Risk-based treatment optimisation to reduce radiation-induced toxicity in head and neck cancer patients

Radiotherapy plays an important role in the treatment of head and neck cancer (HNC) patients. However, the tumour cannot be adequately radiated without irradiating healthy normal tissue as well. Irradiation of healthy tissues results in numerous toxicities (e.g., xerostomia (dry mouth syndrome) or severe swallowing problems) that significantly impair their quality of life. New radiotherapy treatment techniques, like protons, enable a more precise irradiation of the tumour, thereby reducing the radiation dose to these healthy tissues. The main challenge is how to arrive at the 3D dose distribution that cures patients with the lowest toxicity burden. This process requires detailed information on the relationship between the 3D dose distribution and the risk of toxicities. This relationship is described in multivariable prediction models, commonly referred to as Normal Tissue Complication Probability (NTCP) models. In this thesis we developed and validated a comprehensive set of NTCP models that predict the risk of various common radiation-induced toxicities. Together these NTCP models converge into a corresponding risk profile, the Comprehensive Individual Toxicity Risk (CITOR) profile. It provides new insight into the involvement of healthy tissues in the development of toxicities, indicating which healthy tissues are more important to spare. The oral cavity appears to be the predominant healthy tissue that is associated with multiple toxicities and should therefore be spared with a high priority. Some of the NTCP models of this CITOR profile are currently used nationally in clinical practice to optimise the dose distribution and to select HNC patients for proton therapy

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 1,083 HNC patients (development: 750, validation: 333) treated with definitive radiotherapy with or without chemotherapy. Clinical factors were scored at baseline. Physician-rated and patient-rated outcome measures and QOL (EORTC QLQ-HN35 and QLQ-C30) were prospectively scored at baseline and 6, 12, 18 and 24 months after radiotherapy. The impact of 20 common toxicities and symptoms (related to swallowing, salivary function, speech, pain and general complaints) on QOL (0-100 scale) was established for each time point by combining principal component analysis and multivariable linear regression. RESULTS: Radiation-induced toxicities and symptoms resulted in a significant decline in QOL of patients with 12.4±12.8 points at 6 months to 16.6±17.1 points at 24 months. The multivariable linear models described the QOL points subtracted for each toxicity and symptom after radiotherapy. For example, xerostomia and weight loss had a significant but minor effect (on average -0.5 and -0.6 points) while speech problems and fatigue had a much greater impact (on average -11.9 and -17.4 points) on QOL. R2 goodness-of-fit values for the QOL models ranged from 0.64 (6 months) to 0.72 (24 months). CONCLUSION: The relative impact of physician-rated toxicities and patient-rated symptoms on QOL was quantified and can be used to optimize, compare and select HNC radiotherapy treatment plans, to balance the relevance of toxicities and to achieve the best QOL for individual patients

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. A semi auto-segmentation method was applied to obtain the weekly mean dose (D mean) to OARs. A comprehensive NTCP-profile was applied to obtain NTCP's. The difference between planning and actual values of D mean (ΔD mean) and dichotomized difference of clinical relevance (BIOΔNTCP) were used for modelling to determine the cut-off maximum ΔD mean of OARs in week 1 and 2 (maxΔD mean_1 and maxΔD mean_2). Four strategies to select candidates for ART, using cut-off maxΔD mean were compared. RESULTS: The Spearman's rank correlation test showed significant positive correlation between maxΔD mean and BIOΔNTCP (p-value &lt;0.001). For major BIOΔNTCP (&gt;5%) of acute and late toxicity, 10.9% and 4.5% of the patients were true candidates for ART. Strategy C using both cut-off maxΔD mean_1 (3.01 and 5.14 Gy) and cut-off maxΔD mean_2 (3.41 and 5.30 Gy) showed the best sensitivity, specificity, positive and negative predictive values (0.92, 0.82, 0.38, 0.99 for acute toxicity and 1.00, 0.92, 0.38, 1.00 for late toxicity, respectively). CONCLUSIONS: We propose an efficient selection strategy for ART that is able to classify the subgroup of patients with &gt;5% BIOΔNTCP for late toxicity using imaging in the first two treatment weeks.</p

