Search Results (172)

This study aimed to investigate the distribution of thermal neutron fluence generated during proton-beam therapy (PBT) scanning, focusing on neutrons produced within the body using Monte Carlo simulations (MCSs). MCSs used the Particle and Heavy Ion Treatment Code System to define a 35 × 35 × 35 cm³ water phantom, and proton-beam energies ranging from 70.2 to 228.7 MeV were investigated. The MCS results were compared with neutron fluence measurements obtained from gold activation analysis, showing good agreement with a difference of 3.54%. The internal thermal neutron distribution generated by PBT was isotropic around the proton-beam axis, with the Bragg peak depth varying between 3.45 and 31.9 cm, while the thermal neutron peak depth ranged from 5.41 to 15.9 cm. Thermal neutron generation depended on proton-beam energy, irradiated particle count, and depth. Particularly, the peak of the thermal neutron fluence did not occur within the treatment target volume but in a location outside the target, closer to the source. This discrepancy between the Bragg peak and the thermal neutron fluence peak is a key finding of this study. These data are crucial for optimizing beam angles to maximize dose enhancement within the target during clinical applications of neutron capture-enhanced particle therapy. Full article

Photoacoustic (PA) imaging (PAI) holds great promise for non-invasive biomedical diagnostics. However, the efficacy of current contrast agents is often limited by photobleaching, toxicity, and complex synthesis processes. In this study, we introduce a novel, biocompatible PAI contrast agent: a recombinant water-soluble chlorophyll-binding protein (WSCP) from Lepidium virginicum (LvP) reconstituted with chlorophyll a (LvP-chla). LvP-chla exhibits a strong and narrow absorption peak at 665 nm, with a molar extinction coefficient substantially higher than oxyhemoglobin and deoxyhemoglobin, enabling robust signal generation orthogonal to endogenous chromophores. Phantom studies confirmed a linear relationship between PA signal amplitude and LvP-chla concentration, demonstrating its stability and reliability. In vitro cytotoxicity testing using 4T1 cells showed high cell viability at 5 mg/mL, justifying its use for in vivo studies. In vivo experiments with a 4T1 tumor-bearing mouse model demonstrated successful tumor localization following intratumoral injection of LvP-chla, with clear visualization via spectroscopic differentiation from endogenous absorbers at 665 nm and 685 nm. Toxicity assessments, both in vitro and in vivo, revealed no adverse effects, and clearance studies confirmed minimal retention after 96 h. These findings show that LvP-chla is a promising contrast agent that enhances PAI capabilities through its straightforward synthesis, stability, and biocompatibility. Full article

Background/Objectives: This work prospectively evaluates the vendor-provided Low Variance (LOVA) apparent diffusion coefficient (ADC) gradient nonlinearity correction (GNC) technique for primary tumors, neck nodal metastases, and normal masseter muscles in patients with head and neck cancers (HNCs). Methods: Multiple b-value diffusion-weighted (DW)-MR images were acquired on a 3.0 T scanner using a single-shot echo planar imaging (SS-EPI) and multi-shot (MS)-EPI for diffusion phantom materials (20% and 40% polyvinylpyrrolidone (PVP) in water). Pretreatment DW-MRI acquisitions were performed for sixty HNC patients (n = 60) who underwent chemoradiation therapy. ADC values with and without GNC were calculated offline using a monoexponential diffusion model over all b-values, relative percentage (r%) changes (Δ) in ADC values with and without GNC were calculated, and the ADC histograms were analyzed. Results: Mean ADC values calculated using SS-EPI DW data with and without GNC differed by ≤1% for both PVP20% and PVP40% at the isocenter, whereas off-center differences were ≤19.6% for both concentrations. A similar trend was observed for these materials with MS-EPI. In patients, the mean rΔADC (%) values measured with SS-EPI differed by 4.77%, 3.98%, and 5.68% for primary tumors, metastatic nodes, and masseter muscle. MS-EPI exhibited a similar result with 5.56%, 3.95%, and 4.85%, respectively. Conclusions: This study showed that the GNC method improves the robustness of the ADC measurement, enhancing its value as a quantitative imaging biomarker used in HNC clinical trials. Full article

