A scoring system predicting acute radiation dermatitis in patients with head and neck cancer treated with intensity-modulated radiotherapy

Feature-Based vs. Deep-Learning Fusion Methods for the In Vivo Detection of Radiation Dermatitis Using Optical Coherence Tomography, a Feasibility Study

Acute radiation dermatitis (ARD) is a common and distressing issue for cancer patients undergoing radiation therapy, leading to significant morbidity. Despite available treatments, ARD remains a distressing issue, necessitating further research to improve prevention and management strategies. Moreover, the lack of biomarkers for early quantitative assessment of ARD impedes progress in this area. This study aims to investigate the detection of ARD using intensity-based and novel features of Optical Coherence Tomography (OCT) images, combined with machine learning. Imaging sessions were conducted twice weekly on twenty-two patients at six neck locations throughout their radiation treatment, with ARD severity graded by an expert oncologist. We compared a traditional feature-based machine learning technique with a deep learning late-fusion approach to classify normal skin vs. ARD using a dataset of 1487 images. The dataset analysis demonstrates that the deep learning approach outperformed traditional machine learning, achieving an accuracy of 88%. These findings offer a promising foundation for future research aimed at developing a quantitative assessment tool to enhance the management of ARD.

Global hotspots and research trends of radiation-induced skin injury: a bibliometric analysis from 2004 to 2023

Background

Radiation therapy has become an important treatment for many malignant tumours after surgery and for palliative tumour care. Although modern radiotherapy technology is constantly improving, radiation damage to normal tissues is often difficult to avoid, and radiation-induced skin injury (RSI) is a common complication, manifested as skin erythema, peeling, ulceration, and even bone and deep organ damage, seriously affect the quality of life for patients. Basic research and clinical trials related to RSI have achieved certain results, while no researchers have conducted comprehensive bibliometric studies.

Objective

A comprehensive bibliometric analysis of publications on RSI published between 2004 and 2023 was conducted to identify current hotspots and future directions in this area of study.

Methods

RSI-related publications published between January 1, 2004, and December 31, 2023, were retrieved from the Web of Science Core Collection (WoSCC) database for analysis using VOSviewer and CiteSpace analytics.

Results

A total of 1009 publications on RSI from 2004 to 2023 were included in the WoSCC database. The United States had the highest productivity with 299 papers, accounting for 29.63% of the total production, followed by China with 193 papers (19.13%) and Japan with 111 papers (11.00%). In terms of research institutions and journals, the University of Toronto and Journal of Supportive Care in Cancer published the highest number of papers. Professor Edward Chow published the most articles, while Professor Shuyu Zhang was the most cited. The top ten most-cited papers focused on the pathogenesis, prevention, and management of RSI. Keyword co-occurrence analysis and the top 25 keywords with the strongest citation bursts suggest that current research focuses on the pathogenesis, prevention, and treatment management of RSI.

Conclusion

This study conducted a systematic bibliometric analysis of RSI publications from 2004 to 2023; identified the trends in RSI publications, major research countries, major research institutions, major research journals, major research authors, and major research keywords; and revealed the future development direction and research hotspots of this field. This study provides a valuable reference for future RSI research.

Radiation-induced skin injury in the head and neck region: pathogenesis, clinics, prevention, treatment considerations and proposal for management algorithm

Worldwide increase of head and neck cancers ranks these malignancies among top causes of cancer in human population. Radiation induced skin injury (RISI) is one of the major side effects of radiotherapy (RT). Skin of the neck is exposed to radiation due to necessity of therapeutic or prophylactic (elective) irradiation of neck lymph nodes and target organs, including the larynx and hypopharynx. The location of the neck exposes these regions of the skin to various additional exposomes such as ultraviolet radiation (UVR), pollution and cigarette smoke. There are many controversies or inconsistencies regarding RISI, from molecular aspects and therapy to terminology. There is lack of high-quality and large-sample studies in both forms of RISI: acute (aRISI) and chronic (cRISI). Finally, no gold standards in the management of aRISI and cRISI have been established yet. In this article, the authors discuss the pathogenesis, clinical picture, prevention and clinical interventions and present a proposed treatment algorithm.

