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Despite recent advances in the treatment of high-grade gliomas, overall survival (OS) remains poor, which underlines the importance of searching for and determining prognostic imaging biomarkers. The purpose of our retrospective study was to correlate patient survival with relative cerebral blood volume (rCBV) and permeability surface area-product (PS) measured using perfusion computed tomography (PCT) in patients with high-grade gliomas.This study was composed of 54 patients with high-grade gliomas (World Health Organization [WHO] grade III, n = 14; WHO grade IV, n = 40) who underwent pretreatment PCT. Kaplan-Meier survival estimates were computed to describe OS for patients with high-versus-low PCT parameters, as well as grade III and IV gliomas.Differences in OS between high and low rCBV, PS, and rCBV + PS were significant (P.001) for all high-grade gliomas. After adjustment for WHO grade, rCBV (P = .041) and rCBV + PS (P = .013) estimates remained significant, whereas PS estimates were not (P = .214). PS estimates showed a statistically significant difference for OS in the grade III glioma group (P = .011), whereas for grade IV gliomas, rCBV estimates were statistically significant (P = .019). rCBV + PS was statistically significant for OS in both grade III (P = .001) and grade IV (P = .004) glioma groups.Blood volume and permeability estimates measured using PCT can help predict survival in patients with high-grade gliomas. Patients with high PCT parameters showed worse OS compared to the patients with low PCT. Both rCBV and rCBV + PS remained statistically significant even after adjustment for WHO grade, suggesting these may be better predictors of OS than histological grade.

The U.S. Department of Energy (DOE) Building Technologies Program has set the aggressive goal of producing marketable net-zero energy buildings by 2025. This goal will require collaboration between the DOE laboratories and the building industry. We developed standard or reference energy models for the most common commercial buildings to serve as starting points for energy efficiency research. These models represent fairly realistic buildings and typical construction practices. Fifteen commercial building types and one multifamily residential building were determined by consensus between DOE, the National Renewable Energy Laboratory, Pacific Northwest National Laboratory, and Lawrence Berkeley National Laboratory, and represent approximately two-thirds of the commercial building stock.

The building energy simulation program, Energy Plus (E+), cannot use standard window performance indices (U, SHGC, VT) to model window energy impacts. Rather, E+ uses more accurate methods which require a physical description of the window. E+ needs to be able to accept U and SHGC indices as window descriptors because, often, these are all that is known about a window and because building codes, standards, and voluntary programs are developed using these terms. This paper outlines a procedure, developed for E+, which will allow it to use standard window performance indices to model window energy impacts. In this 'Block' model, a given U, SHGC, VT are mapped to the properties of a fictitious 'layer' in E+. For thermal conductance calculations, the 'Block' functions as a single solid layer. For solar optical calculations, the model begins by defining a solar transmittance (Ts) at normal incidence based on the SHGC. For properties at non-normal incidence angles, the 'Block' takes on the angular properties of multiple glazing layers; the number and type of layers defined by the U and SHGC. While this procedure is specific to E+, parts of it may have applicability to other window/building simulation programs.

Infrared (IR) imaging radiometers, which measure relative levels of thermal radiation energy, can be used for noninvasive surface temperature measurements of building thermal envelope components undergoing steady-state heat flow in laboratory thermal chambers. One advantage of IR measurement is that it provides large contiguous sets of surface temperature data which are useful for validating the accuracy of complex computer models that predict heat flow through thermally insulated systems. Because they give such detailed information about surface temperature, IR measurements complement hot-box measurements of heat flow. This paper recommends general procedures for reliable quantitative thermographic measurements in chambers operated for winter heating conditions. Actual surface temperature depends on heat flow, surface emittance, and environmental conditions such as air temperature, air flow field, and background thermal radiation. The infrared temperature measurements are affected by many of the same factors including surface emittance, air temperature, background thermal radiation, and air humidity. Equipment specifications for the absolute accuracy of infrared temperature measurements are typically ′1° to ′2°C. Measurements that use a temperature-controlled reference emitter to remove error appear to show accuracies of ′0.5°C for flat specimens with low temperature gradients.