Clinical and MRI responses to etanercept in early non-radiographic axial spondyloarthritis : 48-week results from the EMBARK study

Objective: To evaluate the efficacy and safety of etanercept (ETN) after 48 weeks in patients with early active non-radiographic axial spondyloarthritis (nr-axSpA). Methods: Patients meeting Assessment of SpondyloArthritis international Society (ASAS) classification criteria for axSpA, but not modified New York radiographic criteria, received double-blind ETN 50 mg/week or placebo (PBO) for 12 weeks, then open-label ETN (ETN/ETN or PBO/ETN). Clinical, health, productivity, MRI and safety outcomes were assessed and the 48-week data are presented here. Results: 208/225 patients (92%) entered the open-label phase at week 12 (ETN, n=102; PBO, n=106). The percentage of patients achieving ASAS40 increased from 33% to 52% between weeks 12 and 48 for ETN/ETN and from 15% to 53% for PBO/ETN (within-group p value <0.001 for both). For ETN/ETN and PBO/ETN, the EuroQol 5 Dimensions utility score improved by 0.14 and 0.08, respectively, between baseline and week 12 and by 0.23 and 0.22 between baseline and week 48. Between weeks 12 and 48, MRI Spondyloarthritis Research Consortium of Canada sacroiliac joint (SIJ) scores decreased by -1.1 for ETN/ETN and by -3.0 for PBO/ETN, p<0.001 for both. Decreases in MRI SIJ inflammation and C-reactive protein correlated with several clinical outcomes at weeks 12 and 48. Conclusions: Patients with early active nr-axSpA demonstrated improvement from week 12 in clinical, health, productivity and MRI outcomes that was sustained to 48 weeks

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. Planning results, NTCP and predicted QOL were compared with the clinical conventional VMAT plans. RESULTS: QOL-weighted NTCP-guided VMAT plans were clinically acceptable, had target coverage equally adequate as the clinical plans, but prioritised sparing of organs at risk (OAR) related to toxicities and symptoms that had the highest impact on QOL. NTCP was reduced for, e.g., dysphagia (-6.1% for ≥ grade 2/ -7.6% for ≥ grade 3) and moderate-to-severe fatigue / speech problems / hoarseness (-0.7%/ -1.5%/ -2.5%) at 6 months, respectively. Concurrently, the average NTCP of toxicities related to salivary function increased with +0.4% to +5.7%. QOL-weighted NTCP-guided plans were produced in less time, were less dependent on the treatment planner experience and yielded more consistent results. The average predicted QOL improved by 0.7, 0.9, 1.0, and 1.1 points on a 0-100 scale (p < 0.001) at 6, 12, 18, and 24 months, respectively, compared to the clinical plans. CONCLUSION: Semi-automatic QOL-weighted NTCP-guided VMAT treatment plan optimisation is feasible. It prioritised sparing of OARs related to high-impact toxicities and symptoms and resulted in a systematic improvement of predicted QOL compared to conventional VMAT

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. Planning CT scans were used for evaluating skeletal muscle mass. Characteristics of sarcopenic and non-sarcopenic patients were compared. The impact of sarcopenia was analysed by adding sarcopenia to the linear predictors of current NTCP models predicting physician- and patient-rated acute toxicities. Results: The cut-off values of sarcopenia in the study population (n = 977) were established at skeletal muscle index = 2, p = 3 dysphagia (week 3-6 during RT, p 0.99). Conclusion: Sarcopenia in HNC patients was an independent prognostic factor for radiation-induced physician-rated acute grade >= 3 dysphagia, which might be explained by its impact on swallowing muscles. However, addition of sarcopenia did not improve the NTCP model performance. (c) 2022 The Author(s). Published by Elsevier B.V. Radiotherapy and Oncology 170 (2022) 122-128 This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)

The VIRUS-P Exploration of Nearby Galaxies (VENGA): Spatially resolved gas-phase metallicity distributions in barred and unbarred spirals

