Thermosensitive liposomes have emerged as a viable strategy for localized delivery and triggered release of chemotherapy. MR-guided focused ultrasound (MRgFUS) has the capability of heating tumors in a controlled manner, and when combined with thermosensitive liposomes can potentially reduce tumor burden in vivo. However, the impact of this drug delivery strategy has rarely been investigated. We have developed a unique liposome formulation modified with p(NIPAAm-co-PAA), a polymer that confers sensitivity to both temperature and pH. These polymer-modified thermosensitive liposomes (PTSL) demonstrated sensitivity to focused ultrasound, and required lower thermal doses and were more cytotoxic than traditional formulations in vitro. A set of acoustic parameters characterizing optimal release from PTSL in vitro was applied in the design of a combined MRgFUS/PTSL delivery platform. This platform more effectively reduced tumor burden in vivo when compared to free drug and traditional formulations. Histological analysis indicated greater tumor penetration, more extensive ECM
Spatial frequency domain imaging (SFDI) is a wide-field diffuse optical imaging modality that has attracted considerable interest in recent years. Typically, diffuse reflectance measurements of spatially modulated light are used to quantify the optical absorption and reduced scattering coefficients of tissue, and with these, chromophore concentrations are extracted. However, uncertainties in estimated absorption and reduced scattering coefficients are rarely reported, and we know of no method capable of providing these when look-up table (LUT) algorithms are used to recover the optical properties. We present a method to generate optical property uncertainty estimates from knowledge of diffuse reflectance measurement errors. By employing the Cramér-Rao bound, we can quickly and efficiently explore theoretical SFDI performance as a function of spatial frequencies and sample optical properties, allowing us to optimize spatial frequency selection for a given application. In practice, we can also obtain useful uncertainty estimates for optical properties recovered with a two-frequency LUT algorithm, as we demonstrate with tissue-simulating phantom and experiments. Finally, we illustrate how absorption coefficient uncertainties can be propagated forward to yield uncertainties for chromophore concentrations, which could significantly impact the interpretation of experimental results.
We present a Monte Carlo (MC) method to determine depth-dependent probability distributions of photon visitation and detection for optical reflectance measurements performed in the spatial frequency domain (SFD). These distributions are formed using an MC simulation for radiative transport that utilizes a photon packet weighting procedure consistent with the two-dimensional spatial Fourier transform of the radiative transport equation. This method enables the development of quantitative metrics for SFD optical sampling depth in layered tissue and its dependence on both tissue optical properties and spatial frequency. We validate the computed depth-dependent probability distributions using SFD measurements in a layered phantom system with a highly scattering top layer of variable thickness supported by a highly absorbing base layer. We utilize our method to establish the spatial frequency-dependent optical sampling depth for a number of tissue types and also provide a general tool to determine such depths for tissues of arbitrary optical properties.
Inflation of hollow elastic structures can become unstable and exhibit a runaway phenomenon if the tension in their walls does not rise rapidly enough with increasing volume. Biological systems avoid such inflation instability for reasons that remain poorly understood. This is best exemplified by the lung, which inflates over its functional volume range without instability. The goal of this study was to determine how the constituents of lung parenchyma determine tissue stresses that protect alveoli from instability-related overdistension during inflation. We present an analytical model of a thick-walled alveolus composed of wavy elastic fibres, and investigate its pressure–volume behaviour under large deformations. Using second-harmonic generation imaging, we found that collagen waviness follows a beta distribution. Using this distribution to fit human pressure–volume curves, we estimated collagen and elastin effective stiffnesses to be 1247 kPa and 18.3 kPa, respectively. Furthermore, we demonstrate that linearly elastic but wavy collagen fibres are sufficient to achieve inflation stability within the physiological pressure range if the alveolar thickness-to-radius ratio is greater than 0.05. Our model thus identifies the constraints on alveolar geometry and collagen waviness required for inflation stability and provides a multiscale link between alveolar pressure and stresses on fibres in healthy and diseased lungs.
Significance: Spatial frequency domain imaging (SFDI) is a diffuse optical measurement technique that can quantify tissue optical absorption (μ a ) and reduced scattering (μ 0 s ) on a pixelby-pixel basis. Measurements of μ a at different wavelengths enable the extraction of molar concentrations of tissue chromophores over a wide field, providing a noncontact and label-free means to assess tissue viability, oxygenation, microarchitecture, and molecular content. We present here openSFDI: an open-source guide for building a low-cost, small-footprint, threewavelength SFDI system capable of quantifying μ a and μ 0 s as well as oxyhemoglobin and deoxyhemoglobin concentrations in biological tissue. The companion website provides a complete parts list along with detailed instructions for assembling the openSFDI system.Aim: We describe the design of openSFDI and report on the accuracy and precision of optical property extractions for three different systems fabricated according to the instructions on the openSFDI website.Approach: Accuracy was assessed by measuring nine tissue-simulating optical phantoms with a physiologically relevant range of μ a and μ 0 s with the openSFDI systems and a commercial SFDI device. Precision was assessed by repeatedly measuring the same phantom over 1 h. Results:The openSFDI systems had an error of 0 AE 6% in μ a and −2 AE 3% in μ 0 s , compared to a commercial SFDI system. Bland-Altman analysis revealed the limits of agreement between the two systems to be AE0.004 mm −1 for μ a and −0.06 to 0.1 mm −1 for μ 0 s . The openSFDI system had low drift with an average standard deviation of 0.0007 mm −1 and 0.05 mm −1 in μ a and μ 0 s , respectively. Conclusion:The openSFDI provides a customizable hardware platform for research groups seeking to utilize SFDI for quantitative diffuse optical imaging.
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