Calendar

Muna Aryal Rizal, PhD
Mentor: Jeremy Dahl, PhD and Raag Airan, MD, PhD

Noninvasive Focused Ultrasound Accelerates Glymphatic Transport to Bypass the Blood-Brain Barrier

ABSTRACT

Recent advancement in neuroscience revealed that the Central Nervous System (CNS) comprise glial-cell driven lymphatic system and coined the term called “Glymphatic pathway” by Neuroscientist, Maiden Nedergaard. Furthermore, it has been proven in rodent and non-human primate studies that the glymphatic exchange efficacy can decay in healthy aging, alzheimer’s disease models, traumatic brain injury, cerebral hemorrhage, and stroke. Studies in rodents have also shown that the glymphatic function can accelerate by doing easily-implemented, interventions like physical exercise, changes in body posture during sleep, intake of omega-3 polyunsaturated fatty acids, and low dose alcohol (0.5 g/kg). Here, we proposed for the first time to accelerate the glymphatic function by manipulating the whole-brain ultrasonically using focused ultrasound, an emerging clinical technology that can noninvasively reach virtually throughout the brain. During this SCIT seminar, I will introduce the new ultrasonic approach to accelerates glymphatic transport and will share some preliminary findings.

Eduardo Somoza, MD
Mentor: Sandy Napel, PhD

Prediction of Clinical Outcomes in Diffuse Large B-Cell Lymphoma (DLBCL) Utilizing Radiomic Features Derived from Pretreatment Positron Emission Tomography (PET) Scan

ABSTRACT

Diffuse Large B-Cell lymphoma (DLBCL) is the most common type of lymphoma, accounting for a third of cases worldwide. Despite advancements in treatment, the five-year percent survival for this patient population is around sixty percent. This indicates a clinical need for being able to predict outcomes before the initiation of standard treatment. The approach we will be employing to address this need is the creation of a prognostic model from pretreatment clinical data of DLBCL patients seen at Stanford University Medical Center. In particular, there will be a focus on the derivation of radiomic features from pretreatment positron emission tomography (PET) scans as this has not been thoroughly investigated in similar published research efforts. We will layout the framework for our approach, with an emphasis on the aspects of our design that will allow for the translation of our efforts to multiple clinical settings. More importantly, we will discuss the importance and challenges of assembling a quality clinical database for this type of research. Ultimately, we hope our efforts will lead to the development of a prognostic model that can be utilized to guide treatment in DLBCL patients with refractory disease and/or high risk of relapse after completion of standard treatment.

The Office of Accessible Education and Apple present:

Apple Accessibility: Tools for Everyone

“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.

Stanford School of Medicine’s
1^st Annual Conference on Disability in Healthcare and Medicine

Saturday, June 20, 2020

8:00am – 2:30pm Pacific Daylight Time (PDT)
Zoom Webinar

The conference goals are:

• Supporting students and healthcare providers with disabilities
• Training healthcare providers to better care for patients with disabilities
• Research into the intersection of providers and patients with disabilities

Target audience:

• Nursing students and nurses
• PA students and PA’s
• Medical students and medical doctors
• All other interested healthcare providers and allies

Register Today!

Join us for the 3rd Annual Diversity and Inclusion Forum on Friday, October 9, 2020 on Zoom! This virtual event will highlight innovative workshops developed by our residents and fellows with their educational mentors who have participated in the 2019-2020 cohort of the Leadership Education in Advancing Diversity Program.

The event will be an enriching opportunity for all faculty, residents, fellows, postdocs, students, staff, and community members to learn tools and strategies to enable them to become effective change agents for diversity, equity, and inclusion in medical education.

All are welcome to participate and we look forward to seeing you on Friday, October 9!

Register here:

https://mailchi.mp/046c21726371/diversityforum2020-1632872?e=4a913cab2d

In honor of the 30th anniversary of the Americans with Disabilities Act and October as National Disability Employment Awareness Month, join the Stanford Medicine Abilities Coalition (SMAC) for a first of its kind StanfordMed LIVE event focused on disability. Now more than ever during the COVID-19 pandemic, disabilities, health conditions, and illness impact not only our patients but also all of us, both personally and as members of the Stanford Medicine community. Stanford Medicine leadership will share information, answer questions, and engage in a roundtable discussion about the state of disability at Stanford and how best to support faculty, staff, and students living with disability and chronic illness. We encourage our community to submit questions and comments here to be shared broadly with the Stanford Medicine community. The same link can be used to request any accommodations needed for the livestream. Additional information for the webcast itself will be sent out closer to the event.

Livestream link: https://livestream.com/accounts/1973198/events/9288854

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.

Date: April 10, 2021 (8 AM-6PM)

• • 8 AM-8:20 AM opening remarks Zainub and Pete
  • 8:20 AM-9:20 AM Talk 1 “I fought the law and no one won”
• 10 minute Break
• 9:30 AM-10:30 AM talk 2 students and doctors with disabilities panel

• 20 minute break

• • 10:50 AM-11:50 AM Breakout
  • One hour lunch  (TBD)
  • 12:50 PM-1:50 PM Talk 3 the frontiers of disability research 
• Lisa Meeks is moderating
• Bonnie Swenor invited
  • 10 minute break
  • 2:00 PM-3:00 PM breakout 2
• 10 minute break
• 3:10 PM-4:10 PM talk 4 do-it-yourself disability advocacy (Poullos/Tolchin with students)

• 4:10 PM-4:30 PM closing remarks

• 4:30 PM-6 PM virtual happy hour

Alone in the Ring (a research-based theatre production about inclusive healthcare workplaces) is coming to campus during the Annual Stanford School of Medicine Diversity Week and National Disability Employment Awareness Month, SMAC and Stanford Medicine and the Muse hope to continue the discussion on how to spark and sustain change towards inclusive workspaces. Alone in the Ring is followed by a discussion between the team and audience members. During the presentation, audience members are encouraged to reflect: How inclusive is your workspace? How could you make it more accessible?

Register for this event