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Background And Introduction: Brain metastasis velocity (BMV) has been proposed as a prognostic factor for overall survival (OS) in patients with brain metastases (BMs). In this study, we conducted an external validation and comparative assessment of the performance of all three BMV scores.
Materials And Methods: Patients treated with intracranial stereotactic radiotherapy (SRT) for BM at a single center between 2014 and 2018 were identified. Where possible, all three BMV scores were calculated. Log-rank tests and linear, logistic and Cox regression analysis were used for validation and predictor identification of OS.
Results: For 333 of 384 brain metastasis patients, at least one BMV score could be calculated. In a sub-group of 187 patients, "classic" BMV was validated as categorical (p < 0.0001) and continuous variable (HR 1.02; 95% CI 1.02-1.03; p < 0.0001). In a sub-group of 284 patients, "initial" BMV was validated as categorical variable (high-risk vs. low-risk; p < 0.01), but not as continuous variable (HR 1.02; 95% CI 0.99-1.04; p = 0.224). "Volume-based" BMV could not be validated in a sub-group of 104 patients. On multivariable Cox regression analysis, iBMV (HR 1.85; 95% CI 1.01-3.38; p < 0.05) and cBMV (HR 2.32; 95% CI 1.15 4.68; p < 0.05) were predictors for OS for intermediate-risk patients after first SRT and first DBFs, respectively. cBMV proved to be the dominant predictor for OS for high-risk patients (HR 2.99; 95% CI 1.30-6.91; p < 0.05).
Conclusion: This study externally validated cBMV and iBMV as prognostic scores for OS in patients treated with SRT for BMs whereas validation of vBMV was not achieved.
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http://dx.doi.org/10.1016/j.radonc.2023.109917 | DOI Listing |
BMJ Health Care Inform
September 2025
Center for Sleep and Circadian Medicine, The Affiliated Brain Hospital, Guangzhou Medical University, Guangzhou, Guangdong, China
Objectives: The objectives were to examine the associations between accelerometer-measured circadian rest-activity rhythm (CRAR), the most prominent circadian rhythm in humans and the risk of mortality from all-cause, cancer and cardiovascular disease (CVD) in patients with cancer.
Methods: 7456 cancer participants from the UK Biobank were included. All participants wore accelerometers from 2013 to 2015 and were followed up until 24 January 2024, with a median follow-up of 9.
Radiother Oncol
September 2025
Department of Radiation Oncology, University Hospital Bonn, Bonn, Germany; Institute of Experimental Oncology, University Hospital Bonn, Bonn, Germany. Electronic address:
Background: In recent years, intraoperative radiotherapy (IORT) with low-energy X-rays is emerging as an alternative to postoperative stereotactic radiotherapy (SRT) of the resection cavity in patients with resectable brain metastases (BMs).
Methods: We performed a systematic review of the MEDLINE, Embase, and Scopus databases, including all original articles on IORT for resectable BMs from 2015 to 2025. Data on safety, local control, and survival outcomes were collected.
Radiother Oncol
September 2025
Amsterdam UMC, Location University of Amsterdam, Department of Neurosurgery, Meibergdreef 9, Amsterdam, the Netherlands; Amsterdam Neuroscience, Amsterdam, the Netherlands; Cancer Center Amsterdam, Amsterdam, the Netherlands.
Background And Purpose: Staged Gamma Knife radiosurgery (SGKRS) delivers high-dose radiotherapy to large brain metastases (BM) in two or three fractions with a time interval of several weeks. Various systemic treatments have also demonstrated favorable intracranial responses. Therefore, the outcome of patients undergoing radiosurgery and systemic treatment for large BM is of high interest but unknown.
View Article and Find Full Text PDFStem Cell Reports
September 2025
Laboratory of Neural Stem Cells and Functional Neurogenetics, Farmington, CT 06030, USA; Departments of Neuroscience, Neurology, Genetics and Genome Sciences, UConn Health, Farmington, CT 06030, USA. Electronic address:
Intratumoral heterogeneity in glioblastoma is thought to underlie its remarkable ability to recur and resist therapies. Its origins, however, remain unknown. In this issue, Liu et al.
View Article and Find Full Text PDFComput Med Imaging Graph
August 2025
Academy for Engineering and Technology, Fudan University, Shanghai, 200433, People's Republic of China; Department of Radiology, Huashan Hospital, Fudan University, Shanghai, 200040, People's Republic of China; Shanghai Engineering Research Center of Intelligent Imaging for Critical Brain Diseases,
Recent advancements in artificial intelligence have significantly enhanced the efficiency of abdominal MRI segmentation, thereby improving the screening and diagnosis of liver diseases. However, accurate precise liver segmentation in MRI remains a challenging task due to the high variability in liver morphology and the limited availability of high-quality annotated datasets. To address these challenges, this study presents an advanced semi-supervised learning framework that integrates cross-teaching with pseudo-label generation and intra-batch entropy minimization.
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