The Remove-the-Mask Open-Source head and neck Surface-Guided radiation therapy system.

Background and Purpose: Surface Guided Radiotherapy (SGRT) for head and neck radiotherapy is challenging as obstructions are common and non-rigid facial motion can compromise surface accuracy. The purpose of this work was to develop and benchmark the Remove the Mask (RtM) SGRT system, an open-source system especially designed to address the challenges faced in radiotherapy of head and neck cancer. Materials and Methods: The accuracy of the RtM SGRT system was benchmarked using a head phantom positioned on a robotic motion platform capable of sub-millimetre accuracy which was used to induce unidirectional shifts and to reproduce three real head motion traces. We also assessed the accuracy of the system in ten humans volunteers. The ground truth motion of the volunteers was obtained using a commercial motion capture system with an accuracy < 0.3 mm. Results: The mean tracking error of the RtM SGRT system for the ten volunteers was of -0.1 ± 0.4 mm -0.6 ± 0.6 mm and 0.3 ± 0.2 mm, and 0.0 ± 0.2° 0.0 ± 0.1° and 0.0 ± 0.2° for translations and rotations along the left-right, superior-inferior and anterior-posterior axes respectively and we also found similar results in measurements with the head phantom. Forced facial motion was associated with lower tracking accuracy. The RtM SGRT system achieved submillimetre accuracy. Conclusion: The RtM SGRT system is a low-cost, easy to build and open-source SGRT system that can achieve an accuracy that meets international commissioning guidelines. Its open-source and modular design allows for the development and easy translation of novel surface tracking techniques.

Pharyngeal Constrictor Dose-Volume Histogram Metrics and Patient-Reported Dysphagia in Head and Neck Radiotherapy.

AIMS: Head and neck radiotherapy long-term survival continues to improve and the management of long-term side-effects is moving to the forefront of patient care. Dysphagia is associated with dose to the pharyngeal constrictors and can be measured using patient-reported outcomes to evaluate its effect on quality of life. The aim of the present study was to relate pharyngeal constrictor dose-volume parameters with patient-reported outcomes to identify prognostic dose constraints. MATERIALS AND METHODS: A 64-patient training cohort and a 24-patient testing cohort of oropharynx and nasopharynx cancer patients treated with curative-intent chemoradiotherapy were retrospectively examined. These patients completed the MD Anderson Dysphagia Inventory outcome survey at 12 months post-radiotherapy to evaluate late dysphagia: a composite score lower than 60 indicated dysphagia. The pharyngeal constrictor muscles were subdivided into four substructures: superior, middle, inferior and cricopharyngeal. Dose-volume histogram (DVH) metrics for each of the structure combinations were extracted. A decision tree classifier was run for each DVH metric to identify dose constraints optimising the accuracy and sensitivity of the cohort. A 60% accuracy threshold and feature selection method were used to ensure statistically significant DVH metrics were identified. These dose constraints were then validated on the 24-patient testing cohort. RESULTS: Existing literature dose constraints only had two dose constraints performing above 60% accuracy and sensitivity when evaluated on our training cohort. We identified two well-performing dose constraints: the pharyngeal constrictor muscle D63% < 55 Gy and the superior-middle pharyngeal constrictor combination structure V31Gy < 100%. Both dose constraints resulted in ≥73% mean accuracy and ≥80% mean sensitivity on the training and testing patient cohorts. In addition, a pharyngeal constrictor muscle mean dose <57 Gy resulted in a mean accuracy ≥74% and mean sensitivity ≥60%. CONCLUSION: Mid-dose pharyngeal constrictor muscle and substructure combination dose constraints should be used in the treatment planning process to reduce late patient-reported dysphagia.

The impact of radiation caries on morbidity and mortality outcomes of head and neck squamous cell carcinoma patients.

