Development of Phantom Material that Resembles Compression Properties of Human Brain Tissue for Training Models

Experimental Assessment of Traction Force and Associated Fetal Brain Deformation in Vacuum-Assisted Delivery

Vacuum-assisted delivery (VAD) uses a vacuum cup on the fetal scalp to apply traction during uterine contractions, assisting complicated vaginal deliveries. Despite its widespread use, VAD presents a higher risk of neonatal morbidity compared to natural vaginal delivery and biomechanical evidence for safe VAD traction forces is still limited. The aim of this study is to develop and assess the feasibility of an experimental VAD testing setup, and investigate the impact of traction forces on fetal brain deformation. A patient-specific fetal head phantom was developed and subjected to experimental VAD in two testing setups: one with manual and one with automatic force application. The skull phantom was 3D printed using multi-material Polyjet technology. The brain phantom was cast in a 3D-printed mold using a composite hydrogel, and sonomicrometry crystals were used to estimate the brain deformation in three brain regions. The experimental VADs on the fetal head phantom allowed for quantifying brain strain with traction forces up to 112 N. Consistent brain crystal movements aligned with the traction force demonstrated the feasibility of the setup. The estimated brain deformations reached up to 4% and correlated significantly with traction force (p < 0.05) in regions close to the suction cup. Despite limitations such as the absence of scalp modeling and a simplified strain computation, this study provides a baseline for numerical studies and supports further research to optimize the safety of VAD procedures and develop VAD training platforms.

Structural and Rheological Properties of a Fish Collagen-Based Hydrogel Considered as a Brain Tissue Phantom

Hydrogels have gained attention as phantoms of soft materials mimicking properties of the brain tissue aimed at creating adjustable physical media for studying rheological models, training models for surgeons, tissue substitutes used in the process of surgical treatment of neurological diseases, and testing personal protective gears. In this work, we report the results of exploring the shear rheological properties of a material synthesized on the basis of fish collagen and discuss its relevance to the properties of biological samples under similar experimental conditions. It is shown that the stress-strain relations and the storage and loss moduli of the artificial and biological materials exhibit high similarity under amplitude shear sweep as well as responses to low-frequency oscillatory perturbations. The respective rheological models and perspectives for the use of this hydrogel material are discussed.

Characterization and selection of a skull surrogate for the development of a biofidelic head model

This research paper explores the advancement of physical models simulating the human skull-brain complex, focusing on applications in simulating mild Traumatic Brain Injury (mTBI). Existing models, especially head forms, lack biofidelity in accurately representing the native structures of the skull, limiting the understanding of intracranial injury parameters beyond kinematic head accelerations. This study addresses this gap by investigating the use of additive manufacturing (AM) techniques to develop biofidelic skull surrogates. Materials such as Polylactic Acid (PLA), a bone-simulant PLA variant, and Hydroxyapatite-coated Poly(methyl methacrylate) (PMMA) were used to create models tested for their flexural modulus and strength. The trabecular bone regions were simulated by adjusting infill densities (30%, 50%, 80%) and print raster directions, optimizing manufacturing parameters for biofidelic performance. Among the tested materials, PLA and its bone-simulating variant printed at 80% infill density with a side (tangential) print orientation demonstrated the closest approximation to the mechanical properties of cranial bone, yielding a mean flexural modulus of 1337.2 MPa and a mean ultimate strength of 56.9 MPa. Statistical analyses showed that infill density significantly influenced the moduli and strength of the printed simulants. Digital Image Correlation (DIC) corroborated the comparable performance of the simulants, showing similar strain and displacement behaviors to native skull bone. Notably, the performance of the manufactured cortical and trabecular regions underscored their crucial role in achieving biofidelity, with the trabecular structure providing critical dampening effects when the native bone is loaded. This study establishes PLA, particularly its bone-simulant variant, as an optimal candidate for cranial bone simulants, offering significant potential for developing more accurate biofidelic head models in mTBI research.

A comprehensive review on modeling aspects of infusion-based drug delivery in the brain

Brain disorders represent an ever-increasing health challenge worldwide. While conventional drug therapies are less effective due to the presence of the blood-brain barrier, infusion-based methods of drug delivery to the brain represent a promising option. Since these methods are mechanically controlled and involve multiple physical phases ranging from the neural and molecular scales to the brain scale, highly efficient and precise delivery procedures can significantly benefit from a comprehensive understanding of drug-brain and device-brain interactions. Behind these interactions are principles of biophysics and biomechanics that can be described and captured using mathematical models. Although biomechanics and biophysics have received considerable attention, a comprehensive mechanistic model for modeling infusion-based drug delivery in the brain has yet to be developed. Therefore, this article reviews the state-of-the-art mechanistic studies that can support the development of next-generation models for infusion-based brain drug delivery from the perspective of fluid mechanics, solid mechanics, and mathematical modeling. The supporting techniques and database are also summarized to provide further insights. Finally, the challenges are highlighted and perspectives on future research directions are provided. STATEMENT OF SIGNIFICANCE: Despite the immense potential of infusion-based drug delivery methods for bypassing the blood-brain barrier and efficiently delivering drugs to the brain, achieving optimal drug distribution remains a significant challenge. This is primarily due to our limited understanding of the complex interactions between drugs and the brain that are governed by principles of biophysics and biomechanics, and can be described using mathematical models. This article provides a comprehensive review of state-of-the-art mechanistic studies that can help to unravel the mechanism of drug transport in the brain across the scales, which underpins the development of next-generation models for infusion-based brain drug delivery. More broadly, this review will serve as a starting point for developing more effective treatments for brain diseases and mechanistic models that can be used to study other soft tissue and biomaterials.

