A novel, multi-active emollient for the prevention of acute radiation dermatitis in breast cancer patients: a randomized clinical trial.

PURPOSE: To investigate the efficacy of a novel, multi-active emollient in preventing and managing acute radiation dermatitis (ARD) in breast cancer patients undergoing moderate hypofractionated (HF) radiotherapy (RT) compared to standard of care. METHODSA: A monocentric, open-label, randomized clinical trial (RCT) with breast cancer patients receiving moderate HF (dose: 40.05-55.86 Gy, fractions: 15-21) was conducted between January 2022 and May 2023. The experimental group received the novel emollient, while the control group received the standard skin care. Patients applied the skin care products twice daily during the complete RT course. The primary outcome was the severity of ARD at the final RT session measured by the modified Radiation Therapy Oncology Group (RTOG) criteria. Secondary outcomes included patient symptoms, quality of life (QoL), and treatment satisfaction. RESULTS: A total of 100 patients with 50 patients per group were enrolled. In the control group, 50% of the patients developed RTOG grade 1 ARD and 48% grade 2 or higher, while in the experimental group, the severity of ARD was significantly lower with 82% grade 1 and 16% grade 2 ARD (P = .013, χ2-test). The frequency and severity of xerosis were significantly lower in the experimental compared to the control group (Ps ≤ .036, Mann Whiney U test). The impact of ARD on the QoL was low, and treatment satisfaction was high in both groups, with no significant difference. CONCLUSION: This RCT shows that the novel, multi-active emollient significantly reduced the ARD RTOG grade. Research in a more diverse patient population is warranted. TRIAL REGISTRATION: ClinicalTrials.gov: NCT04929808 (11/06/2021).

PET imaging in adaptive radiotherapy of gastrointestinal tumors.

INTRODUCTION: Radiotherapy is a cornerstone in the multimodality treatment of several gastrointestinal (GI) tumors. Positron-emission tomography (PET) has an established role in the diagnosis, response assessment and (re-)staging of these tumors. Nevertheless, the value of PET in adaptive radiotherapy remains unclear. This review focuses on the role of PET in adaptive radiotherapy, i.e. during the treatment course and in the delineation process. EVIDENCE ACQUISITION: The MEDLINE database was searched for the terms ("Radiotherapy"[Mesh] AND "Positron-Emission Tomography"[Mesh] AND one of the site-specific keywords, yielding a total of 1710 articles. After abstract selection, 27 papers were identified for esophageal neoplasms, 1 for gastric neoplasms, 9 for pancreatic neoplasms, 6 for liver neoplasms, 1 for biliary tract neoplasms, none for colonic neoplasms, 15 for rectal neoplasms and 12 for anus neoplasms. EVIDENCE SYNTHESIS: The use of PET for truly adaptive radiotherapy during treatment for GI tumors has barely been investigated, in contrast to the potential of the PET-defined metabolic tumor volume for optimization of the target volume. The optimized target definition seems useful for treatment individualization such as focal boosting strategies in esophageal, pancreatic and anorectal cancer. Nevertheless, for all GI tumors, further investigation is needed. CONCLUSIONS: In general, too little data are available to conclude on the role of PET imaging during radiotherapy for ART strategies in GI cancer. On the other hand, based on the available evidence, the use of biological imaging for target volume adaptation seems promising and could pave the road towards individualized treatment strategies.

Moderate dose escalation with volumetric modulated arc therapy improves outcome in rectal cancer.

