James Duncan - US grants

The objective of this research is to investigate the factors controlling the magnitudes of the lateral earth pressures induced by compacting soil. The project will include laboratory tests to investigate the effects of compaction method, compactive effort, dry density, and water content on the magnitudes of compaction induced earth pressures. Tests will be conducted in a model test bin and in compacting soils in layers; the induced lateral pressures will be measured. These tests will provide a means of studying variations in pressures depending on the direction of roller travel and will provide a basis for assessing the effectiveness of available analytical techniques under carefully controlled conditions. This effort will take a fundamental approach to a basic geotechnical engineering process and will extensively use a new type of instrumentation, the temperature compensated mercury oedometer.

Although the important human pathogen, Streptococcus pyogenes, has been studied for many years, important questions about the pathogenesis of streptococcal diseases and the contribution of streptococcal products to these infections remain to be answered. This proposal deals with the streptococcal cytolytic toxins, streptolysin O and streptolysin S. The long-term objectives of our research are to determine precisely how these toxins affect the membranes of sensitive cells, and to understand what role, if any, the toxins play in the pathogenesis of acute streptococcal infections and in the nonsupportive sequelae of such infections. The specific aims of this proposal are first, to study the effects of both toxins on membranes and membrane constituents, using liposomes and cultures of human cells as targets of toxin action. We will examine the effects of streptolysin O on model membranes (liposomes), analyze the damaging effects of streptolysin S on cultures of human cells and study the reversability of this process, and investigate the effects of the streptococcal toxins on phagocytosis. Second, we will obtain monoclonal antibodies to streptolysin O and use them to study the structure of the toxin and to correlate structure with function. In addition, we will use the monoclonal antibodies to compare streptolysin O with the related thiol-activated cytolytic toxins.

An image understanding system is proposed to analyze cardiac dysfunction found by combining information from multiple, noninvasive imaging modality studies. The system is a model for intelligent multimodality image understanding in general, but is applied to a very specific problem: detection and rating of left ventricular (LV) aneurysms. Key features of the system are: 1) its ability to handle and quantify uncertain or partial image- derived information in a concise way using probabilistic evidential reasoning, 2) its ability to fuse pertinent relative information from independent diagnostic images of the same patient to achieve an algorithm-assembled, consensus, quantitative opinion of cardiac shape and motion, and finally 3) to arrive at a decision- level set of numbers that quantify and localize left ventricular aneurysm formation for each patient. The availability of data such as described in 3) will enable more precise prognostic or diagnostic risk classification for patients, making therapy alternatives more rational. Because of the subjective probabilistic reasoning strategy (based on the principle of maximum entropy) the final quantitative results will carry not only the system's assessment of a particular patients' heart, but also the degree of confidence that the automated analysis system has in the result it presents. This confidence is increased when similar LV motion and shape is perceived by the multiple imaging modalities. The proposed system design is influenced by current artificial intelligence and image understanding technologies, but remains firmly grounded in more classical mathematical and statistical methodology. The system will be initially tested using radionuclide angiographic (RNA) and two-dimensional echocardiographic (2DE) semi- quantified (manual tracing of LV borders) and then fully quantified (by the system's own border-finding algorithm) studies and compared with qualitative readings, quantified contrast ventriculograms, and then with surgeon's and pathologist's measurements and reports. Preliminary studies show that 1) RNA left lateral view qualitative studies correlate well with pathology, 2) that complementary 2DE views help resolve RNA problems with finding the anterior LV wall and 3) quantification of LV motion and shape better defines the spectrum between normal and grossly abnormal. Subsequent incorporation of magnetic resonance images (which have improved LV boundary definition) into the evaluation system will test its ability to adapt to and profit from new types of data.

Interstitial cystitis (IC) is an idiopathic disease characterized by irritative voiding symptoms, pain, and characteristic bladder lesions seen on cystoscopic examination. The etiology and pathogenesis of the disease are unknown and no uniformly effective treatment is available. Some of the characteristics of IC, including the abrupt onset of symptoms in some patients, and the inflammatory changes seen in the bladder, are compatible with, and even suggestive of, and infective etiology of the disease. Recent studies have suggested that fastidious microorganisms, particularly Gardnerella vaginalis, may be associated with IC. Studies using modern molecular tools to detect and identify infectious agents in the bladder tissue or urine of IC patients have never been carried out. We propose to reexamine the role of infectious agents in the etiology of IC, using state-of-the-art molecular tools based on ribosomal RNA (rRNA) and polymerase chain reaction (PCR) technology. This unique approach supersedes all previous attempts to find infectious agents in these patients because it allows one to detect and identify any organism present in clinical specimens of IC patients with culture. Thus, the task of searching for fastidious organisms by laborious and difficult culture procedures is obviated by the use of specific oligonucleotide probes that are specific for these organisms. Furthermore, previously uncultured and undescribed bacteria can be identified using broad-range rRNA probes that will recognize any bacterial organism. These molecular techniques are now widely used in infectious disease studies, and they offer important advantages in studying a disease such as IC. They are highly specific, sensitive, and versatile; archival tissue, including frozen and paraffin-embedded tissue can be analyzed. Furthermore, samples such as urine and exfoliated bladder cells, which are obtained from IC patients by less invasive procedures of low morbidity, are suitable for this type of analysis. Our hypothesis is that fastidious or cryptic infectious agents may contribute to the etiology of IC. We propose to address this question using a molecular approach. We will: 1. Examine urine, bladder cells and biopsy samples from IC patients for the presence of fastidious organisms using rRNA-PCR techniques. 2. Search for previously uncultured organism in bladder tissue and urine of IC patients with rRNA-PCR procedures. 3. Study the virulence determinants of any fastidious organism identified in this study emphasizing the interaction of the organism with bladder cells.

The quantification of left ventricular (LV) regional function from diagnostic images permits clinically important measurements to be made that are crucial for managing patients with ischemic heart disease. However, such measurements have been hampered by limitations in conventional imaging and image analysis methodology. These limitations have prohibited the accurate regional assessment of myocardial injury and/or the prediction of vessel patency, and include the facts that: 1.) most conventional imaging methods provide two-dimensional (2D) temporal slice or projection sequences, which cannot possibly permit viewing or analysis of the true motion of the heart, which rigidly moves and deforms in a three-dimensional (3D) space. 2.) Most approaches to regional image-based analysis of LV function: a.) make gross and restrictive assumptions about the general direction of LV motion or thickening (e.g. towards a center of mass) and b.) utilize only the end diastolic (ED) and end-systolic (ES) image frames, ignoring the fact that the LV actually goes through a temporal wave of contraction and the asynchrony of surface motion or LV thickening from region to region may be indicative of ischemia. The proposed research will use advanced techniques from computer vision to analyze 3D cardiac image sequences in order to more accurately estimate regional LV function. Our methodology makes use of mathematical optimization models related to the motion of 3D elastically deformable objects, an approach that is much more adaptable to the nonlinear, non-rigid regional motion of the LV than those based on the restrictive assumptions mentioned above. The approach will estimate and track the trajectories of motion of a dense field of points that sample the LV endocardial and epicardial surfaces at 1 point in time, over the entire cardiac cycle. In addition, these trajectories will be used to create quantitative measures of endocardial surface motion and LV thickening. the system will be validated using computer simulations of linearly deformable objects and image data acquired from acute dog studies. The acute dogs will have image-distinguishable markers sewn to the LV wall, and will be used not only for validation, but also to test the algorithm-derived measures' ability to predict the location and extent of myocardial injury. This testing will use data from two different imaging modalities, 4D gated/cine Magnetic Resonance Imaging and 4D real-time cine Computed Tomographic Imaging (using data from the Dynamic Spatial Reconstructor). Ultimately, our goal is to better distinguish and characterize the spatial/temporal extent and function of regions of ischemia and infarction in the LV wall, as well as gain insight into LV post-MI remodeling issues.

