Profile of planning: A study of a three-year project on the implementation of collaborative library media programs

The implementation of collaborative planning and teaching models in ten flexibly scheduled elementary and middle school library media centers was studied to determine which factors facilitated the collaborative planning process and to learn what occurs when library media specialists (LMSs) and classroom teachers (CTs) plan together. In this qualitative study, 61 principals, CTs, and LMSs were interviewed on a range of topics including the principal's role, school climate, the value of team planning, the importance of information literacy instruction, and the ideal learning environment. Other data sources were observations, videotapes of planning sessions, and documents. This three-year school reform effort was funded by the Library Power Project to improve library programs, to encourage collaborative planning, and to increase curricular integration of information literacy skills instruction. ^ The findings included a description of typical planning sessions and the identification of several major factors which impacted the success of collaborative planning: the individuals involved, school climate, time for planning, the organization of the school, the facility and collection, and training. Of these factors, the characteristics and actions of the people involved were most critical to the implementation of the innovation. The LMS was the pivotal player and, in the views of CTs, principals, and LMSs themselves, must be knowledgeable about curriculum, the library collection, and instructional design and delivery; must be open and welcoming to CTs and use good interpersonal skills; and must be committed to information literacy instruction and willing to act as a change agent. The support of the principal was vital; in schools with successful programs, the principal served as an advocate for collaborative planning and information literacy instruction, provided financial support for the library program including clerical staff, and arranged for LMSs and CTs to have time during the school day to plan together. ^ CTs involved in positive planning partnerships with LMSs were flexible, were open to change, used a variety of instructional materials, expected students to be actively involved in their own learning, and were willing to team teach with LMSs. Most CTs planning with LMSs made lesson plans in advance and preferred to plan with others. Also, most CTs in this study planned with grade level or departmental groups, which expedited the delivery of information literacy instruction and the effective use of planning time. ^ Implications of the findings of this research project were discussed for individual schools, for school districts, and for colleges and universities training LMSs, CTs, and administrators. Suggestions for additional research were also included. ^

Teachers' perceptions of the usefulness of Individual Education Plans (IEP)

Since 1997 federal special education policy mandated that all classroom teachers take part in planning and implementation of Individualized Education Plans (IEP) for students with disabilities. This legislation has given teachers new responsibilities because it requires greater participation in the IEP process. The purpose of this study was to examine teachers' perceptions of the usefulness of Individualized Education Plans (IEP). ^ Eighty seven certified Miami-Dade County Public School teachers, 60 general education teachers and 27 special education teachers were surveyed using an updated version of Rheams' (1989) The Teacher Perceptions of the Usefulness of IEPs. Subjects completed a survey form containing a demographic cover page, 18 Likert-scale statements and 3 open ended questions. This study looked at differences in perceptions by teacher group affiliation (general and special), grade level taught (elementary and secondary), and years of experience (<=5 and >5 years). The dependent variables were teacher preparedness; feasibility of IEP implementation; relevancy of IP to classroom instruction; and legal, professional and personal accountability with regard to the IEP. ^ Results of the Multivariate Analysis of Variance (MANOVA) revealed that (a) special education teachers held a more positive perception of overall IEP usefulness than general education teachers, (b) special educators held more positive perceptions concerning issues of feasibility and preparedness, (c) elementary level teachers viewed the IEP more positively than secondary level teachers, specifically in the areas of preparedness and feasibility. ^ Findings of this study indicate that general and secondary educators have not embraced the legislation and incorporated it into their planning and instruction. These findings provide policymakers, institutions of higher education, and school administrators with insight as to how to better translate policy into classroom instructional practice. Consideration should be given to implementing (a) honest communication and shared decision making with regard to IEP directed curriculum and instruction, (b) updated pre and in-service IEP development and implementation training, and (c) opportunities for collaboration and increased plan time, especially on the secondary level. ^

Selected psychosocial and demographic factors affecting levels of pre-retirement planning

