Localized characterization of brain tissue mechanical properties by needle induced cavitation rheology and volume controlled cavity expansion.

Changes in the elastic properties of brain tissue have been correlated with injury, cancers, and neurodegenerative diseases. However, discrepancies in the reported elastic moduli of brain tissue are persistent, and spatial inhomogeneities complicate the interpretation of macroscale measurements such as rheology. Here we introduce needle induced cavitation rheology (NICR) and volume-controlled cavity expansion (VCCE) as facile methods to measure the apparent Young's modulus E of minimally manipulated brain tissue, at specific tissue locations and with sub-millimeter spatial resolution. For different porcine brain regions and sections analyzed by NICR, we found E to be 3.7 ± 0.7 kPa and 4.8 ± 1.0 kPa for gray matter, and white matter, respectively. For different porcine brain regions and sections analyzed by VCCE, we found E was 0.76 ± 0.02 kPa for gray matter and 0.92 ± 0.01 kPa for white matter. Measurements from VCCE were more similar to those obtained from macroscale shear rheology (0.75 ± 0.06 kPa) and from instrumented microindentation of white matter (0.97 ± 0.40 kPa) and gray matter (0.86 ± 0.20 kPa). We attributed the higher stiffness reported from NICR to that method's assumption of a cavitation instability due to a neo-Hookean constitutive response, which does not capture the strain-stiffening behavior of brain tissue under large strains, and therefore did not provide appropriate measurements. We demonstrate via both analytical modeling of a spherical cavity and finite element modeling of a needle geometry, that this strain stiffening may prevent a cavitation instability. VCCE measurements take this stiffening behavior into account by employing an incompressible one-term Ogden model to find the nonlinear elastic properties of the tissue. Overall, VCCE afforded rapid and facile measurement of nonlinear mechanical properties of intact, healthy mammalian brain tissue, enabling quantitative comparison among brain tissue regions and also between species. Finally, accurate estimation of elastic properties for this strain stiffening tissue requires methods that include appropriate constitutive models of the brain tissue response, which here are represented by inclusion of the Ogden model in VCCE.

Probing Mechanical Properties of Brain in a Tuberous Sclerosis Model of Autism.

Causes of autism spectrum disorders (ASD) are understood poorly, making diagnosis and treatment challenging. While many studies have investigated the biochemical and genetic aspects of ASD, whether and how mechanical characteristics of the autistic brain can modulate neuronal connectivity and cognition in ASD are unknown. Previously, it has been shown that ASD brains are characterized by abnormal white matter and disorganized neuronal connectivity; we hypothesized that these significant cellular-level structural changes may translate to changes in the mechanical properties of the autistic brain or regions therein. Here, we focused on tuberous sclerosis complex (TSC), a genetic disorder with a high penetrance of ASD. We investigated mechanical differences between murine brains obtained from control and TSC cohorts at various deformation length- and time-scales. At the microscale, we conducted creep-compliance and stress relaxation experiments using atomic force microscope(AFM)-enabled indentation. At the mesoscale, we conducted impact indentation using a pendulum-based instrumented indenter to extract mechanical energy dissipation metrics. At the macroscale, we used oscillatory shear rheology to quantify the frequency-dependent shear moduli. Despite significant changes in the cellular organization of TSC brain tissue, we found no corresponding changes in the quantified mechanical properties at every length- and time-scale explored. This investigation of the mechanical characteristics of the brain has broadened our understanding of causes and markers of TSC/ASD, while raising questions about whether any mechanical differences can be detected in other animal models of ASD or other disease models that also feature abnormal brain structure.

High-velocity micro-particle impact on gelatin and synthetic hydrogel.

The high-velocity impact response of gelatin and synthetic hydrogel samples is investigated using a laser-based microballistic platform for launching and imaging supersonic micro-particles. The micro-particles are monitored during impact and penetration into the gels using a high-speed multi-frame camera that can record up to 16 images with nanosecond time resolution. The trajectories are compared with a Poncelet model for particle penetration, demonstrating good agreement between experiments and the model for impact in gelatin. The model is further validated on a synthetic hydrogel and the applicability of the results is discussed. We find the strength resistance parameter in the Poncelet model to be two orders of magnitude higher than in macroscopic experiments at comparable impact velocities. The results open prospects for testing high-rate behavior of soft materials on the microscale and for guiding the design of drug delivery methods using accelerated microparticles.

Characterizing viscoelastic mechanical properties of highly compliant polymers and biological tissues using impact indentation.