AIMS: Radiation caries (RC) is a highly prevalent and chronic complication of head and neck radiotherapy (HNRT) and presents a challenge for clinicians and patients. The present study aimed to assess the impact of RC on the morbidity and mortality outcomes of head and neck squamous cell carcinoma (HNSCC) patients. METHODS AND RESULTS: Patients were divided into three groups: (1) RC (n = 20), (2) control (n = 20), and (3) edentulous (n = 20). Information regarding the number of appointments, dental procedures, osteoradionecrosis (ORN), prescriptions, and hospital admissions were collected. Mortality outcomes were assessed through disease-free survival (DFS) and overall survival (OS) rates. RC patients required more dental appointments (p < .001), restorations (p < .001), extractions (p = .001), and antibiotic and analgesic prescriptions (p < .001). Kaplan-Meier subgroup analyses showed a significantly increased risk of ORN in RC compared to edentulous patients (p = .015). RC patients presented lower DFS rates (43.2 months) than the control and edentulous groups (55.4 and 56.1 months, respectively). CONCLUSIONS: RC impacts morbidity outcomes among cancer survivors due to increased demand for medication prescriptions, multiple specialized dental appointments, invasive surgical treatments, increased risk of ORN, and increased need for hospital admissions.

Standardizing and improving dose predictions for head and neck cancers using complete sets of OAR contours.

BACKGROUND: Radiotherapy dose predictions have been trained with data from previously treated patients of similar sites and prescriptions. However, clinical datasets are often inconsistent and do not contain the same number of organ at risk (OAR) structures. The effects of missing contour data in deep learning-based dose prediction models have not been studied. PURPOSE: The purpose of this study was to investigate the impacts of incomplete contour sets in the context of deep learning-based radiotherapy dose prediction models trained with clinical datasets and to introduce a novel data substitution method that utilizes automated contours for undefined structures. METHODS: We trained Standard U-Nets and Cascade U-Nets to predict the volumetric dose distributions of patients with head and neck cancers (HNC) using three input variations to evaluate the effects of missing contours, as well as a novel data substitution method. Each architecture was trained with the original contour (OC) inputs, which included missing information, hybrid contour (HC) inputs, where automated OAR contours generated in software were substituted for missing contour data, and automated contour (AC) inputs containing only automated OAR contours. 120 HNC treatments were used for model training, 30 were used for validation and tuning, and 44 were used for evaluation and testing. Model performance and accuracy were evaluated with global whole body dose agreement, PTV coverage accuracy, and OAR dose agreement. The differences in these values between dataset variations were used to determine the effects of missing data and automated contour substitutions. RESULTS: Automated contours used as substitutions for missing data were found to improve dose prediction accuracy in the Standard U-Net and Cascade U-Net, with a statistically significant difference in some global metrics and/or OAR metrics. For both models, PTV coverage between input variations was unaffected by the substitution technique. Automated contours in HC and AC datasets improved mean dose accuracy for some OAR contours, including the mandible and brainstem, with a greater improvement seen with HC datasets. Global dose metrics, including mean absolute error, mean error, and percent error were different for the Standard U-Net but not for the Cascade U-Net. CONCLUSION: Automated contours used as a substitution for contour data improved prediction accuracy for some but not all dose prediction metrics. Compared to the Standard U-Net models, the Cascade U-Net achieved greater precision.

Oral Surgery and Osteoradionecrosis in Patients Undergoing Head and Neck Radiation Therapy: An Update of the Current Literature.

Osteoradionecrosis (ORN) is a serious long-term complication of head and neck radiotherapy (RT), which is often triggered by dental extractions. It results from avascular aseptic necrosis due to irradiated bone damage. ORN is challenging to treat and can lead to severe complications. Furthermore, ORN causes pain and distress, significantly reducing the patient's quality of life. There is currently no established preventive strategy. This narrative review aims to provide an update for the clinicians on the risk of ORN associated with oral surgery in head and neck RT patients, with a focus on the timing suitable for the oral surgery and possible ORN preventive treatments. An electronic search of articles was performed by consulting the PubMed database. Intervention and observational studies were included. A multidisciplinary approach to the patient is highly recommended to mitigate the risk of RT complications. A dental visit before commencing RT is highly advised to minimize the need for future dental extractions after irradiation, and thus the risk of ORN. Post-RT preventive strategies, in case of dento-alveolar surgery, have been proposed and include antibiotics, hyperbaric oxygen (HBO), and the combined use of pentoxifylline and tocopherol ("PENTO protocol"), but currently there is a lack of established standards of care. Some limitations in the use of HBO involve the low availability of HBO facilities, its high costs, and specific clinical contraindications; the PENTO protocol, on the other hand, although promising, lacks clinical trials to support its efficacy. Due to the enduring risk of ORN, removable prostheses are preferable to dental implants in these patients, as there is no consensus on the appropriate timing for their safe placement. Overall, established standards of care and high-quality evidence are lacking concerning both preventive strategies for ORN as well as the timing of the dental surgery. There is an urgent need to improve research for more efficacious clinical decision making.