In September 2002, the State of Florida implemented a new retirement structure for those employed in the Florida Public School System. Teachers were given the option to maintain their existing defined benefit plan or choose the newly offered defined contribution plan. The variables that affect planning for retirement are innumerable. Identifying the most significant variables is essential to understanding how one plans for retirement. ^ This study examined the relationship between hypothesized psychosocial and demographic factors and an individual's level of pre-retirement planning. The criterion variable, the level of pre-retirement planning, comprised two concepts. First, the time spent thinking about retirement was determined by the score an individual received on a pre-retirement planning scale. This scale included the concepts of information gathering, goals, anticipated resources, and long-range planning. Second, implementation of retirement plan procedures was determined by the percentage an individual annually deferred to retirement. ^ The survey used for data collection contained 50 close-ended items. It was distributed to all full-time teachers in nine randomly selected elementary, middle, and senior high schools throughout Miami-Dade County Public Schools. Multiple regression and crosstabulation indicated that math anxiety, general risk, years of service, and total family income were significant predictors of the level of pre-retirement planning, as measured by the pre-retirement planning scale. In addition, the statistical analysis indicated that math anxiety, internal locus of control, years of service, and total family income were significant predictors of the level pre-retirement planning, as measured by the amount deferred to retirement. An individual's level of math anxiety and family income were the two factors that were the most significant predictors for both concepts on the level of pre-retirement planning. ^ Based on the findings of the study, recommendations focused on assessing an individual's level of math anxiety and educating teachers, particularly pre-service candidates, about the factors that affect pre-retirement planning. Further research should investigate the benefit of such educational programs. ^

A youth vision of the city: The socio-spatial lives and exclusion of street girls in Bogota, Colombia

This dissertation documents the everyday lives and spaces of a population of youth typically constructed as out of place, and the broader urban context in which they are rendered as such. Thirty-three female and transgender street youth participated in the development of this youth-based participatory action research (YPAR) project utilizing geo-ethnographic methods, auto-photography, and archival research throughout a six-phase, eighteen-month research process in Bogotá, Colombia. ^ This dissertation details the participatory writing process that enabled the YPAR research team to destabilize dominant representations of both street girls and urban space and the participatory mapping process that enabled the development of a youth vision of the city through cartographic images. The maps display individual and aggregate spatial data indicating trends within and making comparisons between three subgroups of the research population according to nine spatial variables. These spatial data, coupled with photographic and ethnographic data, substantiate that street girls’ mobilities and activity spaces intersect with and are altered by state-sponsored urban renewal projects and paramilitary-led social cleansing killings, both efforts to clean up Bogotá by purging the city center of deviant populations and places. ^ Advancing an ethical approach to conducting research with excluded populations, this dissertation argues for the enactment of critical field praxis and care ethics within a YPAR framework to incorporate young people as principal research actors rather than merely voices represented in adultist academic discourse. Interjection of considerations of space, gender, and participation into the study of street youth produce new ways of envisioning the city and the role of young people in research. Instead of seeing the city from a panoptic view, Bogotá is revealed through the eyes of street youth who participated in the construction and feminist visualization of a new cartography and counter-map of the city grounded in embodied, situated praxis. This dissertation presents a socially responsible approach to conducting action-research with high-risk youth by documenting how street girls reclaim their right to the city on paper and in practice; through maps of their everyday exclusion in Bogotá followed by activism to fight against it.^

Spatial variability in Florida Bay particulate organic matter composition: combining flow cytometry with stable isotope analyses

