Background: CyberKnife® stereotactic radiosurgery enables frameless, image-guided treatment of multiple brain metastases. Collimator type (Fixed vs. Iris) and planning strategy (Simultaneous vs. Separate) may influence low-dose normal brain exposure, plan quality, and treatment delivery efficiency. Objectives: The objective of the study was to compare the dosimetric performance of different collimator types and planning strategies in patients with three or four brain metastases under standardized planning conditions. Materials and Methods: Twenty patients were retrospectively replanned using four treatment configurations: Fixed Separate, Fixed Simultaneous, Iris Separate, and Iris Simultaneous. All plans were generated using identical prescription doses and planning objectives. Dosimetric evaluation included normal brain V8, V10, V12 (volumes receiving ≥8 Gy, ≥10 Gy, and ≥12 Gy), mean brain dose (Vmean), Paddick conformity index (PCI), and gradient index (GI). Comparisons were performed using Friedman and Wilcoxon signed-rank tests. Estimated treatment time was recorded for all plans. Results: Significant differences were observed for V8 (P = 0.039), Vmean (P = 0.019), and PCI (P < 0.001), whereas V10 (P = 0.180), V12 (P = 0.103), and GI (P = 0.420) showed no significant differences among the planning approaches. Median dosimetric values tended to favor Iris Simultaneous planning for reducing low-dose normal brain exposure. The significant PCI difference was primarily attributable to lower conformity in the Iris Separate plans. Total planning target volume demonstrated a near-significant positive association with V12 (P = 0.057). Iris-based plans were associated with shorter estimated treatment times. Conclusion: Under standardized planning conditions, Iris Simultaneous planning demonstrated favorable trends in reducing low-dose normal brain exposure while improving treatment delivery efficiency. Although conformity differed significantly among planning approaches, mainly because of lower PCI values in the Iris Separate plans, dose gradient characteristics remained comparable. These findings suggest that planning strategy may influence conformity more than dose fall-off in CyberKnife treatment of multiple brain metastases. Nevertheless, given the limited sample size, these results should be interpreted cautiously and validated in larger prospective studies.
Magnetic spinel ferrite nanoparticles with redox-active surface characteristics have attracted increasing attention as candidate nanomaterials for enhancing radiation-mediated therapeutic response. This study involved the creation of CoFe₂O₄ nanoparticles through a precisely managed chemical co-precipitation approach, followed by thermal annealing to obtain structurally stable inverse spinel nanostructures. The formation of a phase-pure cubic spinel lattice was confirmed by X-ray diffraction and Raman spectroscopy, whereas electron microscopy revealed predominantly spherical nanoparticles with sizes in the range of 20–40 nm. Nitrogen adsorption–desorption analysis demonstrated mesoporous surface characteristics with specific surface area values between 42 and 73 m2/g, supporting enhanced nanoparticle–cell interaction. The incorporation of redox-active Co2⁺ and Fe3⁺ species into the spinel lattice was validated by X-ray photoelectron spectroscopy. Biological assessments utilizing the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide assay indicated concentration-dependent cytotoxicity against MCF-7 breast cancer lines; however, normal L929 fibroblasts retained comparatively higher viability, suggesting targeted action. The observed cytotoxic behavior is attributed to reactive oxygen species-mediated mitochondrial dysfunction induced by transition-metal-dependent redox activity. In addition, antioxidant activity measured using 2,2 diphenyl-1-picrylhydrazyl assay confirmed concentration-dependent radical scavenging behavior, supporting the redox-modulating capability of the synthesized nanoparticles. The combined structural stability, mesoporous surface architecture, and ROS-mediated selective cytotoxic response suggest that CoFe₂O₄ nanoparticles may serve as promising ferrite-based candidate nanomaterials for nanoparticle-assisted radiotherapy applications. These findings support further investigation of mixed-metal ferrite nanoparticles as potential radiosensitizing agents under clinically relevant fractionated radiation dose conditions.
