Cancer Research UK, OHSU Knight Cancer Institute and the Canary Center at Stanford, present the Early Detection of Cancer Conference series. The annual Conference brings together experts in early detection from multiple disciplines to share ground breaking research and progress in the field.
The Conference is part of a long-term commitment to invest in early detection research, to understand the biology behind early stage cancers, find new detection and screening methods, and enhance uptake and accuracy of screening.
The 2021 conference will take place October 6-8 virtually. For more information visit the website: http://earlydetectionresearch.com/
CME Grand Rounds – “Community Based Partnered Research: Revisiting a Critical Concept for Radiology”
Christoph L. Lee, MD, MS, MBA
Professor
Radiology
University of Washington
Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
Meeting ID: 600 003 703
Password: 566048
Or iPhone one-tap (US Toll): +18333021536,,600003703# or +16507249799,,600003703#
Or Telephone:
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or +1 833 302 1536 (US, Canada, Caribbean Toll Free)
International numbers available: https://stanford.zoom.us/u/acuqphnvqT
ABSTRACT
Coming soon!
BIO
Coming soon!
CEDSS: The First Cell: A new model for cancer research and treatment
Azra Raza, M.D.
Chan Soon-Shiong Professor of Medicine
Director, Myelodysplastic Syndrome Center
Columbia University Medical Center
Location: Zoom
Meeting URL: https://stanford.zoom.us/s/99340345860
Dial: US: +1 650 724 9799 or +1 833 302 1536 (Toll Free)
Meeting ID: 993 4034 5860
Passcode: 711508
ABSTRACT
Cancer research continues to be predicated on a 1970’s model of research and treatment. Despite half a century of intense research, we are failing spectacularly to improve the outcome for patients with advanced disease. Those who are cured continue to be treated mostly with the older strategies (surgery-chemo-radiation). Our contention is that the real solution to the cancer problem is to diagnose cancer early, at the stage of The First Cell. The rapidly evolving technologies are doing much in this area but need to be expanded. We study a pre-leukemic condition called myelodysplastic syndrome (MDS) with the hope that we can detect the first leukemia cells as the disease transforms to acute myeloid leukemia (AML). Towards this end, we have collected blood and bone marrow samples on MDS and AML patients since 1984. Today, our Tissue Repository has more than 60,000 samples. We propose novel methods to identify surrogate markers that can identify the First Cell through studying the serial samples of patients who evolve from MDS to AML.
ABOUT
Dr. Raza is a Professor of Medicine and Director of the MDS Center at Columbia University in New York, NY.She started her research in Myelodisplastic Syndromes (MDS) in 1982 and moved to Rush University, Chicago, Illinois in 1992, where she was the Charles Arthur Weaver Professor in Oncology and Director, Division of Myeloid Diseases. The MDS Program, along with a Tissue Repository containing more than 50,000 samples from MDS and acute leukemia patients was successfully relocated to the University of Massachusetts in 2004 and to Columbia University in 2010.
Before moving to New York, Dr. Raza was the Chief of Hematology Oncology and the Gladys Smith Martin Professor of Oncology at the University of Massachussetts in Worcester. She has published the results of her laboratory research and clinical trials in prestigious, peer reviewed journals such as The New England Journal of Medicine, Nature, Blood, Cancer, Cancer Research, British Journal of Hematology, Leukemia, and Leukemia Research. Dr. Raza serves on numerous national and international panels as a reviewer, consultant and advisor and is the recipient of a number of awards.
Hosted by: Utkan Demirci, Ph.D.
Sponsored by: The Canary Center & the Department of Radiology
Stanford University – School of Medicine
CME Grand Rounds – Topic: TBD
Jocelyn D. Chertoff, MD, MS
Professor
Radiology, Obstetrics & Gynecology
Chair, Radiology
Dartmouth Hitchcock Medical Center
Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
Meeting ID: 600 003 703
Password: 566048
Or iPhone one-tap (US Toll): +18333021536,,600003703# or +16507249799,,600003703#
Or Telephone:
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or +1 833 302 1536 (US, Canada, Caribbean Toll Free)
International numbers available: https://stanford.zoom.us/u/acuqphnvqT
ABSTRACT
Coming soon!
BIO
Coming soon!
MIPS Seminar Series: Title TBA
Steven Paul Poplack, MD
Professor of Radiology (Breast Imaging)
Stanford University Medical Center
Location: Coming soon!
12:00pm – 12:45pm Seminar & Discussion
RSVP: Coming soon!
ABSTRACT
Coming soon!
ABOUT
Coming soon!
Hosted by: Katherine Ferrara, PhD
Sponsored by: Molecular Imaging Program at Stanford & the Department of Radiology
CME Grand Rounds Etta K. Moskowitz Lectureship – Topic: TBD
Elizabeth Krupinski, PhD
Professor & Vice Chair for Research
Radiology & Imaging Sciences
Emory University School of Medicine
Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
Meeting ID: 600 003 703
Password: 566048
Or iPhone one-tap (US Toll): +18333021536,,600003703# or +16507249799,,600003703#
Or Telephone:
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or +1 833 302 1536 (US, Canada, Caribbean Toll Free)
International numbers available: https://stanford.zoom.us/u/acuqphnvqT
ABSTRACT
Coming soon!
