotid gland (cPG) - were identified as predictors for late-xerostomia following head and neck cancer (HNC) radiotherapy. The aim of the current study was to assess in an independent validation cohort whether these pre-treatment PET-IBM can improve late-xerostomia prediction compared to the prediction with baseline xerostomia and mean cPG dose alone.

Materials And Methods: The prediction endpoint was patient-rated moderate-to-severe xerostomia at 12 months after radiotherapy.

The relation between prediction model performance measures and patient selection outcomes for proton therapy in head and neck cancer.

Background: Normal-tissue complication probability (NTCP) models predict complication risk in patients receiving radiotherapy, considering radiation dose to healthy tissues, and are used to select patients for proton therapy, based on their expected reduction in risk after proton therapy versus photon radiotherapy (ΔNTCP). Recommended model evaluation measures include area under the receiver operating characteristic curve (AUC), overall calibration (CITL), and calibration slope (CS), whose precise relation to patient selection is still unclear. We investigated how each measure relates to patient selection outcomes.

Impact of sarcopenia on acute radiation-induced toxicity in head and neck cancer patients.

Background And Purpose: Sarcopenia is related to late radiation-induced toxicities and worse survival in head and neck cancer (HNC) patients. This study tested the hypothesis that sarcopenia improves the performance of current normal tissue complication probability (NTCP) models of radiation-induced acute toxicity in HNC patients.

Material/methods: This was a retrospective analysis in a prospective cohort of HNC patients treated from January 2007 to December 2018 with (chemo)radiotherapy.

Quality of life and toxicity guided treatment plan optimisation for head and neck cancer.

Purpose: To evaluate the feasibility of semi-automatic Quality of Life (QOL)-weighted normal tissue complication probability (NTCP)-guided VMAT treatment plan optimisation in head and neck cancer (HNC) and compare predicted QOL to that obtained with conventional treatment.

Materials And Methods: This study included 30 HNC patients who were treated with definitive radiotherapy. QOL-weighted NTCP-guided VMAT plans were optimised directly on 80 multivariable NTCP models of 20 common toxicities and symptoms on 4 different time points (6, 12, 18 and 24 months after radiotherapy) and each NTCP model was weighted relative to its impact on QOL.

Patient-Reported Toxicity and Quality-of-Life Profiles in Patients With Head and Neck Cancer Treated With Definitive Radiation Therapy or Chemoradiation.

Purpose: Radiation therapy is an effective but burdensome treatment for head and neck cancer (HNC). We aimed to characterize the severity and time pattern of patient-reported symptoms and quality of life in a large cohort of patients with HNC treated with definitive radiation therapy, with or without systemic treatment.

Methods And Materials: A total of 859 patients with HNC treated between 2007 and 2017 prospectively completed the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-Head and Neck Cancer module (QLQ-HN35) and Core Quality of Life Questionnaire (QLQ-C30) at regular intervals during and after treatment for up to 5 years.

Impact of radiation-induced toxicities on quality of life of patients treated for head and neck cancer.

Purpose: The aim of this study is to establish the relative impact of physician-rated toxicities and patient-rated symptoms in head and neck cancer (HNC) on quality of life (QOL) and to weigh the various toxicities and symptoms during treatment plan optimization and selection.

Materials And Methods: This prospective cohort study comprised 1083 HNC patients (development: 750, validation: 333) treated with definitive radiotherapy with or without chemotherapy. Clinical factors were scored at baseline.

Risk of ischaemic cerebrovascular events in head and neck cancer patients is associated with carotid artery radiation dose.

Background And Purpose: Radiotherapy in the head and neck area may cause vascular damage to the carotid arteries, increasing the risk of anterior circulation ischaemic cerebrovascular events (ICVEs). However, limited data exists on the relationship between radiation dose to the carotid arteries and risk of ICVE. The purpose of this study was therefore to determine the relationship between radiation dose to the carotid arteries and anterior circulation ICVE risk.

Comprehensive toxicity risk profiling in radiation therapy for head and neck cancer: A new concept for individually optimised treatment.

Background And Purpose: A comprehensive individual toxicity risk profile is needed to improve radiation treatment optimisation, minimising toxicity burden, in head and neck cancer (HNC) patients. We aimed to develop and externally validate NTCP models for various toxicities at multiple time points.

Materials And Methods: Using logistic regression, we determined the relationship between normal tissue irradiation and the risk of 22 toxicities at ten time points during and after treatment in 750 HNC patients.

Key challenges in normal tissue complication probability model development and validation: towards a comprehensive strategy.

Normal Tissue Complication Probability (NTCP) models can be used for treatment plan optimisation and patient selection for emerging treatment techniques. We discuss and suggest methodological approaches to address key challenges in NTCP model development and validation, including: missing data, non-linear response relationships, multicollinearity between predictors, overfitting, generalisability and the prediction of multiple complication grades at multiple time points. The methodological approaches chosen are aimed to improve the accuracy, transparency and robustness of future NTCP-models.

Impact of sarcopenia on survival and late toxicity in head and neck cancer patients treated with radiotherapy.

Background And Purpose: Sarcopenia is emerging as an adverse prognostic factor for survival and complication risk in cancer patients. This study aims to determine the impact of sarcopenia on survival and late toxicity in a large cohort of head and neck squamous cell carcinoma (HNSCC) patients treated with definitive (chemo)radiotherapy ((C)RT).

Materials And Methods: HNSCC patients treated with definitive (C)RT from January 2007 to June 2016 were included.

Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring.

Introduction: Adequate head and neck (HN) organ-at-risk (OAR) delineation is crucial for HN radiotherapy and for investigating the relationships between radiation dose to OARs and radiation-induced side effects. The automatic contouring algorithms that are currently in clinical use, such as atlas-based contouring (ABAS), leave room for improvement. The aim of this study was to use a comprehensive evaluation methodology to investigate the performance of HN OAR auto-contouring when using deep learning contouring (DLC), compared to ABAS.

Is there a different dose-effect relation between the primary tumor and involved lymph nodes in locally advanced non-small-cell lung cancer? A hypothesis-generating study.

Purpose: It is unknown whether the dose-response relation of the primary tumor in NSCLC is different from that of the involved lymph nodes (LN). As the recurrence rate is much lower in LN, we hypothesized that LN need a lower radiation dose.

Material And Methods: A retrospective analysis of prospective data was performed on patients with locally advanced NSCLC treated with (chemo)radiotherapy.