Reduced radiation-induced toxicity by using proton therapy for the treatment of oropharyngeal cancer

Patients with squamous cell carcinoma of the oropharynx are generally treated with (chemo) radiation. Patients with oropharyngeal cancer have better survival than patients with squamous cell carcinoma of other head and neck subsites, especially when related to human papillomavirus. However, radiotherapy results in a substantial percentage of survivors suffering from significant treatment-related side-effects. Late radiation-induced side-effects are mostly irreversible and may even be progressive, and particularly xerostomia and dysphagia affect health-related quality of life. As the risk of radiation-induced side-effects highly depends on dose to healthy normal tissues, prevention of radiation-induced xerostomia and dysphagia and subsequent improvement of health-relatedquality of life can be obtained by applying proton therapy, which offers the opportunity to reduce the dose to both the salivary glands and anatomic structures involved in swallowing.This review describes the results of the first cohort studies demonstrating that proton therapy results in lower dose levels in multiple organs at risk, which translates into reduced acute toxicity (i.e. up to 3 months after radiotherapy), while preserving tumour control. Next to reducing mucositis, tube feeding, xerostomia and distortion of the sense of taste, protons can improve general well-being by decreasing fatigue and nausea. Proton therapy results in decreased rates of tube feeding dependency and severe weight loss up to 1 year after radiotherapy, and may decrease the risk of radionecrosis of the mandible. Also, the model-based approach for selecting patients for proton therapy in the Netherlands is described in this review and future perspectives are discussed

Evaluation of CBCT-based synthetic CTs for clinical adoption in proton therapy of head & neck patients.:E-Poster

PurposeIn adaptive proton therapy, weekly verification CTs (rCTs) are commonly acquired and used to monitor patient anatomy. Cone-Beam CTs (CBCT) on the other hand are used for daily pre-treatment position verification. These CBCT images however suffer from severe imaging artifacts preventing accurate proton dose calculations, meaning that CBCTs are unsuitable for treatment planning purposes. Recent advances in converting CBCT images to high quality synthetic CTs (sCTs) using Deep Convolution Neural Networks (DCNN) show that these sCTs can be suitable for proton dose calculations and therefore assist clinical adaptation decisions.The aim of this study was to compare weekly high definition rCTs to same-day sCT images of head and neck cancer patients in order to verify dosimetric accuracy of DCNN generated CBCT-based sCTs.Materials and MethodsA dataset of 46 previously treated head and neck cancer patients was used to generate synthetic CTs from daily pre-treatment patient alignment CBCTs using a previously developed and trained U-net like DCNN. Proton dose was then recalculated on weekly rCTs and same-day sCTs utilizing clinical treatment plans. To assess the dosimetric accuracy of sCTs, dose to the clinical target volumes (CTV D98) and mean dose in selected organs-at-risk (OAR; Oral cavity, Parotid gland left, Submandibular gland right) was calculated and compared between rCTs and same-day sCTs. Furthermore, Normal Tissue Complication Probability (NTCP) models for xerostomia and dysphagia were used to assess the clinical significance of dose differences.ResultsFor target volumes, the average difference in D98% between rCT and sCT pairs (N=284) was 0.34±3.86 % [-0.18±2.06 Gy] for the low dose CTV (54.25 Gy) and 0.23±3.62 % [-0.16±2.48 Gy] for the high dose CTV (70 Gy). For the OARs the following mean dose differences were observed; Oral Cavity: 4.15±9.78 % [0.75±1.39 Gy], Parotid L: 5.34±11.6 % [0.58±1.40 Gy], Submandibular R: 2.17±8.55 % [0.55±2.57 Gy]. The average NTCP difference was -0.15±0.58 % for grade 3 dysphagia, -0.26±0.54 % for grade 3 xerostomia, -0.53±1.20 % for grade 2 dysphagia and -0.71±1.40 % for grade 2 xerostomia. ConclusionFor target coverage and NTCP difference, the deep learning based sCTs showed high agreement with weekly verification CTs. However, some outliers were observed (also indicated by the increased standard deviation) and warrant further investigation and improvements before clinical implementation. Furthermore, stringent quality control tools for synthetic CTs are required to allow reliable deployment in adaptive proton therapy workflows.<br/

Objective Acoustic-Phonetic Speech Analysis in Patients Treated for Oral or Oropharyngeal Cancer