The quantification of left ventricular (LV) regional function from diagnostic images permits clinically important measurements to be made that are crucial for managing patients with ischemic heart disease. However, such measurements have been hampered by limitations in conventional imaging and image analysis methodology. These limitations have prohibited the accurate regional assessment of myocardial injury and/or the prediction of vessel patency, and include the facts that: 1.) most conventional imaging methods provide two-dimensional (2D) temporal slice or projection sequences, which cannot possibly permit viewing or analysis of the true motion of the heart, which rigidly moves and deforms in a three-dimensional (3D) space. 2.) Most approaches to regional image-based analysis of LV function: a.) make gross and restrictive assumptions about the general direction of LV motion or thickening (e.g. towards a center of mass) and b.) utilize only the end diastolic (ED) and end-systolic (ES) image frames, ignoring the fact that the LV actually goes through a temporal wave of contraction and the asynchrony of surface motion or LV thickening from region to region may be indicative of ischemia. The proposed research will use advanced techniques from computer vision to analyze 3D cardiac image sequences in order to more accurately estimate regional LV function. Our methodology makes use of mathematical optimization models related to the motion of 3D elastically deformable objects, an approach that is much more adaptable to the nonlinear, non-rigid regional motion of the LV than those based on the restrictive assumptions mentioned above. The approach will estimate and track the trajectories of motion of a dense field of points that sample the LV endocardial and epicardial surfaces at 1 point in time, over the entire cardiac cycle. In addition, these trajectories will be used to create quantitative measures of endocardial surface motion and LV thickening. the system will be validated using computer simulations of linearly deformable objects and image data acquired from acute dog studies. The acute dogs will have image-distinguishable markers sewn to the LV wall, and will be used not only for validation, but also to test the algorithm-derived measures' ability to predict the location and extent of myocardial injury. This testing will use data from two different imaging modalities, 4D gated/cine Magnetic Resonance Imaging and 4D real-time cine Computed Tomographic Imaging (using data from the Dynamic Spatial Reconstructor). Ultimately, our goal is to better distinguish and characterize the spatial/temporal extent and function of regions of ischemia and infarction in the LV wall, as well as gain insight into LV post-MI remodeling issues.

This research is primarily aimed at robustly locating deformable structures/objects of approximately known shape from natural images. The problem of locating and recognizing underlying object structures in an image is of importance in many image analysis and computer vision applications including robot vision, pattern recognition and biomedical image processing. Algorithms that can reliably perform these basis tasks are at the core of a variety of systems that will permit humans to more effectively interact with pictorial data for the purposes of visualization, analysis, control or, as in the case of image database systems, retrieval of task-specific information within these applications areas. The robust identification and measurement of such structure is not always achievable using a single analysis technique that depends on a single image derived source of information. This is especially true when one is dealing with a wide range of images obtained under different conditions having different image content. The approach in this research project utilizes two different sources of image-derived information: 1.) gray-level gradients and ii.) homogeneity of intensity or texture elements, etc., as well as model-based information (i.e approximate object shape). Furthermore, two different processing methods are combined in this approach, in order to integrate the above-mentioned information sources: a) regionbased methods, which are primarily based on homogeneity properties and b.) boundary methods which capitalize on both gradient (imagederived) and shape (model based) properties. A game theoretic framework will be used, where, unlike the global objective approach which is widely used as an integration method in computer vision, the modularity of the underlying objectives are retained. The integration problem is then framed as a family of coupled and coex isting objectives whereby the output of one module depends upon the previous outputs of the other modules. This effort will build on initial work which has been able to locate structure in two dimensional images. It will also extend the concept to analyzing three dimensional image data. Both theoretical and experimental investigations will be carried out regarding the applicability and the limits of the approach.

Autism is a developmental disorder that severely disrupts the social, cognitive and communicative skills of an individual. A host of brain structures are probably involved in its pathophysiology, including the cerebellum, brain stem, cortex and basal ganglia. Recent Magnetic Resonance Imaging (MRI) studies have produced mixed results, perhaps because of sample size limitations, etiologic heterogeneity and difficulties associated with accurately quantifying the regions of interest. The accurate, robust and efficient segmentation of these neuroanatomical structures from MRIs is a difficult problem. A variety of segmentation methods have been attempted to quantitate those brain structures. Success, however, has been limited, mainly because a single technique is likely to be unsuccessful over a wide range of structures. To circumvent that, we propose an integrated approach that attempts to capitalize on both region homogeneity and boundary information allowing us to use the wider source of naturally available information. This combination of information sources is achieved using a rational form of decision making which besides being technically more general than the commonly used single objective optimization approach, is computationally far less burdensome as well. The resulting robust method not only has the ability to handle a wide collection of neuroanatomical structures, but also is capable of suitably addressing MR imaging artifacts such as noise, poor image contrast, partial volume effect and inhomogeneous gain field due to appropriate integration of the aforementioned information sources. Our initial effort would be to extend and adapt our method which presently works on two dimensional images to more accurately capture the subtleties of the present problem. Also, we plan to extend it to three dimensional images to be better able to capture the actual structures involved. Validation for accuracy and reproducibility would be performed using electronically-generated phantoms as well as post mortem data available from the NIH Visible Human project. Finally, we intend to compare the algorithm-generated results with those found by human expert tracing of the same data, using MRI studies from a separately funded NIH project studying high functioning autism, Asperger's syndrome and matched controls. The automated approach will also allow us to investigate additional structures and will illustrate the ability of our approach to reproducibly detect subtle changes in structure.

Accurate quantification of left ventricular (LV) regional deformation has been shown to be important for understanding management of patients with ischemic heart disease. Quantitative, noninvasive measurement of 3D strain properties from images has been primarily limited to special forms of magnetic resonance acquisitions, especially MR tagging, and to a lesser extent MR phase contrast velocity. In previous years of this project, we have been working on developing an image analysis strategy capable of measuring strain from any one of a variety of imaging modalities. While our approach is capable of utilizing the specialized MR tag or velocity data mentioned above, we have been able to show using a strategy based on biomechanical modeling, differential geometric features and mathematical optimization, that dense 3D LV strain information can be recovered from standard (magnitude) cine-gradient echo MR (cine- MRI) acquisitions, as well as from 3D cine-computed tomography and 3D echocardiography (3DE) at the patient's bedside. However, for our system to be fully robust to variations in image data across the subject population, as well as to reduce the time and expertise required to initialize the system (primarily in the LV segmentation step), further effort it needed. To address these issues, we intend to extend our approach to incorporate temporal continuity constraints, provide feedback and integration between the segmentation/deformation algorithm modules, integrate a notion of active contraction into our biomechanical model and pose our entire approach in a probabilistic framework, where certain models and prior-learned-information from subject populations can e more readily incorporated. We are confident that these improvements to out system will make it more robust to image variation, reduce user- interaction to a minimum and ultimately provide more accurate results within a clinically- tolerable amount of time. We will confirm these incremental improvements, further validate our approach and verify the utility of in vivo strains for distinguishing transmural injury and its extend using acute and sub-acute (3 days post injury) canine models of infarction and two imaging modalities (cine-MRI and 3DE). Finally, we plan to verify that strain values using our approach are reproducibly derivable from a set of normal and abnormal human image datasets, acquired from 3 different imaging modalities.

Project IV extends our previous neuroimaging project which developed rigorous methodologies to examine particular brain structures between well-described subject groups and will also compare measures of brain function in these cohort. In our previous efforts, we obtained neuroanatomical Magnetic Resonance studies on over 320 children. While rigorous studies were performed on some of these subjects, complete image analysis was hampered by limitations in the subject groups, especially the normal group, due to necessary subtyping by gender and handedness. In this new grant, we propose to capitalize on our previous efforts by first performing additional MR neuroanatomical imaging using the same protocols as before on additional normal subjects in order to form a more complete control group. Next, rigorous statistical testing can be performed on the corpus callosum and the temporal lobes (focusing on planum temporale) using the sum total of this data. This neuroanatomical structures analysis will also be extended to include a measurement related to the asymmetry of the caudate nucleus. At the end of this effort, we hope to carefully and rigorously affirm or refute a variety of hypotheses relating brain structure and learning disorders currently being reported in the literature. In addition, not only do we plan to extend our previous studies of brain structure, but we also plan a major effort to examine brain function using non-invasive magnetic resonance imaging techniques in well- characterized reading disabled children to measure changes in blood flow in specific brain regions during specific cognitive tasks. Here, we will first develop methodology that will permit us to evaluate differences in the brain's response to different activation tasks in the frontal cortex and the temporal lobes. Next, we will compare these changes in children from three subject groups: dyslexic, attention disordered and normal children. MR promises to be the first method suitable for functional changes.

DESCRIPTION: (Applicant's Description) This proposal requests support for the 1997 meeting on Information Processing in Medical Imaging (IPMI), to be held at Green Mountain College in Poultney, Vermont in June of 1997. In its previous 14 meetings, this biennial conference has traditionally concentrated on the latest advancements in the acquisition, processing, analysis and display of medical images. In the 1997 meeting, it is intended to continue this tradition, but also to incorporate new efforts from people in the computer vision and applied mathematics communities who are now beginning to work in the medical image processing and analysis areas. While the advances that will be reported at this meeting are applicable to many disciplines, they will be especially important in the study of neurologic disorders, cardiovascular disease, and cancer, as well as with regard to the handling and archiving of medical image information in general. In the past, the IPMI meeting has attracted scientists from a broad range of disciplines, including electrical engineers, computer scientists, physicists, statisticians, cardiologists, radiologists, neurosurgeons and oncologists, who share a common interest in improving the quality of health care, via advancements in the understanding and implementation of medical imaging technology. Approximately 125 individuals will be invited to attend, with 30 speakers delivering papers and another 30 people presenting posters. Young investigators will especially be encouraged to apply and to attend. Paper selections will be made by peer-reviewing full 20 page submissions, and will be published in a proceedings that will be available at the meeting.

