Calendar

Apr
22
Wed
2020
IBIIS/AIMI Seminar - Tiwari @ ZOOM - See Description for Zoom link
IBIIS/AIMI Seminar – Tiwari
Apr 22 @ 1:00 pm – 2:00 pm ZOOM - See Description for Zoom link
IBIIS/AIMI Seminar - Tiwari @ ZOOM - See Description for Zoom link

Radiomics and Radio-Genomics: Opportunities for Precision Medicine

Zoom: https://stanford.zoom.us/j/99904033216?pwd=U2tTdUp0YWtneTNUb1E4V2x0OTFMQT09 

Pallavi Tiwari, PhD
Assistant Professor of Biomedical Engineering
Associate Member, Case Comprehensive Cancer Center
Director of Brain Image Computing Laboratory
School of Medicine | Case Western Reserve University


Abstract:
In this talk, Dr. Tiwari will focus on her lab’s recent efforts in developing radiomic (extracting computerized sub-visual features from radiologic imaging), radiogenomic (identifying radiologic features associated with molecular phenotypes), and radiopathomic (radiologic features associated with pathologic phenotypes) techniques to capture insights into the underlying tumor biology as observed on non-invasive routine imaging. She will focus on clinical applications of this work for predicting disease outcome, recurrence, progression and response to therapy specifically in the context of brain tumors. She will also discuss current efforts in developing new radiomic features for post-treatment evaluation and predicting response to chemo-radiation treatment. Dr. Tiwari will conclude with a discussion on her lab’s findings in AI + experts, in the context of a clinically challenging problem of post-treatment response assessment on routine MRI scans.

Apr
24
Fri
2020
Mini-Grand Rounds - Ann Leung, MD @ Zoom
Mini-Grand Rounds – Ann Leung, MD
Apr 24 @ 7:00 am – 7:30 am Zoom
Mini-Grand Rounds - Ann Leung, MD @ Zoom

Mini-Grand Rounds: Stanford University Medical Center and COVID-19: A Chest Radiologist’s Perspective

Ann Leung, MD
Associate Chair, Clinical Affairs
Professor, Radiology

7:00am – 7:30am, Zoom

The Stanford Radiology Mini-Grand Round live session events are by invitation only. Invites with link to Zoom video will be sent via email to Department faculty and staff only. Recordings will be made available to the public shortly after the event.

Apr
27
Mon
2020
Mini-Grand Rounds - David Larson, MD, MBA @ Zoom
Mini-Grand Rounds – David Larson, MD, MBA
Apr 27 @ 7:00 am – 7:30 am Zoom
Mini-Grand Rounds - David Larson, MD, MBA @ Zoom

Mini-Grand Rounds: The Outlook for Radiology in the Next Phases of the Pandemic and Beyond

David Larson, MD, MBA
Vice Chair, Education and Clinical Operations
Associate Professor, Radiology

7:00am – 7:30am, Zoom

The Stanford Radiology Mini-Grand Round live session events are by invitation only. Invites with link to Zoom video will be sent via email to Department faculty and staff only. Recordings will be made available to the public shortly after the event.

May
26
Tue
2020
Cancer Early Detection Seminar Series - Eric Fung, M.D., Ph.D. @ Zoom - See Description for Zoom Link
Cancer Early Detection Seminar Series – Eric Fung, M.D., Ph.D.
May 26 @ 11:00 am – 12:00 pm Zoom - See Description for Zoom Link
Cancer Early Detection Seminar Series - Eric Fung, M.D., Ph.D. @ Zoom - See Description for Zoom Link

CEDSS: “Multicancer detection of early-stage cancers with simultaneous tissue localization using a plasma cfDNA-based targeted methylation assay”

Eric Fung, M.D., Ph.D.

Senior Medical Director

GRAIL, Inc.

Please see zoom details below:
Meeting URL: https://stanford.zoom.us/j/230531527
Dial: +1 650 724 9799 (US, Canada, Caribbean Toll) or +1 833 302 1536 (US, Canada, Caribbean Toll Free)
Meeting ID: 230 531 527

ABOUT

Dr. Eric Fung is Vice President, Clinical Development at GRAIL, where he leads several clinical development programs in support of the development of a blood-based multi-cancer detection test. Dr. Fung has previously held clinical development and R&D leadership roles at Affymetrix, Vermillion, Ciphergen, and Roche Molecular Diagnostics. Dr. Fung has led clinical trials leading to FDA clearance of multiple IVD products. Dr. Fung received his MD, PhD from the Johns Hopkins University School of Medicine.

