PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 7502725

Optimization of dose distribution for LINAC based radiosurgery using elliptical collimators.

G F Popescu·J E Rodgers·R von Hanwehr
View original source ↗Export metadata ↓

Abstract

The use of non-circular collimators is considered on all or some of the arcs used for radiosurgery on a linear accelerator in order to obtain conformal dose distribution for non-spherical lesions using a single isocenter. An extension of software to allow for use of non-circular collimators and a mathematical optimization based on prescribed doses on the lesion surface and on points in normal tissue (critical structures) are presented. Tests of the optimization method on simulated cases indicate that several boosts from selected positions along the arcs, superimposed on an optimized arc configuration allows one to obtain a highly conformal dose distribution with simple elliptical inserts. The optimization method can be applied to any type of collimation and is particularly effective with variable dose-rate machines.

Explore related subjects

Brain NeoplasmsComputer SimulationHumansMathematical ComputingParticle AcceleratorsRadiosurgeryRadiotherapy Planning, Computer-AssistedSoftwareJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

G F Popescu, J E Rodgers, R von Hanwehr. 1995. Optimization of dose distribution for LINAC based radiosurgery using elliptical collimators.. https://doi.org/10.1007/978-3-7091-9399-0_8

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2026

Leveraging single-cell and spatial omics for brain tumour insights to improve therapeutic strategies.

Single-cell and spatial omics (SPOs) technologies have advanced how healthcare physicians characterise brain tumours by enabling detailed understanding of their cellular architecture, functional states, and microenvironmental dynamics. These approaches provide high-resolution detection of tumour heterogeneity and allow precise analysis of the brain tumour microenvironment. Their application has also led to the discovery of novel biomarkers used for early brain tumour detection, prognosis, and improved tumour stratification. Furthermore, integrative multi-omic analyses have revealed new therapeutic targets, clarified mechanisms of drug resistance, and uncovered molecular pathways underpinning treatment failure. By bridging cellular-level insights with spatial context, SPOs hold significant promise for advancing personalised diagnostics, predicting therapeutic response, and guiding the development of targeted interventions for brain tumours. Despite these advances, several limitations constrain the full translational potential of SPOs, including high experimental costs, substantial computational demands, lack of standardised protocols, and challenges in data integration and reproducibility. Addressing these barriers through scalable bioinformatic pipelines, consensus experimental frameworks, and cost-effective platforms remains critical for broadening accessibility and enabling clinical adoption.

Brain Neoplasms↗
PubMed2026

Identification of Critical Genes Related to Breast Cancer with Brain Metastasis Through Bioinformatics Analysis.

INTRODUCTION: Distant metastasis accounts for the majority of Breast Cancer (BC)-related mortality. The brain is one of the most common regions of metastasis. However, the underlying molecular mechanisms remain uncertain. METHODS: In this study, gene expression profiles were downloaded from the Gene Expression Omnibus (GEO) database. Datasets GSE100534 and GSE52604, containing 16 primary brain tumor samples and 38 breast cancer brain metastasis samples, were used to identify the Differentially Expressed Genes (DEGs). The Metascape database was used to analyze enriched Gene Ontology (GO) entries and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway entries in DEGs. The STRING database was then used to construct a Protein-Protein Interaction (PPI) network, and the Cytoscape platform was employed to visualize the network. Furthermore, the Kaplan-Meier curve was used to analyze the Relapse-Free Survival (RFS) among the hub genes. Finally, the iRegulon plugin was used to construct a regulatory network to find the transcription factors (TFs) that regulate the expression of the hub genes. RESULTS: A total of 344 DEGs, including 182 up-regulated and 162 down-regulated genes, were identified by using the limma package in R. A module with 18 nodes and 9 hub genes was selected from the PPI network by using the plugins MCODE and Cyto- Hubba, respectively. KEGG pathway analysis demonstrated that brain metastasis in BC was closely related to the oocyte cell cycle. The Kaplan-Meier curve showed that high expression of these 9 hub genes was associated with poor RFS in BC patients. TFs' analysis showed that E2F4, SIN3A, FOXM1, and TFDP1 interacted with these hub genes. DISCUSSION: This study revealed that Breast Cancer Brain Metastasis (BCBM) may have a promoting effect on the cell cycle of oocytes and affect the maturation and division of oocytes through the KEGG and GO analyses of 344 DEGs. The selected 9 hub genes (ASPM, BUB1, BUB1B, CCNA2, CCNB1, CDK1, NDC80, NCAPG, and TOP2A) and 4 transcription factors (E2F4, SIN3A, FOXM1, TFDP1) may play a critical role in brain metastasis of BC. CONCLUSION: The results of this study may aid in the early diagnosis and suggest potential targets for the treatment of BCBM.

Brain Neoplasms↗
PubMed2024

Simultaneous targeting of peripheral and brain tumors with a therapeutic nanoparticle to disrupt metabolic adaptability at both sites.

Brain metastasis of advanced breast cancer often results in deleterious consequences. Metastases to the brain lead to significant challenges in treatment options, as the blood-brain barrier (BBB) prevents conventional therapy. Thus, we hypothesized that creation of a nanoparticle (NP) that distributes to both primary tumor site and across the BBB for secondary brain tumor can be extremely beneficial. Here, we report a simple targeting strategy to attack both the primary breast and secondary brain tumors utilizing a single NP platform. The nature of these mitochondrion-targeted, BBB-penetrating NPs allow for simultaneous targeting and drug delivery to the hyperpolarized mitochondrial membrane of the extracranial primary tumor site in addition to tumors at the brain. By utilizing a combination of such dual anatomical distributing NPs loaded with therapeutics, we demonstrate a proof-of-concept idea to combat the increased metabolic plasticity of brain metastases by lowering two major energy sources, oxidative phosphorylation (OXPHOS) and glycolysis. By utilizing complementary studies and genomic analyses, we demonstrate the utility of a chemotherapeutic prodrug to decrease OXPHOS and glycolysis by pairing with a NP loaded with pyruvate dehydrogenase kinase 1 inhibitor. Decreasing glycolysis aims to combat the metabolic flexibility of both primary and secondary tumors for therapeutic outcome. We also address the in vivo safety parameters by addressing peripheral neuropathy and neurobehavior outcomes. Our results also demonstrate that this combination therapeutic approach utilizes mitochondrial genome targeting strategy to overcome DNA repair-based chemoresistance mechanisms.

Brain Neoplasms↗