An Overview of X-ray Photon Counting Spectral Imaging (x-CSI) with a Focus on Gold Nanoparticle Quantification in Oncology

This review article offers an overview of the differences between traditional energy integrating (EI) X-ray imaging and the new technique of X-ray photon counting spectral imaging (x-CSI). The review is motivated by the need to image gold nanoparticles (AuNP) in vivo if they are to be used clinically to deliver a radiotherapy dose-enhancing effect (RDEE). The aim of this work is to familiarise the reader with x-CSI as a technique and to draw attention to how this technique will need to develop to be of clinical use for the described oncological applications. This article covers the conceptual differences between x-CSI and EI approaches, the advantages of x-CSI, constraints on x-CSI system design, and the achievements of x-CSI in AuNP quantification. The results of the review show there are still approximately two orders of magnitude between the AuNP concentrations used in RDEE applications and the demonstrated detection limits of x-CSI. Two approaches to overcome this were suggested: changing AuNP design or changing x-CSI system design. Optimal system parameters for AuNP detection and general spectral performance as determined by simulation studies were different to those used in the current x-CSI systems, indicating potential gains that may be made with this approach.

What Is the Appropriate Skin Cleaning Method for Nasopharyngeal Cancer Radiotherapy Patients? a Randomized Controlled Trial

Purpose To determine the effect of various cleaning methods for skin with acute radiation dermatitis (RD) in patients treated for nasopharyngeal carcinoma (NPC). Methods A total of 168 NPC inpatients were randomized, while 152 patients completed the whole trial and the data were analyzed. Patients were randomly divided into non-washing group, washing with water alone group, and washing with water and soap group. All three groups received intensity modulated radiation therapy (IMRT) among other treatments. Follow-up from recruitment or the initial radiotherapy dose to 1 month after the final radiotherapy dose. CONSORT checklist was applied as the reporting guidelines for this study. Study evaluated a range of endpoints including incidence, timing, severity of acute RD and quality of life (QOL).Results There were no allergic reactions or aggravating in both washing groups during the whole treatment. The incidence of acute RD was 100% in all three groups, while the degree of severity differed among groups. Washing moderately reduced severity compared with patients without washing; washing also delayed the onset time of acute RD, reduced the incidence of moist desquamation and pruritus. There were no significant difference among groups with respect to pain or burning sensation. Washing improved QOL on physical, emotional, and social functional dimensions. Washing with water and soap was the most effective on reducing itching and improving QOL among three groups. Conclusion Washing irradiated skin reduces the occurrence and severity of acute radiation dermatitis.Clinical trial information ChiCTR2000038231, date of registration 09.18.2020

SIOP PNET5 MB Trial: History and Concept of a Molecularly Stratified Clinical Trial of Risk-Adapted Therapies for Standard-Risk Medulloblastoma

Background. SIOP PNET5 MB was initiated in 2014 as the first European trial using clinical, histological, and molecular parameters to stratify treatments for children and adolescents with standard-risk medulloblastoma. Methods. Stratification by upfront assessment of molecular parameters requires the timely submission of adequate tumour tissue. In the standard-risk phase-III cohort, defined by the absence of high-risk criteria (M0, R0), pathological (non-LCA), and molecular biomarkers (MYCN amplification in SHH–MB or MYC amplification), a randomized intensification by carboplatin concomitant with radiotherapy is investigated. In the LR stratum for localized WNT-activated medulloblastoma and age <16 years, a reduction of craniospinal radiotherapy dose to 18 Gy and a reduced maintenance chemotherapy are investigated. Two additional strata (WNT-HR, SHH-TP53) were implemented during the trial. Results. SIOP PNET5 MB is actively recruiting. The availability of adequate tumour tissue for upfront real-time biological assessments to assess inclusion criteria has proven feasible. Conclusion. SIOP PNET5 MB has demonstrated that implementation of biological parameters for stratification is feasible in a prospective multicentre setting, and may improve risk-adapted treatment. Comprehensive research studies may allow assessment of additional parameters, e.g., novel medulloblastoma subtypes, and identification and validation of biomarkers for the further refinement of risk-adapted treatment in the future.

