Superior Anti-Tumor Response After Microbeam and Minibeam Radiation Therapy in a Lung Cancer Mouse Model.

Objectives: The present study aimed to compare the tumor growth delay between conventional radiotherapy (CRT) and the spatially fractionated modalities of microbeam radiation therapy (MRT) and minibeam radiation therapy (MBRT). In addition, we also determined the influence of beam width and the peak-to-valley dose ratio (PVDR) on tumor regrowth.

Methods: A549, a human non-small-cell lung cancer cell line, was implanted subcutaneously into the hind leg of female CD1 mice.

Heterogeneity-driven phenotypic plasticity and treatment response in branched-organoid models of pancreatic ductal adenocarcinoma.

In patients with pancreatic ductal adenocarcinoma (PDAC), intratumoural and intertumoural heterogeneity increases chemoresistance and mortality rates. However, such morphological and phenotypic diversities are not typically captured by organoid models of PDAC. Here we show that branched organoids embedded in collagen gels can recapitulate the phenotypic landscape seen in murine and human PDAC, that the pronounced molecular and morphological intratumoural and intertumoural heterogeneity of organoids is governed by defined transcriptional programmes (notably, epithelial-to-mesenchymal plasticity), and that different organoid phenotypes represent distinct tumour-cell states with unique biological features in vivo.

Pneumonitis after normofractionated radioimmunotherapy: a method for dosimetric evaluation.

Background: Post-Therapy-Pneumonitis (PTP) is a critical side effect of both, thoracic radio(chemo)therapy (R(C)T) and immune checkpoint inhibition (ICI). However, disease characteristics and patient-specific risk factors of PTP after combined R(C)T + ICI are less understood. Given that RT-triggered PTP is strongly dependent on the volume and dose of RT [1], driven by inflammatory mechanisms, we hypothesize that combination therapy of R(C)T with ICI influences the dose-volume-effect correlation for PTP.

Radiosurgery Society Case-Based Guide to Stereotactic Body Radiation Therapy for Challenging Cases of Spinal Metastases.

Purpose: Spinal stereotactic body radiation therapy (SBRT) has become the standard of care in management of patients with limited sites of metastatic disease, radioresistant histologies, painful vertebral metastases with long life expectancy and cases of reirradiation. Our case-based guidelines aim to assist radiation oncologists in the appropriate utilization of SBRT for common, yet challenging, cases of spinal metastases.

Methods And Materials: Cases were selected to include scenarios of large volume sacral disease with nerve entrapment, medically inoperable disease abutting the thecal sac, and local failure after prior SBRT.

Bone marrow toxicity in patients with locally advanced cervical cancer undergoing multimodal treatment with VMAT/IMRT: are there dosimetric predictors for toxicity?

Purpose: For women with locoregionally advanced cervical cancer, the standard of care treatment is the curatively intended chemoradiation therapy (CRT). A relationship between bone marrow (BM) dose-volume histograms (DVHs) and acute hematological toxicity (HT) has been debated recently. Aim of this study was the evaluation of BM dose constraints and HT in a contemporary patient cohort.

Dosiomics and radiomics-based prediction of pneumonitis after radiotherapy and immune checkpoint inhibition: The relevance of fractionation.

Objectives: Post-therapy pneumonitis (PTP) is a relevant side effect of thoracic radiotherapy and immunotherapy with checkpoint inhibitors (ICI). The influence of the combination of both, including dose fractionation schemes on PTP development is still unclear. This study aims to improve the PTP risk estimation after radio(chemo)therapy (R(C)T) for lung cancer with and without ICI by investigation of the impact of dose fractionation on machine learning (ML)-based prediction.

Pencil beam kernel-based dose calculations on CT data for a mixed neutron-gamma fission field applying tissue correction factors.

For fast neutron therapy with mixed neutron and gamma radiation at the fission neutron therapy facility MEDAPP at the research reactor FRM II in Garching, no clinical dose calculation software was available in the past. Here, we present a customized solution for research purposes to overcome this lack of three-dimensional dose calculation.The applied dose calculation method is based on two sets of decomposed pencil beam kernels for neutron and gamma radiation.

Proton-FLASH: effects of ultra-high dose rate irradiation on an in-vivo mouse ear model.

