Imaging, Visualization and Simulation
Friday, June 17, 2011
In technical, financial, medical, and social spheres, handling massive data sets has become a major focus of research and innovation. Across these diverse sectors, the goals are to improve accuracy, reliability, and efficiency and to enhance understanding, processing, and analysis of complex information.
Progress in this area is related to advances in imaging, visualization, and simulation. Available techniques continue to improve in their resolution, temporal and spatial flexibility, and signal character. Innovations in image processing, visualization, and simulation of multi-dimensional and multi-modal data further augment our ability to create accurate, high-resolution images and real-time video. They also enable broader access to sophisticated analytical tools in places where they matter most, such as in the healthcare industry to improve surgical intervention and clinical diagnosis. In parallel, these advances are leading to enhanced medical education and training modules.
This conference will bring together specialists from many areas of expertise to present novel ideas, solutions, and applications that will advance our ability to manage massive data sets. Presentations will feature cutting-edge concepts and tools for data processing, integration, analysis, and simulation in areas of clinical and research technology, from modeling protein dynamics with atomic-level resolution to 4-dimensional cardiac imaging.
Andrew F. Laine, DSc
Jacqueline Merrill, RN, MPH, DNSc
Vincent P. Tomaselli, PhD
Center for Advanced Information Management, Columbia University
For a complete list of Sponsors, view the Sponsors tab.
Photo Credit & Description
Event image courtesy of D. E. Shaw Research. Snapshots of the folding and unfolding of a protein, obtained from a simulation of unprecedented length performed on the special-purpose supercomputer Anton. Transitions are observed between a disordered "unfolded" state (red and gray) and an ordered "folded" state (blue).
*Presentation times are subject to change.
Registration and Continental Breakfast
Technology and Economic Development
The Intersection of Imaging, Visualization, and Simulation in Surgery
Quantitative Evaluation of 4D Myocardial Strain Measures via Optical Flow with a Finite Element Field Model Fitted to Sonomicrometry
Visual Analytics for Evidence-Based Medicine
Clinical Application of Multidimensional Visualization in Cardiac Imaging
Optimizing "Blended Learning" for Bedside Ultrasound Training: Incorporation of e-Learning, Simulation, and other Multimedia Tools
In Silico Public Health: What Can Simulation Modeling Tell Us That We Don't Already Know?
An Animated Multivariate Visualization of Clinical and Physiological Data in a Neonatal ICU
Medical Imaging Tools from Concept to Clinical Practice: Validation and Investment Challenges
Poster Session and Networking Reception
Andrew F. Laine, DSc
Dr. Laine received his D.Sc. degree from Washington University (St. Louis) School of Engineering and Applied Science in Computer Science in 1989 and BS degree from Cornell University. He was a Professor in the Department of Computer and Information Sciences and Engineering at the University of Florida (Gainesville) from 1990-1997. He currently directs the Heffner Biomedical Imaging Laboratory in the Department of Biomedical Engineering and serves as Vice Chair. He holds a joint appointment in the Department of Radiology. Andrew is also an affiliated faculty member in the Department of Biomedical Informatics (College of Physicians and Surgeons) where he serves as liaison for imaging informatics as well as imaging specialist for the Center for Advanced Information Management. His research interests include methods of multi-resolution analysis applied to problems in medical imaging, image processing, computer-aided diagnosis, pattern recognition, and applied mathematics. He is a Fellow of the IEEE and Fellow of American Institute of Medical and Biological Engineers (AIMBE).
Jacqueline Merrill, RN, MPH, DNSc
Dr. Merrill is a public health nurse and associate research scientist in the Department of Biomedical Informatics. She holds a doctorate in nursing science with a concentration in public health informatics. As a result of her experience in clinical care, public health practice, and policy research, she has a broad knowledge of healthcare issues and particular understanding of health information technology as it relates to public health systems. Her current research takes a complex adaptive systems approach toward public health management using network analysis to improve performance in local health departments. Jackie's public health experience includes six years with the New York City Department of Health and Mental Hygiene in the Bureau of School Health and the Office of Nursing and Quality Improvement. She is former project director at the Center for Health Policy at the School of Nursing, Columbia University. On July 1 she will return to the School of Nursing as an Associate Professor of Clinical Nursing with an interdisciplinary appointment in Biomedical Informatics.