BACKGROUND: Locally advanced rectal cancer is frequently treated with a long course of preoperative chemoradiotherapy. We investigated the effect of moderate dose escalation with volumetric modulated arc therapy (VMAT) up to 50 Gy in 25 fractions compared to 3D conformal radiotherapy (3D-CRT) to 45 Gy in 25 fractions in rectal cancer patients. Dose-volume parameters, acute toxicity, and complete response rates were compared. MATERIAL AND METHODS: For both groups, 65 patients were selected from our database through availability. Dose-volume parameters and acute toxicity data were compared using a Mann-Whitney U-test. Univariate and multivariate analyses correcting for tumor and nodal stage, distance to the mesorectal fascia and interval to surgery were used to compare complete response rates. RESULTS: Lower mean doses to the small and large bowel were observed in the VMAT group compared to the 3D-CRT group (21 Gy vs. 29 Gy [p < .001] and 26 Gy vs. 30 Gy [p = .002], respectively). Similar beneficial dose-volume parameters were observed for the bladder, sacrum and femoral heads. Furthermore, patients receiving VMAT experienced significantly less diarrhea, flatulence, non-infective cystitis, urinary frequency, dermatitis, and fatigue. In univariate analysis, a significant increase in complete response rate after moderate dose escalation with VMAT was observed (34% vs. 15%, p = .015). However, this did not remain significant when corrected for tumor and nodal stage, distance to the mesorectal fascia, and interval to surgery. CONCLUSIONS: Moderate dose escalation with VMAT resulted in superior dose-volume parameters compared to 3D-CRT, translating into lower acute toxicity. Additionally, improved tumor response after VMAT up to 50 Gy might contribute to a higher percentage of patients achieving a complete response.

Safety and efficiency of a fully automatic workflow for auto-segmentation in radiotherapy using three commercially available deep learning-based applications.

Advancements in radiotherapy auto-segmentation necessitate reliable and efficient workflows. Therefore, a standardized fully automatic workflow was developed for three commercially available deep learning-based auto-segmentation applications and compared to a manual workflow for safety and efficiency. The workflow underwent safety evaluation with failure mode and effects analysis. Notably, eight failure modes were reduced, including seven with severity factors ≥7, indicating the effect on patients, and two with Risk Priority Number value >125, which assesses relative risk level. Efficiency, measured by mouse clicks, showed zero clicks with the automatic workflow. This automation illustrated improvement in both safety and efficiency of workflow.

Optimizing volumetric modulated arc therapy prostate planning using an automated Fine-Tuning process through dynamic adjustment of optimization parameters.

In radiotherapy treatment planning, optimization is essential for achieving the most favorable plan by adjusting optimization criteria. This study introduced an innovative approach to automatically fine-tune optimization parameters for volumetric modulated arc therapy prostate planning, ensuring all constraints were met. A knowledge-based planning model was invoked, and the fine-tuning process was applied through an in-house developed script. Among 25 prostate plans, this fine-tuning increased the number of plans meeting all constraints from 10/25 to 22/25, with a reduction in mean monitor units per gray without increasing plan's complexity. This automation improved efficiency by saving time and resources in treatment planning.

Nonoperative versus operative approach according to the response to neoadjuvant chemoradiotherapy for rectal cancer: A prospective cohort study.

Purpose: To report on organ preservation following chemoradiotherapy (CRT) in a prospective cohort of locally advanced rectal cancer patients. Methods and materials: Fifty-two patients received CRT. MRI and 18F-FDG-PET/CT were performed prior to CRT. Response assessment was done 6 and 12 weeks after CRT using digital rectal examination, MRI, 18F-FDG-PET/CT and endoscopy. For clinical complete response or minimal residual disease, a watch-and-wait (W&W) protocol was started.Regrowth-free survival (ReFS), Total Mesorectal Excision-free disease-free survival, distant metastasis-free survival (DMFS) and overall survival (OS) were evaluated using Kaplan-Meier method. Functional outcome was compared with the Wilcoxon signed-rank test using EORTC QLQ-C30, MSKCC BFI, LARS and IIEF-5/FSFI-5 questionnaires. A previously developed prediction model performance was tested using receiver operating characteristic analysis. Results: 29/52 patients entered a W&W protocol. There was no difference in two-year DMFS (81.1 % vs 78.8 %, p = 0.82), two-year OS (96.4 % vs 100 %, p = 0.38) and two-year DFS (77.5 % vs 78.8 %, p = 0.87) between W&W patients and those who underwent surgery at 12 weeks after CRT. Two-year DMFS differed between W&W with local regrowth, W&W with sustained response and patients who had surgery (66.7 % vs 88.0 % vs 78.8 %; p = 0.04). At 6 and 12 months, W&W patients reported good QoL and bowel function. The model validation reached an AUC of 0.627. Conclusion: Good functional outcome in patients with rectal cancer allocated to surveillance after CRT needs to be balanced against potentially worse DMFS in a subset of patients without sustained clinical complete response. Reliable prediction of patients eligible for surveillance programs needs further investigation.