Development and Application of Prototype System Based on Light-Emitting Diode Arrays (660 nm) with a Top Hat Beam Profile in Order to Optimize Photobiomodulation Protocols for Treatment of Radiation-Induced Oral Mucositis in Rats.

Background: Oral mucositis (OM) is a common adverse effect of radiation to the head and neck. Recent research has shown that extra oral photobiomodulation (EO-PBM) reduces the severity of OM. However, appropriate EO-PBM therapy parameters for OM severity reduction have not been documented. Objective: This work aims to optimize EO-PBM radiation parameters for lowering the severity of radiation-induced OM in rats by establishing a photobiomodulation (PBM) treatment system based on light-emitting diode arrays with top-hat beam profile. Methods: The 36 rats are separated into 2 control groups and 4 groups receiving PBM treatment. The PBM groups are exposed to irradiance between 4 and 24 J/cm2 at 660 nm. The cheek pouch mucosa is removed after scarification for biochemical and histological examination. Student's t-test, and one-way analysis of variance (ANOVA) followed by Tukey's Multiple were applied to compare the statistical significance of differences between control groups and PBM treatment groups. Results: Statistical analysis reveals that PBM irradiation at 12 J/cm2 (200 sec) with a flatness of 0.8 and a diameter of 3 cm substantially decreased the level of inflammatory cytokines compared with the positive control group. Conclusions: Our results indicate that the designed treatment PBM system is capable of delivering the optical parameters necessary for therapeutic treatment.

Drug Therapeutics Delivery to the Salivary Glands: Intraglandular and Intraductal Injections.

Salivary gland hypofunction and xerostomia following pathological conditions like Sjogren's syndrome or head and neck radiotherapy usually lead to tremendous impairment of oral health, speech, and swallowing. The use of systemic drugs to alleviate the symptoms of these conditions has been associated with various adverse effects. Techniques of local drug delivery to the salivary gland have grown enormously to address this problem properly. The techniques include intraglandular and intraductal injections. In this chapter, we will provide a review of the literature for both techniques while incorporating our lab experience in using them.

Systematic dosimetric evaluation of risk of osteoradionecrosis (DERO): First results of dose reporting for preventing teeth osteoradionecrosis after head and neck irradiation.

PURPOSE: OsteoRadioNecrosis (ORN) is a late complication of radiation for head and neck cancer. Predicting ORN is a major challenge. We developed DERO (Dosimetric Evaluation of Risk of ORN), a semi-automatic tool which reports doses delivered to tooth-bearing sectors, to guide post-therapeutic dental care. We present the method and the first results of a 125-patient prospective cohort. MATERIAL AND METHODS: Dosimetric data of patients treated with IMRT for head and neck cancer were prospectively segmented to the DERO algorithm. Four arches corresponding to 8-tooth sectors were semi-automatically generated. Thirty-two cylindrical Regions Of Interest (ROI) corresponding to each tooth and surrounding periodontium were created by linear interpolation. Mean doses (Dmean) of ROI were extracted and included in a database, along with data about primary tumor site, laterality and dose values from organs at risk. Dmean to tooth sectors were computed for molar sectors, (teeth X5 to X8) and anterior sectors (teeth X1 to X4). An individual dose map was generated and delivered to patients and dentists. RESULTS: Dosimetric data from 125 patients treated with Tomotherapy® were prospectively collected and analyzed: 9 parotid tumors (PA), 41 Sub-Hyoid tumors (larynx, hypopharynx) (SH), 43 Oropharynx tumors (OR), 32 Oral Cavity tumors (OC). Irradiation was unilateral for 100% of PA tumors (9), 12% of OR tumors (5) and 47% of OC tumors (15). For unilateral cervical irradiation, Dmean in ipsilateral molar sectors was 54Gy for OC tumors, 45Gy for OR tumors, 20Gy for PA tumors. For Oral Cavity bilateral irradiation, Dmean was high in all tooth sectors, 49 to 55Gy. For SH tumors, Dmean in molar sectors was 27Gy. A dose gradient of 10 to 20Gy was observed between molar and anterior sectors whether radiation was uni or bilateral. CONCLUSION: Mandibular molar sectors of Oropharynx and Oral Cavity tumors were exposed to high Dmean of 40 to 50Gy. On the other hand, tooth sectors received lower doses for SH radiation. The DERO tool guide post-radiation dental care with a personalized dosimetric cartography to patient. With data update and patient follow-up, we will be able to determine ORN risk after head and neck radiation.

