Search Results (51)

This study aims to demonstrate the feasibility of ultrashort echo time (UTE)-based susceptibility source separation for musculoskeletal (MSK) imaging, enabling discrimination between diamagnetic and paramagnetic tissue components, with a particular focus on hemophilic arthropathy (HA). Three key techniques were integrated to achieve UTE-based susceptibility source separation: Iterative decomposition of water and fat with echo asymmetry and least-squares estimation for B0 field estimation, projection onto dipole fields for local field mapping, and χ-separation for quantitative susceptibility mapping (QSM) with source decomposition. A phantom containing varying concentrations of diamagnetic (CaCO₃) and paramagnetic (Fe₃O₄) materials was used to validate the method. In addition, in vivo UTE-QSM scans of the knees and ankles were performed on five HA patients using a 3T clinical MRI scanner. In the phantom, conventional QSM underestimated susceptibility values due to the mixed-source cancelling the effect. In contrast, source-separated maps provided distinct diamagnetic and paramagnetic susceptibility values that correlated strongly with CaCO₃ and Fe₃O₄ concentrations (r = −0.99 and 0.95, p < 0.05). In vivo, paramagnetic maps enabled improved visualization of hemosiderin deposits in joints of HA patients, which were poorly visualized or obscured in conventional QSM due to susceptibility cancellation by surrounding diamagnetic tissues such as bone. This study demonstrates, for the first time, the feasibility of UTE-based quantitative susceptibility source separation for MSK applications. The approach enhances the detection of paramagnetic substances like hemosiderin in HA and offers potential for improved assessment of bone and joint tissue composition. Full article

Deeply implanted biomedical devices like leadless pacemakers require an antenna with minimal volume and high radiation efficiency to ensure reliable in-body communication and long operational time within the human body. This paper introduces a novel implantable antenna designed to significantly reduce the spatial requirements within an implantable capsule while maintaining high radiation efficiency in lossy media like heart tissue. The design principles of the proposed antenna are outlined, followed by antenna parameters and an equivalent circuit study that demonstrates how to fine-tune the antenna’s resonant frequency. The radiation characteristics of the antenna are thoroughly investigated, revealing a radiation efficiency of up to 28% at the Medical Implant Communication System (MICS) band and 56% at the 2.4 GHz ISM band. The transmission efficiency between two deeply implanted antennas within heart tissue has been improved by more than 15 dB compared to the current state of the art. The radiation and transmission performance of the proposed antennas has been validated through comprehensive simulations using anatomical human body models, phantom measurements, and in vivo animal experiments, confirming their superior radiation performance. Full article

Clinical application of AI/DL-aided acquisitions for quantitative bi-parametric (q-bp)MRI requires validation and harmonization across vendor platforms. An AI/DL-accelerated q-bpMRI, including 5-echo T₂ and 4-b-value apparent diffusion coefficient (ADC) mapping, was implemented on two 3T clinical scanners by two vendors alongside the qualitative standard-of-care (SOC) MRI protocols for six patients with biopsy-confirmed prostate cancer (PCa). AI/DL versus SOC bpMRI image quality was compared for MR-visible PCa lesions on a 4-point Likert-like scale. Quantitative validation and protocol bias assessment were performed using a multiparametric phantom with reference T₂ and diffusion kurtosis values mimicking prostate tissue ranges. Six-minute q-bpMRI achieved acceptable diagnostic quality comparable to the SOC. Better SNR was observed for DL/AI versus SOC ADC with method-dependent distortion susceptibility and resolution enhancement. The measured biases were unaffected by AI/DL reconstruction and related to acquisition protocol parameters: constant for spin-echo T₂ (−7 ms to +5 ms) and ADC (4b-fit: −0.37 µm²/ms and 2b-fit: −0.19 µm²/ms), while nonlinear for echo-planar T₂ (−37 ms to +14 ms). Measured phantom ADC bias dependence on b-value range was consistent with that observed for PCa lesions. Bias correction harmonized lesion T₂ and ADC values across different AI/DL-aided q-bpMRI acquisitions. The developed workflow enables harmonization of AI/DL-accelerated quantitative T₂ and ADC mapping in multi-vendor clinical settings. Full article