Predicting the tumor response to chemoradiotherapy for rectal cancer: Model development and external validation using MRI radiomics.

BACKGROUND: In well-responding patients to chemoradiotherapy for locally advanced rectal cancer (LARC), a watch-and-wait strategy can be considered. To implement organ-sparing strategies, accurate patient selection is needed. We investigate the use of MRI-based radiomics models to predict tumor response to improve patient selection. MATERIALS AND METHODS: Models were developed in a cohort of 70 patients and validated in an external cohort of 55 patients. Patients received chemoradiation followed by surgery and underwent T2-weighted and diffusion-weighted MRI (DW-MRI) before and after chemoradiation. The outcome measure was (near-)complete pathological tumor response (ypT0-1N0). Tumor segmentation was done on T2-images and transferred to b800-images and ADC maps, after which quantitative and four semantic features were extracted. We combined features using principal component analysis and built models using LASSO regression analysis. The best models based on precision and performance were selected for validation. RESULTS: 21/70 patients (30%) achieved ypT0-1N0 in the development cohort versus 13/55 patients (24%) in the validation cohort. Three models (t2_dwi_pre_post, semantic_dwi_adc_pre, semantic_dwi_post) were identified with an area-under-the-curve (AUC) of 0.83 (95% CI 0.70-0.95), 0.86 (95% CI 0.75-0.98) and 0.84 (95% CI 0.75-0.94) respectively. Two models (t2_dwi_pre_post, semantic_dwi_post) validated well in the external cohort with AUCs of 0.83 (95% CI 0.70-0.95) and 0.86 (95% CI 0.76-0.97). These models however did not outperform a previously established four-feature semantic model. CONCLUSION: Prediction models based on MRI radiomics non-invasively predict tumor response after chemoradiation for rectal cancer and can be used as an additional tool to identify patients eligible for an organ-preserving treatment.

Development and validation of an MRI-based model to predict response to chemoradiotherapy for rectal cancer.

BACKGROUND AND PURPOSE: To safely implement organ preserving treatment strategies for patients with rectal cancer, well-considered selection of patients with favourable response is needed. In this study, we develop and validate an MRI-based response predicting model. METHODS: A multivariate model using T2-volumetric and DWI parameters before and 6 weeks after chemoradiation (CRT) was developed using a cohort of 85 rectal cancer patients and validated in an external cohort of 55 patients that underwent preoperative CRT. RESULTS: Twenty-two patients (26%) achieved ypT0-1N0 response in the development cohort versus 13 patients (24%) in the validation cohort. Two T2-volumetric parameters (ΔVolume% and Sphere_post) and two DWI parameters (ADC_avg_post and ADCratio_avg) were retained in a model predicting (near-)complete response (ypT0-1N0). In the development cohort, this model had a good predictive performance (AUC = 0.89; 95% CI 0.80-0.98). Validation of the model in an external cohort resulted in a similar performance (AUC = 0.88 95% CI 0.79-0.98). CONCLUSION: An MRI-based prediction model of (near-)complete pathological response following CRT in rectal cancer patients, shows a high predictive performance in an external validation cohort. The clinically relevant features in the model make it an interesting tool for implementation of organ-preserving strategies in rectal cancer.