Currently, advanced RT techniques such as VMAT and HT are being developed to optimize tumor coverage while minimizing radiation exposure to the surrounding organs that are at risk. Despite their growing clinical use, comparative studies evaluating the dosimetric and radiobiological effects of these modalities remain limited. In this study, A549, HeLa, and HepG2 cells were exposed to a single 2 Gy dose, using three RT techniques (3D-CRT, dual arc VMAT, and HT). Treatment plans were generated using a water phantom to ensure consistent target coverage and comparable dosimetric parameters across the techniques. Multiple radiobiological endpoints were assessed to evaluate the cellular responses. Although all three techniques yielded similar dosimetric parameters without statistically significant differences, the biological responses varied among the cell lines. Notably, VMAT and HT demonstrated superior tumor cell suppression compared to 3D-CRT. This was likely due to their enhanced dose conformity and modulation precision, which potentially led to improved tumor cell killing. These findings highlight the importance of integrating radiobiological assessments with physical dose metrics to inform the clinical application of advanced RT technologies. However, this study had several limitations. The use of a single radiation dose limited its clinical relevance, and the immediate post-irradiation assessments may not have captured delayed biological responses. Additionally, the small number of replicates may have reduced the study’s statistical power. Future studies incorporating dose fractionation schemes, time course analyses, and larger sample sizes are warranted to better simulate clinical conditions and further elucidate the radiobiological effects of advanced RT techniques. Full article

Monte Carlo simulation relies on pseudo-random number generators. In general, the quality of these generators can have a direct impact on simulation results. The GATE toolbox, widely adopted in radiotherapy, offers three generators from which users can choose: Mersenne Twister, Ranlux-64, and James-Random. In this study, we used these generators to simulate the head of a medical linear accelerator for 6 MV photons in order to assess their potential impact on the results obtained in radiotherapy simulation. Simulations were conducted for four different field openings. The simulations included a linac head model and a water phantom, all components of the head of the medical linear accelerator, and a water phantom placed at a distance of 100 cm from the electron source. Statistical analysis based on normal probability and Bland–Altman plots were used to compare dose distributions in the voxelized water phantom obtained by each generator. Experimental data (dose profiles, percentage dose at depth, and other dosimetric parameters) were measured using an appropriate quality assurance protocol for comparison with the different simulations. The evaluation of dosimetric criteria shows significant variations, particularly in the physical penumbra of the dose profile for large fields. The gamma index analysis highlights significant distinctions in generator performance. In all simulations, the average time of the primary particle generation rate, number of tracks, and steps in the simulation of different random number generators showed differences. The Mersenne Twister generator was distinguished by high performance in several aspects, particularly in terms of execution time, primary particle production, track and step production flow rate, and coming closer to the experimental results. Regarding computational time, the simulation using the Mersenne Twister generator was about 18% faster than the one using the James-Random generator and 27% faster than the simulation using the Ranlux-64 generator. This suggests that this generator is the most reliable for accurate and fast modeling of the medical linear accelerator head for 6 MV energy. Full article

Lung computed tomography (CT) images are widely used to diagnose chronic obstructive pulmonary disease (COPD) by evaluating signs of lung tissue destruction. Accurate diagnosis requires standardizing the CT numbers in lung CT images to distinguish between normal and damaged tissue. The CT number standardization method proposed by Chen-Mayer et al., which uses the linearity of Martinez’s formula, showed promising results in phantom studies. However, our findings reveal that the CT number of water varies significantly, depending on scanning conditions and the characteristics of its container, making it an unreliable reference for lung CT number standardization. To enhance the standardization method, we modified the approach to exclude water and used only solid foams from the COPD gene2 phantom as references. To evaluate the proposed method, we collected 234 CT images of the COPD gene2 phantom from 8 different CT scanners and assessed performance by analyzing CT number standard deviations and variations. The modification resulted in improved reliability and consistency in CT number standardization. Additionally, for a detailed analysis, we segmented the dataset based on CT dose index (CTDI), X-ray tube potential, and reconstruction algorithms to examine the impact of different scanning protocols on standardization performance. Full article