Diffusion-weighted magnetic resonance (DWMR) images were acquired using a custom-designed, 3D-printed breast-mimicking phantom. The smoothing factor of the non-local means (NLM) algorithm was then optimized for noise reduction. Phantoms were fabricated using polylactic acid, polyethylene terephthalate, and various concentrations of polyvinylpyrrolidone. DWMR images were obtained across b-values ranging from zero to 2000 s/mm². Based on image contrast, the NLM algorithm was applied to the b = 1000 s/mm² image, testing smoothing factors from 0.001 to 0.150. The NLM algorithm’s performance was quantitatively evaluated using a single DWMR image acquired from this custom phantom. At the optimized smoothing factor, the signal-to-noise ratio (SNR) improved from 96.87 ± 3.42 to 215.81 ± 4.18, and the contrast-to-noise ratio (CNR) from 43.63 ± 2.97 to 131.98 ± 3.56, representing 2.22-fold and 3.02-fold enhancements, respectively. No formal statistical tests were conducted as the analysis was based on a single acquisition. The optimized NLM algorithm also outperformed conventional denoising methods—median, Wiener, and total variation—in both noise suppression and contrast preservation. These findings suggest that the NLM algorithm with optimized parameters is likely to be more effective than existing approaches for enhancing breast DWMR image quality. However, further validation using in vivo patient datasets is essential to confirm its diagnostic utility and clinical generalizability because of the absence of tissue heterogeneity, motion, and physiological noise in the phantom environment. Full article

Objective: Microwave hyperthermia is a clinically validated adjunctive therapy in oncology, employing antenna applicators to selectively raise tumor tissue temperature to 40–44 °C. For deep-seated tumors, especially those in anatomically complex areas like the head and neck (H&N) region, phased array antennas are typically employed. Determining optimal antenna feeding coefficients is crucial to maximize the specific absorption rate (SAR) within the tumor and minimize hotspots in healthy tissues. Conventionally, this optimization relies on meta-heuristic global algorithms such as particle swarm optimization (PSO). Methods: In this study, we consider a deterministic alternative to PSO in microwave hyperthermia SAR-based optimization, which is based on the Alternating Projections Algorithm (APA). This method iteratively projects the electric field distribution onto a set of constraints to shape the power deposition within a predefined mask, enforcing SAR focusing within the tumor while actively suppressing deposition in healthy tissues. To address the challenge of selecting appropriate power levels, we introduce an adaptive power threshold search mechanism using a properly defined quality parameter, which quantifies the excess of deposited power in healthy tissues. Results: The proposed method is validated on both a simplified numerical testbed and a realistic anatomical phantom. Results demonstrate that the proposed method achieves heating quality comparable to PSO in terms of tumor targeting, while significantly improving hotspot suppression. Conclusions: The proposed APA framework offers a fast and effective deterministic alternative to meta-heuristic methods, enabling SAR-based optimization in microwave hyperthermia with improved tumor targeting and enhanced suppression of hotspots in healthy tissue. Full article

Among the leading etiologies of limb amputations are diabetes mellitus, alongside trauma and peripheral vascular disease conditions, whose complications are major indications for surgery, which can subsequently elicit chronic refractory postamputation pain. ‘Phantom limb pain’ (PLP) denotes pain that is perceived as occurring in an absent part of the limb following amputation. Even though it is a relatively common complication among amputees—with an estimated prevalence as high as ~80 percent—the underlying mechanisms of this puzzling condition remain poorly understood. Current theories predominantly emphasize the role of the nervous system and neuropsychopathology in the development of PLP. However, these neurocentric explanations are disputed and have not yet been translated into effective treatments or a definitive cure for the condition, nor have several notable anomalies been settled, which has prompted researchers to call for the exploration of alternative theories. The aim of this paper is to offer an alternative mechanical mechanism for explaining PLP and spontaneous phantom sensations. This work introduces a theoretical model for the mechanism of PLP, drawing on a recent study that proposed this model to explain fibromyalgia-type psychosomatic syndromes as disorders driven by overactive soft tissue myofibroblasts. The manuscript proposes a shift from purely neurocentric models of PLP to a framework where the extracellular matrix and connective tissue, specifically myofascial tissue and inflammatory myofibroblasts—which are often overlooked in research—take part in its pathogenesis. In this suggested model, surgical interventions disrupt the biomechanical stability of the fascio-musculoskeletal biotensegrity-like system, thus acting as a contributing factor in the chronic pain manifestation. The term ‘biotensegrity’ refers to the dynamic biomechanical behavior of a living system that is stabilized by compressive and tensile force elements, a characteristic quality of myofascial tissue. In this framework, abnormal extracellular matrix remodeling, driven by overactive peripheral myofibroblasts, and the concomitant mechanical effects exerted on sensory nerves embedded within the fascia and reaching the neuroma microenvironment contribute to the generation and perception of spontaneous PLP and phantom sensations. The interplay between abnormal extracellular matrix, the neuroma’s intrinsic excitability, as well as peripheral and central neurophysiological mechanisms, collectively provide a biophysical neuropathophysiological basis to help explain PLP. This offers a different unexplored perspective on a condition with poorly understood mechanisms. Full article