Vincent P. Tomaselli, PhD
Center for Advanced Information Management, Columbia University
Dr. Tomaselli is currently Deputy Director of the Center for Advanced Information Management at Columbia University. Prior to joining Columbia, he was Deputy Director for Business Development and Operations at the Center for Advanced Technology in Ultrafast Photonics at the City University of New York (1994-2001). From 1990 to 1994, he was a Senior Project Scientist at Woodward-Clyde Consultants, an environmental sciences firm where he oversaw work on database management and health effects of low frequency electromagnetic fields. From 1988 to 1990, he was Director of the Center for Photonics and Imaging Science, and Professor of Electrical Engineering and Physics at Fairleigh Dickinson University (FDU), College of Science and Engineering. Prior to that, he served as Assistant Dean for Research and Graduate Studies, and University Grants Administrator. While at FDU, he was a consultant to Allied-Signal Corporation (now Honeywell), Guidance Systems Division, and a Visiting Research Scientist at the Institute for Chemistry, University of Genoa, Italy for which he received a Fulbright Award. Earlier he was a Research Physicist at the Uniroyal Research Center, Polymer Physics Department. He has a PhD in physics from New York University where his thesis work was in experimental solid-state biophysics.
David E. Shaw, PhD
D.E. Shaw Research
Dr. Shaw serves as chief scientist of D.E. Shaw Research and as a senior research fellow at the Center for Computational Biology and Bioinformatics at Columbia University. He received his Ph.D. from Stanford University in 1980, served on the faculty of the Computer Science Department at Columbia until 1986, and founded the D.E. Shaw group in 1988. Since 2001, Dr. Shaw has been involved in hands-on research in the field of computational biochemistry. His lab is currently involved in the development of new algorithms and machine architectures for high-speed biomolecular simulations, and in the application of such simulations to basic scientific research and computer-assisted drug design. Dr. Shaw was appointed to the President's Council of Advisors on Science and Technology by President Clinton in 1994 and again by President Obama in 2009. He is a fellow of the American Academy of Arts and Sciences and of the American Association for the Advancement of Science, a member of the Computer Science and Telecommunications Board of the National Academies, and a winner of the ACM Gordon Bell Prize.
Mostafa Analoui, PhD
The Livingston Group
Dr. Analoui is Head of Healthcare and Life Sciences at The Livingston Group (New York, NY) and Chairman and CEO of Cense Biosciences, Inc. Previously he was the Senior Director at Pfizer Global Research and Development. He is also adjunct Professor of Oral Pathology, Medicine and Radiology at Indiana University. Dr. Analoui is actively involved in investment, management and scientific/business development of nanotechnology, drug discovery/development, diagnostic imaging, and global strategies. While at Pfizer, he was the Site Head for Global Clinical Technology in Groton and New London, a division focusing on emerging technologies for development and validation of biomarkers and diagnostics for drug development. Prior to joining Pfizer, Dr. Analoui was the Director of Oral and Maxillofacial Imaging Research, Associate Professor of Radiology at Indiana University, and Associate Professor of Biomedical Engineering and Electrical & Comp Engineering at Purdue University. He was also President and CEO of Therametric Technology Inc. He has received his Ph.D. from Purdue University, followed by Post-Doctoral Fellowship at IBM TJ Watson Research Center in NY. In addition to industry leadership in biomedical and technology fields, he consults and lectures in US, Europe and Asia. He has also served on various scientific, regulatory, and business advisory committees and boards, including NIH, NSF, PhRMA, NASA, and OECD. Dr. Analoui has authored over 130 publications, including journal articles, book chapters and technical reports. He is senior member of IEEE, SPIE, and RSNA. He currently serves as board member of VirtualScopics (Nasdaq: VSCP), Calando Pharmaceutical (Nasdaq: ARWR), BEACON (Biomedical Engineering Alliance and Consortium) and NanoBusiness Alliance.