Computational modeling and uncertainty prediction of hyperelastic constitutive responses of damaged brain tissue under different temperature and strain rates

The effect of strain rate and temperature on the hyperelastic material stress-strain characteristics of the damaged porcine brain tissue is evaluated in this present work. The desired constitutive responses are obtained using the commercially available finite element (FE) tool ABAQUS, utilizing 8-noded brick elements. The model's accuracy has been verified by comparing the results from the previously published literature. Further, the stress-strain behavior of the brain tissue is evaluated by varying the damages at various strain rates and temperatures (13, 20, 27, and 37°C) under compression test. Additionally, the sensitivity analysis of the model is computed to check the effect of input parameters, that is, the temperature, strain rate, and damages on the material properties (shear modulus). The modeling and discussion sections enumerate the inclusive features and model capabilities.

Agarose Phantoms for Insertion Characterization of Amorphous SiC Microelectrode Probes in Rat Brain Tissue

Penetrating, Ultra-small Microelectrode Arrays (UMEAs) have been shown to evoke less foreign body response on implantation in neural tissue. This may be attributed to reduced tissue displacement on implantation and reduced mechanical mismatch between the highly flexible UMEA and tissue. However, the high flexibility of UMEAs makes implantation challenging. Establishing a robust model of tissue insertion may provide information on the forces encountered during implantation, assess the likelihood of UMEA penetration without buckling. In this study we measured insertion forces of amorphous SiC probes in rat cortex, and in 0.8 wt% and 1.2 wt% agarose models of brain tissue. The primary findings indicate that the 1.2% agarose model accurately predicts the maximum force of insertion obtained from measurements in rat. This suggests the suitability of the 1.2 wt% agarose model for the mechanical characterization of UMEAs prior to in vivo experimentation.

Assembled Embedded 3D Hydrogel System for Asynchronous Drug Delivery to Inhibit Postoperative Recurrence of Malignant Glioma and Promote Neurological Recovery

Surgical resection of glioblastoma multiforme (GBM) often results in tumor recurrence and mild neurologic deficits. Here, a 3D asynchronous drug delivery system is innovatively developed to address the dual challenges of GBM recurrence and postoperative neurological deficit. Based on transcriptome analysis of tumor cells and tumor microenvironment (TME) cells between primary and recurrent mouse GBM tissues, a novel dual‐targeting approach is developed to combine mTOR pathway inhibition with microglia/macrophage repolarization. Then, in situ injectable methacrylated gelatin (GelMA) is constructed to perfectly fit into the tumor resection cavity and achieve direct delivery of dual‐targeted drugs, exhibiting outstanding postoperative GBM inhibitory effects in vivo. At the same time, neurotrophic factor‐saturated 3D‐printed GelMA patches are used to construct a 3D asynchronous drug delivery system, allowing gradual penetration of the neurotrophic factors into the underlying hydrogel to promote axonal sprouting after GBM suppression. Notably, this 3D asynchronous drug delivery system promotes neurological recovery without weakening the efficacy of inhibiting tumor recurrence. Therefore, this study not only proposes a new dual‐targeted GBM treatment strategy but also pioneers the construction of a 3D asynchronous drug delivery system for the comprehensive treatment of GBM. This study is expected to improve the poor prognosis of patients with GBM.

Poro-viscoelastic material parameter identification of brain tissue-mimicking hydrogels

Understanding and characterizing the mechanical and structural properties of brain tissue is essential for developing and calibrating reliable material models. Based on the Theory of Porous Media, a novel nonlinear poro-viscoelastic computational model was recently proposed to describe the mechanical response of the tissue under different loading conditions. The model contains parameters related to the time-dependent behavior arising from both the viscoelastic relaxation of the solid matrix and its interaction with the fluid phase. This study focuses on the characterization of these parameters through indentation experiments on a tailor-made polyvinyl alcohol-based hydrogel mimicking brain tissue. The material behavior is adjusted to ex vivo porcine brain tissue. An inverse parameter identification scheme using a trust region reflective algorithm is introduced and applied to match experimental data obtained from the indentation with the proposed computational model. By minimizing the error between experimental values and finite element simulation results, the optimal constitutive model parameters of the brain tissue-mimicking hydrogel are extracted. Finally, the model is validated using the derived material parameters in a finite element simulation.