We present a study of the excitation conditions and metallicity of ionized gas (Zgas) in eight nearby barred and unbarred spiral galaxies from the VIRUS-P Exploration of Nearby Galaxies (VENGA) survey, which provides high spatial sampling and resolution (median ∼387 pc), large coverage from the bulge to outer disc, broad wavelength range (3600–6800 Å), and medium spectral resolution (∼120 km s−1 at 5000 Å). Our results are: (1) We present high resolution gas excitation maps to differentiate between regions with excitation typical of Seyfert, LINER, or recent star formation. We find LINER-type excitation at large distances (3–10 kpc) from the centre, and associate this excitation with diffuse ionized gas (DIG). (2) After excluding spaxels dominated by Seyfert, LINER, or DIG, we produce maps with the best spatial resolution and sampling to date of the ionization parameter q, star formation rate, and Zgas using common strong line diagnostics. We find that isolated barred and unbarred spirals exhibit similarly shallow Zgas profiles from the inner kpc out to large radii (7–10 kpc or 0.5–1.0 R25). This implies that if profiles had steeper gradients at earlier epochs, then the present-day bar is not the primary driver flattening gradients over time. This result contradicts earlier claims, but agrees with recent IFU studies. (3) The Zgas gradients in our z ∼ 0 massive spirals are markedly shallower, by ∼0.2 dex kpc−1, than published gradients for lensed lower mass galaxies at z ∼ 1.5–2.0. Cosmologically motivated hydrodynamical simulations best match this inferred evolution, but the match is sensitive to adopted stellar feedback prescriptions

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. METHODS: The DLC neural network was trained on 589 HN cancer patients. DLC was compared to ABAS by providing each method with an independent validation cohort of 104 patients, which had also been manually contoured. For each of the 22 OAR contours - glandular, upper digestive tract and central nervous system (CNS)-related structures - the dice similarity coefficient (DICE), and absolute mean and max dose differences (|Δmean-dose| and |Δmax-dose|) performance measures were obtained. For a subset of 7 OARs, an evaluation of contouring time, inter-observer variation and subjective judgement was performed. RESULTS: DLC resulted in equal or significantly improved quantitative performance measures in 19 out of 22 OARs, compared to the ABAS (DICE/|Δmean dose|/|Δmax dose|: 0.59/4.2/4.1 Gy (ABAS); 0.74/1.1/0.8 Gy (DLC)). The improvements were mainly for the glandular and upper digestive tract OARs. DLC significantly reduced the delineation time for the inexperienced observer. The subjective evaluation showed that DLC contours were more often preferable to the ABAS contours overall, were considered to be more precise, and more often confused with manual contours. Manual contours still outperformed both DLC and ABAS; however, DLC results were within or bordering the inter-observer variability for the manual edited contours in this cohort. CONCLUSION: The DLC, trained on a large HN cancer patient cohort, outperformed the ABAS for the majority of HN OARs

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. The toxicities involved swallowing, salivary, mucosal, speech, pain and general complaints. Studied pre-dictors included patient, tumour and treatment characteristics and dose parameters of 28 organs. The resulting NTCP models were externally validated in 395 HNC patients. Results: The NTCP models involved 14 organs that were associated with at least one toxicity. The oral cavity was the predominant organ, associated with 12 toxicities. Other important organs included the parotid and submandibular glands, buccal mucosa and swallowing muscles. In addition, baseline toxicity, treatment modality, and tumour site were common predictors of toxicity. The median discrimination performance (AUC) of the models was 0.71 (interquartile range: 0.68-0.75) at internal validation and 0.67 (interquartile range: 0.62-0.71) at external validation. Conclusion: We established a comprehensive individual toxicity risk profile that provides essential insight into how radiation exposure of various organs translates into multiple acute and late toxicities. This comprehensive understanding of radiation-induced toxicities enables a new radiation treatment optimisation concept that balances multiple toxicity risks simultaneously and minimises the overall tox-icity burden for an individual HNC patient who needs to undergo radiation treatment. (C) 2021 The Author(s). Published by Elsevier B.V