This report provides recommendations that architects, designers, contractors, developers, owners, and lessees of medium box retail buildings can use to achieve whole-building energy savings of at least 50% over ASHRAE Standard 90.1-2004. The recommendations are given by climate zone and address building envelope, fenestration, lighting systems, HVAC systems, building automation and controls, outside air treatment, service water heating, plug loads, and photovoltaic systems. The report presents several paths to 50% savings, which correspond to different levels of integrated design. These are recommendations only, and are not part of a code or standard. The recommendations are not exhaustive, but we do try to emphasize the benefits of integrated building design, that is, a design approach that analyzes a building as a whole system, rather than as a disconnected collection of individually engineered subsystems.

This report provides recommendations that architects, designers, contractors, developers, owners, and lessees of grocery store buildings can use to achieve whole-building energy savings of at least 50% over ASHRAE Standard 90.1-2004.

This paper describes the calibration and validation of a combustion cogeneration model for whole-building simulation. As part of IEA Annex 42, we proposed a combustion cogeneration model for studying residentialscale cogeneration systems based on both Stirling and internal combustion engines. We implemented this model independently in the EnergyPlus, ESP-r and TRNSYS building simulation programs, and undertook a comprehensive effort to validate the model's predictions. Using established comparative testing and empirical validation principles, we vetted the model's theoretical basis and its software implementations. The results demonstrate acceptable-to-excellent agreement, and suggest the calibrated model can be used with confidence.

This report uses EnergyPlus simulations of each building in the 2003 Commercial Buildings Energy Consumption Survey (CBECS) to document and demonstrate bottom-up methods of modeling the entire U.S. commercial buildings sector (EIA 2006). The ability to use a whole-building simulation tool to model the entire sector is of interest because the energy models enable us to answer subsequent 'what-if' questions that involve technologies and practices related to energy. This report documents how the whole-building models were generated from the building characteristics in 2003 CBECS and compares the simulation results to the survey data for energy use.

This report summarizes the findings from research conducted at NREL to assess the technical potential for zero-energy building technologies and practices to reduce the impact of commercial buildings on the U.S. energy system. Commercial buildings currently account for 18% of annual U.S. energy consumption, and energy use is growing along with overall floor area. Reducing the energy use of this sector will require aggressive research goals and rapid implementation of the research results.

TMIC-12. MODELING AND ESTIMATION OF TUMOR INTERSTITIAL FLUID PRESSURE AND NORMAL TISSUE COMPRESSION USING HYPERFOAM THEORY AND FINITE ELEMENT TECHNIQUE Narsollah Goudarzi1, Reza Faghihi1, James Ewing2, Brent Griffith2, David Nathanson2, Ali Arbab3, and Hassan Bagher-Ebadian2,4; Shiraz University, Shiraz, Fars, Iran; Henry Ford Hospital, Detroit, MI, USA; Georgia Regents University, Atlanta, GA, USA; Oakland University, Rochester, MI, USA Recent studies have shown that mechanical stresses and interstitial fluid pressure (IFP) gradients of solid and embedded tumors directly contribute to their aggressiveness and response to therapy. Thus, studying and modeling these parameters play an important role in diagnosis and therapy of solid tumors. In this study, a mathematical benchmark was developed based on the IF flow, conservation laws for mass and momentum, and hyperfoam theory to model a physiological system containing a solid tumor surrounded by normal tissue. Using a finite element technique, IFP and tissue compression weremodeled fora solid tumor with diameterof 20 mmsurroundedbynormal tissue with thickness of 20 mm. It was hypothesized that the normal tissue can experience elastic and plastic phases during the compression. Hyperelastic parameters of white-matter were recruited in the hyperfoam strain energy function for modeling the distribution of tumor pressure load to its surrounded normal tissue, tumor, and normal IF velocities as well as displacement, stress, strain, and Young modulus of the normal tissue. Results imply that the IFP is highest and almost uniform inside the tumor and due to the small IFP gradient inside the tumor, the IF velocity is almost zero inside the tumor but high in its adjacent normal tissue while it drops abruptly in the normal tissue. Normal tissue displacement is high close to the boundary of the tumor and deceases with distant from tumor boundary. Stress distribution and Young’smodulus in normal tissue arealmostuniform while the hydrostatic strain is highclose to the boundaryof the tumorand decreases smoothly with distant from tumor boundary. This pilot study provides a practical benchmark for characterizing the mechanical properties of embedded tumors and their surrounded normal tissues that are considered as useful information in studying the embedded tumors in research and clinic. Neuro-Oncology 17:v221–v225, 2015. doi:10.1093/neuonc/nov236.12 Published by Oxford University Press on behalf of the Society for Neuro-Oncology 2015.