 

Hosted by: Sanjiv Sam Gambhir, M.D., Ph.D.
Spon
sored by the Canary Center & the Department of Radiology 
Stanford University – School of Medicine

Oct
15
Thu
2020
Cancer Early Detection Seminar Series - Paul Boutros, Ph.D., M.B.A. @ Zoom - See Description for Zoom Link
Cancer Early Detection Seminar Series – Paul Boutros, Ph.D., M.B.A.
Oct 15 @ 11:00 am – 12:00 pm Zoom - See Description for Zoom Link
Cancer Early Detection Seminar Series - Paul Boutros, Ph.D., M.B.A. @ Zoom - See Description for Zoom Link

CEDSS: “The Origins and Detection of Lethal Prostate Cancer”

Paul Boutros, Ph.D., M.B.A.
Director, Cancer Data Sciences
UCLA

Please see zoom details below:
Meeting URL: https://stanford.zoom.us/s/93515779500
Dial: +1 650 724 9799 or +1 833 302 1536
Meeting ID: 935 1577 9500
Meeting Passcode: 767148

ABOUT
Boutros earned his B.Sc. degree from the University of Waterloo in Chemistry in 2004, and his Ph.D. degree from the University of Toronto, Canada, in Medical Biophysics in 2008. At Toronto, he also earned an executive M.B.A. from the Rothman School of Management. In 2008, Boutros started his independent research career at the Ontario Institute for Cancer Research first as a fellow (2008–2010) and then as principal investigator (2010–2018). He moved to California to join the UCLA faculty in 2018.

 

Hosted by: Utkan Demirci, Ph.D.
Spon
sored by the Canary Center & the Department of Radiology 
Stanford University – School of Medicine

Oct
21
Wed
2020
SCIT Quarterly Seminar @ See description for ZOOM link
SCIT Quarterly Seminar
Oct 21 @ 10:00 am – 11:00 am See description for ZOOM link

ZOOM LINK HERE

“High Resolution Breast Diffusion Weighted Imaging”
Jessica McKay, PhD

ABSTRACT: Diffusion-weighted imaging (DWI) is a quantitative MRI method that measures the apparent diffusion coefficient (ADC) of water molecules, which reflects cell density and serves as an indication of malignancy. Unfortunately, however, the clinical value of DWI is severely limited by the undesirable features in images that common clinical methods produce, including large geometric distortions, ghosting and chemical shift artifacts, and insufficient spatial resolution. Thus, in order to exploit information encoded in diffusion characteristics and fully assess the clinical value of ADC measurements, it is first imperative to achieve technical advancements of DWI.

In this talk, I will largely focus on the background of breast DWI, providing the clinical motivation for this work and explaining the current standard in breast DWI and alternatives proposed throughout the literature. I will also present my PhD dissertation work in which a novel strategy for high resolution breast DWI was developed. The purpose of this work is to improve DWI methods for breast imaging at 3 Tesla to robustly provide diffusion-weighted images and ADC maps with anatomical quality and resolution. This project has two major parts: Nyquist ghost correction and the use of simultaneous multislice imaging (SMS) to achieve high resolution. Exploratory work was completed to characterize the Nyquist ghost in breast DWI, showing that, although the ghost is mostly linear, the three-line navigator is unreliable, especially in the presence of fat. A novel referenceless ghost correction, Ghost/Object minimization was developed that reduced the ghost in standard SE-EPI and advanced SMS. An advanced SMS method with axial reformatting (AR) is presented for high resolution breast DWI. In a reader study, AR-SMS was preferred by three breast radiologists compared to the standard SE-EPI and readout-segmented-EPI.


