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Conventional B-mode ultrasound imaging has difficulty in delineating homogeneous soft tissues with similar acoustic impedances, as the reflectivity depends on the acoustic impedance at the interface. As a quantitative imaging biomarker sensitive to alteration of biomechanical properties, speed-of-sound (SoS) holds promising potential for tissue and disease differentiation such as delineation of different breast tissue types with similar acoustic impedance. Compared to two-dimensional (2D) SoS images, three-dimensional (3D) volumetric SoS images achieved through a full-angle ultrasound scan can reveal more intricate morphological structures of tissues; however, they generally require a ring transducer. In this study, we introduce a 3D SoS reconstruction system that utilizes hand-held linear arrays instead. This system employs a passive reflector positioned opposite the linear arrays, serving as an echogenic reference for time-of-flight (ToF) measurements, and a high-definition camera to track the location corresponding to each group of transmit-receive data. To merge these two streams of ToF measurements and location tracking, a voxel-based reconstruction algorithm is implemented. Experimental results with gelatin phantom and ex vivo tissue have demonstrated the stability of our proposed method. Moreover, the results underscore the potential of this system as a complementary diagnostic modality, particularly in the context of diseases such as breast cancer. [ABSTRACT FROM AUTHOR]

Laser interstitial thermal therapy (LITT) is popular for treating brain tumours and epilepsy. The strict control of tissue thermal damage extent is crucial for LITT. Temperature prediction is useful for predicting thermal damage extent. Accurately predicting in vivo brain tissue temperature is challenging due to the temperature dependence and the individual variations in tissue properties. Considering these factors is essential for improving the temperature prediction accuracy. Objective . To present a method for predicting patient-specific tissue temperature distribution within a target lesion area in the brain during LITT. Approach . A magnetic resonance temperature imaging (MRTI) data-driven estimation model was constructed and combined with a modified Pennes bioheat transfer equation (PBHE) to predict patient-specific temperature distribution. In the PBHE for temperature prediction, the individual specificity and temperature dependence of thermal tissue properties and blood perfusion, as well as the individual specificity of optical tissue properties were considered. Only MRTI data during one laser irradiation were required in the method. This enables the prediction of patient-specific temperature distribution and the resulting thermal damage region for subsequent ablations. Main results . Patient-specific temperature prediction was evaluated based on clinical data acquired during LITT in the brain, using intraoperative MRTI data as the reference standard. Our method significantly improved the prediction performance of temperature distribution and thermal damage region. The average root mean square error was decreased by 69.54%, the average intraclass correlation coefficient was increased by 37.5%, the average Dice similarity coefficient was increased by 43.14% for thermal damage region prediction. Significance . The proposed method can predict temperature distribution and thermal damage region at an individual patient level during LITT, providing a promising approach to assist in patient-specific treatment planning for LITT in the brain., (© 2024 Institute of Physics and Engineering in Medicine.)

To investigate the effect of longitudinal variations of cap thickness and tissue properties on wall stresses and strains along the atherosclerotic stenosis, stenotic plaque models (uniformly thick, distally thickened, homogenous, and distally stiffened) were constructed and subjected to computational stress analyses with due consideration of fluid-structure interactions (FSI). The analysis considered three different cap thicknesses-45, 65, and 200 μm-and tissue properties-soft, fibrous, and hard. The maximum peak cap stress (PCS) and strain were observed in the upstream throat section and demonstrated increases of the order of 345 and 190%, respectively, as the cap thickness was reduced from 200 to 45 μm in uniformly thick models. Distal stiffening increased PCS in the downstream region; however, the overall effect of this increase was rather small. Distal thickening did not affect maximum PCS and strain values for cap thicknesses exceeding 65 μm; however, a noticeable increase in maximum PCS and corresponding longitudinal variation (or spatial gradient) in stress was observed in the very thin (45-μm-thick) cap. It was, therefore, inferred that existence of a rather thin upstream cap demonstrating distal cap thickening indicates an increased risk of plaque progression and rupture. Graphical Abstract ᅟ. [ABSTRACT FROM AUTHOR]

Robotic devices are being employed in gastrointestinal endoscopy procedures for diagnostics and surgery. However, force measurement, a very important factor for control and haptic feedback, becomes very challenging due to the strict size limitation of such devices and the flexible nature of the endoscope. This paper focuses on the modeling of the interior stomach wall for tool-tissue interactions from two perspectives: (1) If the interaction force between the robotic tool and the tissue can be measured, we utilize the force information to estimate the mechanical property of the stomach wall in real-time; given the force and position information, we would derive mathematically the only system model that can guarantee identifiability under arbitrary manipulation; (2) in the worst case scenario where force measurement is not available, we propose a viscoelastic model to restore force information solely based on position and motion information available from the robot. Ex-vivo experiments were performed on porcine stomach specimens to demonstrate the performance of the proposed models. Based on these findings, generalization and implementations of the modeling in real-time applications were discussed. [ABSTRACT FROM AUTHOR]

Neural oscillations at ∼10 Hz, called alpha oscillations, are one of the most prominent components of neural oscillations in the human brain. In recent years, characteristics (power/frequency/phase) of occipital alpha oscillations have been correlated with various perceptual phenomena. However, the relationship between inter-individual differences in alpha oscillatory characteristics and the properties of the underlying brain structures, such as white matter pathways, is unclear. A possibility is that intrinsic occipital alpha oscillations are mediated by thalamocortical interaction; we hypothesized that the most promising candidate for characterizing the intrinsic alpha oscillation is optic radiation (OR), which is the geniculo-cortical pathway carrying signals between the lateral geniculate nucleus (LGN) and primary visual cortex (V1). We used resting-state magnetoencephalography (MEG) and diffusion-weighted/quantitative magnetic resonance imaging (MRI) (dMRI/qMRI) to correlate the frequency and power of occipital alpha oscillations with the tissue properties of the OR by focusing on the different characteristics across individuals. We found that the peak alpha frequency (PAF) negatively correlated with intracellular volume fraction (ICVF), reflecting diffusion properties in intracellular (axonal) space, whereas the peak alpha power was not correlated with any tissue properties measurements. No significant correlation was found between OR and beta frequency/amplitude or between other white matter tract connecting parietal and inferotemporal cortex and alpha frequency/amplitude. These results support the hypothesis that an interaction between thalamic nuclei and early visual areas is essential for the occipital alpha oscillatory rhythm., (Copyright © 2020 Minami et al.)