Dose-toxicity surface histogram-based prediction of radiation dermatitis severity and shape

Objective.This study aimed to develop a new approach to predict radiation dermatitis (RD) by using the skin dose distribution in the actual area of RD occurrence to determine the predictive dose by grade.Approach.Twenty-three patients with head and neck cancer treated with volumetric modulated arc therapy were prospectively and retrospectively enrolled. A framework was developed to segment the RD occurrence area in skin photography by matching the skin surface image obtained using a 3D camera with the skin dose distribution. RD predictive doses were generated using the dose-toxicity surface histogram (DTH) calculated from the skin dose distribution within the segmented RD regions classified by severity. We then evaluated whether the developed DTH-based framework could visually predict RD grades and their occurrence areas and shapes according to severity.Main results.The developed framework successfully generated the DTH for three different RD severities: faint erythema (grade 1), dry desquamation (grade 2), and moist desquamation (grade 3); 48 DTHs were obtained from 23 patients: 23, 22, and 3 DTHs for grades 1, 2, and 3, respectively. The RD predictive doses determined using DTHs were 28.9 Gy, 38.1 Gy, and 54.3 Gy for grades 1, 2, and 3, respectively. The estimated RD occurrence area visualized by the DTH-based RD predictive dose showed acceptable agreement for all grades compared with the actual RD region in the patient. The predicted RD grade was accurate, except in two patients.Significance. The developed DTH-based framework can classify and determine RD predictive doses according to severity and visually predict the occurrence area and shape of different RD severities. The proposed approach can be used to predict the severity and shape of potential RD in patients and thus aid physicians in decision making.

Risk Prediction Model for Radiation-induced Dermatitis in Patients with Cervical Carcinoma Undergoing Chemoradiotherapy

PURPOSE

Radiation-induced dermatitis (RD) is a common side-effect of therapeutic ionizing radiation that can severely affect patient quality of life. This study aimed to develop a risk prediction model for the occurrence of RD in patients with cervical carcinoma undergoing chemoradiotherapy using electronic medical records (EMRs).

METHODS

Using EMRs, the clinical data of patients who underwent simultaneous radiotherapy and chemotherapy at a tertiary cancer hospital between 2017 and 2022 were retrospectively collected, and the patients were divided into two groups: a training group and a validation group. A predictive model was constructed to predict the development of RD in patients who underwent concurrent radiotherapy and chemotherapy for cervical cancer. Finally, the model's efficacy was validated using a receiver operating characteristic curve.

RESULTS

The incidence of radiation dermatitis was 89.5% (560/626) in the entire cohort, 88.6% (388/438) in the training group, and 91.5% (172/188) in the experimental group. The nomogram was established based on the following factors: age, the days between the beginning and conclusion of radiotherapy, the serum albumin after chemoradiotherapy, the use of single or multiple drugs for concurrent chemotherapy, and the total dose of afterloading radiotherapy. Internal and external verification indicated that the model had good discriminatory ability. Overall, the model achieved an area under the receiver operating characteristic curve of .66.

CONCLUSIONS

The risk of RD in patients with cervical carcinoma undergoing chemoradiotherapy is high. A risk prediction model can be developed for RD in cervical carcinoma patients undergoing chemoradiotherapy, based on over 5 years of EMR data from a tertiary cancer hospital.

INFRARED THERMAL IMAGING CONTROL OF RADIATION DERMATITIS DYNAMICS

BACKGROUND

Radiation-induced dermatitis impairs the quality of life of cancer patients and may lead to the need of interrupting radiotherapy. The grade of dermatitis is subjectively assessed by the visual examination. There is an urgent need for both objective and quantitative methods for assessing the current grade of dermatitis and predicting its severity at an early stage of radiotherapy.

AIM

The aim of the study was to evaluate the advantages and limitations of infrared thermography for monitoring the current level of radiation-induced dermatitis and predicting its severity by quantitative analysis of the thermal field dynamics in the irradiated zone.

MATERIALS AND METHODS

30 adult patients were examined by infrared thermography during the course of 2D conventional radiotherapy for malignant tumors of various types and localizations. Our approach for quantifying the thermal field caused by dermatitis alone was applied. A statistical (correlation and ROC) analysis was performed.