Long-term management plans for restoration of natural flow conditions through the Everglades increase the importance of understanding potential nutrient impacts of increased freshwater delivery on Florida Bay biogeochemistry. Planktonic communities respond quickly to changes in water quality, thus spatial variability in community composition and relationships to nutrient parameters must be understood in order to evaluate future downstream impacts of modifications to Everglades hydrology. Here we present initial results combining flow cytometry analyses of phytoplankton and bacterial populations (0.1–50 μm size fraction) with measurements of δ13C and δ15N composition and dissolved inorganic nutrient concentrations to explore proxies for planktonic species assemblage compositions and nutrient cycling. Particulate organic material in the 0.1–50 μm size fraction was collected from five stations in Northeastern and Western Florida Bay to characterize spatial variability in species assemblage and stable isotopic composition. A dense bloom of the picocyanobacterium, Synechococcus elongatus, was observed at Western Florida Bay sites. Smaller Synechococcus sp. were present at Northeast sites in much lower abundance. Bacteria and detrital particles were also more abundant at Western Florida Bay stations than in the northeast region. The highest abundance of detritus occurred at Trout Creek, which receives freshwater discharge from the Everglades through Taylor Slough. In terms of nutrient availability and stable isotopic values, the S. elongatus population in the Western bay corresponded to low DIN (0.5 μM NH 4 + ; 0.2 μM NO 3 − ) concentrations and depleted δ15N signatures ranging from +0.3 to +0.8‰, suggesting that the bloom supported high productivity levels through N2-fixation. δ15N values from the Northeast bay were more enriched (+2.0 to +3.0‰), characteristic of N-recycling. δ13C values were similar for all marine Florida Bay stations, ranging from −17.6 to −14.4‰, however were more depleted at the mangrove ecotone station (−25.5 to −22.3‰). The difference in the isotopic values reflects differences in carbon sources. These findings imply that variations in resource availability and nutrient sources exert significant control over planktonic community composition, which is reflected by stable isotopic signatures.

Hazard mitigation element quality in coastal comprehensive plans in a state with strong requirements for hazard mitigation plan elements

This dissertation examines the quality of hazard mitigation elements in a coastal, hazard prone state. I answer two questions. First, in a state with a strong mandate for hazard mitigation elements in comprehensive plans, does plan quality differ among county governments? Second, if such variation exists, what drives this variation? My research focuses primarily on Florida's 35 coastal counties, which are all at risk for hurricane and flood hazards, and all fall under Florida's mandate to have a comprehensive plan that includes a hazard mitigation element. Research methods included document review to rate the hazard mitigation elements of all 35 coastal county plans and subsequent analysis against demographic and hazard history factors. Following this, I conducted an electronic, nationwide survey of planning professionals and academics, informed by interviews of planning leaders in Florida counties. I found that hazard mitigation element quality varied widely among the 35 Florida coastal counties, but were close to a normal distribution. No plans were of exceptionally high quality. Overall, historical hazard effects did not correlate with hazard mitigation element quality, but some demographic variables that are associated with urban populations did. The variance in hazard mitigation element quality indicates that while state law may mandate, and even prescribe, hazard mitigation in local comprehensive plans, not all plans will result in equal, or even adequate, protection for people. Furthermore, the mixed correlations with demographic variables representing social and disaster vulnerability shows that, at least at the county level, vulnerability to hazards does not have a strong effect on hazard mitigation element quality. From a theory perspective, my research is significant because it compares assumptions about vulnerability based on hazard history and demographics to plan quality. The only vulnerability-related variables that appeared to correlate, and at that mildly so, with hazard mitigation element quality, were those typically representing more urban areas. In terms of the theory of Neo-Institutionalism and theories related to learning organizations, my research shows that planning departments appear to have set norms and rules of operating that preclude both significant public involvement and learning from prior hazard events.

A dosimetry and radiobiological model for intravascular brachytherapy treatment planning with radioisotope emitting stents

The aim of this study was to develop a practical, versatile and fast dosimetry and radiobiological model for calculation of the 3D dose distribution and radiobiological effectiveness of radioactive stents. The algorithm was written in Matlab 6.5 programming language and is based on the dose point kernel convolution. The dosimetry and radiobiological model was applied for evaluation of the 3D dose distribution of 32P, 90Y, 188Re and 177Lu stents. Of the four, 32P delivers the highest dose, while 90Y, 188Re and 177Lu require high levels of activity to deliver a significant therapeutic dose in the range of 15-30 Gy. Results of the radiobiological model demonstrated that the same physical dose delivered by different radioisotopes produces significantly different radiobiological effects. This type of theoretical dose calculation can be useful in the development of new stent designs, the planning of animal studies and clinical trials, and clinical decisions involving individualized treatment plans.