BIO
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CME Grand Rounds – “Promote Your Academic Career Using Social Media”
Michael Gisondi, MD
Associate Professor & Vice Chair of Education
Emergency Medicine
Stanford University
Join from PC, Mac, Linux, iOS or Android: https://stanford.zoom.us/j/600003703?pwd=RjcwS2MvOG1qVkxyL3U0RmNtUDVWdz09
Meeting ID: 600 003 703
Password: 566048
Or iPhone one-tap (US Toll): +18333021536,,600003703# or +16507249799,,600003703#
Or Telephone:
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or +1 833 302 1536 (US, Canada, Caribbean Toll Free)
International numbers available: https://stanford.zoom.us/u/acuqphnvqT
ABSTRACT
Coming soon!
BIO
Coming soon!
Saeed Hassanpour, PhD
Associate Professor of Biomedical Data Science
Associate Professor of Epidemiology
Associate Professor of Computer Science
Dartmouth Geisel School of Medicine
Deep Learning for Histology Images Analysis
Abstract:
With the recent expansions of whole-slide digital scanning, archiving, and high-throughput tissue banks, the field of digital pathology is primed to benefit significantly from deep learning technology. This talk will cover several applications of deep learning for characterizing histopathological patterns on high-resolution microscopy images for cancerous and precancerous lesions. Furthermore, the current challenges for building deep learning models for pathology image analysis will be discussed and new methodological advances to address these bottlenecks will be presented.
About:
Dr. Saeed Hassanpour is an Associate Professor in the Departments of Biomedical Data Science, Computer Science, and Epidemiology at Dartmouth College. His research is focused on machine learning and multimodal data analysis for precision health. Dr. Hassanpour has led multiple NIH-funded research projects, which resulted in novel machine learning and deep learning models for medical image analysis and clinical text mining to improve diagnosis, prognosis, and personalized therapies. Before joining Dartmouth, he worked as a Research Engineer at Microsoft. Dr. Hassanpour received his Ph.D. in Electrical Engineering with a minor in Biomedical Informatics from Stanford University and completed his postdoctoral training at Stanford Center for Artificial Intelligence in Medicine & Imaging.
MIPS Seminar Series: Title TBA
Matthew Bogyo, PhD
Professor of Pathology and of Microbiology and Immunology and, by courtesy, of Chemical and Systems Biology
Stanford University
Location: Coming soon!
12:00pm – 12:45pm Seminar & Discussion
RSVP: Coming soon!
ABSTRACT
Coming soon!
ABOUT
Dr. Bogyo received a B.Sc. degree in Chemistry from Bates College in 1993 and a Ph.D. in Biochemistry from the Massachusetts Institute of Technology in 1997. After completion of his degree he was appointed as a Faculty Fellow in the Department of Biochemistry and Biophysics at the University of California, San Francisco. Dr. Bogyo served as the Head of Chemical Proteomics at Celera Genomics from 2001 to 2003 while maintaining an Adjunct Faculty appointment at UCSF. In the Summer of 2003 Dr. Bogyo joined the Department of Pathology at Stanford Medical School and was appointed as a faculty member in the Department of Microbiology and Immunology in 2004. His interests are focused on the use of chemistry to study the role of proteases in human disease. In particular his laboratory is currently working on understanding the role of cysteine proteases in tumorgenesis and also in the life cycle of human parasites and bacterial pathogens. Dr. Bogyo currently serves on the Editorial Board of Biochemical Journal, Cell Chemical Biology, Molecular and Cellular Proteomics and is an Academic Editor at PLoS One. Dr. Bogyo is a consultant for several biotechnology and pharmaceutical companies in the Bay Area and is a founder and board member of Akrotome Imaging and Facile Therapeutics.
Hosted by: Katherine Ferrara, PhD
Sponsored by: Molecular Imaging Program at Stanford & the Department of Radiology
Indrani Bhattacharya, PhD
Postdoctoral Research Fellow
Department of Radiology
Stanford University
Title: Multimodal Data Fusion for Selective Identification of Aggressive and Indolent Prostate Cancer on Magnetic Resonance Imaging
Abstract: Automated methods for detecting prostate cancer and distinguishing indolent from aggressive disease on Magnetic Resonance Imaging (MRI) could assist in early diagnosis and treatment planning. Existing automated methods of prostate cancer detection mostly rely on ground truth labels with limited accuracy, ignore disease pathology characteristics observed on resected tissue, and cannot selectively identify aggressive (Gleason Pattern≥4) and indolent (Gleason Pattern=3) cancers when they co-exist in mixed lesions. This talk will cover multimodal and multi-scale fusion approaches to integrate radiology images, pathology images, and clinical domain knowledge about prostate cancer distribution to selectively identify and localize aggressive and indolent cancers on prostate MRI.
Rogier van der Sluijs, PhD
Postdoctoral Research Fellow
Department of Radiology
Stanford University
Title: Pretraining Neural Networks for Medical AI
Abstract: Transfer learning has quickly become standard practice for deep learning on medical images. Typically, practitioners repurpose existing neural networks and their corresponding weights to bootstrap model development. This talk will cover several methods to pretrain neural networks for medical tasks. The current challenges for pretraining neural networks in Radiology will be discussed and recent advancements that address these bottlenecks will be highlighted.