“Machine-learning Approach to Differentiation of Benign and Malignant Peripheral Nerve Sheath Tumors: A Multicenter Study”

Michael Zhang, MD

ABSTRACT: Clinicoradiologic differentiation between benign and malignant peripheral nerve sheath tumors (PNSTs) is a diagnostic challenge with important management implications. We sought to develop a radiomics classifier based on 900 features extracted from gadolinium-enhanced, T1-weighted MRI, using the Quantitative Imaging Feature Pipeline and the PyRadiomics package. Additional patient-specific clinical variables were recorded. A radiomic signature was derived from least absolute shrinkage and selection operator, followed by gradient boost machine learning. A training and test set were selected randomly in a 70:30 ratio. We further evaluated the performance of radiomics-based classifier models against human readers of varying medical-training backgrounds. Following image pre-processing, 95 malignant and 171 benign PNSTs were available. The final classifier included 21 features and achieved a sensitivity 0.676, specificity 0.882, and area under the curve (AUC) 0.845. Collectively, human readers achieved sensitivity 0.684, specificity 0.742, and AUC 0.704. We concluded that radiomics using routine gadolinium enhanced, T1-weighted MRI sequences and clinical features can aid in the evaluation of PNSTs, particularly by increasing specificity for diagnosing malignancy. Further improvement may be achieved with incorporation of additional imaging sequences.

Nov
18
Wed
2020
IBIIS & AIMI Seminar: Deep Tomographic Imaging @ Zoom: https://stanford.zoom.us/j/96731559276?pwd=WG5zcEFwSGlPcDRsOUFkVlRhcEs2Zz09
IBIIS & AIMI Seminar: Deep Tomographic Imaging
Nov 18 @ 12:00 pm – 1:00 pm Zoom: https://stanford.zoom.us/j/96731559276?pwd=WG5zcEFwSGlPcDRsOUFkVlRhcEs2Zz09

Ge Wang, PhD
Clark & Crossan Endowed Chair Professor
Director of the Biomedical Imaging Center
Rensselaer Polytechnic Institute
Troy, New York

Abstract:
AI-based tomography is an important application and a new frontier of machine learning. AI, especially deep learning, has been widely used in computer vision and image analysis, which deal with existing images, improve them, and produce features. Since 2016, deep learning techniques are actively researched for tomography in the context of medicine. Tomographic reconstruction produces images of multi-dimensional structures from externally measured “encoded” data in the form of various transforms (integrals, harmonics, and so on). In this presentation, we provide a general background, highlight representative results, and discuss key issues that need to be addressed in this emerging field.

About:
AI-based X-ray Imaging System (AXIS) lab is led by Dr. Ge Wang, affiliated with the Department of Biomedical Engineering at Rensselaer Polytechnic Institute and the Center for Biotechnology and Interdisciplinary Studies in the Biomedical Imaging Center. AXIS lab focuses on innovation and translation of x-ray computed tomography, optical molecular tomography, multi-scale and multi-modality imaging, and AI/machine learning for image reconstruction and analysis, and has been continuously well funded by federal agencies and leading companies. AXIS group collaborates with Stanford, Harvard, Cornell, MSK, UTSW, Yale, GE, Hologic, and others, to develop theories, methods, software, systems, applications, and workflows.

Jan
19
Tue
2021
Cancer Early Detection Seminar Series - Thomas Kislinger, Ph.D. @ Zoom - See Description for Zoom Link
Cancer Early Detection Seminar Series – Thomas Kislinger, Ph.D.
Jan 19 @ 11:00 am – 12:00 pm Zoom - See Description for Zoom Link
Cancer Early Detection Seminar Series - Thomas Kislinger, Ph.D. @ Zoom - See Description for Zoom Link

CEDSS: Systematic identification of fluid-based biomarkers for ovarian and prostate cancer

 

Thomas Kislinger, Ph.D.
Professor & Chair
Department of Medical Biophysics
University of Toronto

Senior Scientist
Princess Margaret Cancer Centre

 

Zoom Webinar Details 
Meeting URL: https://stanford.zoom.us/s/94878578384
Dial: +1 650 724 9799 or +1 833 302 1536
Webinar ID: 948 7857 8384
Passcode: 692692
Register Here

 

ABOUT

Thomas Kislinger received his MSc in Analytical Chemistry from the University of Munich, Germany (1998). He completed his PhD in 2001, investigating the role of Advanced Glycation Endproducts in diabetic vascular complications at the University of Erlangen, Germany and Columbia University, New York. Between 2002 and 2006 he completed a post-doctoral fellowship at the University of Toronto. In 2006 he joined the Princess Margaret Cancer Centre as an independent investigator. Dr. Kislinger holds positions as Senior Scientist at the Princess Margaret Cancer Centre and as Professor and Chair at the University of Toronto in the Department of Medical Biophysics. The Kislinger lab applies proteomics technologies to translational and basic cancer biology. This includes the development of novel proteomics methodologies, identification of liquid biopsy signatures and the molecular identification of novel cell surface markers.