Prediction of patient survival with brain tumor can play an important role in treatment planning and quality of a patient's life. This study investigates the effect of permeability and perfusion parameters on survival rate. This study identifies the most effective parameters on the survival time and then combines these parameters with experts' knowledge to construct a fuzzy-based model for predicting the survival rate of patients with Glioblastoma Multiforme (GBM). 25 treatment-naive GBM patients were studied using Dynamic Contrast Enhanced Magnetic Resonance Imaging. Using the standard Toft-model combined with Model Selection technique and Maximum-Likelihood algorithm, for each patient, the following permeability parameters were estimated: plasma volume (vp), outward and inward transfer constants (ktrans and kep). The estimated parameters were averaged across the tumor volume for each patient. Histogram of each parameter in whole volume of tumor was calculated and a Normal distribution was assigned to each histogram. Mean and standard deviation of each normal distribution were used to calculate the probability of each parameter being effective on survival rate. All the estimated parameters along with age, gender and hemodynamic parameters (relative Cerebral Blood Volume, rCBV and Cerebral Blood Flow, rCBF) were used as independent features for Cox-proportional-hazard regression model and Wald-test for survival analysis and to identify the parameters with most predictive power of survival. This pilot study revealed that the following physiological parameters are the best candidates to construct the fuzzy-based model for prediction of GBM patient survival: Mean and standard deviation of kep and extra-vascular extra-cellular volume (ve = ktrans/kep), vp, patient age, and rCBV. Compared to the other conventional predictors, the proposed model in this study showed a superior predictive power (∼ 93%) which is due to the fact that it can benefit from experimental data and a set of rules that can be constructed based on the knowledge of experts.

Final report of energy performance analysis and design process evaluation for the Thermal Test Facility at the National Renewable Energy Laboratory.

Acute calcific longus colli tendinitis (LCT) has been reported as an unusual cause of acute-onset neck pain, dysphagia, and headache.(1-5) As described in most of the published reports, LCT traditionally manifests on computed tomography (CT) imaging as paramidline calcium hydroxyapatite crystal deposits anterior to the C1 and C2 vertebral bodies. However, recent studies have brought attention to the disease existing at the C4-C5 and C5-C6 levels.(6,7) Acute LCT is considered relatively benign, typically resolving on its own within several weeks.

The validation of a building simulation program or model is a daunting task, and one that should receive as much attention as algorithm and code development. Previous research in this field has led to a well-accepted approach composed of analytical verification, empirical validation, and inter-program comparative testing to diagnose model deficiencies, mathematical solution errors, and coding errors. Through a case study, this paper demonstrates the utility of inter-program comparative testing. It shows that by comparing program-to-program results, solution problems, coding errors, and deficiencies in mathematical model descriptions can be efficiently identified, diagnosed, and subsequently repaired.

The provision of heat and power to dwellings from micro-cogeneration systems is gaining credence around the developed world as a possible means to reduce the significant carbon emissions associated with the domestic sector. However, achieving the optimum performance for these systems requires that building design practitioners are equipped with robust, integrated models, which will provide a realistic picture of the cogeneration performance in-situ. A long established and appropriate means to evaluate the energy performance of buildings and their energy systems is through the use of dynamic building simulation tools. However, until now, only a very limited number of micro-cogeneration device models have been available to the modelling community and generally these have not been appropriate for use within building simulation codes. This paper describes work undertaken within the International Energy Agency's Energy Conservation in Building and Community Systems Annex 42 to address this problem through the development of a generic, combustion based cogeneration device model that is suitable for integration within building simulation tools and can be used to simulate the variety of Internal Combustion Engine (ICE) and Stirling Engine (SE) cogeneration devices that are and will be available for integration into dwellings. The model is described in detail along with details of how it has been integrated into the ESP-r, Energy Plus and TRNSYS simulation platforms.