Dosimetric Evaluation of Metal Artefact Reduction using Metal Artefact Reduction (MAR) Algorithm and Dual-energy Computed Tomography (CT) Method

Purpose: Computed Tomography (CT) is one of the standard diagnostic imaging modalities for the evaluation of a patient’s medical condition. In comparison to other imaging modalities such as Magnetic Resonance Imaging (MRI), CT is a fast acquisition imaging device with higher spatial resolution and higher contrast-to-noise ratio (CNR) for bony structures. CT images are presented through a gray scale of independent values in Hounsfield units (HU). High HU-valued materials represent higher density. High density materials, such as metal, tend to erroneously increase the HU values around it due to reconstruction software limitations. This problem of increased HU values due to metal presence is referred to as metal artefacts. Hip prostheses, dental fillings, aneurysm clips, and spinal clips are a few examples of metal objects that are of clinical relevance. These implants create artefacts such as beam hardening and photon starvation that distort CT images and degrade image quality. This is of great significance because the distortions may cause improper evaluation of images and inaccurate dose calculation in the treatment planning system. Different algorithms are being developed to reduce these artefacts for better image quality for both diagnostic and therapeutic purposes. However, very limited information is available about the effect of artefact correction on dose calculation accuracy. This research study evaluates the dosimetric effect of metal artefact reduction algorithms on severe artefacts on CT images. This study uses Gemstone Spectral Imaging (GSI)-based MAR algorithm, projection-based Metal Artefact Reduction (MAR) algorithm, and the Dual-Energy method.

Materials and Methods: The Gemstone Spectral Imaging (GSI)-based and SMART Metal Artefact Reduction (MAR) algorithms are metal artefact reduction protocols embedded in two different CT scanner models by General Electric (GE), and the Dual-Energy Imaging Method was developed at Duke University. All three approaches were applied in this research for dosimetric evaluation on CT images with severe metal artefacts. The first part of the research used a water phantom with four iodine syringes. Two sets of plans, multi-arc plans and single-arc plans, using the Volumetric Modulated Arc therapy (VMAT) technique were designed to avoid or minimize influences from high-density objects. The second part of the research used projection-based MAR Algorithm and the Dual-Energy Method. Calculated Doses (Mean, Minimum, and Maximum Doses) to the planning treatment volume (PTV) were compared and homogeneity index (HI) calculated.

Results: (1) Without the GSI-based MAR application, a percent error between mean dose and the absolute dose ranging from 3.4-5.7% per fraction was observed. In contrast, the error was decreased to a range of 0.09-2.3% per fraction with the GSI-based MAR algorithm. There was a percent difference ranging from 1.7-4.2% per fraction between with and without using the GSI-based MAR algorithm. (2) A range of 0.1-3.2% difference was observed for the maximum dose values, 1.5-10.4% for minimum dose difference, and 1.4-1.7% difference on the mean doses. Homogeneity indexes (HI) ranging from 0.068-0.065 for dual-energy method and 0.063-0.141 with projection-based MAR algorithm were also calculated.

Conclusion: (1) Percent error without using the GSI-based MAR algorithm may deviate as high as 5.7%. This error invalidates the goal of Radiation Therapy to provide a more precise treatment. Thus, GSI-based MAR algorithm was desirable due to its better dose calculation accuracy. (2) Based on direct numerical observation, there was no apparent deviation between the mean doses of different techniques but deviation was evident on the maximum and minimum doses. The HI for the dual-energy method almost achieved the desirable null values. In conclusion, the Dual-Energy method gave better dose calculation accuracy to the planning treatment volume (PTV) for images with metal artefacts than with or without GE MAR Algorithm.