Magnetic resonance imaging (MRI) remains one of the most powerful diagnostic tools in medicine; however, its dependence on liquid helium for superconducting magnet cooling poses substantial economic, environmental, and logistical challenges. The global helium shortage and rising operational costs have accelerated the pursuit of sustainable alternatives that can maintain high diagnostic performance while reducing ecological impact. A systematic literature review was conducted using PubMed, Scopus, ScienceDirect, and Google Scholar databases, covering studies published between 2018 and 2025. The analysis focused on innovations in helium-free and cryogen-minimized MRI systems, including cryocooler-based conduction cooling, high-temperature superconductors (HTS), permanent and resistive magnet technologies, and the integration of artificial intelligence (AI) and digital twin frameworks for performance optimization. Findings indicate that helium-free MRI technologies deliver comparable image quality, field stability, and clinical utility to conventional systems while offering significant reductions in helium dependency, power consumption, and maintenance costs. Cryocooler and HTS-based magnets enable higher operational efficiency and reliability, while portable low-field permanent magnet systems enhance accessibility in low-resource settings. Moreover, AI-driven image reconstruction and predictive maintenance via digital twins improve workflow efficiency and sustainability. Helium-free MRI represents a paradigm shift toward sustainable and equitable medical imaging. By combining advanced magnet technologies, intelligent optimization systems, and eco-efficient design, these next-generation scanners address the global helium crisis and environmental footprint of healthcare infrastructure, redefining MRI as a cornerstone of green radiology.
Background: Hippocampal-avoidance whole-brain radiotherapy (HA-WBRT) reduces radiation dose to the hippocampal neural stem-cell niche, helping preserve neurocognitive function in patients with brain metastases. Objective: The objective of this study is to compare tomotherapy using a 1-cm field width with four-arc volumetric-modulated arc therapy (VMAT) for HA-WBRT. Materials and Methods: Twenty patients prescribed 30 Gy in 10 fractions were planned on both platforms. Hippocampi were contoured on T1-weighted magnetic resonance imaging according to the RTOG 0933 atlas. Tomotherapy plans used a 1-cm jaw, pitch 0.500, and modulation factor 1.5–2.0, while VMAT plans used 6 MV photons with one coplanar and three noncoplanar arcs. Plan quality, hippocampal and organ-at-risk (OAR) doses, treatment efficiency, and deliverability (3%/3 mm gamma analysis) were compared. Results: Planning target volume coverage was comparable (V95%: 96.67% ± 0.57% vs. 96.53% ± 0.73%; P = 0.28). Tomotherapy achieved superior homogeneity and conformity (both P < 0.001), with significantly lower hippocampal Dmax, Dmean, D40%, V10 Gy, and bilateral lens and globe doses (all P < 0.001). Gamma pass rates exceeded 95% for both techniques. VMAT provided shorter beam-on time (2.62 ± 0.25 vs. 12.21 ± 0.99 min) and lower monitor units (MU) (786.5 ± 74.9 vs. 12440.5 ± 992.9; both P < 0.001). Conclusion: Tomotherapy with a 1-cm field width provides superior hippocampal sparing, plan quality, and OAR protection while maintaining equivalent target coverage. VMAT achieves substantially faster treatment delivery with fewer MU, offering an alternative when shorter treatment times are preferred.
Purpose: Trainees often have limited understanding of radionuclide dose-calibrator physics because access to radioactive materials is restricted by radiation-safety requirements, and the complexity of established Monte Carlo (MC) platforms can present a barrier to early learning. We present a lightweight, Python-based MC simulation framework designed to visualize energy-dependent photon transport and ionization-chamber response for nuclear medicine education. Materials and Methods: A spherical gas-filled ionization chamber (radius 5 cm) was modelled. Photon free-path lengths were sampled from exponential attenuation distributions; deposited energy was assigned via a Beta-distributed stochastic transfer fraction (biased toward partial deposition). Ionization yield was estimated assuming 33.97 eV is required to produce one ion pair. Three clinically representative radionuclides – 99mTc (140 keV, μ = 0.030 cm−1), 131I (364 keV, μ = 0.015 cm−1), and 18F (511 keV, μ = 0.011 cm−1) – were each simulated with 100,000 independent photon histories. Results: Intrinsic efficiency decreased monotonically with photon energy: 13.65% (99mTc), 7.01% (131I), and 5.25% (18F). Median deposited energy increased from 37.16 keV to 95.87 keV and 132.07 keV; mean ion-pair yield rose from 1180, 3046, and 4254. Detector response increased nonlinearly from 161 to 214 and 223 ion pairs per emitted photon. All trends were consistent with exponential attenuation theory. Conclusions: The framework reproduces first-order ionization-chamber physics without specialist software or radioactive sources. Its transparency, rapid execution, and interactive visualizations make it well suited for classroom demonstrations and self-directed nuclear medicine physics training, while its explicit limitations underscore the gap between educational modelling and clinical-grade Monte Carlo simulation.