The Relationship between the Contouring Time of the Metal Artifacts Area and Metal Artifacts in Head and Neck Radiotherapy.

(1) Background: The impacts of metal artifacts (MAs) on the contouring workload for head and neck radiotherapy have not yet been clarified. Therefore, this study evaluated the relationship between the contouring time of the MAs area and MAs on head and neck radiotherapy treatment planning. (2) Methods: We used treatment planning computed tomography (CT) images for head and neck radiotherapy. MAs were classified into three severities by the percentage of CT images containing MAs: mild (<25%), moderate (25−75%), and severe (>75%). We randomly selected nine patients to evaluate the relationship between MAs and the contouring time of the MAs area. (3) Results: The contouring time of MAs showed moderate positive correlations with the MAs volume and the number of CT images containing MAs. Interobserver reliability of the extracted MAs volume and contouring time were excellent and poor, respectively. (4) Conclusions: Our study suggests that the contouring time of MAs areas is related to individual commitment rather than clinical experience. Therefore, the development of software combining metal artifact reduction methods with automatic contouring methods is necessary to reducing interobserver variability and contouring workload.

Influence of different air CT numbers for IVDT on the dose distribution in TomoTherapy MVCT.

This study aims to evaluate the effect of different air computed tomography (CT) numbers of the image value density table (IVDT) on the retrospective dose calculation of head-and-neck (HN) radiotherapy using TomoTherapy megavoltage CT (MVCT) images. The CT numbers of the inside and outside air and each tissue-equivalent plug of the "Cheese" phantom were obtained from TomoTherapy MVCT. Two IVDTs with different air CT numbers were created and applied to MVCT images of the HN anthropomorphic phantom and recalculated by Planned Adaptive to verify dose distribution. We defined the recalculation dose with MVCT images using both inside and outside air of the IVDT as IVDT MVCT inair ${\mathrm{IVDT}}_{\mathrm{MVCT}}^{\mathrm{inair}}$ and IVDT MVCT outair ${\mathrm{IVDT}}_{\mathrm{MVCT}}^{\mathrm{outair}}$ , respectively. Treatment planning doses calculated on kVCT images were compared with those calculated on MVCT images using two different IVDT tables, namely, IVDT MVCT inair ${\mathrm{IVDT}}_{\mathrm{MVCT}}^{\mathrm{inair}}$ and IVDT MVCT outair ${\mathrm{IVDT}}_{\mathrm{MVCT}}^{\mathrm{outair}}$ . The difference between average MVCT numbers ±1 standard deviation on inside and outside air of the calibration phantom was 65 ± 36 HU. This difference in MVCT number of air exceeded the recommendation lung tolerance for dose calculation error of 2%. The dose differences between the planning target volume (PTV): D98% , D50% , D2% and the organ at risk (OAR): Dmax , Dmean recalculated by IVDT MVCT inair ${\mathrm{IVDT}}_{\mathrm{MVCT}}^{\mathrm{inair}}$ and IVDT MVCT outair ${\mathrm{IVDT}}_{\mathrm{MVCT}}^{\mathrm{outair}}$ using MVCT images were a maximum of 0.7% and 1.2%, respectively. Recalculated doses to the PTV and OAR with MVCT showed that IVDT MVCT outair ${\mathrm{IVDT}}_{\mathrm{MVCT}}^{\mathrm{outair}}$ was 0.5%-0.7% closer to the kVCT treatment planning dose than IVDT MVCT inair ${\mathrm{IVDT}}_{\mathrm{MVCT}}^{\mathrm{inair}}$ . This study showed that IVDT MVCT outair ${\mathrm{IVDT}}_{\mathrm{MVCT}}^{\mathrm{outair}}$ was more accurate than IVDT MVCT inair ${\mathrm{IVDT}}_{\mathrm{MVCT}}^{\mathrm{inair}}$ in recalculating the dose HN cases of MVCT using TomoTherapy.