9818910
Duncan

The project is for a laboratory study of breaking waves. The breaker will be generated by side-bank instability technique. The goal is to understand the dynamics of breaking waves, and to assess effects of breaker wavelength, surfactants and wind on the sub-surface flow fields. Three areas of inquiry are proposed: (1) study the breaking mechanism over a wide range of breaker wavelenghts; (2) study effects of surfactants on breaking waves; (3) study effects of wind on breakers.

This Shared Instrumentation Grant is aimed at providing fast interactive graphics, computational power and memory resources, via a Silicon Graphics Onyx2 Infinite Reality visualization supercomputer to support the research of a group of investigators working on the processing, analysis and visualization of large, multi-dimensional medical images. All of the user projects are involved with the development and validation of computationally intensive, advanced computer vision, image analysis and image processing algorithms. The significant increases in processing, graphics and memory over the hardware currently available to this user group provided by the new system will speed algorithm execution time, visualization rendering time and avoid the use of sub- images and image sub-sampling currently necessary due to memory constraints. Such processing power will speed and enhance algorithm development and allow for interactivity while performing quantitative image analysis tasks for validation and clinical evaluation. The vastly enhanced graphics and computational power will allow dynamic 3D rendering and computational tasks previously infeasible. This system provides a single platform that can serve to graphically initialize and execute algorithms, visualize results, allow for correction of re- initialization, and finally, clinical interpretation and measurement. These projects involve computationally complex tasks such as optimizing multi-dimensional objectives and solving differential equations using finite element methods. The interactivity and graphics capabilities of the Onyx2, particularly in 3D surface and volume rendering, will greatly enhance the algorithm development and validation process. Two projects deal with cardiac image sequences and thus have need for the demanding graphics capabilities necessary for 2D and 3D rendering of temporal sequences with overlaid functional maps. Three other projects require 3D rendering of large brain volumes, with overlaid function or structural or structural surfaces. The Onyx2 would allow such rendering in an interactive fashion for algorithm evaluation and clinical interpretation, diagnosis and treatment planning.

Abstract
CTS-9876434
Kenneth T. Kiger
University of Maryland College Park


Air entrainment by a plunging jet is experienced in a wide range of natural (e.g., a waterfall) and technological (e.g., a chemical plant mixing vessel) flows. This flow has not, however, received attention as a basic flow module for such technological or natural flows.

The proposed study is one that takes clever advantage of existing equipment and experimental techniques to investigate the basic features of this class of flow fields. It is expected that the study will yield bench mark results.

The effectiveness of externam beam radiation treatment for prostate cancer is decreased due to a variety of uncertainties in the treatment setup, including the physical characteristics of the treatment beam, patient positioning issues, patient organ motion and operator non-reproducibility. The development and administration of a treatment plan using image- guided techniques to account for some of these uncertainties can positively impact its effectiveness. However, the use of these techniques to date has been limited by i.) a lack of accuracy, robustness and reproducibility in the registration of the high resolution 3D computed tomographic (3DCT) or simulator images acquired in a reference )or planning) frame to the highly noisy and blurry portal images, acquired in the treatment environment and ii.) the difficulty in measuring organ motion and relating it to these data. Thus, we first propose to develop a new automated, accurate, and robust system for performing bony anatomy- based 3DCT- to- multiple- (2D) portal image registration by simultaneously incorporating portal image segmentation. The system will rely on a combination of dense field (region-based) and sparse field (gradient/boundary features) information and will use information- theoretic metrics in an optimization framework to solve for the mapping parameters. This approach will be validated using a gold standard developed from serial CT acquisitions taken each week during the treatment. Next, we will study the relationship between setup variation due to bony structure movement and that due to organ motion in preparation for the design of a future complete system that can acquire treatment- environment images of the prostate using an ultrasound probe attached to an articulated arm in an external- skin- marker-based frame, and the 3DCT-to-multiple portal registration algorithm described above. The feasibility of using external markers to relate portal and ultrasound information will be a key part of this study as well. Finally, we will evaluate the utility of the 3DCT-to-multiple portal registration approach by applying it to the problem of quantitatively studying the sensitivity of errors in the delivery of an optimal dose distribution for a particular patient on a particular day to variations in patient- positioning-related setup for treatment plans of different complexity. These studies will help us understand the utility of more complex treatment plans and planning systems in today's health care environment.

Autism is a complex disorder of early onset, involving odd and repetitive movements, severe social disability, deficits in social cognition, and disruption of language. While the multiple signs and symptoms in autism suggest several different brain systems are likely involved in its pathobiology, it remains the fact that most efforts aimed at the analysis of neuroanatomical structure related to autism from (primarily Magnetic Resonance (MR) images have been limited to the measurement of rather gross features, such as overall brain size and cross sectional area, or measurements of the corpus callosum and cerebellar vermis, using fairly small samples. These limitations are in large part because, to date, manual and computer-assisted, semi-automated segmentation/measurement of neuroanatomy is a tedious, labor-intensive, and costly process, subject to human variability. The research proposed here is aimed at the further development of an image analysis strategy that will accurately, reproducibly, robustly and efficiently analyze neuroanatomical structure relevant to autism from 3D high resolution MR images. At the core of this effort are unique mathematical approaches to: i.) segment cortical structure using coupled differential equations to simultaneously locate the gray/white and gray/CSF surfaces; ii.) segment subcortical structure by adding shape and inter-structure spatial relationship priors to an approach that integrates boundary finding and region growing; and iii.) nonlinearly register regional neuroanatomical structure to create atlases and match them to segmented information for the purpose of labeling cortical gyri and guiding the subcortical segmentation process. A key feature of the approach is that the final labeling and measurement that is performed is done by carefully focusing on individual regions of the brain, one at a time. The accuracy and robustness of the individual algorithm components to imaging parameters, field inhomogeneities and noise will be demonstrated by validating segmentation, registration, labeling and measurement algorithm results from synthetic data created using an MR image simulator against gold standard source images. The utility of the image analysis strategy for deriving robust, accurate measures in a variety of cortical and subcortical brain regions relevant to autism will be evaluated by running the algorithm on a cohort of 30 normal control and 30 subjects having autism and/or related conditions, sampled from a large, well characterized and separately NIH-funded subject database.

PROPOSAL NO.: 0230646
PRINCIPAL INVESTIGATOR: Saltzman, William
INSTITUTION NAME: Yale University
TITLE: Enhancement of the Undergraduate Biomedical Engineering Curriculum at Yale University

Abstract

The project will reformulate the biomedical engineering undergraduate curriculum at Yale by emphasizing a) faculty involvement with students at all levels throughout the 4 year B.S. program; b) integration of presentation of knowledge through laboratory, lecture, and electronic media; and c) definition of selected areas of emphasis that represent strengths of the Yale research faculty and areas of industrial importance. We propose a core curriculum that presents the core science of BME as well as specialized tracks that provide advanced training in our areas of emphasis: biomedical imaging, biomechanics, and biomolecular engineering. We will implement this proposal in two phases. During the 12-month planning phase, we will offer two new courses (one each at the freshman and senior-levels) and implement new junior-level laboratory modules that incorporate concepts from molecular and cellular biology. We will also explore new concepts and develop a coordinated plan for the second phase, beyond the 12-month planning period, which will include reformulation of the core BME courses and the addition of new advanced level electives in our areas of emphasis.

0221335 Duncan
It has been observed that the rate of gas transfer across the air-sea interface correlates well with the mean squared slope of the high frequency surface waves. It has also been noted that the presence of surfactants, at concentrations that have almost no effect on surface tension, dramatically reduces the high frequency components of the wind wave spectrum. Wave tank studies of wind waves, and wind waves plus mechanically generated waves, with and without soluble surfactants, will seek to understand the mechanisms for this reduction in mean squared slope in the presence of surfactants, as well as the characteristics of high frequency waves. At low concentrations, it is hypothesized that the effects may result from the concentrating of surfactants at the wave crests, where capillary effects are typically largest. A variety of laboratory measurement techniques will be used. A cart carries measurement devices along the wave tank at speeds commensurate with the wave phase. Second Harmonic Generation techniques allow dynamic measurement of surfactant concentration. For these latter studies, the system will be at a fixed location and randomly sample the wind waves.

