FLASH Bragg-Peak Irradiation With a Therapeutic Carbon Ion Beam: First In Vivo Results.

Purpose: In recent years, ultra-high dose rate (UHDR) irradiation has emerged as a promising innovative approach to cancer treatment. Characteristic feature of this regimen, commonly referred to as FLASH effect, demonstrated primarily for electrons, photons, or protons, is the improved normal tissue sparing, whereas the tumor control is similar to the one of the conventional dose-rate (CDR) treatments. The FLASH mechanism is, however, unknown.

Palliative care of proximal femur metastatic disease and osteolytic lesions: results following surgical and radiation treatment.

Background: Femoral bone metastases (FBM) or lesions (FBL) can lead to loss of mobility and independence due to skeletal-related events (SRE), e.g. pain, deformity and pathological fractures.

Proton bunch monitors for the clinical translation of prompt gamma-ray timing.

. Prompt gamma-ray timing is an emerging technology in the field of particle therapy treatment verification. This system measures the arrival times of gamma rays produced in the patient body and uses the cyclotron radio frequency signal as time reference for the beam micro-bunches.

Inter-center comparison of proton range verification prototypes with an anthropomorphic head phantom.

. To compare in reproducible and equalized conditions the performance of two independent proton range verification systems based on prompt gamma-ray detectors from two different proton therapy centers..

Cytotoxic and Radiosensitizing Effects of European and African Propolis in 3D Lung Carcinoma Cell Cultures.

Background/aim: Natural compounds such as propolis have gained wide popularity in the last decades. While its antibacterial, antiviral, and antifungal properties are well known, the anticancer properties of propolis are just beginning to be appreciated. Herein, we comparatively investigate the cytotoxic and radiosensitizing potential of four different ethanolic propolis extracts originating from three different countries (Germany, Ireland, South Africa) in human lung cancer cell models.

Variable-RBE-induced NTCP predictions for various side-effects following proton therapy for brain tumors - Identification of high-risk patients and risk mitigation.

Background And Purpose: Disregarding the increase of relative biological effectiveness (RBE) may raise the risk of acute and late adverse events after proton beam therapy (PBT). This study aims to explore the relationship between variable RBE (above 1.1)-induced normal tissue complication probabilities (NTCP) and patient-specific factors, identify patients at high risk of RBE-induced NTCP increase, and assess risk mitigation by incorporating RBE variability into treatment planning.

Experience Matters: Impact on Technical Success and Complication Rate in Percutaneous Transhepatic Biliary Drainage.

Rationale And Objectives: To investigate factors influencing the success and complication rate of percutaneous transhepatic biliary drainage (PTBD).

Materials And Methods: PTBD procedures between 2017 and 2022 were enrolled retrospectively. Success rate, complications, and technical considerations were compared using Mann-Whitney U-, X-, and Fishers exact tests.

The emerging role of Artificial Intelligence in proton therapy: A review.

Artificial intelligence (AI) has made a tremendous impact in the space of healthcare, and proton therapy is not an exception. Proton therapy has witnessed growing popularity in oncology over recent decades, and researchers are increasingly looking to develop AI and machine learning tools to aid in various steps of the treatment planning and delivery processes. This review delves into the emergent role of AI in proton therapy, evaluating its development, advantages, intended clinical contexts, and areas of application.

Brain tumor detection and segmentation using deep learning.

Objectives: Brain tumor detection, classification and segmentation are challenging due to the heterogeneous nature of brain tumors. Different deep learning-based algorithms are available for object detection; however, the performance of detection algorithms on brain tumor data has not been widely explored. Therefore, we aim to compare different object detection algorithms (Faster R-CNN, YOLO & SSD) for brain tumor detection on MRI data.

Adaptive intensity modulated proton therapy using 4D robust planning: a proof-of-concept for the application of dose mimicking approach.

A four-dimensional robust optimisation (4DRO) is usually employed when the tumour respiratory motion needs to be addressed. However, it is computationally demanding, and an automated method is preferable for adaptive planning to avoid manual trial-and-error. This study proposes a 4DRO technique based on dose mimicking for automated adaptive planning.

Artificial intelligence for response prediction and personalisation in radiation oncology.

Artificial intelligence (AI) systems may personalise radiotherapy by assessing complex and multifaceted patient data and predicting tumour and normal tissue responses to radiotherapy. Here we describe three distinct generations of AI systems, namely personalised radiotherapy based on pretreatment data, response-driven radiotherapy and dynamically optimised radiotherapy. Finally, we discuss the main challenges in clinical translation of AI systems for radiotherapy personalisation.

Glutamine Metabolism and Prostate Cancer.

Glutamine (Gln) is a non-essential amino acid that is involved in the development and progression of several malignancies, including prostate cancer (PCa). While Gln is non-essential for non-malignant prostate epithelial cells, PCa cells become highly dependent on an exogenous source of Gln. The Gln metabolism in PCa is tightly controlled by well-described oncogenes such as MYC, AR, and mTOR.

Aqueous extracts from Dioscorea sansibarensis Pax show cytotoxic and radiosensitizing potential in 3D growing HPV-negative and HPV-positive human head and neck squamous cell carcinoma models.

Numerous natural substances have anti-cancer properties. Especially indigenous people use aqueous plant extracts for tea or ointments including Dioscorea sansibarensis Pax to treat various diseases. The aim of this study was to evaluate the cytotoxic and radiosensitizing potential of aqueous extracts from Dioscorea sansibarensis Pax collected from Kenya in a panel of HPV-negative and -positive head and neck squamous cell carcinoma (HNSCC) cells grown in three-dimensional laminin-rich extracellular matrix (3D lrECM).

Diffusion decrease in normal-appearing white matter structures following photon or proton irradiation indicates differences in regional radiosensitivity.

Purpose: Radio(chemo)therapy (RCT) as part of the standard treatment of glioma patients, inevitably leads to radiation exposure of the tumor-surrounding normal-appearing (NA) tissues. The effect of radiotherapy on the brain microstructure can be assessed by magnetic resonance imaging (MRI) using diffusion tensor imaging (DTI). The aim of this study was to analyze regional DTI changes of white matter (WM) structures and to determine their dose- and time-dependency.

Absolute energy-dependent scintillating screen calibration for real-time detection of laser-accelerated proton bunches.

Laser-plasma accelerators (LPAs) can deliver pico- to nanosecond long proton bunches with ≳100 nC of charge dispersed over a broad energy spectrum. Increasing the repetition rates of today's LPAs is a necessity for their practical application. This, however, creates a need for real-time proton bunch diagnostics.

An operator-independent quality assurance system for automatically generated structure sets.

. This study describes geometry-based and intensity-based tools for quality assurance (QA) of automatically generated structures for online adaptive radiotherapy, and designs an operator-independent traffic light system that identifies erroneous structure sets.A cohort of eight head and neck (HN) patients with daily CBCTs was selected for test development.

A deep-learning-based surrogate model for Monte-Carlo simulations of the linear energy transfer in primary brain tumor patients treated with proton-beam radiotherapy.

This study explores the use of neural networks (NNs) as surrogate models for Monte-Carlo (MC) simulations in predicting the dose-averaged linear energy transfer (LET) of protons in proton-beam therapy based on the planned dose distribution and patient anatomy in the form of computed tomography (CT) images. As LETis associated with variability in the relative biological effectiveness (RBE) of protons, we also evaluate the implications of using NN predictions for normal tissue complication probability (NTCP) models within a variable-RBE context.The predictive performance of three-dimensional NN architectures was evaluated using five-fold cross-validation on a cohort of brain tumor patients (= 151).

Simulation and experimental benchmarking of a proton pencil beam scanning nozzle model for development of MR-integrated proton therapy.

Background: MR-integrated proton therapy is under development. It consists of the unique challenge of integrating a proton pencil beam scanning (PBS) beam line nozzle with an magnetic resonance imaging (MRI) scanner. The magnetic interaction between these two components is deemed high risk as the MR images can be degraded if there is cross-talk during beam delivery and image acquisition.

Minimal cellular automaton model with heterogeneous cell sizes predicts epithelial colony growth.

Regulation of cell proliferation is a crucial aspect of tissue development and homeostasis and plays a major role in morphogenesis, wound healing, and tumor invasion. A phenomenon of such regulation is contact inhibition, which describes the dramatic slowing of proliferation, cell migration and individual cell growth when multiple cells are in contact with each other. While many physiological, molecular and genetic factors are known, the mechanism of contact inhibition is still not fully understood.

Type I conventional dendritic cells and CD8 T cells predict favorable clinical outcome of head and neck squamous cell carcinoma patients.

Head and neck squamous cell carcinoma (HNSCC) is one of the most common tumor entities worldwide, with human papillomavirus (HPV) infection contributing to cancer development. Conventional therapies achieve only limited efficiency, especially in recurrent or metastatic HNSCC. As the immune landscape decisively impacts the survival of patients and treatment efficacy, this study comprehensively investigated the immunological tumor microenvironment (TME) and its association with patient outcome, with special focus on several dendritic cell (DC) and T lymphocyte subpopulations.