Development and Testing of An Automatic Lung IMRT Planning Algorithm

Knowledge-based radiation treatment is an emerging concept in radiotherapy. It

mainly refers to the technique that can guide or automate treatment planning in

clinic by learning from prior knowledge. Dierent models are developed to realize

it, one of which is proposed by Yuan et al. at Duke for lung IMRT planning. This

model can automatically determine both beam conguration and optimization ob-

jectives with non-coplanar beams based on patient-specic anatomical information.

Although plans automatically generated by this model demonstrate equivalent or

better dosimetric quality compared to clinical approved plans, its validity and gener-

ality are limited due to the empirical assignment to a coecient called angle spread

constraint dened in the beam eciency index used for beam ranking. To eliminate

these limitations, a systematic study on this coecient is needed to acquire evidences

for its optimal value.

To achieve this purpose, eleven lung cancer patients with complex tumor shape

with non-coplanar beams adopted in clinical approved plans were retrospectively

studied in the frame of the automatic lung IMRT treatment algorithm. The primary

and boost plans used in three patients were treated as dierent cases due to the

dierent target size and shape. A total of 14 lung cases, thus, were re-planned using

the knowledge-based automatic lung IMRT planning algorithm by varying angle

spread constraint from 0 to 1 with increment of 0.2. A modied beam angle eciency

index used for navigate the beam selection was adopted. Great eorts were made to assure the quality of plans associated to every angle spread constraint as good

as possible. Important dosimetric parameters for PTV and OARs, quantitatively

re

ecting the plan quality, were extracted from the DVHs and analyzed as a function

of angle spread constraint for each case. Comparisons of these parameters between

clinical plans and model-based plans were evaluated by two-sampled Students t-tests,

and regression analysis on a composite index built on the percentage errors between

dosimetric parameters in the model-based plans and those in the clinical plans as a

function of angle spread constraint was performed.

Results show that model-based plans generally have equivalent or better quality

than clinical approved plans, qualitatively and quantitatively. All dosimetric param-

eters except those for lungs in the automatically generated plans are statistically

better or comparable to those in the clinical plans. On average, more than 15% re-

duction on conformity index and homogeneity index for PTV and V40, V60 for heart

while an 8% and 3% increase on V5, V20 for lungs, respectively, are observed. The

intra-plan comparison among model-based plans demonstrates that plan quality does

not change much with angle spread constraint larger than 0.4. Further examination

on the variation curve of the composite index as a function of angle spread constraint

shows that 0.6 is the optimal value that can result in statistically the best achievable

plans.

The Feasibly of Functionally Guided Intensity Modulated Radiation Therapy Treatment Planning Using Perfluoropropane-Enhanced MRI for Lung Cancer

Radiotherapy is commonly used to treat lung cancer. However, radiation induced damage to lung tissue is a major limiting factor to its use. To minimize normal tissue lung toxicity from conformal radiotherapy treatment planning, we investigated the use of Perfluoropropane(PFP)-enhanced MR imaging to assess and guide the sparing of functioning lung. Fluorine Enhanced MRI using Perfluoropropane(PFP) is a dynamic multi-breath steady state technique enabling quantitative and qualitative assessments of lung function(1).

Imaging data was obtained from studies previously acquired in the Duke Image Analysis Laboratory. All studies were approved by the Duke IRB. The data was de-identified for this project, which was also approved by the Duke IRB. Subjects performed several breath-holds at total lung capacity(TLC) interspersed with multiple tidal breaths(TB) of Perfluoropropane(PFP)/oxygen mixture. Additive wash-in intensity images were created through the summation of the wash-in phase breath-holds. Additionally, model based fitting was utilized to create parametric images of lung function(1).