Yanick Beaulieu, MD
Hôpital du Sacré-Coeur de Montréal, University of Montreal
Dr. Beaulieu is Assistant Professor in the Department of Medicine, Director of the Bedside Ultrasound Curriculum at the Hôpital du Sacré-Coeur de Montréal, and Director of Ultrasound Education at CAE Healthcare. CAE is a leading provider of simulation and modeling technology to improve safety and efficiency in healthcare. Yanick held a Critical Care Medicine Fellowship (2002-04) and a Cardiology/Echocardiography Fellowship (1999-2002) at the University of Pittsburgh Medical Center. A graduate of McGill University Medical School, he specialized in internal medicine at the Université de Montréal (1996-99). He has received many awards, including Professor of the Year, Hôpital du Sacré-Coeur de Montréal (2004-5); Critical Care Fellow of the Year (University of Pittsburgh, 2002-3); Research Bursary from the Royal College of Physicians of Canada (2002-3); Dean's Honour List in Cardiology (2002); McLaughlin Award and Bursary for Academic Excellence (University of Montreal, 2002); Quebec's Cardiology Association Award and Bursary for Academic Excellence (2002); and a Fellowship Bursary for Academic Excellence in Cardiology (Sacred-Heart Hospital, Montreal, QC). Dr. Beaulieu has published multiple articles and book chapters on the topic of bedside ultrasound in the intensive care unit and produced a full curriculum that he is teaching to intensivists and other critical care specialists at a national and international level.
Dennis L. Fowler, MD, MPH
Dr. Fowler completed a Surgical Endoscopy Fellowship in 1980 at Massachusetts General Hospital, where he focused on advancing and teaching minimally invasive surgery, after having previously attended medical school and completed a general surgery residency in Kansas City. He joined the minimal access field just as technology entered clinical practice in 1990, and was recruited by Columbia in 2000 from his directorship of the Allegheny Center for Laparoscopic and Minimally Invasive Surgery in Pittsburgh. At Columbia, he directed the Minimal Access Surgery Center (MASC) from 2000-2008, during which time he served as Chief of the Division of General Surgery at Weill Cornell Medical College (2002-2004) and Vice President and Medical Director for Perioperative Services at New York-Presbyterian/Columbia (2004-2008). While Director of Columbia's MASC, Dennis pioneered the field of laparoscopy as an innovator of minimal access surgery devices and procedures. His work with the MASC involved surgical skills training and assessment for Department of Surgery residents, as well as licensed practitioners. He has published extensively on the topics of minimally invasive surgery, technology development, and surgical education. In 2008, he received his MPH degree from Columbia University, and now focuses on improved healthcare outcomes, bringing innovative technology to market (e.g. robotics to reduce the complexity of minimally invasive surgery), the use of simulation for educating healthcare providers, and healthcare delivery.In November 2010, Dennis was appointed Director of the newly established Reemtsma Center for Innovation and Outcomes Research.
David Gotz, PhD
IBM T.J. Watson Research Center
Dr. Gotz is a member of the multi-disciplinary Healthcare Transformation Research Group at IBM. His research focus is on visual analytics, information visualization, and intelligent user interfaces. His work has targeted a variety of application areas ranging from business intelligence to super-computer system administration. His current work explores interactive visual technologies and their applications in the healthcare field. While at IBM, David has been a co-inventor on ten patent-pending innovations in these areas. David received his PhD in Computer Science from the University of North Carolina at Chapel Hill in 2005. Prior to his PhD studies, David received a BS in Computer Science and a Certificate in Economics from Georgia Tech in 1999 where he graduated with Highest Honors. David is an active participant in the academic community, serving as a committee member and reviewer for several leading conferences and journals. He has published numerous papers in peer-reviewed conferences and journals in the areas of visualization, user-interfaces, multimedia systems, and medical informatics, including a paper from the most recent AMIA Symposium (2010) on evidence-based prognostics in healthcare that was a Distinguished Paper Award nominee.
Shunichi Homma, MD
Columbia University Medical Center
Dr. Homma is the Margaret Milliken Hatch Professor of Medicine at the Columbia University Medical Center, where he serves as the Associate Chief of the Cardiology Division as well as the Director of Noninvasive Cardiac Imaging. He also holds an appointment at the Fu School of Engineering at Columbia University. Dr. Homma collaborates extensively with the Department of Biomedical Engineering in developing new ultrasound techniques for cardiac diagnoses, and serves on the PhD Dissertation Committee. He is a graduate of Dartmouth College and Albert Einstein College of Medicine. He has finished internal medicine residency at the Montefiore Medical Center, and cardiology training at Massachusetts General Hospital and Columbia–Presbyterian Medical Center. Dr. Homma is credited with over 500 publications and holds a variety of NIH grants.
Nathaniel Hupert, MD, MPH
Weill Cornell Medical College
Dr. Hupert is a primary care internal medicine specialist and a researcher in public health emergency response and medical decision making. He currently serves as the Director of the Preparedness Modeling Unit of the U.S. Centers for Disease Control and Prevention (CDC), in addition to being Associate Professor of Public Health and Medicine at Cornell University's Weill Medical College in New York City. He trained at Harvard Medical School, the University of Pittsburgh Medical Center, and the Harvard School of Public Health. His research area is computational public health, the application of mathematical and simulation modeling techniques to health problems that extend beyond the bounds of traditional epidemiology. Since September 2000, he has collaborated with local, state, federal, and international public health officials in a series of federally financed research projects on hospital and clinical preparedness for bioterrorism. He led the development of a series of computer simulations to study mass antibiotic distribution and hospital capacity in the event of a large-scale release of a bio-weapon or other catastrophic health event. Since 2005, he has worked in close collaboration with colleagues in the Engineering/Operations Research community to bring state-of-the-art engineering solutions to critical public health problems. Hupert serves on the Anthrax Modeling Working Group of the U.S. Department of Health and Human Services (DHHS) and was a member of the 2007 RAND Expert Panel on Defining Public Health Preparedness. He has participated in a number of national webcasts on bioterrorism preparedness for the CDC's Strategic National Stockpile program and for the DHHS Agency for Healthcare Research and Quality. His training includes A.B., Harvard College (1988); M.D., Harvard Medical School (1994); and M.P.H., Harvard School of Public Health (2000).
Harold Litt, MD, PhD
University of Pennsylvania School of Medicine
Dr. Litt is Chief of the Cardiovascular Imaging section in the Department of Radiology at the University of Pennsylvania School of Medicine. After obtaining A.B. and A.M. degrees in physics at Harvard University, and an M.D. and Ph.D. in biophysics from SUNY at Buffalo, he undertook an internship at Mount Auburn Hospital-Harvard Medical School and residency in diagnostic radiology at the University of Pennsylvania School of Medicine. Following fellowship training in cardiothoracic radiology at the University of California at San Francisco, he returned to Penn, where he is currently Assistant Professor of Radiology and Medicine. Dr. Litt's research concerns novel methods and applications of Computed Tomography and Magnetic Resonance Imaging in cardiovascular disease, including methods for visualization of large clinical imaging datasets. He is currently principal investigator of a large, multicenter trial sponsored by the Commonwealth of Pennsylvania Tobacco Settlement Fund comparing CT with usual care for evaluation of patients presenting to emergency departments with chest pain.
Patricia Ordóñez Rozo, MS
University of Maryland, Baltimore County
Ms. Ordóñez is a doctoral candidate in the Computer Science and Electrical Engineering Department at the University of Maryland, Baltimore County (UMBC). Her anticipated graduation date is August, 2011. She received her M.S. in Computer Science from UMBC in August 2010 and her B. A. in Hispanic and Italian Studies from Johns Hopkins University in 1989. Her current research centers on her dissertation, entitled "Multivariate Time Series Analysis of Physiological and Clinical Data." She is interested in creating clinical decision support systems that aid medical providers to efficiently diagnose and treat patients, and that personalize medicine by applying data mining, machine learning, and visualization techniques to data warehouses of electronic medical data. Patti has served as a lecturer of several undergraduate courses at UMBC during graduate school and as a technical trainer in industry for over 10 years. Prior to delving into technology, she taught high school math and Spanish and coached field hockey. In 2007, she received a National Science Foundation Graduate Research Fellowship to complete her doctorate, which permitted her to pursue her interests in biomedical informatics in collaboration with medical professors at Johns Hopkins School of Medicine. In 2008, her paper, Visualizing Multivariate Time Series Data to Detect Specific Medical Conditions, was nominated for the Best Student Paper Award at AMIA 2008.
This event is funded in part by the Life TechnologiesTM Foundation.
Generating and Examining Molecular Simulations on a Timescale 100 Times Longer than Was Previously FeasibleDavid E. Shaw, PhD, D.E. Shaw Research
Molecular dynamics (MD) simulation has long been recognized as a potentially transformative tool for understanding the behavior of proteins and other biological macromolecules, and for developing a new generation of precisely targeted drugs. Many biologically and pharmaceutically important phenomena, however, occur over timescales that have previously fallen far outside the reach of MD technology. We have constructed a specialized, massively parallel machine, called Anton, that is capable of performing atomic-level simulations of proteins at a speed roughly two orders of magnitude beyond that of the previous state of the art. This specialized hardware, together with software tools designed for the processing of an enormous amount of molecular trajectory data, is now allowing us to visualize and analyze the motions of proteins over periods in excess of a millisecond — approximately 100 times the length of the longest such simulation previously published. Our early studies have already led to significant advances in the understanding of protein folding and other aspects of protein dynamics that were previously inaccessible to either computational or experimental study.
The Intersection of Imaging, Visualization, and Simulation in SurgeryDennis L. Fowler, MD, MPH, College of Physicians and Surgeons, Columbia University
Background: During the past two decades, improved imaging technology has revolutionized surgical interventions. White light based imaging (all forms of endoscopy), magnetic resonance imaging, ultrasound imaging, and imaging based on X-rays have enabled surgeons and other interventionalists to reduce the invasiveness of surgical procedures. The common feature of all of these interventions is the use of a displayed image to guide the treatment (Image Guided Therapy or IGT). IGT creates problems for the surgeon because (s)he must use a displayed 2D image of a 3D space to remotely manipulate instruments that function in that 3D space. This creates a long and steep learning curve because it requires a different set of cognitive and technical skills than traditional surgery.Current Clinical Results: Despite these impediments, IGT improves patient care by reducing the invasiveness of surgery.
Potential Enhancement: The image used for IGT offers the potential to improve surgery in two other ways. First, using modern computational capabilities, we can digitally enhance images to provide visualization that significantly improves on typical 2-dimensional images. Second, the displayed image lends itself to graphical reproduction and the development of virtually simulated clinical scenarios. Virtual simulation of surgical environments enables creation of virtual simulators on which surgeons and trainees can learn both the cognitive and technical skills to safely complete IGT.Summary: Despite the impediments created by IGT, imaging technology offers the potential for better visualization and for simulation training, both of which have significant potential to further improve surgical care.
Quantitative Evaluation of 4D Myocardial Strain Measures via Optical Flow with a Finite Element Field Model Fitted to SonomicrometryAndrew F. Laine, DSc, and Shunichi Homma, MD, Columbia University
Dynamic cardiac metrics, including strains and displacements, can provide a quantitative approach to evaluate cardiac function. However, in current clinical diagnosis, strain measures in 2D are used despite the fact that cardiac motions are complex changes in 4D. Recent advances in 4D ultrasound enable the capability to capture such complex motion in one data set. In our previous work, a 4D optical flow based motion tracking algorithm was developed to extract full 4D dynamic cardiac metrics from such 4D ultrasound data. In order to quantitatively evaluate the method, coronary artery occlusion experiments at various locations were performed on three canine hearts with 4D ultrasound and sonomicrometry data acquired during the occlusion. Optical flow displacement was then mapped onto a finite element field fitted model. Corresponding 4D ultrasound data from these experiments were then analyzed. Estimated principal strains were directly compared to those recorded by sonomicrometry showing strong agreement. This was the first validation study of optical flow based strain estimation for 4D cardiac ultrasound including a direct comparison with sonomicrometry on in vivo data. Finally, a clinical study is presented to validate the performance of 4D cardiac ultrasound strain measures to cardiac MRI using 3D DENSE and 3D CSPAMM as gold standards of myocardial strain. If time permits the talk will also include recent research on other methods to quantify dynamic metrics in medical imaging such as longitudinal studies of the brain and chronic vasculature disease.
Visual Analytics for Evidence-Based MedicineDavid Gotz, PhD, IBM T.J. Watson Research Center
As the adoption rates for electronic medical records and other patient information systems grow, medical institutions are amassing ever larger collections of computerized patient data. We theorize that beyond the traditionally envisioned benefits of electronic records, such as error reduction and eased access to patient information, these large data repositories can be mined to extract valuable information about the effectiveness of historical treatment. If such insights can be customized to the context of a specific patient's care and surfaced at the right point during the delivery of care, this approach promises to enable a new framework for evidence-based medicine. We will describe the key elements of our approach toward achieving this vision and provide a glimpse of our lab's prototype evidence-based visual analytics application.
Clinical Application of Multidimensional Visualization in Cardiac ImagingHarold Litt, MD, PhD, University of Pennsylvania School of Medicine
Recent technical developments in Computed Tomography (CT) and Magnetic Resonance Imaging (MRI) have led to a dramatic increase in the size of datasets generated by these studies, up to 10,000 images in the case of cardiac CT and MRI. Such studies can no longer reasonably be interpreted using two-dimensional and even conventional three-dimensional tools. In addition, purely anatomic imaging is giving way to multiparametric acquisitions, in which functional and physiologic information is obtained along with structure. Both of these trends, i.e. larger image datasets and the combination of structural and functional information, have led to the development of sophisticated visualization tools. We will demonstrate the use and benefits of some of these types of tools for improving the efficiency of study interpretation and integration of anatomic and functional information for improved diagnosis and patient care, particularly in cardiac imaging. Finally, we will discuss the application of quantitative image analysis to research problems in cardiac disease.
Optimizing "Blended Learning" for Bedside Ultrasound Training: Incorporation of E-learning, Simulation, and Other Multimedia ToolsYanick Beaulieu, MD, Hôpital du Sacré-Coeur de Montréal, University of Montreal
The use of bedside ultrasound in acute and non-acute care has great potential to immediately provide diagnostic information at the bedside not assessable by physical examination alone. Its use can speed up and improve the management of a variety of patient conditions. It has also been shown to bring frequent changes in diagnosis and subsequent changes in therapy. Bedside ultrasound is rapidly becoming a standard of care to decrease the risks of complications related to invasive procedures, to improve efficiency of the practitioner, and to improve overall patient care. These improvements could eventually lead to a decrease in morbidity, mortality, and decrease in costs. But its successful application depends entirely on the skills of its users - and therein lays one of the greatest challenges faced by clinicians in widely adopting bedside ultrasound. The demand for training is high but all too often inadequate training programs are in place, if any at all. Developments in e-learning and simulation technologies are creating the groundwork for a revolution in bedside ultrasound education. E-learning is a perfect way to allow learners to develop cognitive skills and knowledge on key aspect of focused clinical ultrasound through flexible, modular programs that enables individualized learning. For the hands-on portion of the training, high-fidelity ultrasound simulators allow comprehensive practical training that includes scanning of various acute pathologies and allow the learners to be challenged with dynamic clinical scenarios. This talk will review how incorporation of e-learning, simulation and other multimedia tools into a "blended learning" strategy can optimize training in bedside ultrasound.