FLASH-radiotherapy may provide significant sparing of healthy tissue through ultra-high dose rates in protons, electrons, and x-rays while maintaining the tumor control. Key factors for the FLASH effect might be oxygen depletion, the immune system, and the irradiated blood volume, but none could be fully confirmed yet. Therefore, further investigations are necessary.

Enhanced RBE of Particle Radiation Depends on Beam Size in the Micrometer Range.

High-linear energy transfer (LET) radiation, such as heavy ions is associated with a higher relative biological effectiveness (RBE) than low-LET radiation, such as photons. Irradiation with low- and high-LET particles differ in the interaction with the cellular matter and therefore in the spatial dose distribution. When a single high-LET particle interacts with matter, it results in doses of up to thousands of gray (Gy) locally concentrated around the ion trajectory, whereas the mean dose averaged over the target, such as a cell nucleus is only in the range of a Gy.

SBRT of Spinal Metastases Using a Simultaneous Integrated Boost Concept in Oligometastatic Cancer Patients Is Safe and Effective.

(1) Purpose: To assess the safety and effectivity of stereotactic body radiotherapy (SBRT) on spinal metastases utilizing a simultaneous integrated boost (SIB) concept in oligometastatic cancer patients. (2) Methods: 62 consecutive patients with 71 spinal metastases received SIB-SBRT between 01/2013 and 09/2022 at our institution. We retrospectively analyzed toxicity, local tumor control (LC), and progression-free (PFS) and overall survival (OS) following SIB-SBRT and assessed possible influencing factors (Kaplan-Meier estimator, log-rank test and Cox proportional-hazards model).

Identification of the unfolded protein response pathway as target for radiosensitization in pancreatic cancer.

Background And Purpose: Due to the high intrinsic radioresistance of pancreatic ductal adenocarcinoma (PDAC), radiotherapy (RT) is only beneficial in 30% of patients. Therefore, this study aimed to identify targets to improve the efficacy of RT in PDAC.

Materials And Methods: Alamar Blue proliferation and colony formation assay (CFA) were used to determine the radioresponse of a cohort of 38 murine PDAC cell lines.

Multitask Learning with Convolutional Neural Networks and Vision Transformers Can Improve Outcome Prediction for Head and Neck Cancer Patients.

Neural-network-based outcome predictions may enable further treatment personalization of patients with head and neck cancer. The development of neural networks can prove challenging when a limited number of cases is available. Therefore, we investigated whether multitask learning strategies, implemented through the simultaneous optimization of two distinct outcome objectives (multi-outcome) and combined with a tumor segmentation task, can lead to improved performance of convolutional neural networks (CNNs) and vision transformers (ViTs).

The importance of planning CT-based imaging features for machine learning-based prediction of pain response.

Patients suffering from painful spinal bone metastases (PSBMs) often undergo palliative radiation therapy (RT), with an efficacy of approximately two thirds of patients. In this exploratory investigation, we assessed the effectiveness of machine learning (ML) models trained on radiomics, semantic and clinical features to estimate complete pain response. Gross tumour volumes (GTV) and clinical target volumes (CTV) of 261 PSBMs were segmented on planning computed tomography (CT) scans.

Identifying core MRI sequences for reliable automatic brain metastasis segmentation.

Background: Many automatic approaches to brain tumor segmentation employ multiple magnetic resonance imaging (MRI) sequences. The goal of this project was to compare different combinations of input sequences to determine which MRI sequences are needed for effective automated brain metastasis (BM) segmentation.

Methods: We analyzed preoperative imaging (T1-weighted sequence ± contrast-enhancement (T1/T1-CE), T2-weighted sequence (T2), and T2 fluid-attenuated inversion recovery (T2-FLAIR) sequence) from 339 patients with BMs from seven centers.

Establishment of a 3D Model to Characterize the Radioresponse of Patient-Derived Glioblastoma Cells.

Glioblastoma multiforme (GBM) is the most common malignant primary brain tumor in adults. Despite modern, multimodal therapeutic options of surgery, chemotherapy, tumor-treating fields (TTF), and radiotherapy, the 5-year survival is below 10%. In order to develop new therapies, better preclinical models are needed that mimic the complexity of a tumor.