Calendar

Apr
13
Mon
2020
Mini-Grand Rounds - Sam Shen, MD, PhD @ Zoom
Mini-Grand Rounds – Sam Shen, MD, PhD
Apr 13 @ 7:00 am – 7:30 am Zoom
Mini-Grand Rounds - Sam Shen, MD, PhD @ Zoom

Mini-Grand Rounds: In the frontlines of the COVID-19 pandemic

Sam Shen, MD, MBA
Associate Chief Quality Officer/Patient Safety Officer, SHC
Vice Chair, Clinical Operations & Quality
Clinical Associate Professor, Emergency Medicine
Stanford University

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
15
Wed
2020
Mini-Grand Rounds - Terry Desser, MD @ Zoom
Mini-Grand Rounds – Terry Desser, MD
Apr 15 @ 7:00 am – 7:30 am Zoom
Mini-Grand Rounds - Terry Desser, MD @ Zoom

Mini-Grand Rounds: Well-being during the COVID-19 pandemic

Terry Desser, MD
Professor, Radiology
Stanford University

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
17
Fri
2020
Mini-Grand Rounds - Tina Hernandez-Boussard, MPH, PhD @ Zoom
Mini-Grand Rounds – Tina Hernandez-Boussard, MPH, PhD
Apr 17 @ 7:00 am – 7:30 am Zoom
Mini-Grand Rounds - Tina Hernandez-Boussard, MPH, PhD @ Zoom

Mini-Grand Rounds: COVID-19: Meeting the Challenge with Data Science

Tina Hernandez-Boussard, MPH, PhD
Professor, Radiology
Stanford University

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
20
Mon
2020
Mini-Grand Rounds - Colin Kahl, PhD @ Zoom
Mini-Grand Rounds – Colin Kahl, PhD
Apr 20 @ 7:00 am – 7:30 am Zoom
Mini-Grand Rounds - Colin Kahl, PhD @ Zoom

Mini-Grand Rounds: Aftershocks: The Coronavirus Pandemic and The New World Disorder

Colin H. Kahl
Senior Fellow at the Freeman Spogli Institute for International Studies
Steven C. Házy Senior Fellow at the Center for International Security and Cooperation
Professor, by courtesy, of Political Science
Co-director of the Center for International Security and Cooperation

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
22
Wed
2020
CANCELLED - IMAGinING THE FUTURE - Elias Zerhouni, M.D. @ CANCELLED
CANCELLED – IMAGinING THE FUTURE – Elias Zerhouni, M.D.
Apr 22 @ 1:00 pm – 2:30 pm CANCELLED
CANCELLED - IMAGinING THE FUTURE - Elias Zerhouni, M.D. @ CANCELLED

Please note this seminar is now cancelled and will be rescheduled for a future date. Please contact Ashley Williams (ashleylw@stanford.edu) with any questions or concerns. Thank you for your understanding!

 

IMAGinING THE FUTURE: “Journey Through Academia, Government and Industry: Lessons Learned”

Elias Zerhouni, M.D.

Professor Emeritus

John Hopkins University

 

Mini-Grand Rounds - Nicholas Bloom, PhD @ Zoom
Mini-Grand Rounds – Nicholas Bloom, PhD
Apr 22 @ 7:00 am – 7:30 am Zoom
Mini-Grand Rounds - Nicholas Bloom, PhD @ Zoom

Mini-Grand Rounds: The short-run challenges and long-run opportunities of working from home

Nicholas Bloom, PhD
Professor (by courtesy), Economics
Senior Fellow, Stanford Institute for Economic Policy Research

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.

SCIT Quarterly Seminar @ Zoom: https://stanford.zoom.us/j/98960758162?pwd=aHJJc3pDS3FONkZIc2FoZ0hqcXU1dz09
SCIT Quarterly Seminar
Apr 22 @ 10:00 am – 11:00 am Zoom: https://stanford.zoom.us/j/98960758162?pwd=aHJJc3pDS3FONkZIc2FoZ0hqcXU1dz09
SCIT Quarterly Seminar @ Zoom: https://stanford.zoom.us/j/98960758162?pwd=aHJJc3pDS3FONkZIc2FoZ0hqcXU1dz09
“Tumor-Immune Interactions in TNBC Brain Metastases”
Maxine Umeh Garcia, PhD

ABSTRACT: It is estimated that metastasis is responsible for 90% of cancer deaths, with 1 in every 2 advanced staged triple-negative breast cancer patients developing brain metastases – surviving as little as 4.9 months after metastatic diagnosis. My project hypothesizes that the spatial architecture of the tumor microenvironment reflects distinct tumor-immune interactions that are driven by receptor-ligand pairing; and that these interactions not only impact tumor progression in the brain, but also prime the immune system (early on) to be tolerant of disseminated cancer cells permitting brain metastases. The main goal of my project is to build a model that recapitulates tumor-immune interactions in brain-metastatic triple-negative breast cancer, and use this model to identify novel druggable targets to improve survival outcomes in patients with devastating brain metastases.

“Classification of Malignant and Benign Peripheral Nerve Sheath Tumors With An Open Source Feature Selection Platform”
Michael Zhang, MD

ABSTRACT: Radiographic differentiation of malignant peripheral nerve sheath tumors (MPNSTs) from benign PNSTs is a diagnostic challenge. The former is associated with a five-year survival rate of 30-50%, and definitive management requires gross total surgical with wide negative margins in areas of sensitive neurologic function. This presentation describes a radiomics approach to pre-operatively identifying a diagnosis, thereby possibly avoiding surgical complexity and debilitating symptoms. Using an open-source, feature extraction platform and machine learning, we produce a radiographic signature for MPNSTs based on routine MRI.

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.

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.