RESULTS

Dermatitis of varying severity was observed in 100% of the patients studied. The dynamics in the intensity of the anomalous thermal fields in the irradiated zone correlated with the dynamics of dermatitis grades, excluding the case of a radiosensitive tumor (correlation coefficient 0.74÷0.84). It was found that the maximum toxicity (dermatitis grade ≥ 3) develops in patients who how significant hyperthermia in the area of interest (≥ 0.7 °C) at an early stage of radiotherapy. The ROC analysis demonstrated the "good quality" of the prognosis method (AUC = 0.871).

CONCLUSIONS

The non-invasive and cheap infrared thermography is a suitable tool for objective quantitative monitoring the current dermatitis grade during radiotherapy as well as predicting its severity for any tumor location.

A novel approach to predict acute radiation dermatitis in patients with head and neck cancer using a model based on Bayesian probability

PURPOSE

In this study, we aimed to establish a method for predicting the probability of each acute radiation dermatitis (ARD) grade during the head and neck Volumetric Modulated Arc Therapy (VMAT) radiotherapy planning phase based on Bayesian probability.

METHODS

The skin dose volume >50 Gy (V50), calculated using the treatment planning system, was used as a factor related to skin toxicity. The empirical distribution of each ARD grade relative to V50 was obtained from the ARD grades of 119 patients (55, 50, and 14 patients with G1, G2, and G3, respectively) determined by head and neck cancer specialists. Using Bayes' theorem, the Bayesian probabilities of G1, G2, and G3 for each value of V50 were calculated with an empirical distribution. Conversely, V50 was obtained based on the Bayesian probabilities of G1, G2, and G3.

RESULTS

The empirical distribution for each graded patient group demonstrated a normal distribution. The method predicted ARD grades with 92.4 % accuracy and provided a V50 value for each grade. For example, using the graph, we could predict that V50 should be ≤24.5 cm3 to achieve G1 with 70 % probability.

CONCLUSIONS

The Bayesian probability-based ARD prediction method could predict the ARD grade at the treatment planning stage using limited patient diagnostic data that demonstrated a normal distribution. If the probability of an ARD grade is high, skin care can be initiated in advance. Furthermore, the V50 value during treatment planning can provide radiation oncologists with data for strategies to reduce ARD.

An Experimental Model of Proton-Beam-Induced Radiation Dermatitis In Vivo

Radiation dermatitis (RD) is one of the most common side effects of radiation therapy. However, to date, there is a lack of both specific treatments for RD and validated experimental animal models with the use of various sources of ionizing radiation (IR) applied in clinical practice. The aim of this study was to develop and validate a model of acute RD induced using proton radiation in mice. Acute RD (Grade 2-4) was obtained with doses of 30, 40, and 50 Gy, either with or without depilation. The developed model of RD was characterized by typical histological changes in the skin after irradiation. Moreover, the depilation contributed to a skin histology alteration of the irradiated mice. The assessment of animal vital signs indicated that there was no effect of proton irradiation on the well-being or general condition of the animals. This model can be used to develop effective therapeutic agents and study the pathogenesis of radiation-induced skin toxicity, including that caused by proton irradiation.

Quantitative radiomics approach to assess acute radiation dermatitis in breast cancer patients

PURPOSE

We applied a radiomics approach to skin surface images to objectively assess acute radiation dermatitis in patients undergoing radiotherapy for breast cancer.

METHODS

A prospective cohort study of 20 patients was conducted. Skin surface images in normal, polarized, and ultraviolet (UV) modes were acquired using a skin analysis device before starting radiotherapy ('Before RT'), approximately 7 days after the first treatment ('RT D7'), on 'RT D14', and approximately 10 days after the radiotherapy ended ('After RT D10'). Eighteen types of radiomic feature ratios were calculated based on the values acquired 'Before RT'. We measured skin doses in ipsilateral breasts using optically stimulated luminescent dosimeters on the first day of radiotherapy. Clinical evaluation of acute radiation dermatitis was performed using the Radiation Therapy Oncology Group scoring criteria on 'RT D14' and 'After RT D10'. Several statistical analysis methods were used in this study to test the performance of radiomic features as indicators of radiodermatitis evaluation.