Oral mucous membrane grafting for unilateral lid margin keratinization following radiotherapy.

We describe the outcomes of oral mucous membrane grafting as a surgical technique for unilateral lid margin keratinization following radiotherapy. A 47-year- old woman presented with an 8-month history of a white spot in her right eye. She had a history of adenoid cystic carcinoma of the right spheno-ethmoid sinus, for which she underwent radiotherapy. Slit-lamp evaluation revealed lid margin keratinization of the right upper and lower eyelids and a keratin plaque on the corneal surface. We performed excision of the keratin plaque and lid margin keratinization, followed by oral mucous membrane grafting of the upper and lower eyelid margins. Histopathological evaluation of the excised lid margin revealed keratinized stratified squamous epithelium, consistent with lid margin keratinization. The corneal surface and lid margins showed no recurrent keratin deposition at the final follow-up, 11 months postoperatively.

Deep Learning-Based Segmentation of Head and Neck Organs-at-Risk with Clinical Partially Labeled Data.

Radiotherapy is one of the main treatments for localized head and neck (HN) cancer. To design a personalized treatment with reduced radio-induced toxicity, accurate delineation of organs at risk (OAR) is a crucial step. Manual delineation is time- and labor-consuming, as well as observer-dependent. Deep learning (DL) based segmentation has proven to overcome some of these limitations, but requires large databases of homogeneously contoured image sets for robust training. However, these are not easily obtained from the standard clinical protocols as the OARs delineated may vary depending on the patient's tumor site and specific treatment plan. This results in incomplete or partially labeled data. This paper presents a solution to train a robust DL-based automated segmentation tool exploiting a clinical partially labeled dataset. We propose a two-step workflow for OAR segmentation: first, we developed longitudinal OAR-specific 3D segmentation models for pseudo-contour generation, completing the missing contours for some patients; with all OAR available, we trained a multi-class 3D convolutional neural network (nnU-Net) for final OAR segmentation. Results obtained in 44 independent datasets showed superior performance of the proposed methodology for the segmentation of fifteen OARs, with an average Dice score coefficient and surface Dice similarity coefficient of 80.59% and 88.74%. We demonstrated that the model can be straightforwardly integrated into the clinical workflow for standard and adaptive radiotherapy.

A newly developed patient fixation system using a dedicated mouthpiece and dental impression materials for head and neck radiotherapy: a preliminary study.

We evaluated the basic characteristics and efficacy of our newly developed patient fixation system for head and neck radiotherapy that uses a dedicated mouthpiece and dental impression materials. The present investigation demonstrated that with this system, the changes in the absorbed dose to water depending on the material of the mouthpiece were small, with a maximum of 0.32% for a 10-MV photon beam. For the dental impression material, we selected a silicone material with the lowest Hounsfield unit (HU) value that had little effect on the generation of artifacts and the quality of the X-ray beam. Multiphase magnetic resonance imaging (MRI) revealed that the head-up and -down motions in the thermoplastic shell without the mouthpiece were 5.76 ± 1.54 mm, whereas the motion with the mouthpiece decreased significantly to 1.72 ± 0.92 mm (P = 0.006). Similarly, the head-left and -right motion displacement decreased from 6.32 ± 1.86 mm without the mouthpiece to 1.80 ± 0.42 mm with the mouthpiece (P = 0.003). Regarding the tongue depressor function of the mouthpiece, the median distance from the hard palate to the surface of the tongue was 28.42 mm. The present results indicate that the new immobilization device developed herein that uses a mouthpiece and a thermoplastic shell is useful for suppressing patients' head motions and tongue positions.

Mouthpiece polymer-gel dosimeter for in vivo oral dosimetry during head and neck radiotherapy.