Background/Objectives: Cranial reconstruction (cranioplasty) is a surgical procedure performed to restore skull function and aesthetics following trauma, oncological conditions, or congenital defects. Magnetic resonance imaging (MRI) is commonly used for the postoperative monitoring and diagnosis of patients with cranial implants. However, MRI artifacts caused by these implants can compromise imaging accuracy and diagnostic precision. This study aims to evaluate the extent of MRI artifacts caused by titanium and polyether ether ketone (PEEK) cranial implants and to identify optimal imaging sequences to minimize these artifacts. Methods: Phantom skull models with cranial defects of varying sizes (one-quarter, one-third, and one-half of the skull) were used to simulate real-world clinical conditions. The defects were filled with a water-based medium containing simulated brain tissue and tumor models. Custom 3D-printed titanium and PEEK cranial implants were fixed onto the phantom skulls and scanned using 1.5 T and 3 T MRI scanners. Various imaging sequences were tested, with a focus on optimizing parameters to reduce artifact formation. Turbo Spin Echo (TSE) sequences with fat saturation were implemented to assess their effectiveness in artifact reduction. Results: The study found that MRI artifacts varied based on the implant material, defect size, and magnetic field strength. A higher field strength (3 T) resulted in more pronounced artifacts. However, the use of TSE sequences with fat saturation significantly reduced artifacts and improved lesion visualization, enhancing diagnostic accuracy. Conclusions: This research highlights the importance of optimized MRI protocols when imaging patients with cranial implants. Proper selection of imaging sequences, particularly TSE with fat saturation, can mitigate artifacts and improve diagnostic precision, ultimately benefiting patient outcomes in clinical radiology. Full article

Background: Bone marrow (BM) adipocytes play a critical role in the progression of both solid tumor metastases and expansion of hematological malignancies across a spectrum of ages, from pediatric to aging populations. Single-point biopsies remain the gold standard for monitoring BM diseases, including hematologic malignancies, but these are limited in capturing the full complexity of loco-regional and global BM microenvironments. Non-invasive imaging techniques such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and Positron Emission Tomography (PET) could provide valuable alternatives for real-time evaluation in both preclinical translational and clinical studies. Methods: We developed a preclinical proton density fat fraction (PDFF) MRI technique for the quantitative assessment of BM composition, focusing on the fat fraction (FF) within mouse femurs. We validated this method using aging mice and young mice subjected to 10 Gy X-ray irradiation, compared to young control mice. Water–fat phantoms with varying fat percentages (0% to 100%) were used to optimize the imaging sequence, and immunohistochemical (IHC) staining with H&E validated equivalent adipose content in the femur BM region. Results: Significant differences in FF were observed across age groups (p = 0.001 for histology and p < 0.001 for PDFF) and between irradiated and control mice (p = 0.005 for histology and p = 0.002 for PDFF). A strong correlation (R²~0.84) between FF values from PDFF-MRI and histology validated the accuracy of the technique. Conclusions: These findings highlight PDFF-MRI’s potential as a non-invasive, real-time, in vivo biomarker for quantitatively assessing the BM fat fraction in preclinical studies, particularly in studies evaluating the effects of aging, disease progression, and cytotoxic cancer therapies, including chemotherapy and radiation. Full article

Background/Objectives: To evaluate the detectability of iodine in mediastinal lesions with photon counting CT (PCCT) compared to conventional CT (CCT) in a phantom study. Methods: Mediastinal lesions were simulated by five cylindrical inserts with diameters from 1 to 12 mm within a 10 cm solid water phantom that was placed in the mediastinal area of an anthropomorphic chest phantom with fat ring (QRM-thorax, QRM L-ring, 30 cm × 40 cm cross-section). Inserts were filled with iodine contrast at concentrations of 0.238 to 27.5 mg/mL. A clinical chest protocol at 120 kV on a high-end CCT (Somatom Force, Siemens Healthineers) was compared to the same protocol on a PCCT (Naeotom Alpha, Siemens Healthineers). Images reconstructed with a soft tissue kernel at 1 mm thickness and a 512 matrix served as a reference. For PCCT, we studied the result of reconstructing virtual mono-energetic images (VMIs) at 40, 50, 60 and 70 keV, reducing exposure dose up by 66%, reducing slice thickness to 0.4 and 0.2 mm, and increasing matrix size from 512 to 768 and 1024. Two observers with similar experience independently determined the smallest insert size for which iodine enhancement could still be detected. Consensus was reached when detectability thresholds differed between observers. Results: CTDIvol on PCCT and CCT was 3.80 ± 0.12 and 3.60 ± 0.01 mGy, respectively. PCCT was substantially more sensitive than CCT for detection of iodine in small mediastinal lesions: to detect a 3 mm lesion, 11.2 mg/mL iodine was needed with CCT, while only 1.43 mg/mL was required at 40 keV and 50 keV with PCCT. Moreover, dose reduced by 66% resulted in a comparable detection of iodine between PCCT and CCT for all lesions, except 3 mm. Detection increased from 11.2 mg/mL on CCT to 4.54 mg/mL on PCCT. A matrix size of 1024 reduced this detection threshold further, to 0.238 mg/mL at 40 and 50 keV. For 5 mm lesions, this detection threshold of 0.238 mg/mL was already achieved with a 512 matrix. Very small, 1 mm lesions did not profit from PCCT except if reconstructed with a 1024 matrix, which reduced the detection threshold from 27.5 mg/mL to 11.2 mg/mL. Reduced slice thickness decreased iodine detection of 3–12 mm lesions but not for 1 mm lesions. Conclusions: Iodine detectability with PCCT is at least equal to CCT for simulated mediastinal lesions of 1–12 mm, even at a dose reduction of 66%. Iodine detectability further profits from virtual monoenergetic images of 40 and 50 keV and increased reconstruction matrix. Full article