RESULTS

As the skin was damaged by radiation, the energy for normal mode and sum variance for polarized and UV modes decreased significantly for ipsilateral breasts, whereas contralateral breasts exhibited a smaller decrease with statistical significance. The radiomic feature ratios at 'RT D7' had strong correlations to skin doses and those at 'RT D14' and 'after RT D10' with statistical significance.

CONCLUSIONS

The energy for normal mode and sum variance for polarized and UV modes demonstrated the potential to evaluate and predict acute radiation, which assists in its appropriate management.

Dermoscopy of acute radiation-induced dermatitis in patients with head and neck cancers treated with radiotherapy

Head and neck cancer (HNC) was the seventh most common cancer in the world in 2018. Treatment of a patient may include surgery, radiotherapy (RT), chemotherapy, targeted therapy, immunotherapy, or a combination of these methods. Ionizing radiation used during RT covers relatively large volumes of healthy tissue surrounding the tumor. The acute form of radiation-induced dermatitis (ARD) are skin lesions that appear usually within 90 days of the start of RT. This is a prospective study which compares 2244 dermoscopy images and 374 clinical photographs of irradiated skin and healthy skin of 26 patients at on average 15 time points. Dermoscopy pictures were evaluated independently by 2 blinded physicians. Vessels in reticular distribution, white, yellow or brown scale in a patchy distribution, perifollicular pigmentation and follicular plugs arranged in rosettes were most often observed. For these dermoscopic features, agreement with macroscopic features was observed. Two independent predictors of severe acute toxicity were identified: gender and concurrent chemotherapy. Knowledge of dermoscopic features could help in the early assessment of acute toxicity and the immediate implementation of appropriate therapeutic strategies. This may increase the tolerance of RT in these groups of patients.

Review of optical reporters of radiation effects in vivo: tools to quantify improvements in radiation delivery technique

Significance

Radiation damage studies are used to optimize radiotherapy treatment techniques. Although biological indicators of damage are the best assays of effect, they are highly variable due to biological heterogeneity. The free radical radiochemistry can be assayed with optical reporters, allowing for high precision titration of techniques.

Aim

We examine the optical reporters of radiochemistry to highlight those with the best potential for translational use in vivo, as surrogates for biological damage assays, to inform on mechanisms.

Approach

A survey of the radical chemistry effects from reactive oxygen species (ROS) and oxygen itself was completed to link to DNA or biological damage. Optical reporters of ROS include fluorescent, phosphorescent, and bioluminescent molecules that have a variety of activation pathways, and each was reviewed for its in vivo translation potential.

Results

There are molecular reporters of ROS having potential to report within living systems, including derivatives of luminol, 2'7'-dichlorofluorescein diacetate, Amplex Red, and fluorescein. None have unique specificity to singular ROS species. Macromolecular engineered reporters unique to specific ROS are emerging. The ability to directly measure oxygen via reporters, such as Oxyphor and protoporphyrin IX, is an opportunity to quantify the consumption of oxygen during ROS generation, and this translates from in vitro to in vivo use. Emerging techniques, such as ion particle beams, spatial fractionation, and ultra-high dose rate FLASH radiotherapy, provide the motivation for these studies.

Conclusions

In vivo optical reporters of radiochemistry are quantitatively useful for comparing radiotherapy techniques, although their use comes at the cost of the unknown connection to the mechanisms of radiobiological damage. Still their lower measurement uncertainty, compared with biological response assay, makes them an invaluable tool. Linkage to DNA damage and biological damage is needed, and measures such as oxygen consumption serve as useful surrogate measures that translate to in vivo use.

Radiation-induced alterations in multi-layered, in-vitro skin models detected by optical coherence tomography and histological methods

BACKGROUND

Inflammatory skin reactions and skin alterations are still a potential side effect in radiation therapy (RT), which also need attention for patients' health care.

METHOD

In a pre-clinical study we consider alterations in irradiated in-vitro skin models of epidermal and dermal layers. Typical dose regimes in radiation therapy are applied for irradiation. For non-invasive imaging and characterization optical coherence tomography (OCT) is used. Histological staining method is additionally applied for comparison and discussion.