Objective: Speech impairment often occurs in patients after treatment for head and neck cancer. New treatment modalities such as surgical reconstruction or (chemo) radiation techniques aim at sparing anatomical structures that are correlated with speech and swallowing. In randomized trials investigating efficacy of various treatment modalities or speech rehabilitation, objective speech analysis techniques may add to improve speech outcome assessment. The goal of the present study is to investigate the role of objective acoustic-phonetic analyses in a multidimensional speech assessment protocol. Patients and Methods: Speech recordings of 51 patients (6 months after reconstructive surgery and postoperative radiotherapy for oral or oropharyngeal cancer) and of 18 control speakers were subjectively evaluated regarding intelligibility, nasal resonance, articulation, and patient-reported speech outcome (speech subscale of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-Head and Neck 35 module). Acoustic-phonetic analyses were performed to calculate formant values of the vowels /a, i, u/, vowel space, air pressure release of /k/ and spectral slope of /x/. Results: Intelligibility, articulation, and nasal resonance were best predicted by vowel space and /k/. Within patients, /k/ and /x/ differentiated tumor site and stage. Various objective speech parameters were related to speech problems as reported by patients. Conclusion: Objective acoustic-phonetic analysis of speech of patients is feasible and contributes to further development of a speech assessment protocol. Copyright (C) 2009 S. Karger AG, Base

Assessment of manual adjustment performed in clinical practice following deep learning contouring for head and neck organs at risk in radiotherapy

Background and purpose: Auto-contouring performance has been widely studied in development and commissioning studies in radiotherapy, and its impact on clinical workflow assessed in that context. This study aimed to evaluate the manual adjustment of auto-contouring in routine clinical practice and to identify improvements regarding the auto-contouring model and clinical user interaction, to improve the efficiency of auto-contouring. Materials and methods: A total of 103 clinical head and neck cancer cases, contoured using a commercial deep-learning contouring system and subsequently checked and edited for clinical use were retrospectively taken from clinical data over a twelve-month period (April 2019–April 2020). The amount of adjustment performed was calculated, and all cases were registered to a common reference frame for assessment purposes. The median, 10th and 90th percentile of adjustment were calculated and displayed using 3D renderings of structures to visually assess systematic and random adjustment. Results were also compared to inter-observer variation reported previously. Assessment was performed for both the whole structures and for regional sub-structures, and according to the radiation therapy technologist (RTT) who edited the contour. Results: The median amount of adjustment was low for all structures (<2 mm), although large local adjustment was observed for some structures. The median was systematically greater or equal to zero, indicating that the auto-contouring tends to under-segment the desired contour. Conclusion: Auto-contouring performance assessment in routine clinical practice has identified systematic improvements required technically, but also highlighted the need for continued RTT training to ensure adherence to guidelines

Prediction of Radiation-Induced Parotid Gland-Related Xerostomia in Patients With Head and Neck Cancer:Regeneration-Weighted Dose

Purpose: Despite improvements to treatment, patients with head and neck cancer (HNC) still experience radiation-induced xerostomia due to salivary gland damage. The stem cells of the parotid gland (PG), concentrated in the gland's main ducts (stem cell rich [SCR] region), play a critical role in the PG's response to radiation. Treatment optimization requires a dose metric that properly accounts for the relative contributions of dose to this SCR region and the PG's remainder (non-SCR region) to the risk of xerostomia in normal tissue complication probability (NTCP) models for xerostomia.Materials and methods: Treatment and toxicity data of 1013 prospectively followed patients with HNC treated with definitive radiation therapy (RT) were used. The regeneration-weighted dose, enabling accounting for the hypothesized different effects of dose to the SCR and non-SCR region on the risk of xerostomia, was defined as Dreg PG = Dmean SCR region + r × Dmean non-SCR region, where Dreg is the regeneration-weighted dose, Dmean is the mean dose, and r is the weighting factor. Considering the different volumes of these regions, r &gt; 3.6 in Dreg PG demonstrates an enhanced effect of the SCR region. The most predictive value of r was estimated in 102 patients of a previously published trial testing stem cell sparing RT. For each endpoint, Dreg PG, dose to other organs, and clinical factors were used to develop NTCP models using multivariable logistic regression analysis in 663 patients. The models were validated in 350 patients.Results: Dose to the contralateral PG was associated with daytime, eating-related, and physician-rated grade ≥2 xerostomia. Consequently, r was estimated and found to be smaller than 3.6 for most PG function-related endpoints. Therefore, the contribution of Dmean SCR region to the risk of xerostomia was larger than predicted by Dmean PG. Other frequently selected predictors were pretreatment xerostomia and Dmean oral cavity. The validation showed good discrimination and calibration.Conclusions: Tools for clinical implementation of stem cell sparing RT were developed: regeneration-weighted dose to the parotid gland that accounted for regional differences in radiosensitivity within the gland and NTCP models that included this new dose metric and other prognostic factors