Varian Eclipse treatment planning software was used for putative treatment planning. For each subject two plans were made, a standard plan, with no regional functional lung information considered other than current standard models. Another was created using functional information to spare functional lung while maintaining dose to the target lesion. Plans were optimized to a prescription dose of 60 Gy to the target over the course of 30 fractions.

A decrease in dose to functioning lung was observed when utilizing this functional information compared to the standard plan for all five subjects. PFP-enhanced MR imaging is a feasible method to assess ventilatory lung function and we have shown how this can be incorporated into treatment planning to potentially decrease the dose to normal tissue.

Sensor Planning for Bayesian Nonparametric Target Modeling

Bayesian nonparametric models, such as the Gaussian process and the Dirichlet process, have been extensively applied for target kinematics modeling in various applications including environmental monitoring, traffic planning, endangered species tracking, dynamic scene analysis, autonomous robot navigation, and human motion modeling. As shown by these successful applications, Bayesian nonparametric models are able to adjust their complexities adaptively from data as necessary, and are resistant to overfitting or underfitting. However, most existing works assume that the sensor measurements used to learn the Bayesian nonparametric target kinematics models are obtained a priori or that the target kinematics can be measured by the sensor at any given time throughout the task. Little work has been done for controlling the sensor with bounded field of view to obtain measurements of mobile targets that are most informative for reducing the uncertainty of the Bayesian nonparametric models. To present the systematic sensor planning approach to leaning Bayesian nonparametric models, the Gaussian process target kinematics model is introduced at first, which is capable of describing time-invariant spatial phenomena, such as ocean currents, temperature distributions and wind velocity fields. The Dirichlet process-Gaussian process target kinematics model is subsequently discussed for modeling mixture of mobile targets, such as pedestrian motion patterns.

Novel information theoretic functions are developed for these introduced Bayesian nonparametric target kinematics models to represent the expected utility of measurements as a function of sensor control inputs and random environmental variables. A Gaussian process expected Kullback Leibler divergence is developed as the expectation of the KL divergence between the current (prior) and posterior Gaussian process target kinematics models with respect to the future measurements. Then, this approach is extended to develop a new information value function that can be used to estimate target kinematics described by a Dirichlet process-Gaussian process mixture model. A theorem is proposed that shows the novel information theoretic functions are bounded. Based on this theorem, efficient estimators of the new information theoretic functions are designed, which are proved to be unbiased with the variance of the resultant approximation error decreasing linearly as the number of samples increases. Computational complexities for optimizing the novel information theoretic functions under sensor dynamics constraints are studied, and are proved to be NP-hard. A cumulative lower bound is then proposed to reduce the computational complexity to polynomial time.

Three sensor planning algorithms are developed according to the assumptions on the target kinematics and the sensor dynamics. For problems where the control space of the sensor is discrete, a greedy algorithm is proposed. The efficiency of the greedy algorithm is demonstrated by a numerical experiment with data of ocean currents obtained by moored buoys. A sweep line algorithm is developed for applications where the sensor control space is continuous and unconstrained. Synthetic simulations as well as physical experiments with ground robots and a surveillance camera are conducted to evaluate the performance of the sweep line algorithm. Moreover, a lexicographic algorithm is designed based on the cumulative lower bound of the novel information theoretic functions, for the scenario where the sensor dynamics are constrained. Numerical experiments with real data collected from indoor pedestrians by a commercial pan-tilt camera are performed to examine the lexicographic algorithm. Results from both the numerical simulations and the physical experiments show that the three sensor planning algorithms proposed in this dissertation based on the novel information theoretic functions are superior at learning the target kinematics with