Description (provided by application): Magnetic resonance functional and spectroscopic imaging (fMRI, MRS) of the brain provides tremendous opportunities in the study and treatment of epilepsy. In neocortical epilepsy, where the epileptogenic region is highly variable in size, structure and location, deeper insight into the biochemical and functional characteristics of the region and surrounding tissue may provide critical data to assist the neurosurgeon and neurologist in localization and treatment. To fully utilize the multiple forms of information (MR and EEG), these data must be transformed into a common space and integrated into the intraoperative environment. We will develop high resolution MRS and fMRI at 4T and advanced analysis and integration methods to better define the epileptogenic tissue and surrounding regions, and enhance our understanding of the biochemical mechanisms underlying the dysfunction in neocortical epilepsy. We will validate these measurements against the gold standard of intracranial electrical recording. These goals will be achieved in this bioengineering research partnership (BRP) by bringing together six partners from 3 academic institutions (Yale (lead institution), Albert Einstein and the Univ. of Minnesota) and 1 industrial partner (Medtronics SNT) to carry out four integrated programs of scientific investigation and bioengineering development in the area of bioimaging and intervention: 1) development of high resolution fMRI and MRS at 4T for the study of epilepsy; 2) investigation with MRS of the relationship between neuronal damage or loss through the measurement of N-acetylaspartate (NAA), alterations in neurotransmitter metabolism through the measurement of gamma amino butyric acid (GABA) and glutamate, and abnormalities in electrical activity in the epileptogenic region and surrounding tissue; 3) investigation of the relationship between fMRI activation amplitude and the cognitive task, underlying cortical structure, cortical metabolic state, and physiology, and the impact of epilepsy on these factors; 4) development of integration methodologies for fusing multimodal structural and functional (image- and electrode-derived) information for the study and treatment of epilepsy. We anticipate that by developing and integrating these high resolution functional and metabolic images of neocortical epilepsy, we will improve our understanding and treatment of this difficult disorder. The first year's effort will include high resolution coil and integrated software platform design and development, as well as the acquisition of normal control studies. In years 2 through 5, the coils will be incorporated into the MR imaging platforms, the software platform will be fully developed and hypotheses related to the biochemical makeup of neocortical epileptogenic tissue and its relation to brain function will be evaluated.

"Slickensides" are surfaces of weakness formed in stiff clays as a result of large shear displacements - on the order of 50 mm to 250 mm - concentrated on a discrete surface of sliding. Platy clay particles become aligned parallel to the surface of sliding, resulting in the formation of a smooth surface with shear strength that is much lower than the strength of the adjacent clay through which the slickensided surface forms.

As a result of this low shear strength in comparison with the adjacent clay, slickensided rupture surfaces are likely loci of displacements during earthquakes. However, there have been no studies of the behavior of slickensided surfaces when subjected to the rapid cyclic loading that occurs during earthquakes. As a result, engineers must rely on assumption and judgment when estimating strengths for seismic deformation analyses, and these vary considerably among practicing engineers. For example, for one particular project in northern California, the difference of opinion regarding the shear strength that should be used resulted in recommendations for stabilization of the slopes that differed in cost by a factor of ten. At present, there is no way to determine whether one of these designs was dangerously inadequate, or the other was wasteful overkill.

The broader impacts of this research program include opportunities for undergraduate and graduate students to participate in the laboratory experiments at Virginia Tech, and for freshman through senior-level students to observe the centrifuge experiments at UC Davis, and to work as assistants in preparing the centrifuge models. Both UC Davis and Virginia Tech have very active programs to recruit minority students to participate in research through the Minority Opportunities for Research in Engineering at UC Davis, and the Office of Minority Engineering Programs and coalition with Historically Black Colleges and Universities at Virginia Tech. The project also involves an active collaboration with Dr. Binod Tiwari of Niigata University, who has considerable experience in the types of experiments involved and will spend time at Virginia Tech and UC Davis, which will help to establish closer relationships between researchers in Japan and in the United States.

DESCRIPTION (provided by applicant): Magnetic resonance (MR) imaging has been used successfully to find and quantify gross functional deficits and neuroanatomical changes related to a number of neuropsychiatric disorders. However, often these results have been found using pooled populations of subjects within the test groups and within grossly-defined regions of the brain. One area where MR brain imaging has recently begun to show promise is in the autism spectrum of disorders (ASD). These are developmental disorders that probably involve a host of brain regions in their pathobiology. Functional MR (fMRI) studies indicate that there may be differences in regional brain function in response to several different face recognition and social attribute discrimination tasks. Recent work in our laboratory and elsewhere, focused on functionally- indicated zones such as the amgydala and the fusiform gyrus, have now begun to find group-wise structural differences between normal controls and ASD subjects. While these initial indications are promising, it remains the case, as noted above, that studies have been limited in terms of their ability to localize information spatially and to delineate subgroups within ASD. Our proposed efforts are centered on developing unique mathematical approaches that consider functional and structural information together in order to develop more sensitive and spatially-specific measurements. These approaches will: i.) estimate clustered regions of functional (fMRI-derived) parameters that adhere to particular gray matter structural zones, ii.) segment & measure key anatomical structure using object-neighbor and intensity constraints and iii.) nonrigidly register structural images from different subjects using both feature and intensity information. We will first perform confirmatory studies on normal controls. Finally, to show the effectiveness of our new approaches for studying a specific neuropsychiatric disorder, we will test their ability to separate subgroups in the autism spectrum (autism, Asperger's, PDD NOS) using both functional and structural measures.

DESCRIPTION (provided by applicant): The International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) has been established as one of the premier meetings in medical imaging where cutting-edge ideas in medical image processing and analysis and image-guided intervention are presented. MICCAI 2005 will be organized in Palm Springs, California from October 26th to the 29th of that year, and will continue many of the ongoing traditions of the meeting, including single track oral sessions, equal emphasis on oral presentations and posters, peer-reviewed eight page papers, a high standard of papers (maintained through a 40 % acceptance rate), a CME accredited meeting, a day of tutorial sessions and student awards sponsored by industry. In addition, the meeting will include some newly proposed topic areas related to image-guided drug delivery. We expect approximately 600 attendees from the medical image processing, image analysis, visualization; image-guided intervention and medical robotics basic research communities as well as clinical investigators active in these areas. Furthermore, we will publish a two volume proceedings that will document the meeting. This proposal will support our ability to encourage student investigators to attend the meeting, will permit us to attract high quality plenary speakers and will allow us to insure the that the oral presentations will be of high quality by supporting the rental of audio/visual equipment.

[unreadable] DESCRIPTION (provided by applicant): More precisely delivering higher doses to the target volume at each treatment fraction, while limiting exposure to surrounding normal tissue, is the key goal for external beam prostate radiotherapy. Efforts to quantitatively assess this process have shown that a variety of uncertainties in the treatment setup including patient positioning, patient organ motion, characteristics of the treatment beam and operator variability issues make achieving this goal difficult. Previous efforts on this grant and by others have attempted to use the registration of planning day 3D computed tomographic images and intra- treatment megavolt portal images to try to account for some of these uncertainties, sometimes augmented by ultrasound imaging to try to estimate organ motion. While results are at times promising, these technologies are limited in their utility. Furthermore, while the ability to deliver more precisely- shaped plans has advanced significantly due to the advent of intensity modulated radiotherapy (IMRT) systems, the advanced development of image-guidance systems necessary to accurately deliver these more complex plans has been lacking. However, IMRT treatment systems with kilovolt (kV) 3D cone-beam CT (3DCBCT) imaging on the same platform have been developed, promising high quality imaging of both bone and soft tissue at each treatment fraction. We propose here to develop an advanced image analysis strategy that will permit the fully automatic nonrigid registration of planning day 3DCT images to 3DCBCT images acquired at each treatment day, while simultaneously and automatically segmenting the prostate, rectum and bladder in the treatment images. It is our view that this will ultimately facilitate the optimal, image-guided adaptation of an initial plan to each treatment day image, taking full advantage of these high resolution datasets. The approach will be validated using images formed from simulated deformations and evaluated using sets of patient images acquired at two different facilities over 6 weeks of treatment. [unreadable] [unreadable]

[unreadable] DESCRIPTION (provided by applicant): Accurate, comprehensive, quantification of regional left ventricular (LV) deformation is crucial for detection, risk stratification, and management of patients with ischemic heart disease. In this BRP, four partners from two academic institutions and industry will work together to develop and validate an integrated imaging/ image analysis system that will accurately, robustly and reproducibly quantify regional LV strain and strain rate from four-dimensional (3 spatial dimensions and time) echocardiographic (4DE) image sequences. Intramural displacement will be estimated using a phase-sensitive-correlation-based speckle tracking approach being developed by a team lead by Matthew O'Donnell at the University of Michigan. This information will be derived from radiofrequency (RF) signal data acquired from an ultrasound array, giving access to beam-formed acoustic data, using an approach being developed by a team lead by Jeff Powers, Ph.D. from Philips Medical Systems. Displacement information at the myocardial surface will be derived from B-mode images using a shape-tracking strategy being developed by a team lead by James Duncan, Ph.D. at Yale University, who will also serve as the PI of the BRP. Intramural and surface displacement information will be combined using an integrated segmentation/deformation estimator based on a biomechanical model (also being developed at Yale), to provide comprehensive, 4D estimates of myocardial strains, strain rates and material parameters. The approach will be validated/evaluated using phantoms and in vivo testing in collaboration with a team lead by Yale cardiologist Albert Sinusas, M.D. In vivo evaluation will include experiments based on acute and chronic canine models of ischemic injury for the quantification of transmurality of injury, subsequent LV remodeling and response to ACE inhibitor therapy. Clinical feasibility will be established in human studies. The 4DE-derived indices of LV deformation will be shown to be comparable to those derived from Magnetic Resonance (MR) tagging. [unreadable] [unreadable] [unreadable]

