Search Results (177)

Breast tissue-mimicking phantoms are essential tools for validating microwave imaging systems designed for early breast cancer detection. In this work, we report the fabrication and comprehensive characterization of oil-in-gelatin phantoms emulating normal, benign, and malignant breast tissues. The phantoms were manufactured with controlled mixtures of kerosene, safflower oil, and gelatin, and their dielectric properties were experimentally evaluated using a free-space transmission method with a Vector Network Analyzer across the 100 MHz–10 GHz range. Results demonstrated significant contrast in permittivity and conductivity among the different tissue types, consistent with values reported in the literature. Long-term stability was confirmed for up to six months under controlled storage. Additional structural and thermal characterization was performed using Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA), providing insight into molecular composition and thermal response. The proposed method enables reproducible, low-cost, and stable phantom fabrication, offering reliable tissue models to support experimental validation and optimization of microwave-based breast cancer detection systems. Full article

Photon-counting computed tomography (PCCT) represents a major technological innovation compared to conventional CT, offering improved spatial resolution, reduced electronic noise, and intrinsic spectral capabilities. These advances open new perspectives for synergy with radiomics, a field that extracts quantitative features from medical images. The ability of PCCT to generate multiple types of datasets, including high-resolution conventional images, iodine maps, and virtual monoenergetic reconstructions, increases the richness of extractable features and potentially enhances radiomics performance. This narrative review investigates the current evidence on the interplay between PCCT and radiomics in cardiothoracic imaging. Phantom studies demonstrate reduced reproducibility between PCCT and conventional CT systems, while intra-scanner repeatability remains high. Nonetheless, PCCT introduces additional complexity, as reconstruction parameters and acquisition settings significantly may affect feature stability. In chest imaging, early studies suggest that PCCT-derived features may improve nodule characterization, but existing machine learning models, such as those applied to interstitial lung disease, may require recalibration to accommodate the new imaging paradigm. In cardiac imaging, PCCT has shown particular promise: radiomic features extracted from myocardial and epicardial tissues can provide additional diagnostic insights, while spectral reconstructions improve plaque characterization. Proof-of-concept studies already suggest that PCCT radiomics can capture myocardial aging patterns and discriminate high-risk coronary plaques. In conclusion, evidence supports a growing synergy between PCCT and radiomics, with applications already emerging in both lung and cardiac imaging. By enhancing the reproducibility and richness of quantitative features, PCCT may significantly broaden the clinical potential of radiomics in computed tomography. Full article

Experimental measurement of dose distributions is a pivotal step in the quality assurance of radiotherapy treatments, especially for those relying on high delivery accuracy such as hadron therapy. This study investigated the response of a polymer gel dosimeter to determine its suitability in performing geometric beam characterizations for hadron therapy under high-quenching conditions. Different extraction energies of proton and carbon ion beams were considered. Gel dose–response linearity and long-term stability were confirmed through optical measurements. Gel phantoms were irradiated with pencil beams and analyzed via magnetic resonance imaging. A multi-echo T₂-weighted sequence was used to reconstruct depth–dose profiles and transversal distributions acquired by the gels, which were benchmarked against reference data. As expected, a response-quenching effect in the Bragg peak region was noted. Nonetheless, the studied gel formulation proved reliable in acquiring the geometric characteristics of the beams, even without correcting for the quenching effect. Indeed, depth–dose distributions acquired by the gels showed an excellent agreement with measured particle range with respect to reference values, with mean discrepancies of 0.5 ± 0.2 mm. Single-spot transverse FWHM values at increasing depths also presented an average agreement within 1 mm with values determined with radiochromic films, thus supporting the excellent spatial resolving capabilities of the dosimetric gel. Full article