Anthropomorphic CT phantoms are essential training tools for interventional radiology. Given the high technical demands and stringent safety requirements in this field, realistic CT phantoms are vital simulation tools that support effective hands-on training, procedural planning, and risk mitigation. However, commercially available phantom geometries are limited in their scope. This study investigates the use of polyvinyl alcohol (PVA) to fabricate customizable training phantoms. PVA, a non-toxic material, can be processed into PVA cryogels (PVA-C) with tissue-like mechanical properties. We modified PVA-C (10 wt.% PVA) by incorporating various additives to adjust X-ray attenuation and achieve Hounsfield units (HUs) similar to different soft tissues. HU values were measured at X-ray tube voltages of 70, 120, and 150 kV. The inclusion of barium sulfate (e.g., U = 120 kV; 0.1–2 wt.%: 33.29 ± 5.45–323.72 ± 12.64 HU) and iohexol (e.g., U = 120 kV; 0.1–2 wt.%: 26.05 ± 4.74–161.99 ± 5.69 HU) significantly increased HU values. Iohexol produced more homogeneous HU distributions than barium sulfate and cellulose derivatives, with the latter having air gaps and inconsistencies. The tested formulations encompassed a wide range of soft tissue densities, with HU values varying significantly across the energy range (p < 0.001). While cellulose derivatives showed variable HU modulation, their primary role appears to be in modifying phantom texture and morphology rather than precise attenuation control. In conclusion, PVA-C demonstrates strong potential for use in interventional radiology training phantoms. Further studies may enhance phantom realism by replicating tissue textures, for example, through the incorporation of cellulose-based substances. Full article

Medical phantoms are essential to imaging calibration, clinician training, and the validation of therapeutic procedures. However, most ultrasound phantoms prioritize acoustic realism while neglecting the viscoelastic and anisotropic properties of fibrous soft tissues. This gap limits their effectiveness in modeling realistic biomechanical behavior, especially in wave-based diagnostics and therapeutic ultrasound. Current materials like gelatine and agarose fall short in reproducing the complex interplay between the solid and fluid components found in biological tissues. To address this, we developed a soft, anisotropic composite whose dynamic mechanical properties resemble fibrous biological tissues such as skin and skeletal muscle. This material enables wave propagation and vibration studies in controllably anisotropic media, which are rare and highly valuable. We demonstrate the tunability of damping and stiffness aligned with fiber orientation, providing a versatile platform for modeling soft-tissue dynamics and validating biomechanical simulations. The phantoms achieved Young’s moduli of 7.16–11.04 MPa for skin and 0.494–1.743 MPa for muscles, shear wave speeds of 1.51–5.93 m/s, longitudinal wave speeds of 1086–1127 m/s, and sound absorption coefficients of 0.13–0.76 dB/cm/MHz, with storage, loss, and complex moduli reaching 1.035–6.652 kPa, 0.1831–0.8546 kPa, and 2.138–10.82 kPa. These values reveal anisotropic response patterns analogous to native tissues. This novel natural fibrous composite system affords sustainable, low-cost ultrasound phantoms that support both mechanical fidelity and acoustic realism. Our approach offers a route to next-gen tissue-mimicking phantoms for elastography, wave propagation studies, and dynamic calibration across diverse clinical and research applications. Full article

Breast cancer remains one of the leading causes of death among women globally. Early detection is critical for improving patient outcomes, making the development of accurate and efficient detection methods essential for facilitating timely treatment and enhancing patients’ quality of life. Lesion sites are often associated with localized temperature increases, which can be identified by characterizing thermal gradients using thermometry tools. Ultrasound-based techniques are preferred for obtaining thermal patterns due to their noninvasive, non-ionizing nature and cost-effectiveness compared to methods like magnetic resonance imaging. This study focuses on developing breast tissue models with varying acoustic properties, specifically the speed of sound across temperatures ranging from 32 °C to 36 °C in increments of 0.5 °C for ultrasonic inspection and diagnostic applications. These models simulate healthy and tumorous breast tissue, including the fat, gland, and tumor layers. Signal variations were analyzed using cross-correlation methods to assess the changes in the speed of sound as a function of temperature. The proposed methodology offers a cost-effective, rapid, and precise approach to phantom production, facilitating the detection of temperature changes in 0.5 °C intervals through cross-correlation analysis of the acquired signals. Full article

