Object: In this paper, the authors' goal was to analyze the incidence, timing, and treatment of new metastases following initial treatment with 20-Gy Gamma Knife surgery (GKS) alone in patients with limited brain metastases without whole-brain radiation therapy (WBRT).
Methods: A retrospective analysis of 114 consecutive adults (75 women and 34 men; median age 61 years) with KPS scores of 60 or higher who received GKS for 1-3 brain metastases ≤ 2 cm was performed (median lesion volume 0.35 cm(3)). Five patients lacking follow-up data were excluded from analysis. After treatment, patients underwent MR imaging at 6 weeks and every 3 months thereafter. New metastases were preferentially treated with additional GKS. Indications for WBRT included development of numerous metastases, leptomeningeal disease, or diffuse surgical-site recurrence.
Results: The median overall survival from GKS was 13.8 months. Excluding the 3 patients who died before follow-up imaging, 12 patients (11.3%) experienced local failure at a median of 7.4 months. Fifty-three patients (50%) developed new metastases at a median of 5 months. Six (7%) of 86 instances of new lesions were symptomatic. Most patients (67%) with distant failures were successfully treated using salvage GKS alone. Whole-brain radiotherapy was indicated in 20 patients (18.3%). Thirteen patients (11.9%) died of neurological disease.
Conclusions: For patients with limited brain metastases and functional independence, 20-Gy GKS provides excellent disease control and high-functioning survival with minimal morbidity. New metastases developed in almost 50% of patients, but additional GKS was extremely effective in controlling disease. Using our algorithm, fewer than 20% of patients required WBRT, and only 12% died of progressive intracranial disease.
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http://dx.doi.org/10.3171/2011.2.JNS101724 | DOI Listing |
Adv Sci (Weinh)
January 2025
The department of oncology, Xiangya Hospital, Central South University, Changsha, 410008, China.
Non-small cell lung cancer (NSCLC) frequently metastasizes to the brain, significantly worsened prognoses. This study aimed to develop an interpretable model for predicting survival in NSCLC patients with brain metastases (BM) integrating radiomic features and RNA sequencing data. 292 samples are collected and analyzed utilizing T1/T2 MRIs.
View Article and Find Full Text PDFF1000Res
January 2025
Department of Medical Imaging Technology, Manipal College of Health Professions, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.
Introduction: Magnetic resonance imaging (MRI) is essential for brain imaging, but conventional methods rely on qualitative contrast, are time-intensive, and prone to variability. Magnetic resonance finger printing (MRF) addresses these limitations by enabling fast, simultaneous mapping of multiple tissue properties like T1, T2. Using dynamic acquisition parameters and a precomputed signal dictionary, MRF provides robust, qualitative maps, improving diagnostic precision and expanding clinical and research applications in brain imaging.
View Article and Find Full Text PDFInt J Nanomedicine
January 2025
Department of Neurosurgery, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221002, People's Republic of China.
Glioma is the most common primary malignant brain tumor with a poor survival rate. It is characterized by diffuse and invasive growth and heterogeneity, which limits tumor identification and complete resection. Therefore, the precise detection and postoperative adjuvant therapy of gliomas have become increasingly important and urgent.
View Article and Find Full Text PDFCancer Imaging
January 2025
Department of Imaging, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
Background: Radiomic analysis of quantitative features extracted from segmented medical images can be used for predictive modeling of prognosis in brain tumor patients. Manual segmentation of the tumor components is time-consuming and poses significant reproducibility issues. We compare the prediction of overall survival (OS) in recurrent high-grade glioma(HGG) patients undergoing immunotherapy, using deep learning (DL) classification networks along with radiomic signatures derived from manual and convolutional neural networks (CNN) automated segmentation.
View Article and Find Full Text PDFBMC Biol
January 2025
Faculty of Biology, Johannes Gutenberg University Mainz, Mainz, Germany.
Background: Glioblastoma multiforme (GBM) is characterized by its cellular complexity, with a microenvironment consisting of diverse cell types, including oligodendrocyte precursor cells (OPCs) and neoplastic CD133 + radial glia-like cells. This study focuses on exploring the distinct cellular transitions in GBM, emphasizing the role of alternative polyadenylation (APA) in modulating microRNA-binding and post-transcriptional regulation.
Results: Our research identified unique APA profiles that signify the transitional phases between neoplastic cells and OPCs, underscoring the importance of APA in cellular identity and transformation in GBM.
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