Background/Objectives: Magnetic drug targeting (MDT) using polyethene glycol (PEG)-coated magnetoresponsive nanoclusters (MNCs) can localize therapeutics, but washout from high-shear arterial flow limits efficacy. This study assesses how PEG molecular weight influences MNC deposition and washout resistance under a pulsatile flow. Methods: Magnetite MNCs were synthesized via solvothermal polyol reactions and PEGylated with PEG-2000, PEG-6000, or PEG-10,000. Characterization included TEM, DLS, zeta potential, FTIR, TGA, XPS, magnetic analysis, and rheology. In vitro assays used a 3 mm diameter glass phantom with pulsatile flow (0.10–0.45 m/s, 1 Hz) and a rectangular NdFeB (N35) permanent magnet (30 × 20 × 20 mm, 0.45 T) positioned 11 mm from the vessel wall. Washout performance was quantified by obstruction degree (OD), magnet coverage degree (MCd), washout degree (WD), washout rate constant (k_out), and half-life (τ₁/₂). Results: MNC-6000 balanced magnetic responsiveness (Ms = 72 emu/g), colloidal stability (ζ = +13.1 mV), and hydrodynamic size (535 nm), yielding superior retention (MCd = 72.3%, OD = 19.6%, WD = 17.9%, τ₁/₂ = 6.93 min). MNC-2000 exhibited faster loss (k_out = 0.14 min⁻¹, τ₁/₂ = 4.95 min), while MNC-10,000 produced higher OD (≈53%) with embolic risk. Magnetic mapping indicated vessel wall thresholds of B ≥ 0.18 T and ∇B ≥ 10 T/m for stable capture. Limitations: Limitations of this work include the use of a single-magnet geometry, an in vitro phantom model without endothelial biology, and a maximum targeting depth of ~12–14 mm. Conclusions: The PEG molecular weight modulates MDT performance through its effects on nanocluster stability, deposition morphology, and washout kinetics. The proposed OD, MCd, and WD metrics provide clinically relevant endpoints for optimizing MDT nanoparticle design and magnet configurations. Full article

This paper proposes the use of quantitative methods for the characterization of tissues by linking, into a single approach, ideas coming from the spectral analysis methods commonly used to determine the attenuation coefficient with the envelope statistics formulation. Initially, the Homodyned K-distribution model used to fit data obtained from ultrasound signal envelopes was reviewed, and the necessary equations to further derive the attenuation coefficient from this model were developed. To test and discuss the performance of these methods, experimental work was conducted in phantoms. To this end, a series of tissue-mimicking materials composed of poly-vinyl alcohol (PVA) loaded with different particles (aluminium, alumina, cellulose) at varying concentrations were manufactured. A single-channel scanning system was employed to analyse these samples. It was verified that quantitative images obtained from the attenuation coefficient and from the scatterer clustering μ parameter (associated with scatterer concentration) effectively discriminate materials exhibiting similar echo envelope patterns, enhancing the information obtained in comparison with the conventional analysis based on B-scans. Additionally, the implementation of quantitative bi-parametric imaging mappings based on both the μ parameter and the attenuation coefficient, as a means to rapidly visualize results and identify areas characterized by specific acoustic features, was also proposed. Full article

In this work, we analyze a scalar field model which gives rise to stable bound states in field space characterized by nonzero motion that breaks the underlying time translation symmetry of its Hamiltonian, known as time crystals. We demonstrate that an ideal fluid made up of these time crystals behaves as phantom dark energy characterized by an equation of state $w<-1$, speed of sound squared $c_s^2\ge 0$, and nonnegative energy density $\rho \ge 0$. Full article