DESCRIPTION (provided by applicant): High resolution structural, functional and spectroscopic magnetic resonance (MR) imaging of the brain are powerful technologies for the study of epilepsy. Image-guided surgical resection has proven to be an effective treatment for many cases of medically intractable epilepsy. In neocortical, bilateral or otherwise diffuse epilepsy, however, localization of the epileptogenic region is more difficult and it is often impossible to surgically remove all of the potentially epileptogenic tissue due to its involvement in brain function. Responsive neurostimulation has emerged as a promising complementary technique for the treatment of epilepsy which can also serve as a powerful tool for interrogating brain function. We are pursuing a program of MR imaging research on the study of localization-related epilepsy and its response to two interventions: surgical resection and responsive neurostimulation. Key challenges include developing high field MR image acquisition technology, developing an improved understanding of the biochemical and functional signatures of the epileptogenic region and surrounding tissue, improved modeling of neurostimulation and the integration of this multimodal information into the planning and treatment environments. These goals will be achieved in this bioengineering research partnership (BRP) by bringing together six academic and two industrial partners to carry out four integrated programs of bioengineering development and scientific investigation: 1) advanced development of MR imaging technology (structural, functional, and spectroscopic) for the study and treatment of localization-related epilepsy, 2) development of image analysis strategies for image-guided planning, modeling, intervention, and evaluation, 3) multimodal investigation of alterations in the presence of epilepsy and their relationship to electrical connectivity as seen from intracranial EEG signals, and 4) investigation of functional and biochemical changes in the brain, as quantified by MR, in response to resection and neurostimulation therapy. These programs of research are designed to lead to improvement of our understanding and treatment of patients with localization-related epilepsy through the use of advanced integrated magnetic resonance imaging.

Applications of magnetic resonance (MR) techniques to research in the life sciences are growing rapidly. State-of-the-art heteronuclear MR spectroscopy (MRS) and multi-modal MR imaging (MRI) methodologies cultivated at the Magnetic Resonance Research Center (MRRC) at Yale have moved in vivo animal research into central roles in experimental neuroscience, addressing fundamental issues with far reaching implications for brain function. Since the formation of the Yale MRRC in the early in 1980s, the number of . horizontal-bore magnets for in vivo studies have multiplied three-fold in 2004. The present number of ' magnets for in vivo studies - three each for animals and humans - were needed to match the growing number of investigators across many disciplines - a majority of whom are supported by NINDS. The strength of the Yale MRRC has been, and still is, the dynamic interaction between rodent and human research. Active interplay between heteronuclear MRS and multi-modal MRI methods in rodents and humans have furthermore rapidly progressed. Because MR technology requires unwavering infrastructural support for state-of-the-art exploits to be successfully applied, long-term stability of Yale MRRC is contingent on sustained support. A program in "Quantitative Neuroscience with Magnetic Resonance (QNMR)" at Yale will support shared resources and facilities used by NINDS-funded investigators at Yale, and thereby generate greater productivity than would be possible via independent efforts. QNMR will consist of three research Cores - each dedicated to improving effectiveness of ongoing research based upon multimodal MRI, heteronuclear MRS, neurophysiology - and one service Core - designed for rapid data analysis, access, sharing, and backup using high-performance cluster of workstations. We expect that QNMR will promote a more cooperative and interactive research environment for neuroscientists who are utilizing MR technology at Yale, and will nurture new cross-disciplinary approaches in medicine, physiology, and neuroscience.

Intellectual Merit: The generation of droplets and their subsequent motion and evaporation in wind wave systems are important components of the processes of mass, heat and momentum transfer across the air-water interface. Measurements of the distribution and sizes of these droplets have been made in wave tanks and in the field. It is well known that the ocean surface is covered by surfactant mono-layers and that surfactants can have important effects on many free surface phenomena including the ejection of water droplets. The objective of the proposed laboratory experiments is to explore the mechanism of droplet formation by breaking waves and the subsequent motion and evaporation of these droplets with and without surfactants. Experiments with mechanically generated waves, wind waves and mechanically generated waves in the presence of wind will be carried out in clean water and water mixed with various concentrations of several soluble surfactants, and limited experiments in salt water. Cinematic Laser Induced Fluorescence (LIF) measurements of the streamwise and cross stream breaking wave pro le histories, shadowgraph movies of droplet ejections, subsequent motions and size distributions, and Particle Image Velocimetry (PIV) measurements of the 'flow field in the wave crest will be performed from an instrument carriage which will be set to move along the tank with the breaking wave crests or other significant features of the wave system. Measurements of the vertical distribution of droplets and droplet fluxes will also be carried out at fixed locations in the wave tank. Water surface proper-ties including surface pressure isotherms and surface viscoelastic properties will be measured using a Langmuir trough/longitudinal wave propagation device set up in a small tank and using water samples taken from the wave tank. Also, the maximum bubble pressure method will be used in the wave tank in order to determine the in-situ diffusion constants and surface tension. Finally, Second Harmonic Generation (SHG) measurements of instantaneous free surface surfactant concentration will be performed at a fixed location in the tank. All of the above measurements will be used to explore the physics of the droplet ejection, motion and evaporation process.

Broader Impacts: Since droplet production by breaking waves makes an important contribution to air-sea transfer processes, the proposed research will contribute to our understanding of the climate including important phenomena such as global climate change. The results of this study will be applicable to understanding engineering flows (such as flow around ships or in chemical processing) in which free surface and spray generation are involved. The study will contribute to the education of students in the sciences by supporting one graduate student, one undergraduate student and a part-time post doctoral researcher. The PI will also give approximately one talk or host one field visit to his laboratory each semester for local area high school students in order to introduce them to the subject area of this research. It is hoped that this may foster interest in pursuing oceanography in their university studies.

DESCRIPTION (provided by applicant): High resolution structural, functional and spectroscopic magnetic resonance (MR) imagings of the brain are powerful technologies for the study of epilepsy. Image-guided surgical resection has proven to be an effective treatment for many cases of medically intractable epilepsy. In neocortical, bilateral or otherwise diffuse epilepsy, however, localization of the epileptogenic region is more difficult and it is often impossible to surgically remove all of the potentially epileptogenic tissue due to its involvement in brain function. Responsive neurostimulation has emerged as a promising complementary technique for the treatment of epilepsy which can also serve as a powerful tool for interrogating brain function. We have been pursuing a program of MR imaging research on the study of localization related epilepsy and its response to two interventions: surgical resection and responsive neurostimulation. In the past 7 years of effort, we brought together internationally-recognized expertise in i.) neurosurgery/ neurology/electrophysiology, ii.) multiple disciplines of high field magnetic resonance, in particular, radiofrequency (rf) coil development, functional MRI, metabolic and spectroscopic MR and iii.) mathematical image analysis, via a group of six academic and two industrial partners. We developed and applied our methods to acquire and integrate multimodal magnetic resonance spectroscopic imaging (MRSI) and MRI information to enable better definition of neocortical epileptogenic substrates, enhance our understanding of the biochemical signatures underlying these substrates and differentiate these regions from normally functioning cortex. In this Competitive Revision, we propose to add a Yale PET imaging Partner to the BRP (lead by Dr. Richard Carson) and include high resolution FDG PET pre-interventional imaging using a high resolution HRRT scanner and perform validation against detailed electrical mapping of brain regions affected by seizure. Our goal is to integrate MRI, MRSI, and FDG-PET data to obtain higher specificity and sensitivity for localizing epileptogenic tissue and networks than any individual modality on its own. Relevance to Public Health: The understanding of the structure, function and metabolism of the normal and epileptogenic brain will add to the understanding of epilepsy in particular and neurodegenerative disease in general, ultimately helping to make appropriate interventional decisions. The ideas may lead to the definition of quantitative biomarkers that would help monitor progress in any one of several therapeutic interventions. PUBLIC HEALTH RELEVANCE: High resolution Magnetic Resonance structural and functional imaging (MRI), Magnetic Resonance Spectroscopic Imaging (MRSI) and Positron Emission Tomographic (PET) Imaging are powerful quantitative multidimensional imaging technologies that offer complimentary information about brain structure, function and metabolism. This information can be used to study longitudinal behavior of the brains of normal subjects and those with epilepsy in an integrated manner. As part of our existing BRP we have been developing, validating, and integrating quantitative information from multiple imaging modalities to study epilepsy with the goals of guiding surgery and tracking progress during therapeutic treatment. In the work proposed in this supplement we will add ultra high resolution quantitative FDG-PET to the armamentarium of biomarkers and assess its effectiveness in improving the sensitivity and specificity of identifying epileptogenic tissue and networks by imaging. We anticipate these developments will apply to a wide range of neurological disorders.