Optical coherence tomography (OCT) phantoms are essential tools for calibrating imaging systems, validating diagnostic algorithms, and bridging technological advancements with clinical applications. This review explores the development and application of materials used in OCT phantoms, emphasising their optical, mechanical, and biochemical fidelity to biological tissues. Gelatin-based phantoms (n = 1.35) offer controllable absorbance and scattering, with penetration depths (PDs) of 500–2000 µm and scattering coefficients (SCs) of 5–20 cm⁻¹ but are unstable at room temperature. Silicone phantoms (n = 1.41) are durable and stable, with SCs of 10–15 cm⁻¹, suitable for long-term studies. Polydimethylsiloxane (PDMS) phantoms (n = 1.41) provide manageable optical properties and are used in microfluidic applications. Polyvinyl alcohol (PVA) phantoms (n = 1.48) mimic soft tissue mechanics, with SCs of 5–15 cm⁻¹, but require freeze–thaw cycles. Fibrin phantoms (n = 1.38) simulate blood clotting, with SCs of 5–20 cm⁻¹. Scattering particles like polystyrene (n = 1.57) and titanium dioxide (TiO₂, n = 2.49) offer modifiable properties, while silica microspheres (SiO₂, n = 3.6) and gold nanoshells (n = 2.59) provide customisable optical characteristics. These materials and particles are crucial for simulating biological tissues, enhancing OCT imaging, and developing diagnostic applications. Despite progress, challenges persist in achieving submicron resolution, long-term stability, and cost-effective scalability. Full article

Background: Transcranial direct current stimulation (tDCS)-induced electric fields (EFs) acting on brain tissues are hardly controllable. Among physical models used in neuroscience research, watermelons are known as head-like phantoms for their dielectric properties. In this study, we aimed to define an inexpensive and reliable method to qualitatively define the spatial distribution of tDCS-induced EFs based on the use of watermelons. Methods: After creating the eight cranial foramina and identifying the location of the 21 EEG scalp electrodes on the peel of a watermelon, voltage differences during stimulation were recorded in each of the 21 scalp electrode positions, one at a time, at four different depths. The recordings were graphically represented by using polar coordinates with the watermelon approximated to a perfect sphere. Results: To validate the model, we performed three experiments in well-known montages. The results obtained were in line with the expected behavior of the EFs. Conclusions: Watermelon might be a cheap and feasible phantom head model to characterize the EFs induced by tDCS and, potentially, even other non-invasive brain stimulation techniques. Full article

Background: Ultrasonography is commonly employed during thoracic regional anesthesia; however, its accuracy can be affected by factors such as obesity and poor penetration through the rib window. Needle-sized ultrasound transducers, known as intra-needle ultrasound (INUS) transducers, have been developed to detect the pleura and fascia using a one-dimensional radio frequency mode ultrasound signal. In this study, we aimed to use time-frequency analysis to characterize the pleural signal and develop an automated tool to identify the pleura during medical procedures. Methods: We developed an INUS system and investigated the pleural signal it measured by establishing a phantom study, and an in vivo animal study. Signals from the pleura, endothoracic fascia, and intercostal muscles were analyzed. Additionally, we conducted time- and frequency-domain analyses of the pleural and alveolar signals. Results: We identified the unique characteristics of the pleura, including a flickering phenomenon, speckle-like patterns, and highly variable multi-band spectra in the ultrasound signal during the breathing cycle. These characteristics are likely due to the multiple reflections from the sliding visceral pleura and alveoli. This automated identification of the pleura can enhance the safety for thoracic regional anesthesia, particularly in difficult cases. Conclusions: The unique flickering pleural signal based on INUS can be processed by time-frequency domain analysis and further tracked by an auto-identification algorithm. This technique has potential applications in thoracic regional anesthesia and other interventions. However, further studies are required to validate this hypothesis. Key Points Summary: Question: How can the ultrasound pleural signal be distinguished from other tissues during breathing? Findings: The frequency domain analysis of the pleural ultrasound signal showed fast variant and multi-band characteristics. We suggest this is due to ultrasound distortion caused by the interface of multiple moving alveoli. The multiple ultrasonic reflections from the sliding pleura and alveoli returned in variable and multi-banded frequency. Meaning: The distinguished pleural signal can be used for the auto-identification of the pleura for further clinical respiration monitoring and safety during regional anesthesia. Glossary of Terms: intra-needle ultrasound (INUS); radio frequency (RF); short-time Fourier transform (STFT); intercostal nerve block (ICNB); paravertebral block (PVB); pulse repetition frequency (PRF). Full article

