"sCT-Feasibility" - a feasibility study for deep learning-based MRI-only brain radiotherapy.

BACKGROUND: Radiotherapy (RT) is an important treatment modality for patients with brain malignancies. Traditionally, computed tomography (CT) images are used for RT treatment planning whereas magnetic resonance imaging (MRI) images are used for tumor delineation. Therefore, MRI and CT need to be registered, which is an error prone process. The purpose of this clinical study is to investigate the clinical feasibility of a deep learning-based MRI-only workflow for brain radiotherapy, that eliminates the registration uncertainty through calculation of a synthetic CT (sCT) from MRI data. METHODS: A total of 54 patients with an indication for radiation treatment of the brain and stereotactic mask immobilization will be recruited. All study patients will receive standard therapy and imaging including both CT and MRI. All patients will receive dedicated RT-MRI scans in treatment position. An sCT will be reconstructed from an acquired MRI DIXON-sequence using a commercially available deep learning solution on which subsequent radiotherapy planning will be performed. Through multiple quality assurance (QA) measures and reviews during the course of the study, the feasibility of an MRI-only workflow and comparative parameters between sCT and standard CT workflow will be investigated holistically. These QA measures include feasibility and quality of image guidance (IGRT) at the linear accelerator using sCT derived digitally reconstructed radiographs in addition to potential dosimetric deviations between the CT and sCT plan. The aim of this clinical study is to establish a brain MRI-only workflow as well as to identify risks and QA mechanisms to ensure a safe integration of deep learning-based sCT into radiotherapy planning and delivery. DISCUSSION: Compared to CT, MRI offers a superior soft tissue contrast without additional radiation dose to the patients. However, up to now, even though the dosimetrical equivalence of CT and sCT has been shown in several retrospective studies, MRI-only workflows have still not been widely adopted. The present study aims to determine feasibility and safety of deep learning-based MRI-only radiotherapy in a holistic manner incorporating the whole radiotherapy workflow. TRIAL REGISTRATION: NCT06106997.

Detailed in vitro analyses of the impact of multimodal cancer therapy with hyperthermia and radiotherapy on the immune phenotype of human glioblastoma cells.

PURPOSE: Improvements of heat-delivery systems have led to hyperthermia (HT) being increasingly recognized as an adjunct treatment modality also for brain tumors. But how HT affects the immune phenotype of glioblastoma cells is only scarcely known. MATERIALS AND METHODS: We therefore investigated the effect of in vitro HT, radiotherapy (RT), and the combination of both (RHT) on cell death modalities, immune checkpoint molecule (ICM) expression and release of the danger signal HSP70 of two human glioblastoma cell lines (U87 and U251) by using multicolor flow cytometry and ELISA. Hyperthermia was performed once or twice for 60-minute sessions reaching temperatures of 39 °C, 41 °C, and 44 °C, respectively. RT was administered with 5 x 2 Gy. RESULTS: A hyperthermia chamber for cell culture t-flasks regulating the temperature via a contact sensor was developed. While the glioblastoma cells were rather radioresistant, particularly in U251 cells, the combination of RT with HT significantly increased the percentage of apoptotic and necrotic cells for all temperatures examined and for both, single and double HT application. In line with that, an increased release of HSP 70 was seen only in U251 cells, mainly following treatment with HT at temperatures of 44 °C alone or in combination with RT. In contrast, immune suppressive (PD-L1, PD-L2, HVEM) and immune stimulatory (ICOS-L, CD137-L and Ox40-L) ICMs were significantly increased mostly on U87 cells, and particularly after RHT with 41 °C. CONCLUSIONS: Individual assessment of the glioblastoma immune cell phenotype with regard to the planned treatment is mandatory to optimize multimodal radio-immunotherapy protocols including HT.