Fabrication of a positional brain shift phantom through the utilization of the frozen intermediate hydrogel state

Synthetic models (phantoms) of the brain-skull system are useful tools for the study of surgical events that are otherwise difficult to study directly in humans. To date, very few studies can be found which replicate the full anatomical brain-skull system. Such models are required to study the more global mechanical events that can occur in neurosurgery, such as positional brain shift. Presented in this work is a novel workflow for the fabrication of a biofidelic brain-skull phantom which features a full hydrogel brain with fluid-filled ventricle/fissure spaces, elastomer dural septa and fluid-filled skull. Central to this workflow is the utilization of the frozen intermediate curing state of an established brain tissue surrogate, which allows for a novel moulding and skull installation approach that permits a much fuller recreation of the anatomy. The mechanical realism of the phantom was validated through indentation testing of the phantom's brain and simulation of the supine to prone brain shift event, while the geometric realism was validated through magnetic resonance imaging. The developed phantom captured a novel measurement of the supine to prone brain shift event with a magnitude that accurately reproduces that seen in the literature.

Brain-Mimicking Phantom for Photoablation and Visualization

While the use of tissue-mimicking (TM) phantoms has been ubiquitous in surgical robotics, the translation of technology from laboratory experiments to equivalent intraoperative tissue conditions has been a challenge. The increasing use of lasers for surgical tumor resection has introduced the need to develop a modular, low-cost, functionally relevant TM phantom to model the complex laser-tissue interaction. In this paper, a TM phantom with mechanically and thermally similar properties as human brain tissue suited for photoablation studies and subsequent visualization is developed. The proposed study demonstrates the tuned phantom response to laser ablation for fixed laser power, time, and angle. Additionally, the ablated crater profile is visualized using optical coherence tomography (OCT), enabling high-resolution surface profile generation.

3D Extrusion Printing of Biphasic Anthropomorphic Brain Phantoms Mimicking MR Relaxation Times Based on Alginate-Agarose-Carrageenan Blends

The availability of adapted phantoms mimicking different body parts is fundamental to establishing the stability and reliability of magnetic resonance imaging (MRI) methods. The primary purpose of such phantoms is the mimicking of physiologically relevant, contrast-creating relaxation times T1 and T2. For the head, frequently examined by MRI, an anthropomorphic design of brain phantoms would imply the discrimination of gray matter and white matter (WM) within defined, spatially distributed compartments. Multichannel extrusion printing allows the layer-by-layer fabrication of multiple pastelike materials in a spatially defined manner with a predefined shape. In this study, the advantages of this method are used to fabricate biphasic brain phantoms mimicking MR relaxation times and anthropomorphic geometry. The printable ink was based on purely naturally derived polymers: alginate as a calcium-cross-linkable gelling agent, agarose, ι-carrageenan, and GdCl3 in different concentrations (0-280 μmol kg-1) as the paramagnetic component. The suggested inks (e.g., 3Alg-1Agar-6Car) fulfilled the requirements of viscoelastic behavior and printability of large constructs (>150 mL). The microstructure and distribution of GdCl3 were assessed by scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDX). In closely monitored steps of technological development and characterization, from monophasic and biphasic samples as printable inks and cross-linked gels, we describe the construction of large-scale phantom models whose relaxation times were characterized and checked for stability over time.

Transport in the Brain Extracellular Space: Diffusion, but Which Kind?

The mechanisms of transport of substances in the brain parenchyma have been a hot topic in scientific discussion in the past decade. This discussion was triggered by the proposed glymphatic hypothesis, which assumes a directed flow of cerebral fluid within the parenchyma, in contrast to the previous notion that diffusion is the main mechanism. However, when discussing the issue of “diffusion or non-diffusion”, much less attention was given to the question that diffusion itself can have a different character. In our opinion, some of the recently published results do not fit into the traditional understanding of diffusion. In this regard, we outline the relevant new theoretical approaches on transport processes in complex random media such as concepts of diffusive diffusivity and time-dependent homogenization, which expands the understanding of the forms of transport of substances based on diffusion.

Tissue-Scale Biomechanical Testing of Brain Tissue for the Calibration of Nonlinear Material Models

Brain tissue is one of the most complex and softest tissues in the human body. Due to its ultrasoft and biphasic nature, it is difficult to control the deformation state during biomechanical testing and to quantify the highly nonlinear, time-dependent tissue response. In numerous experimental studies that have investigated the mechanical properties of brain tissue over the last decades, stiffness values have varied significantly. One reason for the observed discrepancies is the lack of standardized testing protocols and corresponding data analyses. The tissue properties have been tested on different length and time scales depending on the testing technique, and the corresponding data have been analyzed based on simplifying assumptions. In this review, we highlight the advantage of using nonlinear continuum mechanics based modeling and finite element simulations to carefully design experimental setups and protocols as well as to comprehensively analyze the corresponding experimental data. We review testing techniques and protocols that have been used to calibrate material model parameters and discuss artifacts that might falsify the measured properties. The aim of this work is to provide standardized procedures to reliably quantify the mechanical properties of brain tissue and to more accurately calibrate appropriate constitutive models for computational simulations of brain development, injury and disease. Computational models can not only be used to predictively understand brain tissue behavior, but can also serve as valuable tools to assist diagnosis and treatment of diseases or to plan neurosurgical procedures. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC.