![IBIIS/AIMI Seminar - A.I.-Based Decision Support Systems for Precision & Participative Medicine: Focus on Oncology and Radiomics @ Clark Center](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/11/radiology.png)
A.I.-Based Decision Support Systems for Precision & Participative Medicine:
Focus on Oncology and Radiomics
Join via Zoom: https://stanford.zoom.us/j/499245954
Abstract:
Precision medicine is the future of health care: please watch the animation at https://vimeo.com/241154708. As a technology-intensive and -dependent medical discipline, oncology will be at the vanguard of this impending change. However, to bring about precision medicine, a fundamental conundrum must be solved: Human cognitive capacity, typically constrained to five variables for decision making in the context of the increasing number of available biomarkers and therapeutic options, is a limiting factor to the realization of precision medicine. Given this level of complexity and the restriction of human decision making, current methods are untenable. A solution to this challenge is multifactorial decision support systems (DSSs), continuously learning artificial intelligence platforms that integrate all available data-clinical, imaging, biologic, genetic, cost-to produce validated predictive models. DSSs compare the personalized probable outcomes-toxicity, tumor control, quality of life, cost effectiveness-of various care pathway decisions to ensure optimal efficacy and economy. DSSs can be integrated into the workflows both strategically (at the multidisciplinary tumor board level to support treatment choice, eg, surgery or radiotherapy) and tactically (at the specialist level to support treatment technique, eg, prostate spacer or not). In some countries, the reimbursement of certain treatments, such as proton therapy, is already conditional on the basis that a DSS is used. DSSs have many stakeholders-clinicians, medical directors, medical insurers, patient advocacy groups-and are a natural consequence of big data in health care. Here, we provide an overview of DSSs, their challenges, opportunities, and capacity to improve clinical decision making, with an emphasis on oncology and radiomics.
About:
Philippe Lambin is a Clinician, Radiation Oncologist, with a PhD in Molecular Radiation Biology, “ERC advanced grant laureate”, co-inventor of Radiomics, multifactorial Decision Support Systems, Distributed learning, the use of immunocytokines with Radiation and pioneer in translational research with a focus on tumour hypoxia and immunotherapy. He is/has been leading 30 clinical trials. He has and is Professor at the University of Maastricht (head of the new Dpt of Precision Oncology: The D-Lab & The M-Lab, focusing on “Convergence Sciences” and Decision Support Systems. He is co-author of more than 488 peer reviewed scientific papers (Hirsch Index: 94 Google scholar), co-inventor of more than 17 patents (filed or submitted) of which 5 are in the (pre)commercialization phase and (co) promoter of more than 59 completed PhD’s.
Refreshments will be provided.
![CCSB Seminar: Identifying and Rationally Modulating Cellular Drivers of Tumor Response @ Clark Center S360](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/10/Shalek_Feature_Justin_Knight_2018-300x122.jpg)
Alex K. Shalek, PhD
Pfizer-Laubach Career Development Associate Professor
Institute for Medical Engineering & Science
Department of Chemistry and Koch Institute
Massachusetts Institute of Technology
Abstract: While several methods exist for sampling tissues in clinical contexts, without high-fidelity tools for comprehensively profiling them, we are both limited in our capacity to understand how constituent cells and their interactions impact prognosis, and to select and develop precision therapeutics. Recent years have witnessed transformative and intersecting advances in nanofabrication and molecular biology that now enable deep profiling of low-input samples. Collectively, these afford new and exciting opportunities to study cellular heterogeneity, starting from the level of the single cell, and may unlock the diagnostic, prognostic, and discovery potential of clinical isolates. Illustratively, I will introduce how we can leverage single-cell genomic approaches – and, in particular, single-cell RNA-Seq – to explore the extensive functional diversity between cells, uncovering, from the “bottom-up,” distinct cell states and their molecular drivers. Moreover, I will discuss high-throughput experimental strategies and demonstrate, in the context of Acute Lymphoblastic Leukemia, how they can be leveraged to achieve the statistical power necessary to reconstruct intracellular circuits, enumerate and redefine cell states and types, and transform our understanding of cellular decision-making in health and disease on a genomic scale.
