STOCHASTIC EFFICIENCY ANALYSIS USING MULTIPLE UTILITY FUNCTIONS

Evaluating the risk of a particular decision depends on the risk aversion of the decision maker related to the underlying utility function. The objective of this paper is to use stochastic efficiency with respect to a function (SERF) to compare the ranking of risky alternatives using alternative utility functional forms.Research Methods/ Statistical Methods,

Stochastic efficiency analysis with risk aversion bounds: a simplified approach

A method of stochastic dominance analysis with respect to a function (SDRF) is described and illustrated. The method, called stochastic efficiency with respect to a function (SERF), orders a set of risky alternatives in terms of certainty equivalents for a specified range of attitudes to risk. It can be applied for conforming utility functions with risk attitudes defined by corresponding ranges of absolute, relative or partial risk aversion coefficients. Unlike conventional SDRF, SERF involves comparing each alternative with all the other alternatives simultaneously, not pairwise, and hence can produce a smaller efficient set than that found by simple pairwise SDRF over the same range of risk attitudes. Moreover, the method can be implemented in a simple spreadsheet with no special software needed.Risk and Uncertainty,

Comparison of Magnetic Resonance Imaging-Compatible Optical Detectors for In-Magnet Tissue Spectroscopy: Photodiodes Versus Silicon Photomultipliers

Tissue spectroscopy inside the magnetic resonance imaging (MRI) system adds a significant value by measuring fast vascular hemoglobin responses or completing spectroscopic identification of diagnostically relevant molecules. Advances in this type of spectroscopy instrumentation have largely focused on fiber coupling into and out of the MRI; however, nonmagnetic detectors can now be placed inside the scanner with signal amplification performed remotely to the high field environment for optimized light detection. In this study, the two possible detector options, such as silicon photodiodes (PD) and silicon photomultipliers (SiPM), were systematically examined for dynamic range and wavelength performance. Results show that PDs offer 108 (160 dB) dynamic range with sensitivity down to 1 pW, whereas SiPMs have 107 (140 dB) dynamic range and sensitivity down to 10 pW. A second major difference is the spectral sensitivity of the two detectors. Here, wavelengths in the 940 nm range are efficiently captured by PDs (but not SiPMs), likely making them the superior choice for broadband spectroscopy guided by MRI

Weighting Function Effects in a Direct Regularization Method for Image-Guided Near-Infrared Spectral Tomography of Breast Cancer.

Structural image-guided near-infrared spectral tomography (NIRST) has been developed as a way to use diffuse NIR spectroscopy within the context of image-guided quantification of tissue spectral features. A direct regularization imaging (DRI) method for NIRST has the value of not requiring any image segmentation. Here, we present a comprehensive investigational study to analyze the impact of the weighting function implied when weighting the recovery of optical coefficients in DRI based NIRST. This was done using simulations, phantom and clinical patient exam data. Simulations where the true object is known indicate that changes to this weighting function can vary the contrast by 10%, the contrast to noise ratio by 20% and the full width half maximum (FWHM) by 30%. The results from phantoms and human images show that a linear inverse distance weighting function appears optimal, and that incorporation of this function can generally improve the recovered total hemoglobin contrast of the tumor to the normal surrounding tissue by more than 15% in human cases

Effects of Dexamethasone on Satellite Cells and Tissue Engineered Skeletal Muscle Units

Tissue engineered skeletal muscle has potential for application as a graft source for repairing soft tissue injuries, a model for testing pharmaceuticals, and a biomechanical actuator system for soft robots. However, engineered muscle to date has not produced forces comparable to native muscle, limiting its potential for repair and for use as an in vitro model for pharmaceutical testing. In this study, we examined the trophic effects of dexamethasone (DEX), a glucocorticoid that stimulates myoblast differentiation and fusion into myotubes, on our tissue engineered three-dimensional skeletal muscle units (SMUs). Using our established SMU fabrication protocol, muscle isolates were cultured with three experimental DEX concentrations (5, 10, and 25?nM) and compared to untreated controls. Following seeding onto a laminin-coated Sylgard substrate, the administration of DEX was initiated on day 0 or day 6 in growth medium or on day 9 after the switch to differentiation medium and was sustained until the completion of SMU fabrication. During this process, total cell proliferation was measured with a BrdU assay, and myogenesis and structural advancement of muscle cells were observed through immunostaining for MyoD, myogenin, desmin, and α-actinin. After SMU formation, isometric tetanic force production was measured to quantify function. The histological and functional assessment of the SMU showed that the administration of 10?nM DEX beginning on either day 0 or day 6 yielded optimal SMUs. These optimized SMUs exhibited formation of advanced sarcomeric structure and significant increases in myotube diameter and myotube fusion index, compared with untreated controls. Additionally, the optimized SMUs matured functionally, as indicated by a fivefold rise in force production. In conclusion, we have demonstrated that the addition of DEX to our process of engineering skeletal muscle tissue improves myogenesis, advances muscle structure, and increases force production in the resulting SMUs.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/140236/1/ten.tea.2015.0545.pd