little or no prior knowledge

Landscape and planning: strengthening discussions in the decision-making process

Since the emergence of the European Landscape Convention (ELC) in 2000, the important link between landscape and planning has greatly intensified. Now, more than ever, the fundamental role of the planning system in delivering the ELC’s requirements is recognised. This has been further substantiated within Ireland’s recently published National Landscape Strategy. However it has continually been suggested that decision-making processes need to adapt better to the holistic, valueladen and multidimensional approaches underpinning the ELC. In light of these milestones for the preservation, management and planning of landscape, this research sets out to establish synergies and disparities in the existing relationship between landscape and planning. It investigates detailed evidence of the presence and manifestations of landscape in key processes of day-to-day planning practice in Ireland, from individual planning appeals and ‘special’ cases, to the major strategic instruments that inform the making of landscape policies within development plans. This is set within wider theoretical and policy contexts where the compatibility of landscape and planning is subjected to critical scrutiny and then explored through these practical case studies. Driving this research is the intention to make a case for the planning domain to be an ideal ‘home’ for landscape – in all its deep, multidimensional meaning – and for enhancing landscape arguments and objectives in the face of conflict, competing values and power-plays in the real world. Emerging out of this research is a set of recommendations for how, at a national level, new approaches for decision making for and about landscape can be more effective and meaningful.

CT Image Electron Density Quantification in Regions with Metal Implants: Implications for Radiotherapy Treatment Planning

In radiotherapy planning, computed tomography (CT) images are used to quantify the electron density of tissues and provide spatial anatomical information. Treatment planning systems use these data to calculate the expected spatial distribution of absorbed dose in a patient. CT imaging is complicated by the presence of metal implants which cause increased image noise, produce artifacts throughout the image and can exceed the available range of CT number values within the implant, perturbing electron density estimates in the image. Furthermore, current dose calculation algorithms do not accurately model radiation transport at metal-tissue interfaces. Combined, these issues adversely affect the accuracy of dose calculations in the vicinity of metal implants. As the number of patients with orthopedic and dental implants grows, so does the need to deliver safe and effective radiotherapy treatments in the presence of implants. The Medical Physics group at the Cancer Centre of Southeastern Ontario and Queen's University has developed a Cobalt-60 CT system that is relatively insensitive to metal artifacts due to the high energy, nearly monoenergetic Cobalt-60 photon beam. Kilovoltage CT (kVCT) images, including images corrected using a commercial metal artifact reduction tool, were compared to Cobalt-60 CT images throughout the treatment planning process, from initial imaging through to dose calculation. An effective metal artifact reduction algorithm was also implemented for the Cobalt-60 CT system. Electron density maps derived from the same kVCT and Cobalt-60 CT images indicated the impact of image artifacts on estimates of photon attenuation for treatment planning applications. Measurements showed that truncation of CT number data in kVCT images produced significant mischaracterization of the electron density of metals. Dose measurements downstream of metal inserts in a water phantom were compared to dose data calculated using CT images from kVCT and Cobalt-60 systems with and without artifact correction. The superior accuracy of electron density data derived from Cobalt-60 images compared to kVCT images produced calculated dose with far better agreement with measured results. These results indicated that dose calculation errors from metal image artifacts are primarily due to misrepresentation of electron density within metals rather than artifacts surrounding the implants.

New Principles in Planning Evaluation

Maintaining and enhancing living conditions in cities through a combination of physical planning and environmental management is a newly emerging focus of governments around the world. For example, local governments seek to insulate sensitive land uses such as residential areas from environmentally intrusive activities such as major transport facilities and manufacturing. Regional governments protect water quality and natural habitat by enforcing pollution controls and regulating the location of growth. Some national governments fund acquisition of strategically important sites, facilitate the renewal of brown fields, and even develop integrated environmental quality plans. This book provides recently developed and tested methods for assessing the strengths and weaknesses of planning and policy options. Several contributions focus on new substantive areas of concern in planning evaluation, including environmental justice and sustainable urban development. Applications of evaluation in several planning contexts are demonstrated, and special problems that these pose are assessed. Several chapters address how to communicate the process and results to several stakeholder groups, and how to engage these groups in the evaluation process. Each chapter employs a realworld case in practice, thus dealing with the complexity of applying planning evaluation, and providing practical advice useful in similar situations.