Mueller matrix polarimetry is recently attracting more and more attention for its diagnostic potentials. However, for prevalently used division of time Mueller matrix polarimeter based on dual-rotating retarder scheme, beam drift induced by rotating polarizers and waveplates introduces spatial misalignment and pseudo-edge artifacts in imaging results, hindering following accurate microstructural features characterization. In this paper, we quantitatively analyze the beam drift phenomenon in dual-rotating retarder Mueller matrix microscopy and its impact on linear retardance measurement, which is frequently used to reflect tissue fiber arrangement. It is demonstrated that polarizer rotation induces larger beam drift than waveplate rotation due to surface non-uniformity and stress deformation. Furthermore, for waveplates rotated constantly in dual-rotating retarder scheme, their tilt within polarization state analyzer can result in more drift and throughput loss than those within polarization state generator. Finally, phantom and tissue experiments confirm that beam drift, rather than inherent optical path changes, dominates the systematic overestimation of linear retardance in boundary image regions. The findings highlight beam drift as a dominant error source for quantifying linear retardance, necessitating careful optical design alignment and a reliable registration algorithm to obtain highly accurate polarization data for training machine learning models of pathological diagnosis using Mueller matrix microscopy. Full article

Objectives: Atherosclerosis is a chronic inflammatory disease characterized by complex pathological mechanisms. Early detection of vulnerable plaques is critical for assessing rupture risk and preventing acute cardiovascular events. Conventional ultrasound contrast agents (UCAs) are limited in their ability to penetrate the vascular wall and unable to provide detailed information on plaque composition and stability. In this study, we developed biosynthetic gas vesicles (GVs) derived from Halobacterium NRC-1 as UCAs for imaging of vulnerable plaques. Methods: These GVs were functionalized with the VHPKQHR peptide (VHP), enabling specific binding to vascular cell adhesion molecule-1 (VCAM-1), a key biomarker of inflammation in atherosclerosis. In vitro evaluation of VHP-GVs was performed through contrast-enhanced ultrasound imaging using agarose gel phantoms and adhesion assays with inflammatory cell models to assess their targeting capability toward VCAM-1. In vivo ultrasound molecular imaging was performed using the Sprague Dawley (SD) rat model of early-stage atherosclerosis in the left common carotid artery to evaluate imaging efficacy. Results: Both in vitro and in vivo experiments demonstrated that VHP-GVs could effectively penetrate the vascular wall into plaques and generate robust ultrasound contrast signals for precise identification of vulnerable regions. Conclusions: This study establishes a promising tool for the early diagnosis and targeted treatment of atherosclerosis, underscoring the translational potential of biosynthetic nanobubbles in clinical practice. Full article

This paper presents the development and validation of a cost-effective 3D-printed conductive phantom for EEG sensing system validation that achieves 85% cost reduction (£48.10 vs. £300–£500) and 48-hour fabrication time while providing consistent electrical properties suitable for standardized electrode testing. The phantom was fabricated using conductive PLA filament in a two-component design with a conductive upper section and a non-conductive base for structural support. Comprehensive validation employed three complementary approaches: DC resistance measurements (821–1502 $\mathsf{\Omega }$), complex impedance spectroscopy at 100 Hz across anatomical regions (3.01–6.4 k$\mathsf{\Omega }$ with capacitive behavior), and 8-channel EEG system testing (5–11 k$\mathsf{\Omega }$ impedance range). The electrical characterization revealed spatial heterogeneity and consistent electrical properties suitable for comparative electrode evaluation and EEG sensing system validation applications. To establish context, we analyzed six existing phantom technologies including commercial injection-molded phantoms, saline solutions, hydrogels, silicone models, textile-based alternatives, and multi-material implementations. This analysis identifies critical accessibility barriers in current technologies, particularly cost constraints (£5000–20,000 tooling) and extended production timelines that limit widespread adoption. The validated 3D-printed phantom addresses these limitations while providing appropriate electrical properties for standardized EEG electrode testing. The demonstrated compatibility with clinical EEG acquisition systems establishes the phantom’s suitability for electrode performance evaluation and multi-channel system validation as a standardized testing platform, ultimately contributing to democratized access to EEG sensing system validation capabilities for broader research communities. Full article

