Biomedical Physics & Engineering Express最新文献

In the innate immune system, natural killer (NK) cells are effector lymphocytes which control several tumor types and microbial infections by limiting disease spread and tissue damage. With tumor cell killing abilities, with no priming or prior activation, NKs are potential anti-cancer therapies. In clinical practice, NKs are used in intravenous injections as they typically grow as suspension, similar to other blood cells. In this study, we designed a novel and effective biomaterial-based platform for NK cell delivery, which included in-situ NK cell encapsulation into three-dimensional (3D) biocompatible polymeric scaffolds for potential anti-cancer treatments. Depending on physical cross-linking between an alginate (ALG) polymer and a divalent cation, two natural polymers (gelatin (GEL) and hyaluronic acid (HA)) penetrated into pores and generated an inter-penetrating hydrogel system with improved mechanical properties and stability. After extensive characterization of hydrogels, NK cells were encapsulated inside using our in-situ gelation procedure to provide a biomimetic microenvironment. .

In this study, an individualized and stable passive-control lower-limb exoskeleton robot was developed. Users' joint angles and the center of pressure (CoP) of one of their soles were input into a convolutional neural network (CNN)-long short-term memory (LSTM) model to evaluate and adjust the exoskeleton control scheme. The CNN-LSTM model predicted the fitness of the control scheme and output the results to the exoskeleton robot, which modified its control parameters accordingly to enhance walking stability. The sole's CoP had similar trends during normal walking and passive walking with the developed exoskeleton; they-coordinates of the CoPs with and without the exoskeleton had a correlation of 91%. Moreover, electromyography signals from the rectus femoris muscle revealed that it exerted 40% less force when walking with a stable stride length in the developed system than when walking with an unstable stride length. Therefore, the developed lower-limb exoskeleton can be used to assist users in achieving balanced and stable walking with reduced force application. In the future, this exoskeleton can be used by patients with stroke and lower-limb weakness to achieve stable walking.

Objective.Target volumes for radiotherapy are usually contoured manually, which can be time-consuming and prone to inter- and intra-observer variability. Automatic contouring by convolutional neural networks (CNN) can be fast and consistent but may produce unrealistic contours or miss relevant structures. We evaluate approaches for increasing the quality and assessing the uncertainty of CNN-generated contours of head and neck cancers with PET/CT as input.Approach.Two patient cohorts with head and neck squamous cell carcinoma and baseline¹⁸F-fluorodeoxyglucose positron emission tomography and computed tomography images (FDG-PET/CT) were collected retrospectively from two centers. The union of manual contours of the gross primary tumor and involved nodes was used to train CNN models for generating automatic contours. The impact of image preprocessing, image augmentation, transfer learning and CNN complexity, architecture, and dimension (2D or 3D) on model performance and generalizability across centers was evaluated. A Monte Carlo dropout technique was used to quantify and visualize the uncertainty of the automatic contours.Main results. CNN models provided contours with good overlap with the manually contoured ground truth (median Dice Similarity Coefficient: 0.75-0.77), consistent with reported inter-observer variations and previous auto-contouring studies. Image augmentation and model dimension, rather than model complexity, architecture, or advanced image preprocessing, had the largest impact on model performance and cross-center generalizability. Transfer learning on a limited number of patients from a separate center increased model generalizability without decreasing model performance on the original training cohort. High model uncertainty was associated with false positive and false negative voxels as well as low Dice coefficients.Significance.High quality automatic contours can be obtained using deep learning architectures that are not overly complex. Uncertainty estimation of the predicted contours shows potential for highlighting regions of the contour requiring manual revision or flagging segmentations requiring manual inspection and intervention.