In this study, we developed a mouthpiece-type gel dosimeter to prevent the oral mucositis caused by the perturbation effect of dental alloys in the radiotherapy of the head and neck regions and to enable in vivo dosimetry. Understanding the dose distribution in the oral cavity during radiotherapy helps identify the possible site for oral mucositis during treatment. Here agarose, which has a higher melting point than gelatin, was added as a coagulant to stabilize the shape of the dosimeter. The strength and dose response of the dosimeter were investigated. The strength was measured at room temperature, 20°C-40 °C, which is higher than the intraoral temperature. The dose-response curves were obtained by magnetic resonance imaging with R2 ranging from 0 to 25 Gy. The strength and dose response of the mouthpiece-type gel dosimeter were approximately 4 and 2.1 times higher than those of polyacrylamide gel and tetrakis hydroxymethyl phosphonium chloride dosimeters commonly used in the prescribed doses per fraction of treatment. The dosimeter is composed of 4 wt% MgCl2 and 1.5 wt% agarose; thus, it can retain the water equivalence. Through in vivo oral dosimetry in three dimensions for head and neck radiotherapy with dental alloys using the mouthpiece-type gel dosimeter, we obtained three-dimensional dose distributions in the dosimeter. The properties of the dosimeter show that it can be used in the clinic, depending on the prescribed dose.

Weaving attention U-net: A novel hybrid CNN and attention-based method for organs-at-risk segmentation in head and neck CT images.

PURPOSE: In radiotherapy planning, manual contouring is labor-intensive and time-consuming. Accurate and robust automated segmentation models improve the efficiency and treatment outcome. We aim to develop a novel hybrid deep learning approach, combining convolutional neural networks (CNNs) and the self-attention mechanism, for rapid and accurate multi-organ segmentation on head and neck computed tomography (CT) images. METHODS: Head and neck CT images with manual contours of 115 patients were retrospectively collected and used. We set the training/validation/testing ratio to 81/9/25 and used the 10-fold cross-validation strategy to select the best model parameters. The proposed hybrid model segmented 10 organs-at-risk (OARs) altogether for each case. The performance of the model was evaluated by three metrics, that is, the Dice Similarity Coefficient (DSC), Hausdorff distance 95% (HD95), and mean surface distance (MSD). We also tested the performance of the model on the head and neck 2015 challenge dataset and compared it against several state-of-the-art automated segmentation algorithms. RESULTS: The proposed method generated contours that closely resemble the ground truth for 10 OARs. On the head and neck 2015 challenge dataset, the DSC scores of these OARs were 0.91 ± 0.02, 0.73 ± 0.10, 0.95 ± 0.03, 0.76 ± 0.08, 0.79 ± 0.05, 0.87 ± 0.05, 0.86 ± 0.08, 0.87 ± 0.03, and 0.87 ± 0.07 for brain stem, chiasm, mandible, left/right optic nerve, left/right submandibular, and left/right parotid, respectively. Our results of the new weaving attention U-net (WAU-net) demonstrate superior or similar performance on the segmentation of head and neck CT images. CONCLUSIONS: We developed a deep learning approach that integrates the merits of CNNs and the self-attention mechanism. The proposed WAU-net can efficiently capture local and global dependencies and achieves state-of-the-art performance on the head and neck multi-organ segmentation task.

A feature invariant generative adversarial network for head and neck MRI/CT image synthesis.

With the emergence of online MRI radiotherapy treatments, MR-based workflows have increased in importance in the clinical workflow. However proper dose planning still requires CT images to calculate dose attenuation due to bony structures. In this paper, we present a novel deep image synthesis model that generates in an unsupervised manner CT images from diagnostic MRI for radiotherapy planning. The proposed model based on a generative adversarial network (GAN) consists of learning a new invariant representation to generate synthetic CT (sCT) images based on high frequency and appearance patterns. This new representation encodes each convolutional feature map of the convolutional GAN discriminator, leading the training of the proposed model to be particularly robust in terms of image synthesis quality. Our model includes an analysis of common histogram features in the training process, thus reinforcing the generator such that the output sCT image exhibits a histogram matching that of the ground-truth CT. This CT-matched histogram is embedded then in a multi-resolution framework by assessing the evaluation over all layers of the discriminator network, which then allows the model to robustly classify the output synthetic image. Experiments were conducted on head and neck images of 56 cancer patients with a wide range of shape sizes and spatial image resolutions. The obtained results confirm the efficiency of the proposed model compared to other generative models, where the mean absolute error yielded by our model was 26.44(0.62), with a Hounsfield unit error of 45.3(1.87), and an overall Dice coefficient of 0.74(0.05), demonstrating the potential of the synthesis model for radiotherapy planning applications.

A cost-minimization analysis of measures against metallic dental restorations for head and neck radiotherapy.