Proton therapy has emerged as a highly precise and tissue-sparing radiotherapy technique, capitalizing on the unique energy deposition pattern of protons characterized by the Bragg peak. Ensuring treatment accuracy relies on calibration phantoms, often composed of tissue-equivalent polymeric materials. This study investigates the dosimetric behavior of four commonly used polymers—Parylene, Epoxy, Lexan, and Mylar—by analyzing their linear energy transfer (LET) values and Bragg curve characteristics across various proton energies. Experimental LET data were collected and used to train and evaluate the predictive power for Bragg peak of multiple artificial intelligence models, including kNN, SVR, MLP, RF, LWRF, XGBoost, 1D-CNN, LSTM, and BiLSTM. These algorithms were optimized using 10-fold cross-validation and assessed through statistical error and performance metrics including MAE, RAE, RMSE, RRSE, CC, and R². Results demonstrate that certain AI models, particularly RF and LWRF, accurately (in terms of all evaluation metrics) predict Bragg peaks in Epoxy polymers, reducing the reliance on costly and time-consuming simulations. In terms of CC and R² metrics, the LWRF model demonstrated superior performance, achieving scores of 0.9969 and 0.9938, respectively. However, when evaluated against MAE, RMSE, RAE, and RRSE metrics, the RF model emerged as the top performer, yielding values of 12.3161, 15.8223, 10.3536, and 11.4389, in the same order. Additionally, the SVR model achieved the highest number of statistically significant differences when compared pairwise with the other eight models, showing significance against six of them. The findings support the use of AI as a robust tool for designing reliable calibration phantoms and optimizing proton therapy planning. This integrative approach enhances the synergy between materials science, medical physics, and data-driven modeling in advanced radiotherapy systems. Full article

Oncological hyperthermia (HT) is a medical technique aimed at heating a specific region of the human body containing a tumour. The heat makes the tumour cells more sensitive to the cytotoxic effects of radiotherapy and chemotherapy. Electromagnetic (EM) HT devices radiate a single-frequency EM field that induces a temperature increase in the treated region of the body. The typical radiative HT frequencies are between 60 and 150 MHz for deep HT applications, while 434 MHz and 915 MHz are used for superficial HT. The input EM power can reach up to 2000 W in deep HT and 250 W in superficial applications, and the E-field should be linearly polarized. This study proposes the development and use of E-field sensors to measure the distribution and evaluate the polarization of the E-field radiated by HT devices inside equivalent phantoms. This information is fundamental for the validation and assessment of HT systems. The sensor is constituted by three mutually orthogonal probes. Each probe is composed of a dipole, a diode, and a high-impedance transmission line. The fundamental difference in the operability of this sensor with respect to the standard E-field square-law detectors lies in the high-power values of the considered EM sources. Numerical analyses were performed to optimize the design of the E-field sensor in the whole radiative HT frequency range and to characterize the sensor behaviour at the power levels of HT. Then the sensor was realized, and measurements were carried out to evaluate the E-field radiated by commercial HT systems. The results show the suitability of the developed sensor to measure the E-field radiated by HT applicators. Additionally, in the measured devices, the linear polarization is evidenced. Accordingly, the work shows that in these devices, a single probe can be used to completely characterize the field distribution. Full article

A comprehensive framework for ultrasound imaging simulations is presented. Solutions to an inhomogeneous wave equation are provided, yielding a linear model for characterizing ultrasound propagation and scattering in soft tissue. This simulation approach, which is based upon the fast nearfield method, is implemented in the Fast Object-oriented C++ Ultrasound Simulator (FOCUS) and is extended to a range of imaging modalities, including synthetic aperture, B-mode, plane wave, and color Doppler imaging. The generation of radiofrequency (RF) data and the receive beamforming techniques employed for each imaging modality, along with background on color Doppler imaging, are described. Simulation results demonstrate rapid convergence and lower error rates compared to conventional spatial impulse response methods and Field II, resulting in substantial reductions in computation time. Notably, the framework effectively simulates hundreds of thousands of scatterers without the need for a full three-dimensional (3D) grid, and the inherent randomness in the scatterer distributions produces realistic speckle patterns. A plane wave imaging example, for instance, achieves high fidelity using 100,000 scatterers with five steering angles, and the simulation is completed on a personal computer in a few minutes. Furthermore, by modeling scatterers as moving particles, the simulation framework captures dynamic flow conditions in vascular phantoms for color Doppler imaging. These advances establish FOCUS as a robust, versatile tool for the rapid prototyping, validation, and optimization of both established and novel ultrasound imaging techniques. Full article