The Autism spectrum disorders (ASD) are devastating neurodevelopmental disorders with a rising prevalence in the United States that is currently estimated at 1 in 110. The cost of ASD to affected people, families, and society is enormous. Research aimed at uncovering the pathogenesis of this condition, and potentially leading to rational approaches to prevention or treatment, is of the greatest importance. We propose here to use multimodal neuroimaging to identify biomarkers of risk for autism. The discovery of reliable biomarkers will aid in the identification of individuals with ASD as well as those who will subsequently develop or are already developing subtle signs of ASD. In addition, biomarkers could serve to identify early biological risk factors for ASD, ultimately allowing us to achieve the goal of preventing the development of the disorder in people at risk or reducing the degree of severity in those affected. Structural MR image-derived biomarkers related to increased brain volume have revealed differences between ASD and typically-developing comparison participants. Functional (fMRI) differences have also been found (for instance using tasks related to face identity and facial expression as shown by our own group). Recent evidence suggests altered connectivity from both structural (diffusion-based) and functional measures in ASD. However, all of these alterations are quite subtle and the findings have been inconsistent. It is our hypothesis in our proposed work that the use of anatomic and diffusion information to guide and constrain the extraction of fMRI-based functional ASD-related subnetworks whose definition is based on both activation and connectivity maps will provide more sensitive and robust image-derived biomarkers for ASD. Thus, we focus our efforts on the development of a unique mathematical approach that will estimate three functionally-connected subnetworks in the brain related to ASD using a multi-view integration strategy to jointly consider fMRI time course strength/coherence and DTI-based structural paths. This approach will: i.) estimate voxels where activation is most likely in response to biological motion and compute model-enhanced activation regression parameters, ii.) estimate structurally-informed, functionally-connected subnetworks made up of regions of voxels that activate in response to biological motion and iii.) derive important ASD-related parameters of activation signal strength and connectivity that can be used as quantitative biomarkers. We will first apply the strategy to typically developing children and confirm the utility of our measures by illustrating that our approach can produce reliable biomarker information even in the presence of a small number of fMRI runs. Then, to show the effectiveness of the biomarkers that can be derived from our new approach, we will examine signal change and connectivity parameters derived from three ASD-related functional subnetworks that respond to our biological motion task. We will evaluate how well these measures can stratify three subject groups: children with ASD, unaffected siblings of children with ASD and typically developing children. We will then compare the results to three alternative strategies.

? DESCRIPTION (provided by applicant): This is the first competitive renewal of a currently funded T32 grant that provides post-doctoral training in multi-disciplinary multi-modality molecular and translational cardiovascular imaging for highly qualified fellows holding either a MD or/and PhD, in preparation for academic careers as independent investigators in the highly clinically relevant field of cardiovascular imaging. As imaging technology and molecular medicine advances, increasingly complex questions often arise requiring the convergence of perspectives from multiple disciplines. The future of cardiovascular imaging will most likely be practiced by integrated multidisciplinary teams with diverse areas of expertise. The goal of this research training program is to provide the necessary skills needed to work in this new multi-disciplinary investigative environment. Applicants will be recruited from both clinical and basic science departments, with particular attention paid to minority, disabled, and disadvantaged candidates. We will continue to select and enroll applicants in order to maintain support for 4 post-doctoral fellows each year, with an equal balance of physicians and scientists. Post-doctoral fellowship training will be 2-3 years in duration. There will be three primary research focuses in the post-doctoral training, 1) cardiovascular molecular imaging, 2) cardiovascular imaging technologies and analyses, and 3) translational cardiovascular imaging. The primary faculty for this program are from the Yale School of Engineering and Applied Sciences and from multiple departments within the Yale School of Medicine, including: Internal Medicine (Section of Cardiovascular Medicine), Diagnostic Radiology, Surgery, Anesthesiology, and Therapeutic Radiology. The faculty sponsors have been selected based on extramural support, research productivity, and commitment to multi-disciplinary training. Each trainee will be assigned both a basic science/engineering and clinical mentor. Trainee progress will be monitored by individual mentors, the trainee's advisory committee, and the Program Directors. Drs. Sinusas and Duncan will co-manage the program to assure a balanced and integrated experience in the relevant clinical and engineering sciences.

Funds are provided to support a series of laboratory experiments the objective of which is to explore the physics of the water surface response to rainfall and the relationship between the surface response and radar backscatter. The surface response includes splashes and ring waves generated by the spatial and temporal distributions of drop impacts in the rain zones. Experiments with various rain rates, rain drop diameters and spatial distributions of rain on the water surface will be carried out in a wind-wave tank (12.8 m long, 1.15 m wide with a water depth of 0.91 m) with and without wind and surfactants. Experiments with salt water will be performed in a smaller tank. Measurements will include surface profile histories at the center plane of the rain field using a cinematic laser induced fluorescence technique, rain and secondary drop size and trajectories using a cinematic shadowgraph technique. Additional measurements of the turbulent flow fields several centimeters below the mean free surface will be made using Particle Image Velocimetry (PIV). Measurements of radar backscattering from the water surface in and around rain zones will be made with a pulsed ultra-wide band radar system. In cases with surfactants, water surface properties including surface pressure isotherms and surface viscoelasticity will be measured using a Langmuir trough/longitudinal wave propagation device and a maximum bubble pressure measuring device will be used to determine the in-situ diffusion constants and surface tension.

Air-sea transfer of mass, momentum, energy and heat are important components of the dynamical system controlling the local and global climate. Since rainfall over the ocean makes an important contribution to these transfer processes, the results of this project will inform understanding of climate variability. The radar measurements will provide understanding of the information content of remotely sensed measurements of the sea surface using microwaves.

DESCRIPTION (provided by applicant): As imaging technology and molecular medicine advances, more complex questions arise often requiring the convergence of perspectives from multiple disciplines. The future of cardiovascular imaging will most likely be practiced by integrated multidisciplinary teams with diverse expertise. The goal of this research training program is to provide multi-disciplinary post-doctoral multi-modality training in molecular and translational cardiovascular imaging for highly qualified fellows holding either a MD or/and PhD, in preparation for academic careers as independent investigators in the highly clinically relevant field of cardiovascular imaging. Applications will be encouraged from both clinical and basic science departments, with particular attention to the recruitment of minority, disabled, and disadvantaged candidates. We anticipate enrollment of 4 post-doctoral applicants each year into the programs, with an equal balance between physicians and scientists. Post-doctoral fellowship training will be 2-3 years in duration. There will be three primary research focuses in the post-doctoral training, 1) cardiovascular molecular imaging, 2) cardiovascular imaging technologies and analyses, and 3) translational cardiovascular imaging. The primary faculty for this program are from the Yale School of Engineering and Applied Sciences and from multiple departments within the Yale School of Medicine, including: Internal Medicine (Section of Cardiovascular Medicine), Diagnostic Radiology, Surgery, Anesthesiology, and Therapeutic Radiology. The sponsoring faculty was selected based on extramural support, research productivity, and commitment to multi-disciplinary training. Trainee progress will be monitored by individual mentors, the trainee's advisory committee, and the Program Directors. Drs. Sinusas and Duncan will co-manage the program to assure a balance and integration of the training of applicants in the relevant clinical and engineering sciences.

DESCRIPTION (provided by applicant): Stress echocardiography is a clinically established, cost-effective technique for detecting and characterizing coronary artery disease by imaging the left ventricle (LV) of the heart at rest and then after either exercise or pharmacologically-induce stress to reveal ischemia. However, acquisitions are heavily operator dependent, two-dimensional (2D), and interpretation is generally based on qualitative assessment. While a variety of quantitative 2D approaches have been proposed in the research literature, none have been shown to be superior to the still highly variable qualitative visual comparison of rest/stress echocardiographic image sequences for detecting ischemic disease. Here, we propose that the way forward must focus on a new computational image analysis paradigm for quantitative 4D (three spatial dimensions plus time) stress echocardiography. Our strategy integrates information derived from both radiofrequency (RF) and B-mode echocardiographic images acquired using a matrix array probe. The integrated analysis system will yield accurate and robust measures of strain and strain rate - at rest, stress and differentially between rest and stress - that will identify myocardial tissue at-risk after dobutamine-induced stress. This work wil involve the development of novel (1) phase-sensitive, correlation-based RF ultrasound speckle tracking to estimate mid-wall displacements, (2) ma- chine learning techniques to localize the LV bounding surfaces and their displacements from B-mode data, (3) a meshless integration approach based on radial basis functions (RBFs) and Bayesian reasoning/sparse coding to estimate dense spatiotemporal parameters of strain and strain rate and (4) non-rigid registration of rest and stress image sequences to develop unique, 3D differential deformation parameters. The quantitative approach will be validated with implanted sonomicrometers and microsphere-derived flows using an acute canine model of stenosis. The ability of deformation and differential deformation derived from 4D stress echocardiography to detect new myocardial tissue at-risk in the presence of existing infarction will then be determined in a hybrid acute/chronic canine model of infarction with superimposed ischemia. The technique will be translated to humans and evaluated by measuring the reproducibility of our deformation and differential deformation parameters in a small cohort of subjects. Three main collaborators will team on this work. A group led by Matthew O'Donnell from the University of Washington will develop the RF-based speckle tracking methods. An image analysis group led by the PI James Duncan at Yale University will develop methods for segmentation, shape tracking, dense displacement integration and strain computation. A cardiology/physiology group under Dr. Albert Sinusas at Yale will perform the acute and chronic canine studies and the human stress echo studies. A consultant from Philips Medical Systems will work with the entire team to bridge the ultrasound image acquisition technology.