Bio: Alex K. Shalek is currently the Pfizer-Laubach Career Development Associate Professor at MIT, as well as a Core Member of the Institute for Medical Engineering and Science (IMES), an Associate Professor of Chemistry, and an Extramural Member of The Koch Institute for Integrative Cancer Research. He is also an Institute Member of the Broad Institute, an Associate Member of the Ragon Institute, an Assistant in Immunology at MGH, and an Instructor in Health Sciences and Technology at HMS. His research is directed towards the development and application of new technologies that facilitate understanding of how cells collectively perform systems-level functions in healthy and diseased states. Dr. Shalek received his bachelor’s degree summa cum laude from Columbia University and his Ph.D. from Harvard University in chemical physics under the guidance of Hongkun Park, and performed postdoctoral training under Hongkun Park and Aviv Regev (Broad/MIT). To date, his interdisciplinary research has focused on realizing and utilizing nanoscale manipulation and measurement technologies to examine how small components (molecules, cells) drive systems of vast complexity (cellular responses, population behaviors).
![MIPS IMAGinING THE FUTURE Seminar Series - Dr. Jennifer Doudna](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/10/jennifer-199x300.jpg)
Abstract: Gene editing with CRISPR technology is transforming biology. Understanding the underlying chemical mechanisms of RNA-guided DNA and RNA cleavage provides a foundation for both conceptual advances and technology development. I will discuss how bacterial CRISPR adaptive immune systems inspire creation of powerful genome editing tools, enabling advances in both fundamental biology and applications in medicine. I will also discuss the ethical challenges of some of these applications with a focus on what our decisions now might mean for future generations.
About: MIPS IMAGinING THE FUTURE seminar series is aimed at catalyzing interdisciplinary discussions in all area of medicine and disease. The seminar series is open and free to everyone in the Stanford community, as well as anyone from the surrounding community, companies or institutions. Our next seminar will host Dr. Jennifer Doudna, Professor of Chemistry, Biochemistry & Molecular Biology, &Li Ka Shing Chancellor’s Professor in Biomedical and Health, University of California, Berkeley; for her presentation on the “World of CRISPR: Editing Genomes and Altering Our Future”.
More Information: http://med.stanford.edu/radiology/imagining-the-future.html
Register: https://www.onlineregistrationcenter.com/JenniferDoudna
![Cancer Early Detection Seminar Series - Michael Shen, Ph.D.](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/10/mshen-201x300.png)
Cancer Early Detection Seminar
“Best Practices in Hip Imaging”
Michael Shen, PhD
Professor of Medicine, Genetics and Development, Urology and Systems Biology
Columbia University Medical Center
ABSTRACT
TBD
_____________________________________________
Hosted by
Sanjiv Sam Gambhir, MD, PhD<https://med.stanford.edu/profiles/sanjiv-gambhir>
Sponsored by
The Canary Center and the Stanford Cancer Institute
Stanford University
If you would like to be included on the email distribution list for weekly reminders, contact Ashley Williams (ashleylw.at.stanford.edu)
RSVP and more info at: https://www.onlineregistrationcenter.com/register/222/page1.asp?m=298&c=41
![IBIIS & AIMI Seminar - Okyaz Eminaga, MD, PhD @ Clark Center - S360](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/11/okyaz-eminaga-300x300.jpg)
Integrative Biomedical Imaging Informatics at Stanford (IBIIS) and Center for Artificial Intelligence in Medicine & Imaging (AIMI) Seminar: “AI-Aided Diagnostic and Prognostic Tools for Prostate Cancer”
Okyaz Eminaga, MD, PhD
Postdoctoral Research Fellow, Urology
Biomedical Data Sciences
Stanford University
James H. Clark Center, S360
12:00pm-1:00pm – Seminar and Discussion (light refreshments provided)
Join via Zoom: https://stanford.zoom.us/j/613898274
ABSTRACT: Prostate Cancer exhibits different clinical behavior, ranging from indolent to lethal disease. A critical clinical need is identifying characteristics that distinguish indolent from advanced disease to direct treatment to the latter. The recent renaissance of artificial intelligence (AI) research uncovered the potential of AI to improve clinical decision making. In this seminar, we will go through the potential of AI to enhance the diagnosis and the prognosis of prostate cancer using magnetic resonance images, clinical data, and histology images. We will stress the challenges and benefits of having such AI-based solutions in clinical routine.
ABOUT: Dr. Eminaga passed his medical examination (Staatsexamen) 2009 and received his Ph.D. in Medicine 2010 from University of Muenster (major topic: medical informatics) under the supervision of Professor Dr. Axel Semjonow (one of the pioneer physician-scientists and biomarker researcher who worked on the standardization of PSA measurement for prostate cancer which is used nowadays) and Professor Dr. Martin Dugas (who is the head of European Research Center for Information Systems and one of the most influential professors in medical informatics in Europe). For those who don’t know the institute of medical informatics in Muenster. The systematized Nomenclature of Human and Veterinary Medicine (SNOMED), which is now used worldwide in medical information systems, was initiated by this institute more than 30 years ago.
