Fluorescence-enhanced optical imaging on three-dimensional phantoms using a hand-held probe based frequency-domain intensified charge coupled device (ICCD) optical imager

Fluorescence-enhanced optical imaging is an emerging non-invasive and non-ionizing modality towards breast cancer diagnosis. Various optical imaging systems are currently available, although most of them are limited by bulky instrumentation, or their inability to flexibly image different tissue volumes and shapes. Hand-held based optical imaging systems are a recent development for its improved portability, but are currently limited only to surface mapping. Herein, a novel optical imager, consisting primarily of a hand-held probe and a gain-modulated intensified charge coupled device (ICCD) detector, is developed towards both surface and tomographic breast imaging. The unique features of this hand-held probe based optical imager are its ability to; (i) image large tissue areas (5×10 sq. cm) in a single scan, (ii) reduce overall imaging time using a unique measurement geometry, and (iii) perform tomographic imaging for tumor three-dimensional (3-D) localization. Frequency-domain based experimental phantom studies have been performed on slab geometries (650 ml) under different target depths (1-2.5 cm), target volumes (0.45, 0.23 and 0.10 cc), fluorescence absorption contrast ratios (1:0, 1000:1 to 5:1), and number of targets (up to 3), using Indocyanine Green (ICG) as fluorescence contrast agents. An approximate extended Kalman filter based inverse algorithm has been adapted towards 3-D tomographic reconstructions. Single fluorescence target(s) was reconstructed when located: (i) up to 2.5 cm deep (at 1:0 contrast ratio) and 1.5 cm deep (up to 10:1 contrast ratio) for 0.45 cc-target; and (ii) 1.5 cm deep for target as small as 0.10 cc at 1:0 contrast ratio. In the case of multiple targets, two targets as close as 0.7 cm were tomographically resolved when located 1.5 cm deep. It was observed that performing multi-projection (here dual) based tomographic imaging using a priori target information from surface images, improved the target depth recovery over using single projection based imaging. From a total of 98 experimental phantom studies, the sensitivity and specificity of the imager was estimated as 81-86% and 43-50%, respectively. With 3-D tomographic imaging successfully demonstrated for the first time using a hand-held based optical imager, the clinical translation of this technology is promising upon further experimental validation from in-vitro and in-vivo studies.

Achieving zero accidents—A strategic framework for continuous safety improvement in the construction industry

In the U.S., construction accidents remain a significant economic and social problem. Despite recent improvement, the Construction industry, generally, has lagged behind other industries in implementing safety as a total management process for achieving zero accidents and developing a high-performance safety culture. One aspect of this total approach to safety that has frustrated the construction industry the most has been “measurement”, which involves identifying and quantifying the factors that critically influence safe work behaviors. The basic problem attributed is the difficulty in assessing what to measure and how to measure it—particularly the intangible aspects of safety. Without measurement, the notion of continuous improvement is hard to follow. This research was undertaken to develop a strategic framework for the measurement and continuous improvement of total safety in order to achieve and sustain the goal of zero accidents, while improving the quality, productivity and the competitiveness of the construction industry as it moves forward. The research based itself on an integral model of total safety that allowed decomposition of safety into interior and exterior characteristics using a multiattribute analysis technique. Statistical relationships between total safety dimensions and safety performance (measured by safe work behavior) were revealed through a series of latent variables (factors) that describe the total safety environment of a construction organization. A structural equation model (SEM) was estimated for the latent variables to quantify relationships among them and between these total safety determinants and safety performance of a construction organization. The developed SEM constituted a strategic framework for identifying, measuring, and continuously improving safety as a total concern for achieving and sustaining the goal of zero accidents.

An investigation into equations for estimating water requirements and the development of new equations for predicting total water intake

The primary purpose of this study was to investigate agreement among five equations by which clinicians estimate water requirements (EWR) and to determine how well these equations predict total water intake (TWI). The Institute of Medicine has used TWI as a measure of water requirements. A secondary goal of this study was to develop practical equations to predict TWI. These equations could then be considered accurate predictors of an individual’s water requirement. ^ Regressions were performed to determine agreement between the five equations and between the five equations and TWI using NHANES 1999–2004. The criteria for agreement was (1) strong correlation coefficients between all comparisons and (2) regression line that was not significantly different when compared to the line of equality (x=y) i.e., the 95% CI of the slope and intercept must include one and zero, respectively. Correlations were performed to determine association between fat-free mass (FFM) and TWI. Clinically significant variables were selected to build equations for predicting TWI. All analyses were performed with SAS software and were weighted to account for the complex survey design and for oversampling. ^ Results showed that the five EWR equations were strongly correlated but did not agree with each other. Further, the EWR equations were all weakly associated to TWI and lacked agreement with TWI. The strongest agreement between the NRC equation and TWI explained only 8.1% of the variability of TWI. Fat-free mass was positively correlated to TWI. Two models were created to predict TWI. Both models included the variables, race/ethnicity, kcals, age, and height, but one model also included FFM and gender. The other model included BMI and osmolality. Neither model accounted for more than 28% of the variability of TWI. These results provide evidence that estimates of water requirements would vary depending upon which EWR equation was selected by the clinician. None of the existing EWR equations predicted TWI, nor could a prediction equation be created which explained a satisfactory amount of variance in TWI. A good estimate of water requirements may not be predicted by TWI. Future research should focus on using more valid measures to predict water requirements.^