Project Summary Autism spectrum disorder (ASD) is a developmental disorder characterized by impairment of social interaction and communication, as well as repetitive behaviors, with severity ranging from mild to signi?cantly disabling. The prevalence in the United States is rising (currently about 1 in 68 children) and the associated costs are great. In our most recent previous efforts on this project, we have initiated development of a graph-based, Bayesian neuroimage analysis framework and have used it to characterize brain pathology in ASD and identify abnormal functional subnetworks from groupwise data. Key results demonstrated clear differences in task- based functional brain networks between ASD and typically developing control (TDC) groups associated with the perception of biological motion. While our efforts (and those of others) are important for characterizing ASD, advances in the characterization of response to therapy with imaging are crucial for improved understanding, and ultimately personalization, of these therapies. Thus, we propose to put forth a bold new direction: to further develop our analysis methodology and study these task-based subnetworks, now with the goal of characterizing individuals in terms of their predicted response to treatment. We will focus on Pivotal Response Treatment (PRT), an intensive behavioral therapy for children with ASD that improves social communication skills. We ?rst propose to fully develop our uni?ed Bayesian framework to detect both hyper- and hypo-synchronous functional subnetworks within whole-brain, groupwise, task-based fMRI data on a large training dataset of ASD and TDC subjects. We will identify dense subgraphs (communities) that exhibit group differences in functional synchrony between ASD and TDC groups. The groupwise subnetworks will then be mapped to single subject, task-based fMRI data acquired from a cohort of ASD subjects treated with PRT. For each subject, imaging biomarkers based on activation signal strength and functional connectivity will be derived for regions within each hyper- and hypo- synchronous subnetwork at both baseline and after 16 weeks of therapy. Using a random forest regression strategy, we will use a combination of biomarkers from the baseline data to predict response to PRT (using change in Social Responsiveness Scale, 2nd Edition as the primary clinical outcome measure). In addition, we will use a combination of biomarkers from baseline and 16 weeks to predict treatment persistence at 32 weeks. We will compare the prediction capability of our new approach using task-based fMRI to a set of biomarkers with regions identi?ed from groupwise analysis of resting state fMRI (rsfMRI) networks found from the same training subjects noted above using an alternative state-of-the-art method. We will also develop methods to examine potential metabolic alterations in networks using magnetic resonance spectroscopy (MRS) of GABA and glutamate (the major excitatory and inhibitory neurotransmitters) to explore possible biochemical differences associated with ASD, changes in response to PRT and the use of this information as additional imaging biomarkers.

Project Summary/Abstract Liver cancer is the second most common cause of cancer-related death worldwide and is likely to grow even more in the next decade given the epidemic levels of hepatitis B and C and the emergence of non-alcoholic steatohepatitis (NASH) due to obesity in the US. Most liver cancer patients present with disease that cannot be treated surgically. Minimally invasive, catheter-based, intra-arterial therapies such as TACE (transarterial chemoembolization) have become the mainstay therapy and are included in all treatment guidelines because of their ability to achieve local tumor control and extend survival. TACE overcomes the problem of chemoresistance in cancer cells by delivering high dose chemotherapy through image guidance and embolization of the tumor feeding blood vessel. TACE most commonly uses an oily medium (Lipiodol) as a radiopaque drug delivery mate- rial by creating an emulsion between drugs and oil. The recent introduction of drug-eluting bead (DEB) technol- ogy provides an opportunity to achieve the goal of controlled and sustainable drug release to tumors, which was not possible with oily TACE. Although TACE clearly improves patient survival, limitations still exist ? speci?cally, incomplete treatment and tumor recurrence ? attributed to the stimulation of angiogenesis. Most of these issues can be addressed with a greater understanding of the tumor microenvironment, in particular the relationship that exists between hypoxia, acidosis and angiogenesis. In fact, the development of imaging biomarkers re?ecting changes within the tumor microenvironment is increasingly being pursued to individualize cancer therapies and increase their potency. Yet, our ability to characterize the tumor microenvironment using current imaging tech- nology is extremely limited. TACE has had to rely on 2D X-ray angiography until recently when the emergence of intra-procedural dual phase cone beam CT (DP-CBCT) contributed signi?cantly to improving tumor visualization, microcatheter guidance, and treatment endpoint. It is precisely through the longstanding close partnership be- tween Philips, Johns Hopkins and now Yale that this technology was optimized and became broadly accepted as the new standard of practice for TACE, demonstrating the prompt successful translation of research ?ndings to clinical practice. However, the targeting of tumors and assessment of outcomes continues to be limited, relying on qualitative/semi-quantitative enhancement patterns from DP-CBCT and single parameter MR images. The unique partnership between Yale & Philips provides innovative technology that will directly enhance the role of image-guided intervention and address this unmet need by quantitatively characterizing the tumor microenvi- ronment and tumor tissue composition in order to maximize treatment potency and improve outcomes. We will integrate advanced, multiparameter MR with active CBCT imaging and create valuable biomarkers derived from novel machine learning methods for image and data analysis. By providing essential, quantitative information, drug delivery to tumors can be maximized because it will be based on inherent tumor properties. In the same way, the assessment of therapy will be much more precise and therefore useful to identify responders.

The air-sea boundary layer generated by rainfall over the ocean plays an important role
in the transfer of mass, heat, energy and momentum across the air-water interface. This air-sea boundary layer in the rain field includes secondary droplets, stalks, crowns and surface waves that are generated by the impacts of rain drops. Experiments with various rain rates, rain drop diameters and spatial distributions of rain on the water surface will be carried out in two different facilities (rain tower and wind-wave tank) in a laboratory under various conditions of wind and waves. Since rainfall over the ocean makes an important contribution to air-sea transfer processes that affect weather and climate, the research will have a broad impact. The project will contribute to the education of students in the sciences by supporting one graduate student and two undergraduate students. The PIs will also introduce the research to undergraduate classes and give approximately one talk or host one field visit to their research laboratory for local area high school students each semester in order to introduce them to the subject area of this research. It is hoped that this may foster interest in pursuing oceanography in their university studies. Also, results from this research will be posted on the web and photographs and videos and will be submitted to the Gallery of Fluid Motion of the American Physical Society (APS). Winners of this Gallery are published and posted on the web of the APS Division of Fluid Dynamics.


Measurements will include the profile histories of stalks, crowns and surface waves at the center plane of the rain field using a cinematic laser induced fluorescence technique, the sizes and trajectories of both rain drops and secondary droplets using a holographic technique, and radar backscattering from the water surface in the rain zones using a pulsed ultra-wide band radar system. The goal of the laboratory experiments is to investigate the effects of wind and waves on the flow properties and mixing characteristics of the air- sea boundary layer in a rain field. The radar backscattering signatures in response to the changes of the air-sea boundary layer in the rain field will be investigated as well. Efforts to model air-sea transfer process are critically dependent on humidity and evaporation which are in turn greatly enhanced by rainfall. By using the physics learned from the proposed experiments, this study aims to produce important advancement in knowledge and understanding of how wind and waves affect the marine-atmospheric boundary layer in a rain field and make an important contribution that numerical modelers will find useful. Finally, advances in techniques for the measurement of rain impact on the water surface will result from the proposed work and will be applicable to similar measurements in other fields related to fluid mechanics.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Summary Myocardial infarction (MI) causes regional dysfunction placing remote areas of the heart at a mechanical disadvantage resulting in long term adverse left ventricular (LV) remodeling and complicating congestive heart failure (CHF), which remains a leading cause of morbidity and death in the Western world. The current project will focus on evaluating and modulating the critical balance of matrix metalloproteinases (MMP) and tissue inhibitors of matrix metalloproteinases (TIMP) which is known to play an important role during remodeling post-MI. A number of pharmacological and surgical therapies have been proposed to limit post-MI remodeling, including; the intramyocardial administration of biomaterials. These polymeric therapies have demonstrated mixed success in reducing infarct size, increasing angiogenesis, improving regional function, and limiting post-MI remodeling in pre-clinical studies, and have been recently translated to patients. We have established novel noninvasive hybrid SPECT/CT approaches for evaluation of changes in regional myocardial perfusion, angiogenesis, MMP activation, along with echocardiographic imaging approaches for quantitative evaluation of regional myocardial strain and ventricular remodeling. The current multi-PI proposal will focus on; 1) development of a novel imageable MMP-responsive theranostic hydrogel for post-MI therapy and tracking delivery and serial evaluation of hydrogel retention, 2) application of multimodality non-invasive anatomical, physiological and molecular imaging approaches for directing and evaluating the percutaneous intramyocardial delivery of MMP-responsive hydrogels, and 3) the evaluation of the mechanisms by which these injectable MMP-responsive hydrogels that release local TIMP alter myocardial mechanics and limit post- MI remodeling. We hypothesize that the intramyocardial delivery of MMP-responsive hydrogels that locally release TIMP-3 early post-MI will result in; 1) modulation of the local MMP-TIMP balance and the inflammatory response within the MI, 2) alteration of regional and global myocardial mechanics, 3) improvement in angiogenesis and myocardial perfusion, and 4) a reduction of adverse global post-MI remodeling. We also hypothesize that our multimodality imaging approach will facilitate optimal delivery of a theranostic hydrogel, and allow tracking of critical anatomical, physiological and molecular events, along with therapeutic efficacy. Accordingly, we propose to specifically: 1) development an imageable MMP-responsive theranostic hydrogels for post-MI therapy, 2) apply multimodality imaging to direct and evaluate percutaneous image-guided intramyocardial delivery these hydrogels using clinically relevant porcine models of post-MI remodeling, and 3) evaluate the mechanisms of therapeutic efficacy. The diagnostic and therapeutic approaches developed in the proposed project will be directly translatable to the management of patients following MI.