His doctoral dissertation presented a novel documentation architecture for clinical data and imaging called cMDX (clinical map document) that facilitates the concept of the single-source information system for clinical data storage and analysis, and is successfully used in clinical routine for generating the pathology reports with graphical information about the spatial tumor extent for prostatectomy specimens since 2009 at the prostate center of University Hospital Muenster. This work has been also utilized for more than 20 studies related to genomics, translational medicine, epidemiology, urology, radiology, and pathology. Dr. Eminaga also established the biobanking information management system to manage the samples of one of the largest biobanks for prostate cancer in Europe. This biobank is also part of the European P-Mark network for prostate cancer-related biorepositories initiated by Oxford University.
Dr. Eminaga completed his residency in Urology in the University Hospital of Cologne (Germany) with a major focus on uro-oncology. He was also a research fellow in Prostate Center of University Hospital Muenster, doing research in biomarkers, biobanking infrastructure, epidemiology and histopathology. During his residency fellowship, he further evaluated the role of certain miRNA in prostate cancer development under the supervision of the molecular biologist Dr. Warnecke-Eberz. After his residency, he started a research scholarship at the laboratory of Dr. Brooks, doing genomic research and bioinformatics for research topics related to prostate cancer evolution. Now, his current interests have expanded to statistical learning, medical imaging informatics, and integrative data analysis.
He is the recipient of 3 highly-competitive scholarships and his works have been recognized at national and international levels e.g., by the European Association of Urology. Currently, he is an early-investigator research awardee for prostate cancer managed by the department of defense and works on developing decision-aided tools for diagnosis and prognosis of prostate cancer.
Follow us on Twitter: @StanfordIBIIS and @StanfordAIMI
http://ibiis.stanford.edu/events/seminars/2019seminars.html
![AIMI, IBIIS & RSL Special Seminar - John Stafford & Bjorn Carey @ Clark Center - S360](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/11/stafford-carey-300x300.jpg)
“Messaging in the Age of Microtargeting”
John Stafford
Assistant Vice President
Digital Strategy
Stanford University
Bjorn Carey
Senior Director
Digital Strategy
Stanford University
Join via Zoom: https://stanford.zoom.us/j/400566542
Abstract:
Communications has become increasingly data-driven, targeted, and personalized. This has changed how Stanford analyzes communications opportunities from a research perspective and how it engages with relevant audiences. In this presentation, John and Bjorn will share the data and communications strategy underlying three communications initiatives and the resulting execution. They will also provide practical advice for individual thought leadership and communications in this dynamic environment.
About:
John Stafford, MA ’06, is currently Assistant Vice President for Digital Strategy at Stanford, the most senior digital communications role in the university. John is responsible for all aspects of creating a world-class digital communications function: setting the group’s strategy, building analytics and insight programs, counseling on crisis communications, leading multi-channel messaging initiatives, and advising colleagues across the University. He received a Master’s Degree in Communication from Stanford, a B.A. in History from the University of San Francisco, and was a founding advisor to Stanford Medicine X.
Refreshments will be provided.
![AIMI & IBIIS Seminar - Luciano M. Prevedello, MD, MPH @ Clark Center - S360](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/12/luciano-prevedello-300x300.jpg)
“Algorithm Development Lifecycle in Medical Imaging:
Current State and Considerations for the Future”
Luciano M. Prevedello, MD, MPH
Vice-Chair for Medical Informatics and Augmented Intelligence in Imaging
Division Chief, Medical Imaging Informatics
Director, 3D and Advanced Visualization Lab
Associate Professor, Division of Neuroradiology,
Department of Radiology
Ohio State University Wexner Medical Center
Join via Zoom: https://stanford.zoom.us/j/267814863
Abstract:
This presentation will describe some of the most important considerations involved in creating algorithms in medical imaging from inception to deployment as well as continued model improvement and/or monitoring. Examples of experience to date from the OSU laboratory for augmented intelligence in imaging will be provided. New paradigms in model creation and the role of image challenge competitions will also be covered. Current issues with model validation and generalizability will also be introduced as well as considerations for future work in this area.
Refreshments will be provided.