In Silico Public Health: What Can Simulation Modeling Tell Us that We Don't Already Know?Nathaniel Hupert, MD, MPH, Weill Cornell Medical College, Cornell Institute for Disease and Disaster Preparedness
Review of mathematical and simulation modeling studies of the 2009 A/H1N1 influenza pandemic reveals that fewer than 10% of papers published during the declared public health emergency attempted to predict the timing and magnitude of the outbreak. This apparent lack of timely policy-relevant output leads to the question, "What, then, is public health modeling good for?" The answer rests largely with the purpose for which modeling is conducted, which can be captured by the notion of a modeling paradigm. This talk will focus on comparing two contrasting paradigms, the epidemiologic and the analytic/response logistical. If modeling is seen as serving a strictly epidemiological goal of describing outbreaks, much of its potential value for public health operations may be lost. In contrast, employing models to explore potential decision spaces and quantitatively weigh alternative courses of action—focusing on predictive modeling—and using them to determine how best to respond to emergencies in light of resource constraints—focusing on operations research modeling—may bring new and potentially useful insights to key decision makers. This latter view of the role of modeling leads to a new vision for the field of public health response logistics that will require an expanded scope of public health informatics to support appropriate logistical decision making.
An Animated Multivariate Visualization of Clinical and Physiological Data in a Neonatal ICUPatricia Ordóñez Rozo, MS, University of Maryland, Baltimore County
Existing visualizations in the Neonatal Intensive Care Unit (NICU) frequently obscure important trends in clinical data to the clinician's eye in tabular displaysor stacked univariate plots of variables over time. Scales and alarm limits in clinical displays are based on adult norm data, resulting in confusing or misleading displays in the NICU, where norm data differ significantly, even within infants of differing gestational ages. We developed a visualization that provides an integrated, multivariate interface for representing laboratory and physiological data. The visualization automates the personalization of baselines and thresholds in one view of the data that normalizes data points to the patient's state over the total time period reviewed. Consequently, minor changes in the patient's condition are more easily detected, increasing the likelihood of observing numerically small, but clinically significant changes in NICU patients. Other views normalize the data to the providers' specifications to inspect a user-provided range of values more closely. The visualization also captures the rate of change of provider-selected parameters and the relationships among them by allowing providers to experience the changes in multiple variables simultaneously through animation. We present the design of a multivariate time series visualization that is interactive, animated, and personalized to an individual patient, such that clinicians can quickly and efficiently recognize significant changes in the patient's condition.
Medical Imaging Tools from Concept to Clinical Practice: Validation and Investment ChallengesMostafa Analoui, PhD, The Livingston Group
Medical imaging offers a broad range of qualitative and quantitative tools for clinical practice, as well as in vivo research for drug discovery and development. Currently a number of imaging modalities are accepted and routinely used, such as radiography, CT, MRI, PET, US, along with image visualization, rendering and analysis toolboxes. With the advent of new modalities and new imaging biomarkers, there is a long path for moving such novel tools from early scientific discovery to regulatory and clinical acceptance. Additionally imaging data need to be considered along with a slew of other clinical and laboratory data, which demand very complex and multi-variate decision making and modeling. In this presentation, an overview of two key elements for converting imaging concepts to clinical tools will be discussed: Validation and Investment. Validation covers main steps in establishing technical proof of concept, clinical and regulatory acceptance. Depending on nature of modality, tools and clinical utility, this could be a long and expensive path to track. Considering such complexity and modest probability of success, source of funding and investment become a critical bottleneck. A number of examples will be offered to highlight challenges in navigating such concepts to market, along with recommendations for addressing regulatory and investment issues in this process.
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