A dosimetric study compared flattened filter (FF) and unflattened filter-free (FFF) 18 MV medical linear accelerators (LINAC) using BEAMnrc Monte Carlo (MC) calculations and experimental measurements. BEAMnrc MC simulations were initially validated against experimental measurements for an 18 MV FF LINAC, with parameters such as the percentage depth dose (PDD) and beam profile measured and calculated per the International Atomic Energy Agency (IAEA) dosimetry protocol TRS 398. Following the validation of the LINAC and water phantom models for MC simulations, BEAMnrc MC calculations were performed to compare the FF and FFF 18 MV LINAC parameters. The results indicate that the BEAMnrc MC accurately simulated the LINAC model, with PDD uncertainties within 2%. Beam flatness differences between the MC simulations and measurements in the plateau region were within 3% and within 2 mm in the penumbra region. The PDD data show that the 18 MV FFF beam delivered a higher dose rate in the buildup region than the FF beam, while beam profile measurements indicate lower out-of-field doses for FFF beams, especially in the 20 × 20 cm² field. These findings provide crucial dosimetric data for an 18 MV FFF LINAC, which is useful for quality assurance and beam matching, and offer a methodology for quantitatively comparing the dosimetry properties of an individual 18 MV FFF LINAC to reference data. Full article

Objectives: Anthropomorphic phantoms offer a promising solution to minimize animal testing, enable medical training, and support the efficient development of medical devices. The adjustable mechanical, biochemical, and imaging properties of the polyvinyl alcohol cryogel (PVA-C) make it an appropriate phantom material for mimicking soft tissues. Conventional manufacturing (CM) of aqueous solutions requires constant stirring, using a heated water bath, and monitoring. Methods: To explore potential improvements in the dissolution of PVA crystals in water, a microwave-based manufacturing method (MWM) was employed. Samples created using CM and MWM (n = 14 each) were compared. Because PVA-C is a multifunctional phantom material (e.g., in magnetic resonance imaging (MRI)), its MRI properties (T1/T2 relaxation times) and elasticity were determined. Results: T1 relaxation times did not significantly differ between the two methods (p = 0.3577), whereas T2 and elasticity for the MWM were significantly higher than those for the CM (p < 0.001). The MWM reduced the production time by 11% and decreased active user involvement by 93%. Conclusions: The MWM offers a promising, easily implementable, and time-efficient method for manufacturing PVA-C-based phantoms. Nevertheless, manufacturing-related microstructural properties and sample molding require further study. Full article

Existing dosimeters for radiation therapy are typically large, and their performance in in vivo system applications has not been assessed. This study develops a compact real-time dosimeter using silicon photomultipliers, plastic scintillators, and optical fibers and evaluates its in vivo applicability for radiation therapy. Dose calibration, dose-rate dependency and linearity, and short-term repeatability tests were conducted using solid water phantoms and bolus materials, and in vivo dosimetry was performed using an in-house phantom. The characterization evaluation results showed high linearity, with a coefficient of determination of 0.9995 for dose rates of 100–600 monitoring units (MU)/min, confirming an error rate within 2% when converted to dosage. In the short-term repeatability tests, the dosimeter exhibited good characteristics, with relative standard deviation (RSD) values lower than 2% for each beam delivery and an RSD value of 0.03% over ten beam deliveries. Dose measurements using the phantom indicated an average error rate of 3.83% compared to the values calculated using the treatment planning system. These results demonstrate a performance comparable to that of commercial metal-oxide-semiconductor field-effect transistors and plastic scintillator-based dosimeters. Based on these findings, the developed dosimeter has significant potential for in vivo radiation therapy applications. Full article