Background:Dispersion presents both a challenge and a diagnostic opportunity in shear wave elastography (SWE).Shear Wave Rheometry(SWR) is an inversion technique for processing SWE data acquired using an acoustic radiation force impulse (ARFI) excitation. The main advantage of SWR is that it can characterize the shear properties of homogeneous soft media over a wide frequency range. Assumptions associated with SWR include tissue homogeneity, tissue isotropy, and axisymmetry of the ARFI excitation).Objective:Evaluate the validity of the SWR assumptions in ex vivo bovine liver.Approach:SWR was used to measure the shear properties of bovine liver tissue as function of frequency over a large frequency range. Assumptions associated with SWR (tissue homogeneity, tissue isotropy, and axisymmetry of the ARFI excitation) were evaluated through measurements performed at multiple locations and probe orientations. Measurements focused on quantities that would reveal violations of the assumptions.Main results:Measurements of shear properties were obtained over the 25-250 Hz range, and showed a 4-fold increase in shear storage modulus (from 1 to 4 kPa) and over a 10-fold increase in the loss modulus (from 0.2 to 3 kPa) over that decade-wide frequency range. Measurements under different conditions were highly repeatable, and model error was low in all cases.Significance and Conclusion:SWR depends on modeling the ARFI-induced shear wave as a full vector viscoelastic shear wave resulting from an axisymmetric source; it is agnostic to any specific rheological model. Despite this generality, the model makes three main simplifying assumptions. These results show that the modeling assumptions used in SWR are valid in bovine liver over a wide frequency band.

Purpose. This work investigates the small-field dosimetric characteristics of a 2.5 MV sintered diamond target beam and its feasibility for use in linac-based intracranial stereotactic treatments. Due to the increased proportion of low energy photons in the low-Z beam, it was hypothesized that this novel beam would provide sharper dose fall-off compared to the 6 MV beam owing to the reduced energy, and therefore range, of secondary electrons.Methods. Stereotactic treatments of ocular melanoma and trigeminal neuralgia were simulated for 2.5 MV low-Z and 6 MV beams using Monte Carlo to calculate dose in a voxelized anatomical phantom. Two collimation methods were investigated, including a 5 × 3 mm²HDMLC field and a 4 mm cone to demonstrate isolated and combined effects of geometric and radiological contributions to the penumbral width.Results. The measured 2.5 MV low-Z dosimetric profiles demonstrated reduced penumbra by 0.5 mm in both the inline and crossline directions across all depths for both collimation methods, compared to 6 MV. In both treatment cases, the 2.5 MV low-Z beam collimated with the 4 mm cone produced the sharpest dose fall off in profiles captured through isocenter. This improved fall-off resulted in a 59% decrease to the maximum brainstem dose in the trigeminal neuralgia case for the 2.5 MV low-Z MLC collimated beam compared to 6 MV. Reductions to the maximum and mean doses to ipsilateral and contralateral OARs in the ocular melanoma case were observed for the 2.5 MV low-Z beam compared to 6 MV with both collimation methods.Conclusions. While the low dose rate of this novel beam prohibits immediate clinical translation, the results of this study support the further development of this prototype beam to decrease toxicity in intracranial SRS treatments.

Vascular diseases are greatly influenced by the hemodynamic parameters and the accuracy of determining these parameters depends on the use of correct boundary conditions. The present work carries out a two-way fluid-structure interaction (FSI) simulation to investigate the effects of outlet pressure boundary conditions on the hemodynamics through the left coronary artery bifurcation with moderate stenosis (50%) in the left anterior descending (LAD) branch. The Carreau viscosity model is employed to characterise the shear-thinning behaviour of blood. The results of the study reveal that the employment of zero pressure at the outlet boundaries significantly overestimates the values of hemodynamic variables like wall shear stress (WSS), and time-averaged wall shear stress (TAWSS) compared with human healthy and pulsatile pressure outlet conditions. However, the difference between these variables is marginally low for human healthy and pulsatile pressure outlets. The oscillatory shear index (OSI) remains the same across all scenarios, indicating independence from the outlet boundary condition. Furthermore, the magnitude of negative axial velocity and pressure drop across the plaque are found to be higher at the zero pressure outlet boundary condition.

Objective. This study aims to design and fabricate a 3D printed heterogeneous paediatric head phantom and to customize a thorax phantom for radiotherapy dosimetry.Approach. This study designed, fabricated, and tested 3D printed radiotherapy phantoms that can simulate soft tissue, lung, brain, and bone. Various polymers were considered in designing the phantoms. Polylactic acid+, nylon, and plaster were used in simulating different tissue equivalence. Dimensional accuracy, and CT number were investigated. The phantoms were subjected to a complete radiotherapy clinical workflow. Several treatment plans were delivered in both the head and the thorax phantom from a simple single 6 MV beam, parallel opposed beams, and five-field intensity modulated radiotherapy (IMRT) beams. Dose measurements using an ionization chamber and radiochromic films were compared with the calculated doses of the Varian Eclipse treatment planning system (TPS).Main results. The fabricated heterogeneous phantoms represent paediatric human head and adult thorax based on its radiation attenuation and anatomy. The measured CT number ranges are within -786.23 ± 10.55, 0.98 ± 3.86, 129.51 ± 12.83, and 651.14 ± 47.76 HU for lung, water/brain, soft tissue, and bone, respectively. It has a good radiological imaging visual similarity relative to a real human head and thorax depicting soft tissue, lung, bone, and brain. The accumulated dose readings for both conformal radiotherapy and IMRT match with the TPS calculated dose within ±2% and ±4% for head and thorax phantom, respectively. The mean pass rate for all the plans delivered are above 90% for gamma analysis criterion of 3%/3 mm.Significance and conclusion. The fabricated heterogeneous paediatric head and thorax phantoms are useful in Linac end-to-end radiotherapy quality assurance based on its CT image and measured radiation dose. The manufacturing and dosimetry workflow of this study can be utilized by other institutions for dosimetry and trainings.