 

Hosted by: Utkan Demirci, Ph.D.
Spon
sored by: The Canary Center & the Department of Radiology 
Stanford University – School of Medicine

Jan
28
Thu
2021
MIPS Seminar - Carolyn Bertozzi, PhD @ Zoom - See Description for Zoom Link
MIPS Seminar – Carolyn Bertozzi, PhD
Jan 28 @ 12:00 pm – 12:45 pm Zoom - See Description for Zoom Link
MIPS Seminar - Carolyn Bertozzi, PhD @ Zoom - See Description for Zoom Link

MIPS Seminar Series: Translational Opportunities in Glycoscience

Carolyn Bertozzi, PhD
Director, ChEM-H
Anne T. and Robert M. Bass Professor in the School of Humanities and Sciences
Professor, by courtesy, of Chemical and Systems Biology
Stanford University

 

Location: Zoom
Webinar URL: . https://stanford.zoom.us/j/94010708043
Dial: US: +1 650 724 9799  or +1 833 302 1536 (Toll Free)
Webinar ID: 940 1070 8043
Passcode: 659236

12:00pm – 12:45pm Seminar & Discussion
RSVP Here

 

ABSTRACT
Cell surface glycans constitute a rich biomolecular dataset that drives both normal and pathological processes.  Their “readers” are glycan-binding receptors that can engage in cell-cell interactions and cell signaling.  Our research focuses on mechanistic studies of glycan/receptor biology and applications of this knowledge to new therapeutic strategies.  Our recent efforts center on pathogenic glycans in the tumor microenvironment and new therapeutic modalities based on the concept of targeted degradation.

 

ABOUT
Carolyn Bertozzi is the Baker Family Director of Stanford ChEM-H and the Anne T. and Robert M. Bass Professor of Humanities and Sciences in the Department of Chemistry at Stanford University. She is also an Investigator of the Howard Hughes Medical Institute. Her research focuses on profiling changes in cell surface glycosylation associated with cancer, inflammation and infection, and exploiting this information for development of diagnostic and therapeutic approaches, most recently in the area of immuno-oncology. She is an elected member of the National Academy of Medicine, the National Academy of Sciences, and the American Academy of Arts and Sciences. She also has been awarded the Lemelson-MIT Prize, a MacArthur Foundation Fellowship, the Chemistry for the Future Solvay Prize, among many others.

 

Hosted by: Katherine Ferrara, PhD
Sponsored by: Molecular Imaging Program at Stanford & the Department of Radiology

Feb
25
Thu
2021
MIPS Seminar - Joseph M. DeSimone, PhD @ Zoom - See Description for Zoom Link
MIPS Seminar – Joseph M. DeSimone, PhD
Feb 25 @ 12:00 pm – 12:45 pm Zoom - See Description for Zoom Link
MIPS Seminar - Joseph M. DeSimone, PhD @ Zoom - See Description for Zoom Link

MIPS Seminar Series: “Convergent, translational research to improve human health”

Joseph M. DeSimone, PhD
Sanjiv Sam Gambhir Professor of Translational Medicine and Chemical Engineering
Departments of Radiology and Chemical Engineering
Graduate School of Business (by Courtesy)
Stanford University

 

Location: Zoom
Webinar URL: https://stanford.zoom.us/s/98460805010
Dial: +1 650 724 9799 or +1 833 302 1536
Webinar ID: 984 6080 5010
Passcode: 809226

12:00pm – 12:45pm Seminar & Discussion
RSVP Here

 