Fish kills are sudden mass mortalities that occur in freshwater and marine systems worldwide. Fish kill surveys are essential for assessing the ecological and economic impacts of fish kill events, but are often labor-intensive, time-consuming, and spatially limited. This study aims to address these challenges by exploring the application of unoccupied aerial systems (or drones) and deep learning techniques for coastal fish carcass detection. Seven flights were conducted using a DJI Phantom 4 RGB quadcopter to monitor three sites with different substrates (i.e., sand, rock, shored Sargassum). Orthomosaics generated from drone imagery were useful for detecting carcasses washed ashore, but not floating or submerged carcasses. Single shot multibox detection (SSD) with a ResNet50-based model demonstrated high detection accuracy, with a mean average precision (mAP) of 0.77 and a mean average recall (mAR) of 0.81. The model had slightly higher average precision (AP) when detecting large objects (>42.24 cm long, AP = 0.90) compared to small objects (≤14.08 cm long, AP = 0.77) because smaller objects are harder to recognize and require more contextual reasoning. The results suggest a strong potential future application of these tools for rapid fish kill response and automatic enumeration and characterization of fish carcasses. Full article

We have previously shown that the mitochondrial respiratory chain (RC) can switch between the following two states: (i) an “ATP-producing” state characterized by the low production of reactive oxygen species (ROS), the vigorous translocation of hydrogen ions (H⁺), and the storage of energy from the H⁺ gradient in the form of ATP, and (ii) an “ROS-producing” state, where the translocation of H⁺ is slow but the production of ROS is high. Here, we suggest that the RC transition from an ATP-producing to an ROS-producing state initiates a mitochondrial permeability transition (MPT) by generating a burst of ROS. Numerous MPT activators induce the transition of the RC to an ROS-producing state, and the ROS generated in this state activate the MPT. The MPT, in turn, induces changes in conditions that are necessary for the RC to return to an ATP-producing state, decreasing the ROS production rate and restoring the normal permeability of the inner membrane. In this way, the transient MPT prevents cell damage from oxidative stress that would occur if the RC remained in an ROS-producing state. It is shown that an overload of glutamate, which enters through excitatory amino acid transporters (EAATs), induces the RC to switch to an ROS-producing state. Subsequent MPT activation causes a transition back to an ATP-producing state. The model was used to predict the spatial–temporal dynamics of glutamate concentrations and H₂O₂ production rates in a three-dimensional digital phantom of nervous tissue. Full article

Background: The increasing use of technologies operating between 10 and 200 kHz, such as RFID, wireless power transfer systems, and induction cooktops, raises concerns about electromagnetic interference (EMI) with cardiac implantable electronic devices (CIEDs). The mechanisms of interaction within this frequency range have been only partially addressed by both the scientific and regulatory communities. Methods: A physical twin of a pacemaker/implantable defibrillator (PM/ICD) was developed to experimentally assess voltages induced at the input stage by low-to-mid-frequency magnetic fields. The setup simulates the two sensing modalities programmable in PMs/ICDs and allows for the analysis of different implant configurations, lead geometries, and positions within a human body phantom. Results: Characterization of the physical twin demonstrated its capability to reliably measure induced voltages in the range of 5 mV to 1.5 V. Its application enabled the identification of factors beyond the implant’s induction area that contribute to the induced voltage, such as the electrode-tissue interface and body-induced currents. Conclusions: This physical twin represents a valuable tool for experimentally validating the mechanisms of EMI in CIEDs, providing insights beyond current standards. The data obtained can serve as a reference for the validation of numerical models and patient-specific digital twins. Moreover, it offers valuable information to guide future updates and revisions of international electromagnetic compatibility standards for CIEDs. Full article