The aim of this study was to compare the estimated public medical care cost of measures to address metallic dental restorations (MDRs) for head and neck radiotherapy using high-energy mega-voltage X-rays. This was considered a first step to clarify which MDR measure was more cost-effective. We estimated the medical care cost of radiotherapy for two representative MDR measures: (i) with MDR removal or (ii) without MDR removal (non-MDR removal) using magnetic resonance imaging and a spacer. A total of 5520 patients received head and neck radiation therapy in 2018. The mean number of MDRs per person was 4.1 dental crowns and 1.3 dental bridges. The mean cost per person was estimated to be 121 720 yen for MDR removal and 54 940 yen for non-MDR removal. Therefore, the difference in total public medical care cost between MDR removal and non-MDR removal was estimated to be 303 268 800 yen. Our results suggested that non-MDR removal would be more cost-effective than MDR removal for head and neck radiotherapy. In the future, a national survey and cost-effectiveness analysis via a multicenter study are necessary; these investigations should include various outcomes such as the rate of local control, status of oral mucositis, frequency of hospital visits and efforts of the medical professionals.

Effect of Surgical Mask on Setup Error in Head and Neck Radiotherapy.

PURPOSE: With the widespread prevalence of Corona Virus Disease 2019 (COVID-19), cancer patients are suggested to wear a surgical mask during radiation treatment. In this study, cone beam CT (CBCT) was used to investigate the effect of surgical mask on setup errors in head and neck radiotherapy. METHODS: A total of 91 patients with head and neck tumors were selected. CBCT was performed to localize target volume after patient set up. The images obtained by CBCT before treatment were automatically registered with CT images and manually fine-tuned. The setup errors of patients in 6 directions of Vrt, Lng, Lat, Pitch, Roll and Rotation were recorded. The patients were divided into groups according to whether they wore the surgical mask, the type of immobilization mask used and the location of the isocenter. The setup errors of patients were calculated. A t-test was performed to detect whether it was statistically significant. RESULTS: In the 4 groups, the standard deviation in the directions of Lng and Pitch of the with surgical mask group were all higher than that in the without surgical mask group. In the head-neck-shoulder mask group, the mean in the Lng direction of the with surgical mask group was larger than that of the without surgical mask group. In the lateral isocenter group, the mean in the Lng and Pitch directions of the with surgical mask group were larger than that of the without surgical mask group. The t-test results showed that there was significant difference in the setup error between the 2 groups (p = 0.043 and p = 0.013, respectively) only in the Lng and Pitch directions of the head-neck-shoulder mask group. In addition, the setup error of 6 patients with immobilization open masks exhibited no distinguished difference from that of the patients with regular immobilization masks. CONCLUSION: In the head and neck radiotherapy patients, the setup error was affected by wearing surgical mask. It is recommended that the immobilization open mask should be used when the patient cannot finish the whole treatment with a surgical mask.

A Relationship Between Cervical Vertebrae Twisting and Cranial Angle in Head and Neck Radiotherapy.

BACKGROUND/AIM: Because current image-guided radiotherapy systems can only correct six axes, it is impossible to correct the twisting of cervical vertebrae. The purpose of this study was to clarify the relationship between cervical vertebrae twisting and cranial angle. MATERIALS AND METHODS: Nineteen patients who underwent intensity-modulated radiation therapy were retrospectively reviewed. Twisting of cervical vertebrae was analysed using planning computed tomography (CT) and megavoltage CT images for image-guided radiotherapy. RESULTS: Although the cranial angle during planning CT was not strongly correlated with twisting (correlation coefficient <0.7), when the patients were divided into two groups by cranial angle, the twisting of the small-angle group was significantly reduced. Specifically, cranial angles of <25° significantly and efficiently reduced the twisting of the upper cervical vertebra compared with those of the other groups. CONCLUSION: Twisting of the upper cervical vertebrae is reduced by using a cranial angle of <25° during planning CT.

Is the introduction of more advanced radiotherapy techniques for locally-advanced head and neck cancer associated with improved quality of life and reduced symptom burden?

Technical improvements in head and neck cancer radiotherapy over the last decade have resulted in substantial reductions in dose to organs-at-risk. For a mix of tumors, we saw less xerostomia moving from 3D-conformal to more advanced techniques. For oropharynx-only there were additional improvements, including in global quality-of-life and sticky saliva.