Dynamics-Adapted Radiotherapy Dose (DARD) for Head and Neck Cancer Radiotherapy Dose Personalization

Standard of care radiotherapy (RT) doses have been developed as a one-size-fits all approach designed to maximize tumor control rates across a population. Although this has led to high control rates for head and neck cancer with 66–70 Gy, this is done without considering patient heterogeneity. We present a framework to estimate a personalized RT dose for individual patients, based on pre- and early on-treatment tumor volume dynamics—a dynamics-adapted radiotherapy dose (DDARD). We also present the results of an in silico trial of this dose personalization using retrospective data from a combined cohort of n = 39 head and neck cancer patients from the Moffitt and MD Anderson Cancer Centers that received 66–70 Gy RT in 2–2.12 Gy weekday fractions. This trial was repeated constraining DDARD between (54, 82) Gy to test more moderate dose adjustment. DDARD was estimated to range from 8 to 186 Gy, and our in silico trial estimated that 77% of patients treated with standard of care were overdosed by an average dose of 39 Gy, and 23% underdosed by an average dose of 32 Gy. The in silico trial with constrained dose adjustment estimated that locoregional control could be improved by >10%. We demonstrated the feasibility of using early treatment tumor volume dynamics to inform dose personalization and stratification for dose escalation and de-escalation. These results demonstrate the potential to both de-escalate most patients, while still improving population-level control rates.

Reduction of Elective Radiotherapy Treatment Volume in Definitive Treatment of Locally Advanced Head and Neck Cancer—Comparison of a Prospective Trial with a Revised Simulated Contouring Approach

Definitive radiochemotherapy of locally advanced head and neck squamous cell cancer (HNSCC) achieves high locoregional tumor control rates; but is frequently associated with long-term toxicity. A future direction could be a de-escalation strategy focusing on treated volume rather than radiotherapy dose. This analysis evaluates radiotherapy dose and volume parameters of patients treated with a standard contouring approach in a clinical trial context compared with a revised volume-reduced contouring approach. In this case, 30 consecutive patients from the CheckRad-CD8 trial treated at a single study center were included in this analysis. Treatment toxicity and quality of life were assessed at the end of radiotherapy. Standard treatment plans (ST) following state of the art contouring guidelines that were used for patient treatment and volume reduced treatment plans (VRT) according to a revised simulated approach were calculated for each patient. Planning target volumes (PTV) and mean doses to 38 organs-at-risk structures were compared. At the end of radiotherapy patients reported high rates of mucositis; dysphagia and xerostomia. In addition; patient reported quality of life as assessed by the EORTC QLQ-HN35 questionnaire deteriorated. Comparing the two contouring approaches; the elective PTV_56 Gy and the high risk PTV_63 Gy (shrinking field) were significantly smaller in the VRT group. Significant reduction of mean dose to structures of the oral cavity; the larynx as well as part of the swallowing muscles and the submandibular glands was achieved in the simulated VRT-plan. Treatment de-intensification by reduction of the irradiated volume could potentially reduce treatment volume and mean doses to organs at risk. The proposed contouring approach should be studied further in the context of a clinical trial.

Sharp loss: a new loss function for radiotherapy dose prediction based on fully convolutional networks

Background Neural-network methods have been widely used for the prediction of dose distributions in radiotherapy. However, the prediction accuracy of existing methods may be degraded by the problem of dose imbalance. In this work, a new loss function is proposed to alleviate the dose imbalance and achieve more accurate prediction results. The U-Net architecture was employed to build a prediction model. Our study involved a total of 110 patients with left-breast cancer, who were previously treated by volumetric-modulated arc radiotherapy. The patient dataset was divided into training and test subsets of 100 and 10 cases, respectively. We proposed a novel ‘sharp loss’ function, and a parameter γ was used to adjust the loss properties. The mean square error (MSE) loss and the sharp loss with different γ values were tested and compared using the Wilcoxon signed-rank test. Results The sharp loss achieved superior dose prediction results compared to those of the MSE loss. The best performance with the MSE loss and the sharp loss was obtained when the parameter γ was set to 100. Specifically, the mean absolute difference values for the planning target volume were 318.87 ± 30.23 for the MSE loss versus 144.15 ± 16.27 for the sharp loss with γ = 100 (p < 0.05). The corresponding values for the ipsilateral lung, the heart, the contralateral lung, and the spinal cord were 278.99 ± 51.68 versus 198.75 ± 61.38 (p < 0.05), 216.99 ± 44.13 versus 144.86 ± 43.98 (p < 0.05), 125.96 ± 66.76 versus 111.86 ± 47.19 (p > 0.05), and 194.30 ± 14.51 versus 168.58 ± 25.97 (p < 0.05), respectively. Conclusions The sharp loss function could significantly improve the accuracy of radiotherapy dose prediction.