Background: We aimed to measure the pacemaker- and defibrillator-induced distortion at 0.35T and 3.0T magnetic fields. Methods: The pacemaker/defibrillator was placed at the top center of a water-filled/MagPhan phantom, followed by a T1 scan at 3T and a TrueFISP scan at 0.35T. The extent of distortion (i.e., the distance from the device to the furthest signal loss/void/rings) in the water-filled phantom was measured in MIM. For geometrical distortion (i.e., dislocation of geometrical structures), the spheres in the MagPhan phantom were contoured and their distortion was calculated based on their manufacturing coordinate positions. Results: The maximum extent of distortion caused by the defibrillator was 18.8 cm at 0.35T and 5.8 cm at 3.0T. Similarly, the maximum extent of distortion caused by the pacemaker was 9.28 cm at 0.35T and 2.8 cm at 3.0T. Geometrical distortion measurements using the MagPhan phantom showed that the maximum distortion caused by the defibrillator was 12.8 mm at 0.35T and 13.2 mm at 3.0T. Likewise, the maximum distortion caused by the pacemaker was 8.7 mm at 0.35T and 6.0 mm at 3.0T. Conclusions: Defibrillators cause larger distortions/signal voids than pacemakers, and require careful consideration when performing MRI-based treatment planning. To minimize distortion, sequences with lower sensitivity to magnetic field inhomogeneity should be used. Full article

We demonstrate a method to characterize the beam energy, transverse profile, charge, and dose of a pulsed electron beam generated by a 1 kHz TW laser-plasma accelerator. The method is based on imaging with a scintillating screen in an inhomogeneous, orthogonal magnetic field produced by a wide-gap magnetic dipole. Numerical simulations were developed to reconstruct the electron beam parameters accurately. The method has been experimentally verified and calibrated using a medical LINAC. The energy measurement accuracy in the 6–20 MeV range is proven to be better than 10%. The radiation dose has been calibrated by a water-equivalent phantom, RW3, showing a linear response of the method within 2% in the 0.05–0.5 mGy/pulse range. Full article

Water content is one of the most critical characteristics in plant physiological development. Therefore, this information is a crucial factor in determining the water stress conditions of vegetation, which is essential for assessing the wildfire risk and land management decision-making. Remote sensing can be vital for obtaining information over large, limited access areas with global coverage. This is important since conventional techniques for collecting vegetation water content are expensive, time-consuming, and spatially limited. This work aims to evaluate the vegetation live fuel moisture content (LFMC) seasonal variability using a multiscale remote sensing approach, particularly on rockroses, the Cistus ladanifer species, a Western Mediterranean basin native species with wide spatial distribution, over the Herdade da Mitra at the University of Évora, Portugal. This work used four dataset sources, collected monthly between June 2022 and July 2023: (i) Vegetation samples used to calculate the LFMC; (ii) Vegetation reflectance spectral signature using the portable spectroradiometer FieldSpec HandHeld-2 (HH2); (iii) Multispectral optical imagery obtained from the Multispectral Instrument (MSI) sensor onboard the Sentinel-2 satellite; and (iv) Multispectral optical imagery derived from a camera onboard an Unmanned Aerial Vehicle Phantom 4 Multispectral (P4M). Several temporal analyses were performed based on datasets from different sensors and on their intercomparison. Furthermore, the Random Forest (RF) classifier, a machine learning model, was used to estimate the LFMC considering each sensor approach. MSI sensor presented the best results (R² = 0.94) due to the presence of bands on the Short-Wave Infrared Imagery region. However, despite having information only in the Visible and Near Infrared spectral regions, the HH2 presents promising results (R² = 0.86). This suggests that by combining these spectral regions with a RF classifier, it is possible to effectively estimate the LFMC. This work shows how different spatial scales, from remote sensing observations, affect the LFMC estimation through machine learning techniques. Full article