The electrolarynx (EL) is a common device for voice reconstruction in laryngectomy patients, but its mechanical sound source generates significant radiation noise, affecting the naturalness and acceptability of the speech. The parametric acoustic array (PAA), which produces directionally propagated difference-frequency sound waves, presents a promising alternative for creating a more natural glottal-like voice source in the trachea while reducing radiation noise. In this study, we developed a tissue-mimicking phantom to simulate human neck tissue and used a single-transducer-based PAA platform to generate modulated ultrasound signals with glottal waveform characteristics. Ultrasonic microphones captured sound signals fromthe trachea and surrounding air, and signal processing was used to isolate the difference-frequency signals. The results demonstrated that difference-frequency signals were successfully detected in the phantom’s trachea, with time-domain waveforms and frequency spectra closely resembling the designed glottal waveform (Pearson correlation coefficient = 0.9438). Additionally, radiation noise produced by the PAA was significantly lower (23 dB, p < 0.0001) compared to the traditional EL. These findings demonstrate the potential of PAA for voice source reconstruction in laryngectomy patients and suggest its capacity to enhance speech rehabilitation outcomes. Further research is required to refine the frequency range and evaluate clinical applicability. Full article

Micro-computed tomography (micro-CT) is a non-destructive imaging technique that offers highly detailed, 3D visualizations of a target specimen. In the context of breast cancer, micro-CT has emerged as a promising tool for analyzing microcalcifications (MCs), tiny calcium deposits that can indicate at an early stage the presence of cancer. This review aimed to explore the current applications of micro-CT in analyzing breast MCs (ex vivo, animal models, and phantoms) and to identify potential avenues in scientific research. We followed PRISMA guidelines for scoping reviews, yielding 18 studies that met our criteria. The studies varied in their purposes: feasibility and optimization of micro-CT for breast cancer imaging and MC analysis/diagnosis, comparison with other imaging modalities, development of micro-CT scanners and processing algorithms, enhancement of MC detection through contrast agents, etc. In conclusion, micro-CT offers superior image quality and detailed visualization of breast tissue (especially tumor masses and MCs), surpassing traditional methods like mammography and approaching the level of detail of histology. It holds great potential to enhance our understanding of MC characteristics and breast pathologies when used as a supplementary tool. Further research will solidify its role in clinical practice and potentially expand its applications in breast cancer studies. Full article

Multiparametric ultrasound (mpUS) enhances prostate cancer (PCa) diagnosis by using multiple imaging modalities. Tissue-mimicking materials (TMM) phantoms, favoured over animal models for ethical and consistency reasons, were created using polyvinyl alcohol (PVA) with varying molecular weights (Mw). Methods: Four PVA samples, varying in Mw with constant concertation, were mixed with glycerol, silicon carbide (SiC), and aluminium oxide (Al₂O₃). Phantoms with varying depth and inclusion sizes were created and tested using shear-wave elastography (SWE). An mpUS phantom was developed to mimic prostate tissue, including isoechoic and hypoechoic inclusions and vessels. The phantom was scanned using supersonic ultrasound, strain elastography, and Doppler ultrasound. Validation was performed using radical prostatectomy data and shear-wave elastography. Results: The acoustic properties varied with enhancers like glycerol and Al₂O₃. Low Mw PVA samples had a speed of sound ranging from 1547.50 ± 2 to 1553.70 ± 2.2 m/s and attenuation of 0.61 ± 0.062 to 0.63 ± 0.05 dB/cm/MHz. High Mw PVA samples ranged from 1555 ± 2.82 to 1566 ± 4.5 m/s and 0.71 ± 0.02 to 0.73 ± 0.046 dB/cm/MHz. Young’s modulus ranged from 11 ± 2 to 82.3 ± 0.5 kPa across 1 to 10 freeze-thaw cycles. Inclusion size, depth, and interaction statistically affect the SWE measurements with p-value = 0.056327, p-value = 8.0039 × 10⁻⁸, and p-value = 0.057089, respectively. SWE showed isoechoic inclusions, prostate tissue, and surrounding tissue only. The Doppler velocity was measured in three different inner diameters. Conclusion: PVA mixed with enhancer materials creates an mpUS phantom with properties that mimic normal and abnormal prostate tissue, blood vessels, and soft tissue, facilitating advanced diagnostic training and validation. Full article