The article presents, for the first time, a terahertz metamaterial absorber (TMA) designed in the shape of a cross consisting of four orthogonally positioned horn-shaped patches in succession, to detect brain cancer cells. The design exhibits the property of mu-negative material, indicating magnetic resonance. The proposed TMA has achieved an impressive absorption rate of 99.43% at 2.334 THz and a high Q-factor of 47.15. The sensing capability has been investigated by altering the refractive index of the surrounding medium in the range of 1.3 to 1.48, resulting in a sensitivity of 0.502 THz/RIU. The proposed TMA exhibits complete polarization insensitivity, highlighting this as one of its advantageous features. The adequate sensing capability of the proposed TMA in differentiating normal and cancerous brain cells makes it a viable candidate for an early and efficient brain cancer detector. This research can be the foundation for future research on using THz radiation for brain cancer detection.

Radiation therapy plays a pivotal role in modern cancer treatment, demanding precise and accurate dose delivery to tumor sites while minimizing harm to surrounding healthy tissues. Monte Carlo simulations have emerged as indispensable tools for achieving this precision, offering detailed insights into radiation transport and interaction at the subatomic level. As the use of scintillation and luminescence dosimetry becomes increasingly prevalent in radiation therapy, there arises a need for validated Monte Carlo tools tailored to optical photon transport applications. In this paper, an evaluation process of the TOPAS (TOol for PArticle Simulation) Monte Carlo tool for Cerenkov light generation, optical photon transport and radioluminescence based dosimetry is presented. Three distinct sources of validation data are utilized: one from a published set of experimental results and two others from simulations performed with the Geant4 code. The methodology employed for evaluation includes the selection of benchmark experiments, making use of opt3 and opt4 Geant4 physics models and simulation setup, with observed slight discrepancies within the calculation uncertainties. Additionally, the complexities and challenges associated with modeling optical photons generation through luminescence or Cerenkov radiation and their transport are discussed. The results of our evaluation suggests that TOPAS can be used to reliably predict Cerenkov generation, luminescence phenomenon and the behavior of optical photons in common dosimetry scenarios.

Purpose. This review aims to highlight current improvements in microfluidic devices designed for digestive cancer simulation. The review emphasizes the use of multicellular 3D tissue engineering models to understand the complicated biology of the tumor microenvironment (TME) and cancer progression. The purpose is to develop oncology research and improve digestive cancer patients' lives.Methods. This review analyzes recent research on microfluidic devices for mimicking digestive cancer. It uses tissue-engineered microfluidic devices, notably organs on a chip (OOC), to simulate human organ function in the lab. Cell cultivation on modern three-dimensional hydrogel platforms allows precise geometry, biological components, and physiological qualities. The review analyzes novel methodologies, key findings, and technical progress to explain this field's advances.Results. This study discusses current advances in microfluidic devices for mimicking digestive cancer. Micro physiological systems with multicellular 3D tissue engineering models are emphasized. These systems capture complex biochemical gradients, niche variables, and dynamic cell-cell interactions in the tumor microenvironment (TME). These models reveal stomach cancer biology and progression by duplicating the TME. Recent discoveries and technology advances have improved our understanding of gut cancer biology, as shown in the review.Conclusion. Microfluidic systems play a crucial role in modeling digestive cancer and furthering oncology research. These platforms could transform drug development and treatment by revealing the complex biology of the tumor microenvironment and cancer progression. The review provides a complete summary of recent advances and suggests future research for field professionals. The review's major goal is to further medical research and improve digestive cancer patients' lives.