Characterizing Accuracy of Total Hemoglobin Recovery Using Contrast-Detail Analysis in 3D Image-Guided Near Infrared Spectroscopy with the Boundary Element Method

The quantification of total hemoglobin concentration (HbT) obtained from multi-modality image-guided near infrared spectroscopy (IG-NIRS) was characterized using the boundary element method (BEM) for 3D image reconstruction. Multi-modality IG-NIRS systems use a priori information to guide the reconstruction process. While this has been shown to improve resolution, the effect on quantitative accuracy is unclear. Here, through systematic contrast-detail analysis, the fidelity of IG-NIRS in quantifying HbT was examined using 3D simulations. These simulations show that HbT could be recovered for medium sized (20mm in 100mm total diameter) spherical inclusions with an average error of 15%, for the physiologically relevant situation of 2:1 or higher contrast between background and inclusion. Using partial 3D volume meshes to reduce the ill-posed nature of the image reconstruction, inclusions as small as 14mm could be accurately quantified with less than 15% error, for contrasts of 1.5 or higher. This suggests that 3D IG-NIRS provides quantitatively accurate results for sizes seen early in treatment cycle of patients undergoing neoadjuvant chemotherapy when the tumors are larger than 30mm

Contrast-Detail Analysis Characterizing Diffuse Optical Fluorescence Tomography Image Reconstruction

Contrast-detail analysis is used to evaluate the imaging performance of diffuse optical fluorescence tomography (DOFT), characterizing spatial resolution limits, signal-to-noise limits, and the trade-off between object contrast and size. Reconstructed images of fluorescence yield from simulated noisy data were used to determine the contrast-to-noise ratio (CNR). A threshold of CNR=3 was used to approximate a lowest acceptable noise level in the image, as a surrogate measure for human detection of objects. For objects 0.5 cm inside the edge of a simulated tissue region, the smallest diameter that met this criteria was approximately 1.7 mm, regardless of contrast level, and test field diameter had little impact on this limit. Object depth had substantial impact on object CNR, leading to a limit of 4 mm for objects near the center of a 51-mm test field and 8.5 mm for an 86-mm test field. Similarly, large objects near the edge of both test fields required a minimum contrast of 50% to achieve acceptable image CNR. The minimum contrast for large, centered objects ranged between 50% and 100%. Contrast-detail analysis using human detection of lower contrast limits provides fundamentally important information about the performance of reconstruction algorithms, and can be used to compare imaging performance of different systems

Methodology Development for Three-Dimensional MR-Guided Near Infrared Spectroscopy of Breast Tumors

Combined Magnetic Resonance (MR) and Near Infrared Spectroscopy (NIRS) has been proposed as a unique method to quantify hemodynamics, water content, and cellular size and packing density of breast tumors, as these tissue constituents can be quantified with increased resolution and overlaid on the structural features identified by the MR. However, the choices in how to reconstruct and visualize this information can have a dramatic impact on the feasibility of implementing this modality in the clinic. This is especially true in 3 dimensions, as there is often limited optical sampling of the breast tissue, and methods need to accurately reflect the tissue composition. In this paper, the implementation and display of fully 3D MR image-guided NIRS is outlined and demonstrated using in vivo data from three healthy women and a volunteer undergoing neoadjuvant chemotherapy. Additionally, a display feature presented here scales the transparency of the optical images to the sensitivity of the measurements, providing a logical way to incorporate partial volume sets of optical images onto the MR volume. These concepts are demonstrated with 3D data sets using Volview software online

A Coupled Finite Element-Boundary Element Method for Modeling Diffusion Equation in 3d Multi-Modality Optical Imaging

Three dimensional image reconstruction for multi-modality optical spectroscopy systems needs computationally efficient forward solvers with minimum meshing complexity, while allowing the flexibility to apply spatial constraints. Existing models based on the finite element method (FEM) require full 3D volume meshing to incorporate constraints related to anatomical structure via techniques such as regularization. Alternate approaches such as the boundary element method (BEM) require only surface discretization but assume homogeneous or piece-wise constant domains that can be limiting. Here, a coupled finite element-boundary element method (coupled FE-BEM) approach is demonstrated for modeling light diffusion in 3D, which uses surfaces to model exterior tissues with BEM and a small number of volume nodes to model interior tissues with FEM. Such a coupled FE-BEM technique combines strengths of FEM and BEM by assuming homogeneous outer tissue regions and heterogeneous inner tissue regions. Results with FE-BEM show agreement with existing numerical models, having RMS differences of less than 0.5 for the logarithm of intensity and 2.5 degrees for phase of frequency domain boundary data. The coupled FE-BEM approach can model heterogeneity using a fraction of the volume nodes (4-22%) required by conventional FEM techniques. Comparisons of computational times showed that the coupled FE-BEM was faster than stand-alone FEM when the ratio of the number of surface to volume nodes in the mesh (Ns/Nv) was less than 20% and was comparable to stand-alone BEM ( ± 10%)