Purpose: General practitioners (GPs) play a crucial role in providing interdisciplinary care for radiation oncology patients. This study aims to understand the specific needs and challenges faced by general practitioners in Germany when treating oncology patients.
Methods: A comprehensive web-based questionnaire with 24 items was disseminated to GPs in Germany via email using survio.
Metastasis-directed therapy (MDT) for oligometastatic breast cancer (≤ 5 metastases) has shown little effect in specific scenarios of randomized trials. Therefore, we aimed to assess outcomes after metastasis-directed stereotactic radiotherapy (SRT) in various clinical scenarios. We conducted an international retrospective cohort study in thirteen centers including breast cancer patients receiving SRT to any metastatic site.
View Article and Find Full Text PDFBackground: 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.
View Article and Find Full Text PDFBackground: Stereotactic radiosurgery (SRS) is an emerging alternative to whole-brain radiotherapy (WBRT) for treating multiple brain metastases (BM), reducing toxicity, and improving tumor control. The CYBER-SPACE trial compared SRS based on either SPACE or MPRAGE MRI sequence for avoiding or delaying WBRT in patients with 1-10 BM.
Methods: Patients with 1-10 untreated BM were randomized 1:1 to receive SRS of all lesions based on either SPACE or MPRAGE MRI sequences.
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.
View Article and Find Full Text PDFBackground: A reduced Karnofsky performance score (KPS) often leads to the discontinuation of surgical and adjuvant therapy, owing to a lack of evidence of survival and quality of life benefits. This study aimed to examine the clinical and treatment outcomes of patients with KPS < 70 after neurosurgical resection and identify prognostic factors associated with better survival.
Methods: Patients with a preoperative KPS < 70 who underwent surgical resection for newly diagnosed brain metastases (BM) between 2007 and 2020 were retrospectively analyzed.
Background: Novel radiotherapeutic modalities using carbon ions provide an increased relative biological effectiveness (RBE) compared to photons, delivering a higher biological dose while reducing radiation exposure for adjacent organs. This prospective phase 2 trial investigated bimodal radiotherapy using photons with carbon-ion (C12)-boost in patients with WHO grade 2 meningiomas following subtotal resection (Simpson grade 4 or 5).
Methods: A total of 33 patients were enrolled from July 2012 until July 2020.
Background: Despite advances in treatment for brain metastases (BMs), the prognosis for recurrent BMs remains poor and requires further research to advance clinical management and improve patient outcomes. In particular, data addressing the impact of tumor volume and surgical resection with regard to survival remain scarce.
Methods: Adult patients with recurrent BMs between December 2007 and December 2022 were analyzed.
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.
View Article and Find Full Text PDFBackground: 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.