ABSTRACT
In many ways, manufacturing processes define what’s possible in society.  Central to our interests in the DeSimone laboratory are opportunities to make things using cutting-edge fabrication technologies that can improve human health.  This lecture will describe advances in nano- / micro-fabrication and 3D printing technologies that we have made and employed toward this end.  Using novel perfluoropolyether materials synthesized in our lab in 2004, we invented the Particle Replication in Non-wetting Templates (PRINT) technology, a high-resolution imprint lithography-based process to fabricate nano- and micro-particles with precise and independent control over particle parameters (e.g. size, shape, modulus, composition, charge, surface chemistry).  PRINT brought the precision and uniformity associated with computer industry manufacturing technologies to medicine, resulting in the launch of Liquidia Technologies (NASDAQ: LQDA) and opening new research paths, including to elucidate the influence of specific particle parameters in biological systems (Proc. Natl. Acad. Sci. USA 2008), and to reveal insights to inform the design of vaccines (J. Control. Release 2018), targeted therapeutics (Nano Letters 2015), and even synthetic blood (PNAS 2011).  In 2015, we reported the invention of the Continuous Liquid Interface Production (CLIP) 3D printing technology (Science 2015), which overcame major fundamental limitations in polymer 3D printing—slowness, a very limited range of materials, and an inability to create parts with the mechanical and thermal properties needed for widespread, durable utility.  By rethinking the physics and chemistry of 3D printing, we created CLIP to eliminate layer-by-layer fabrication altogether.  A rapid, continuous process, CLIP generates production-grade parts and is now transforming how products are manufactured in industries including automotive, footwear, and medicine.  For example, to help address shortages, CLIP recently enabled a new nasopharyngeal swab for COVID-19 diagnostic testing to go from concept to market in just 20 days, followed by a 400-patient clinical trial at Stanford.  Academic laboratories are also using CLIP to pursue new medical device possibilities, including geometrically complex IVRs to optimize drug delivery and implantable chemotherapy absorbers to limit toxic side effects.  Vast opportunities exist to use CLIP to pursue next-generation medical devices and prostheses.  Moreover, CLIP can improve current approaches; for example, the fabrication of an iontophoretic device we invented several years ago (Sci. Transl. Med. 2015) to drive chemotherapeutics directly into hard-to-reach solid tumors is now being optimized for clinical trials with CLIP.  New design opportunities also exist in early detection, for example to improve specimen collection, device performance (e.g. microfluidics, cell sorting, supporting growth and studies with human organoids), and imaging (e.g. PET detectors, ultrasound transducers).  Here at Stanford, we are pursuing new 3D printing advances, including software treatment planning for digital therapeutic devices in pediatric medicine, as well as the design of a high-resolution printer capable of single-digit micron resolution to advance microneedle designs as a potent delivery platform for vaccines.  The impact of our work on human health ultimately relies on our ability to enable a convergent research program to take shape that allows for new connections to be made among traditionally disparate disciplines and concepts, and to ensure that we maintain a consistent focus on the translational potential of our discoveries and advances.

 

ABOUT
Joseph M. DeSimone is the Sanjiv Sam Gambhir Professor of Translational Medicine and Chemical Engineering at Stanford University. He holds appointments in the Departments of Radiology and Chemical Engineering with a courtesy appointment in Stanford’s Graduate School of Business. Previously, DeSimone was a professor of chemistry at the University of North Carolina at Chapel Hill and of chemical engineering at North Carolina State University. He is also Co-founder, Board Chair, and former CEO (2014 – 2019) of the additive manufacturing company, Carbon.

DeSimone is responsible for numerous breakthroughs in his career in areas including green chemistry, medical devices, nanomedicine, and 3D printing, also co-founding several companies based on his research. He has published over 350 scientific articles and is a named inventor on over 200 issued patents. Additionally, he has mentored 80 students through Ph.D. completion in his career, half of whom are women and members of underrepresented groups in STEM. In 2016 DeSimone was recognized by President Barack Obama with the National Medal of Technology and Innovation, the highest U.S. honor for achievement and leadership in advancing technological progress. He is also one of only 25 individuals elected to all three branches of the U.S. National Academies (Sciences, Medicine, Engineering). DeSimone received his B.S. in Chemistry in 1986 from Ursinus College and his Ph.D. in Chemistry in 1990 from Virginia Tech.

 

Hosted by: Katherine Ferrara, PhD
Sponsored by: Molecular Imaging Program at Stanford & the Department of Radiology