This is a combined experimental and numerical study of droplet generation by breaking wind waves in the presence of surfactants and salt water. Measurements of the average spatial distribution and diameters of droplets in wind wave systems have been made in wave tanks and in the field, but the connection between the dynamics of wave breaking and the generation of droplets is unclear as are the effects of water salinity and surfactants on these generation processes. By combining experimental measurements of the breakers and droplets with numerical simulations of the same breaking events, the strengths of each research method will be used synergistically to explore the physics of the droplet generation mechanisms in breaking waves. Air-sea transfer of mass, momentum, energy and heat is an important component of the dynamical system controlling the weather and global climate, and droplet generation by breaking waves makes an important contribution to these transfer processes. The results of this study will be useful for numerical models of the system. They will also be applicable to understanding engineering flows in which free surface and spray generation are involved, for example in chemical engineering flows. Finally, the droplet diameter and trajectory measurement system used in the proposed study is thought to be adaptable for use as a field measurement system. This project will also contribute to the education of students by fully supporting two graduate students, a half-time postdoctoral researcher and an undergraduate student during the summer months. At the University of Maryland, the PI will organize a week-long summer school on nonlinear water waves. He will also host students and teachers from a middle school program called ThinkStem in visits to his laboratory. At the University of Minnesota, the PI will organize and outreach program for high school students from Native American communities. The program consists of a summer camp aimed at enhancing the students' understanding of the environmental fluid flow processes at the water surfaces in the Great Lakes.

The experiments will provide, among other quantities, highly resolved measurements of the temporal evolution of the breaking wave profiles and similarly resolved measurements of the size and motions of droplets with diameters down to 100 microns and smaller, while the simulations will compute the evolution of the air and water flow fields with state-of-the-art spatial resolution. In both the experiments and simulations, the breakers will be generated mechanically with highly repeatable dispersively focused wave packets and augmented by wind. By introducing soluble surfactants and salt into the water in the experiments and simulations, their effects on wave breaking and droplet generation will be explored. Both the experiments and simulations will identify the time, location and characteristics of the important droplet generation events during the breaking process. The experimental measurements of the droplet generation events will be used to provide data and focus for the numerical simulations and provide data for droplets smaller than the simulations can compute. The simulations will explore the physical processes that generate these droplet ejection events and develop and test sub-grid models for the generation of the smallest droplets. The effects of salinity and surfactants on each droplet generation process will be examined. The knowledge of the effects of salinity and surfactants on the droplet production at these experimental/numerical scales will be used to estimate droplet production at some field-scale conditions.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Project Summary/Abstract Ischemic heart disease remains the top cause of death in the world. Acute myocardial infarction (MI) causes regional dysfunction which places remote areas of the heart at a mechanical disadvantage resulting in long term adverse left ventricular (LV) remodeling and complicating congestive heart failure (CHF). The course of MI and post-MI remodeling is complex and includes vascular and myocellular injury, acute and chronic inflammation, alterations of the extracellular matrix (ECM) and angiogenesis. Stress echocardiography is a clinically established, cost-effective technique for detecting and characterizing coronary artery disease and myocardial injury by imaging the LV at rest and after either exercise or pharmacologically-induced stress to reveal ischemia and/or scar. In our previous effort on this project, we developed quantitative 3D differential deformation measures for stress echocardiography from 4DE-derived LV strain maps taken at rest and after dobutamine stress. These measures can localize and quantify the extent and severity of LV myocardial injury and reveal ischemic regions. We now propose that improved versions of these same measures can be used for both targeting of therapy and outcomes assessment in the treatment of adverse local myocardial remodeling following MI. We choose a particular up and coming therapeutic strategy as an exemplar: the local delivery of injectable hydrogels within the MI region that are intended to alter the biomechanical properties of the LV myocardium, as well as inflammation, and thereby help to minimize adverse remodeling. Our new, robust approach for estimating improved dense displacement and differential deformation measures is based on an innovative data-driven, deep feed-forward, neural network architecture that employs domain adaptation between data from labeled, carefully-constructed synthetic models of physiology and echocardiographic image formation (i.e. with ground truth), and data from unlabeled noisy in vivo porcine or human echocardiography (missing or very limited ground truth). Training is based on tens of thousands of four-dimensional (4D) image-derived patches from these two domains, initially based on displacements derived separately from shape-based processing of conventional B-mode data and block-mode, speckle-tracked processing of raw radio-frequency (RF) data; and later based on learning directly from B-mode and RF image intensity information. After non-rigid registration of rest and stress 4DE image sequences, quantitative 4D differential deformation parameters will be derived from porcine and human echocardiographic test data. These parameters will be derived at baseline, and at several timepoints after delivery of injectable hydrogels into the MI region. The ability of the differential deformation parameters derived from 4D stress echocardiography to guide local delivery of injectable hydrogels in a MI region and assess/predict outcomes will then be determined in a hybrid acute/chronic porcine model of MI and post-MI remodeling. The technique will be translated to humans and evaluated by measuring the reproducibility and the relationship to remodeling of our new robust, deep learning-based differential deformation parameters in a small cohort of subjects.

This is the revision of a second competitive renewal of a currently funded T32 grant that received a very favorable initial review. This grant provides post-doctoral training in multi-disciplinary multi-modality molecular and translational cardiovascular imaging for highly qualified fellows holding either a MD or/and PhD, in preparation for academic careers as independent investigators in the highly clinically relevant field of cardiovascular imaging and image guided intervention. As imaging technology and molecular medicine advances, increasingly complex questions often arise requiring the convergence of perspectives from multiple disciplines. The future of cardiovascular imaging will most likely be practiced by integrated multidisciplinary teams with diverse areas of expertise. The goal of this research training program is to provide the necessary skills needed to work in this new multi-disciplinary investigative environment. Applicants will be recruited from both clinical and basic science departments, with attention paid to recruitment of female, minority, disabled, and disadvantaged candidates. We will continue to select and enroll applicants to maintain support for 6 post- doctoral fellows each year, with an equal balance of physicians and scientists. We have added a new pathway that focuses on image-guided therapy, and have expanded the image analysis pathway to include specific training in machine and deep learning provided by the recently established Translational Image Analysis and Machine Learning (TIAML) Center and partnering with data science center at the university. Post-doctoral fellowship training will be 2-3 years in duration. There will be four primary research focuses in the post-doctoral training, 1) cardiovascular molecular imaging, 2) cardiovascular imaging technologies and analyses, 3) image guided therapy, and 4) translational cardiovascular imaging. The primary faculty for this program are from the Department of Biomedical Engineering of the Yale School of Engineering and Applied Sciences and from multiple departments within the Yale School of Medicine, including: Internal Medicine (Section of Cardiovascular Medicine), Radiology & Biomedical Imaging, and Surgery. The faculty sponsors have been selected based on extramural support, research productivity, and commitment to multi-disciplinary training. Each trainee will be assigned a primary preceptor in the basic sciences and engineering or clinical research and co-mentor with complementary expertise. Trainee progress will be monitored by individual mentors, the trainee?s advisory committee, and the Program Directors. Drs. Sinusas and Duncan will co-manage the program to assure a balanced and integrated experience in the relevant clinical and engineering sciences. We have also established a more formal relationship between our T32 training program and the Vascular Biology T32 training program within the section of Cardiovascular Medicine and will establish an annual research retreat with fellow presentations of research in progress. This retreat should help to better integrate basic, translational and clinical research within the Section of Cardiology and other participating departments.