![AIMI & IBIIS Seminar - Wei Shao, PhD & Saeed Seyyedi, PhD @ Clark Center - S360](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2020/01/shao-seyyedi-300x300.jpg)
“A Deep Learning Framework for Efficient Registration of MRI and Histopathology Images of the Prostate”
Wei Shao, PhD
Postdoctoral Research Fellow
Department of Radiology
Stanford University
“Applications of Generative Adversarial Networks (GANs) in Medical Imaging”
Saeed Seyyedi, PhD
Paustenbach Research Fellow
Department of Radiology
Stanford University
Join via Zoom: https://stanford.zoom.us/j/593016899
Refreshments will be provided
ABSTRACT (Shao)
Magnetic resonance imaging (MRI) is an increasingly important tool for the diagnosis and treatment of prostate cancer. However, MRI interpretation suffers from high interobserver variability and often misses clinically significant cancers. Registration of histopathology images from patients who have undergone surgical resection of the prostate onto pre-operative MRI images allows direct mapping of cancer location onto MR images. This is essential for the discovery and validation of novel prostate cancer signatures on MRI. Traditional registration approaches can be computationally expensive and require a careful choice of registration hyperparameters. We present a deep learning-based pipeline to accelerate and simplify MRI-histopathology image registration in prostate cancer. Our pipeline consists of preprocessing, transform estimation by deep neural networks, and postprocessing. We refined the registration neural networks, originally trained with 19,642 natural images, by adding 17,821 medical images of the prostate to the training set. The pipeline was evaluated using 99 prostate cancer patients. The addition of the images to the training set significantly (p < 0.001) improved the Dice coefficient and reduced the Hausdorff distance. Our pipeline also achieved comparable accuracy to an existing state-of-the-art algorithm while reducing the computation time from 4.4 minutes to less than 2 seconds.
ABSTRACT (Seyyedi)
Generative adversarial networks (GANs) are advanced types of neural networks where two networks are trained simultaneously to perform two tasks of generation and discrimination. GANs have gained a lot of attention to tackle well known and challenging problems in computer vision applications including medical image analysis tasks such as medical image de-noising, detection and classification, segmentation and reconstruction.In this talk, we will introduce some of the recent advancements of GANs in medical imaging applications and will discuss the recent developments of GAN models to resolve real world imaging challenges.
![Early Detection Seminar Series - Victoria Seewaldt, M.D. @ Beckman Center, Munzer Auditorium (B060)](https://web.stanford.edu/group/radweb/cgi-bin/radcalendar/wp-content/uploads/2019/10/seewaldt-victoria-300x300.jpg)
CEDSS: “Strategies to Identify Aggressive Breast Cancer Biology in Black and Latina Women”
Victoria Seewaldt, MD
Ruth Ziegler Professor and Chair, Department of Population Sciences
Associate Director for Population Sciences Research, Comprehensive Cancer Center
City of Hope
Beckman Center, Munzer Auditorium (B060)
11:00am – 12:00pm Seminar & Discussion
12:00pm – 12:15pm Reception & Light Refreshments
RSVP here: https://www.onlineregistrationcenter.com/VictoriaSeewaldt
ABSTRACT
Over 90% of breast cancer is cured; yet there remain highly aggressive breast cancers that develop rapidly and are extremely difficult to treat, much less prevent. Examples are triple-negative breast cancer in Black/African American women and luminal B breast cancers in Black/African Americans and Latinas. Breast cancers that rapidly develop between breast imaging are called “interval cancers”. Here we aim to investigate biologically aggressive precancerous breast lesions and their matched invasive breast cancers in women of diverse race and ethnicity. Our team has the unique ability to perform single cell in situ transcriptional profiling in combination with dynamic and spatial genomics/proteomics; this allows us to identify multi-dimensional spatial and temporal relationships that drive the transition from biologically aggressive pre-cancer to interval breast cancer.
ABOUT
Victoria Seewaldt, M.D., is an accomplished clinician and researcher who’s devoted to improving the lives of her patients and the community at large. She has led community outreach education efforts on cancer prevention through personal wellbeing and directed research aimed at finding biomarkers that can be used for early cancer detection, particularly triple-negative breast cancers that are especially resistant to treatment.
At City of Hope, Dr. Seewaldt will direct efforts to provide breast cancer education, free breast cancer screening and treatment, mentorship of young minority scholars, and a forum for community partnered trials. Clinically, Dr. Seewaldt aims to empower women at high breast cancer risk to be full partners in developing wellness strategies to promote personal health.
Dr. Seewaldt received her medical degree from the University of California, Davis, and completed her residency and clinical fellowship at the University of Washington in Seattle. She then pursued a medical oncology fellowship with the Fred Hutchinson Cancer Research Center and then became an assistant professor at Ohio State University. Afterwards, she transferred to Duke University, where she held various clinical, academic and leadership roles in its School of Medicine and Comprehensive Cancer Center — most recently as a professor, co-leader of the breast and ovarian cancer program and head of the cancer breast prevention program — before joining City of Hope.