Precise and accurate measurement of viscoelastic mechanical properties becomes increasingly challenging as sample stiffness decreases to elastic moduli <1 kPa, largely due to difficulties detecting initial contact with the compliant sample surface. This limitation is particularly relevant to characterization of biological soft tissues and compliant gels. Here, we employ impact indentation which, in contrast to shear rheology and conventional indentation, does not require contact detection a priori, and present a novel method to extract viscoelastic moduli and relaxation time constants directly from the impact response. We first validate our approach by using both impact indentation and shear rheology to characterize polydimethylsiloxane (PDMS) elastomers of stiffness ranging from 100 s of Pa to nearly 10 kPa. Assuming a linear viscoelastic constitutive model for the material, we find that the moduli and relaxation times obtained from fitting the impact response agree well with those obtained from fitting the rheological response. Next, we demonstrate our validated method on hydrated, biological soft tissues obtained from porcine brain, murine liver, and murine heart, and report the equilibrium shear moduli, instantaneous shear moduli, and relaxation time constants for each tissue. Together, our findings provide a new and straightforward approach capable of probing local mechanical properties of highly compliant viscoelastic materials with millimeter scale spatial resolution, mitigating complications involving contact detection or sample geometric constraints. STATEMENT OF SIGNIFICANCE: Characterization and optimization of mechanical properties can be essential for the proper function of biomaterials in diverse applications. However, precise and accurate measurement of viscoelastic mechanical properties becomes increasingly difficult with increased compliance (particularly for elastic moduli <1 kPa), largely due to challenges detecting initial contact with the compliant sample surface and measuring response at short timescale or high frequency. By contrast, impact indentation has highly accurate contact detection and can be used to measure short timescale (glassy) response. Here, we demonstrate an experimental and analytical method that confers significant advantages over existing approaches to extract spatially resolved viscoelastic moduli and characteristic time constants of biological tissues (e.g., brain and heart) and engineered biomaterials.

Characterizing Multiscale Mechanical Properties of Brain Tissue Using Atomic Force Microscopy, Impact Indentation, and Rheometry.

To design and engineer materials inspired by the properties of the brain, whether for mechanical simulants or for tissue regeneration studies, the brain tissue itself must be well characterized at various length and time scales. Like many biological tissues, brain tissue exhibits a complex, hierarchical structure. However, in contrast to most other tissues, brain is of very low mechanical stiffness, with Young's elastic moduli E on the order of 100s of Pa. This low stiffness can present challenges to experimental characterization of key mechanical properties. Here, we demonstrate several mechanical characterization techniques that have been adapted to measure the elastic and viscoelastic properties of hydrated, compliant biological materials such as brain tissue, at different length scales and loading rates. At the microscale, we conduct creep-compliance and force relaxation experiments using atomic force microscope-enabled indentation. At the mesoscale, we perform impact indentation experiments using a pendulum-based instrumented indenter. At the macroscale, we conduct parallel plate rheometry to quantify the frequency dependent shear elastic moduli. We also discuss the challenges and limitations associated with each method. Together these techniques enable an in-depth mechanical characterization of brain tissue that can be used to better understand the structure of brain and to engineer bio-inspired materials.

Optimizing outpatient phlebotomy staffing: tools to assess staffing needs and monitor effectiveness.

CONTEXT: Short patient wait times are critical for patient satisfaction with outpatient phlebotomy services. Although increasing phlebotomy staffing is a direct way to improve wait times, it may not be feasible or appropriate in many settings, particularly in the context of current economic pressures in health care. OBJECTIVE: To effect sustainable reductions in patient wait times, we created a simple, data-driven tool to systematically optimize staffing across our 14 phlebotomy sites with varying patient populations, scope of service, capacity, and process workflows. DESIGN: We used staffing levels and patient venipuncture volumes to derive the estimated capacity, a parameter that helps predict the number of patients a location can accommodate per unit of time. We then used this parameter to determine whether a particular phlebotomy site was overstaffed, adequately staffed, or understaffed. Patient wait-time and satisfaction data were collected to assess the efficacy and accuracy of the staffing tool after implementing the staffing changes. RESULTS: In this article, we present the applications of our approach in 1 overstaffed and 2 understaffed phlebotomy sites. After staffing changes at previously understaffed sites, the percentage of patients waiting less than 10 minutes ranged from 88% to 100%. At our previously overstaffed site, we maintained our goal of 90% of patients waiting less than 10 minutes despite staffing reductions. All staffing changes were made using existing resources. CONCLUSIONS: Used in conjunction with patient wait-time and satisfaction data, our outpatient phlebotomy staffing tool is an accurate and flexible way to assess capacity and to improve patient wait times.

An intervention to improve the timing of vancomycin levels.

OBJECTIVES: Blood samples for vancomycin levels are often drawn too early, leading to potential misinterpretation of results. However, only a few studies describe interventions to reduce mistimed vancomycin levels. METHODS: We implemented an information technology (IT)-based intervention that provided educational instructions to nurses and determined the percentage of levels drawn too early for 27 months before (n = 6,291) and 14 months after (n = 3,608) the intervention. In addition, we conducted nurse interviews (n = 40) and dataset analysis to assess the root causes of mistimed levels. RESULTS: The percentage of vancomycin timing errors decreased from 39% (2,438/6,291) to 32% (1,137/3,608), though in a time series analysis this decrease was not statistically significant (P = .64). Four common causes of mistimed levels were found: (1) unclear provider orders, (2) scheduling levels to be drawn with morning laboratory tests, (3) lack of communication between providers, and (4) failure to adjust the blood draw in relation to the previous dose. CONCLUSIONS: A real-time, IT-based intervention that links the timing of levels with medication administration might have a more substantial impact.