RESULTS

Structural features, such as keratinization, modifications in epidermal cell layer thickness and disorder in the layering-as indications for reactions to ionizing radiation and aging-could be observed by means of OCT and confirmed by histology. We were able to recognize known RT induced changes such as hyper-keratosis, acantholysis, and epidermal hyperplasia as well as disruption and/or demarcation of the dermo-epidermal junction.

CONCLUSION

The results may pave the way for OCT to be considered as a possible adjunctive tool to detect and monitor early skin inflammation and side effects of radiotherapy, thus supporting patient healthcare in the future.

IMPT of head and neck cancer: unsupervised machine learning treatment planning strategy for reducing radiation dermatitis

Radiation dermatitis is a major concern in intensity modulated proton therapy (IMPT) for head and neck cancer (HNC) despite its demonstrated superiority over contemporary photon radiotherapy. In this study, dose surface histogram data extracted from forty-four patients of HNC treated with IMPT was used to predict the normal tissue complication probability (NTCP) of skin. Grades of NTCP-skin were clustered using the K-means clustering unsupervised machine learning (ML) algorithm. A new skin-sparing IMPT (IMPT-SS) planning strategy was developed with three major changes and prospectively implemented in twenty HNC patients. Across skin surfaces exposed from 10 (S10) to 70 (S70) GyRBE, the skin's NTCP demonstrated the strongest associations with S50 and S40 GyRBE (0.95 and 0.94). The increase in the NTCP of skin per unit GyRBE is 0.568 for skin exposed to 50 GyRBE as compared to 0.418 for 40 GyRBE. Three distinct clusters were formed, with 41% of patients in G1, 32% in G2, and 27% in G3. The average (± SD) generalised equivalent uniform dose for G1, G2, and G3 clusters was 26.54 ± 6.75, 38.73 ± 1.80, and 45.67 ± 2.20 GyRBE. The corresponding NTCP (%) were 4.97 ± 5.12, 48.12 ± 12.72 and 87.28 ± 7.73 respectively. In comparison to IMPT, new IMPT-SS plans significantly (P < 0.01) reduced SX GyRBE, gEUD, and associated NTCP-skin while maintaining identical dose volume indices for target and other organs at risk. The mean NTCP-skin value for IMPT-SS was 34% lower than that of IMPT. The dose to skin in patients treated prospectively for HNC was reduced by including gEUD for an acceptable radiation dermatitis determined from the local patient population using an unsupervised MLA in the spot map optimization of a new IMPT planning technique. However, the clinical finding of acute skin toxicity must also be related to the observed reduction in skin dose.

A New Approach to Quantify and Grade Radiation Dermatitis Using Deep-Learning Segmentation in Skin Photographs

AIMS

Objective evaluation of radiation dermatitis is important for analysing the correlation between the severity of radiation dermatitis and dose distribution in clinical practice and for reliable reporting in clinical trials. We developed a novel radiation dermatitis segmentation system based on convolutional neural networks (CNNs) to consistently evaluate radiation dermatitis.

MATERIALS AND METHODS

The radiation dermatitis segmentation system is designed to segment the radiation dermatitis occurrence area using skin photographs and skin-dose distribution. A CNN architecture with a dilated convolution layer and skip connection was designed to estimate the radiation dermatitis area. Seventy-three skin photographs obtained from patients undergoing radiotherapy were collected for training and testing. The ground truth of radiation dermatitis segmentation is manually delineated from the skin photograph by an experienced radiation oncologist and medical physicist. We converted the skin photographs to RGB (red-green-blue) and CIELAB (lightness (L^∗), red-green (a^∗) and blue-yellow (b^∗)) colour information and trained the network to segment faint and severe radiation dermatitis using three different input combinations: RGB, RGB + CIELAB (RGBLAB) and RGB + CIELAB + skin-dose distribution (RGBLAB_D). The proposed system was evaluated using the Dice similarity coefficient (DSC), sensitivity, specificity and normalised Matthews correlation coefficient (nMCC). A paired t-test was used to compare the results of different segmentation performances.

RESULTS

Optimal data composition was observed in the network trained for radiation dermatitis segmentation using skin photographs and skin-dose distribution. The average DSC, sensitivity, specificity and nMCC values of RGBLAB_D were 0.62, 0.61, 0.91 and 0.77, respectively, in faint radiation dermatitis, and 0.69, 0.78, 0.96 and 0.83, respectively, in severe radiation dermatitis.

CONCLUSION

Our study showed that CNN-based radiation dermatitis segmentation in skin photographs of patients undergoing radiotherapy can describe radiation dermatitis severity and pattern. Our study could aid in objectifying the radiation dermatitis grading and analysing the reliable correlation between dosimetric factors and the morphology of radiation dermatitis.

Potential Benefits of Aloe vera and Raphanus sativus var. longipinnatus Gel for Prevention of Radiation-Induced Dermatitis in Head and Neck Cancer Patients

Background

The main therapy for head and neck cancer is radiation, and one of the toxic effects of radiation is radiation dermatitis. Aloe vera is a species of succulent plant of the genus Aloe, widely used in cosmetic and skin care products, as well as daikon (Raphanus sativus var. longipinnatus), which is high in antioxidants.

Objectives

The present study aims to evaluate the potential benefits of Aloe vera and daikon gel combination in head and neck cancer patients to prevent radiation-induced dermatitis.

Methods

A cohort study was conducted with eligible subjects, all head and neck cancer patients receiving radiation therapy selected in consecutive sampling. Samples were divided into two groups; either received Aloe vera and daikon combination gel (study group) or baby oil (control induced dermatitis (RID) were observed.

Results

A total of 44 patients were grouped into intervention (Aloe vera-daikon gel) and control (baby oil) groups. After ten radiotherapies (RT) sessions, the intervention group had a lower percentage of grade 1 RID (35% vs. 91.7%, control: 65% grade 2 RID, P < 0.001). After 20 RT sessions, 40% had no dermatitis, while all patients had RID in the control group (P = 0.061). After 30 RT sessions, the intervention group had a lower RID grade overall (gr 0: 5%, gr 1: 85%, gr 2: 10%) compared to the control group (gr 1: 33.3%, gr 2: 54.3%, gr 3: 8.3%, P = 0.002). After 35 RT sessions, the intervention group also had a lower RID grade overall (gr 0: 5%, gr 1: 65%, gr 2: 20%, gr 3: 10%) compared to the control group (gr 1: 8.3%, gr 2: 37.5%, gr 3: 45.8%, gr 4: 8.3%, P < 0.001).

Conclusions

The combination of Aloe vera and daikon gel showed promising results in reducing the severity of radiation-induced dermatitis for head and neck cancer patients.

Deep learning-based automatic assessment of radiation dermatitis in nasopharyngeal carcinoma (NPC) patients

PURPOSE

Radiation dermatitis (RD) is a common, unpleasant side-effect of patients receiving radiotherapy. In clinical practice, the severity of RD is graded manually through visual inspection, which is labor-intensive and often leads to large inter-rater variations. To overcome these shortcomings, this study aims to develop an automatic RD assessment based on deep learning (DL) techniques, which could efficiently assist the RD severity classification in clinical application.

METHODS

A total of 1205 photographs of the head and neck region were collected from nasopharyngeal carcinoma (NPC) patients undergoing radiotherapy. The severity of RD in these photographs was graded by five qualified assessors based on the Radiation Therapy Oncology Group (RTOG) guidance. An end-to-end RD grading framework was developed by combining a DL-based segmentation network and a DL-based RD severity classifier, which are used for segmenting the neck region from the camera-captured photographs and grading, respectively. U-Net was used for segmentation and another convolutional neural network (CNN) classifier (DenseNet-121) was applied to RD severity classification. Dice Similarity Coefficient (DSC) was used to evaluate the performance of segmentation. Severity classification was evaluated by several metrics, including overall accuracy, precision, recall, and F1-score.

RESULTS

Results of segmentation showed that the averaged DSCs were 91.2% and 90.8% for front and side view, respectively. For RD severity classification, the overall accuracy of test photographs was 83.0%. Our method accurately classified 90.5% of Grade 0, 67.2% of Grade 1, 93.8% of Grade 2, and 100% of Above Grade 2 cases. The overall prediction performance was comparable with human assessors. There was no significant difference in accuracy when using manually or automatically segmented regions (p = 0.683).

CONCLUSION

We have successfully demonstrated a DL-based method for automatic assessment of RD severity in NPC patients. This method holds great potential for efficient and effective assessing and monitoring of RD in NPC patients.

A pilot study of a novel method to visualize three-dimensional dose distribution on skin surface images to evaluate radiation dermatitis

Predicting the radiation dose‒toxicity relationship is important for local tumor control and patients’ quality of life. We developed a first intuitive evaluation system that directly matches the three-dimensional (3D) dose distribution with the skin surface image of patients with radiation dermatitis (RD) to predict RD in patients undergoing radiotherapy. Using an RGB-D camera, 82 3D skin surface images (3DSSIs) were acquired from 19 patients who underwent radiotherapy. 3DSSI data acquired included 3D skin surface shape and optical imaging of the area where RD occurs. Surface registration between 3D skin dose (3DSD) and 3DSSI is performed using the iterative closest point algorithm, then reconstructed as a two-dimensional color image. The developed system successfully matched 3DSSI and 3DSD, and visualized the planned dose distribution onto the patient's RD image. The dose distribution pattern was consistent with the occurrence pattern of RD. This new approach facilitated the evaluation of the direct correlation between skin-dose distribution and RD and, therefore, provides a potential to predict the probability of RD and thereby decrease RD severity by enabling informed treatment decision making by physicians. However, the results need to be interpreted with caution due to the small sample size.

Factors Influencing the Severity of Acute Radiation-Induced Skin and Mucosal Toxicity in Head and Neck Cancer

Background and purpose

Radiotherapy is a crucial part of cancer therapy armamentarium, but it is associated with skin and mucosal toxicity in a substantial proportion of patients with head and neck cancer. Its extent, however, depends on several patient-related and treatment-related factors. In-depth knowledge of these is prudent for better patient management.

Aim

The aim of this study is to assess the factors influencing the severity of acute radiation-induced skin and mucosal toxicity in patients with head and neck cancer receiving external beam radiotherapy.

Materials and methods

This longitudinal observational study included all patients receiving curative external beam radiotherapy for head and neck cancer aged 18 years or above from January 2018 to December 2018. Patient-related and treatment-related characteristics including age, gender, type, staging and site of cancer, history of smoking and diabetes, surface area exposed, and concurrent chemotherapy were compared in patients experiencing severe and non-severe acute skin and mucosal toxicity using the Radiation Therapy Oncology Group (RTOG) scoring system.

Results

Higher age (p = 0.002), TNM stage IV (p = 0.023), and concurrent administration of chemotherapy (p = 0.002) were statistically associated with severe acute radiation-induced skin and mucosa toxicity, whereas gender, surface area irradiated, history of smoking, and diabetes did not show such an association.

Conclusion

Older patients with TNM stage IV malignancy receiving concurrent chemotherapy are at a high risk of developing skin and mucosal toxicity that might interfere with the treatment protocol and warrant hospitalization, compromising their quality of life.

Reducing variability among treatment machines using knowledge-based planning for head and neck, pancreatic, and rectal cancer

Purpose

This study aimed to assess dosimetric indices of RapidPlan model‐based plans for different energies (6, 8, 10, and 15 MV; 6‐ and 10‐MV flattening filter‐free), multileaf collimator (MLC) types (Millennium 120, High Definition 120, dual‐layer MLC), and disease sites (head and neck, pancreatic, and rectal cancer) and compare these parameters with those of clinical plans.

Methods

RapidPlan models in the Eclipse version 15.6 were used with the data of 28, 42, and 20 patients with head and neck, pancreatic, and rectal cancer, respectively. RapidPlan models of head and neck, pancreatic, and rectal cancer were created for TrueBeam STx (High Definition 120) with 6 MV, TrueBeam STx with 10‐MV flattening filter‐free, and Clinac iX (Millennium 120) with 15 MV, respectively. The models were used to create volumetric‐modulated arc therapy plans for a 10‐patient test dataset using all energy and MLC types at all disease sites. The Holm test was used to compare multiple dosimetric indices in different treatment machines and energy types.

Results

The dosimetric indices for planning target volume and organs at risk in RapidPlan model‐based plans were comparable to those in the clinical plan. Furthermore, no dose difference was observed among the RapidPlan models. The variability among RapidPlan models was consistent regardless of the treatment machines, MLC types, and energy.

Conclusions

Dosimetric indices of RapidPlan model‐based plans appear to be comparable to the ones based on clinical plans regardless of energies, MLC types, and disease sites. The results suggest that the RapidPlan model can generate treatment plans independent of the type of treatment machine.

Predictive factors associated with radiation dermatitis in breast cancer

PURPOSE

Radiation dermatitis (RD) is a side effect that frequently arises during radiotherapy (RT) in breast cancer patients. The present study investigates possible predictive factors of RD, as well as the use of skin treatments to manage symptoms.

METHODS

Demographic and treatment characteristics were collected retrospectively, while skin symptoms and treatments were collected prospectively for patients who received adjuvant RT between December 2013 and November 2015. Patients were seen weekly by clinicians throughout treatment, during which a clinician-reported survey was completed on RD symptoms and skin treatments. Possible predictive factors were correlated with skin outcomes through a univariate ordinal logistic regression analysis.

RESULTS

A total of 1093 patients were included in this analysis. Predictive factors for erythema included dose fractionation (p<0.0001), tissue volume irradiated by tangential fields (p = 0.01), and administration of a boost (p = 0.005). High BMI (≥30 kg/m²) (p = 0.0004) and boost (p = 0.02) were predictive of edema. A dose of 50 Gy/25 (p<0.0001) and a high irradiated tissue volume (p = 0.0001) were predictive of desquamation. A dose of 50 Gy/25 (p = 0.0005) and high BMI (p = 0.02) were predictors of pain. Bolus use was the only factor associated with bleeding (p = 0.02). Patients who developed desquamation were likely to receive corticosteroids/antihistamines (p<0.0001), topical antibiotics/antifungals (p<0.001), and dressings (p<0.0001).

CONCLUSION

The findings of this study provide evidence of potential predictors of RD and methods of symptom management based on symptom severity. Prevention of RD is needed among high-risk groups, such as patients with a high BMI or receiving a standard fractionation, boost, or bolus.

Potential benefits of adaptive intensity-modulated proton therapy in nasopharyngeal carcinomas

Purpose

To investigate potential advantages of adaptive intensity‐modulated proton beam therapy (A‐IMPT) by comparing it to adaptive intensity‐modulated X‐ray therapy (A‐IMXT) for nasopharyngeal carcinomas (NPC).

Methods

Ten patients with NPC treated with A‐IMXT (step and shoot approach) and concomitant chemotherapy between 2014 and 2016 were selected. In the actual treatment, 46 Gy in 23 fractions (46Gy/23Fx.) was prescribed using the initial plan and 24Gy/12Fx was prescribed using an adapted plan thereafter. New treatment planning of A‐IMPT was made for the same patients using equivalent dose fractionation schedule and dose constraints. The dose volume statistics based on deformable images and dose accumulation was used in the comparison of A‐IMXT with A‐IMPT.

Results

The means of the D_mean of the right parotid gland (P < 0.001), right TM joint (P < 0.001), left TM joint (P < 0.001), oral cavity (P < 0.001), supraglottic larynx (P = 0.001), glottic larynx (P < 0.001), , middle PCM (P = 0.0371), interior PCM (P < 0.001), cricopharyngeal muscle (P = 0.03643), and thyroid gland (P = 0.00216), in A‐IMPT are lower than those of A‐IMXT, with statistical significance. The means of, D_0.03cc, and D_mean of each sub portion of auditory apparatus and D_30% for Eustachian tube and D_0.5cc for mastoid volume in A‐IMPT are significantly lower than those of A‐IMXT. The mean doses to the oral cavity, supraglottic larynx, and glottic larynx were all reduced by more than 20 Gy (RBE = 1.1).

Conclusions

An adaptive approach is suggested to enhance the potential benefit of IMPT compared to IMXT to reduce adverse effects for patients with NPC.