YoVDO

MRI as a Low-Cost High-Value Imaging Modality - Spring 2020

Offered By: Stanford University via YouTube

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Radiology Courses Deep Learning Courses Medical Imaging Courses Biomarkers Courses Osteoarthritis Courses

Course Description

Overview

Explore a comprehensive seminar on advancing Magnetic Resonance Imaging (MRI) as a cost-effective and high-value medical imaging modality. Delve into the importance of value in healthcare, the radiology value chain, and the unique capabilities of MRI in producing detailed soft tissue contrast. Examine the challenges and tradeoffs in MRI, particularly in knee imaging, and discover innovative approaches to overcome these limitations. Learn about osteoarthritis biomarkers, rapid whole-joint quantification techniques, and the potential of deep learning in enhancing MRI capabilities. Investigate computer-aided diagnosis algorithms, MRI applications around metallic implants, stroke outcome prediction, and non-contrast breast cancer screening. Gain insights into the future of MRI as a low-cost, high-value imaging tool that could potentially replace traditional radiography in certain scenarios.

Syllabus

Intro
Moving Magnetic Resonance Imaging Tov
What is Value?
Why is Value Important?
Radiology Value Chain
Magnetic Resonance Imaging • MRI produces images with exquisite soft tissue contrast
MRI Tradeoffs
Utilization of Knee MRI
Knee MRI Challenges
Disease Timeline
Osteoarthritis Biomarkers • T2 may highlight the collagen hydration and degradation
Limitations
OA Biomarkers with DESS • Enabling rapid whole-joint biomarker quantification.
Bilateral Knee MRI
qDESS Imaging Biomarkers
Improvement Areas • Tradeoffs between in-plane and slice resolution
Comparison Study - 51 Patients Sensitivity
T2 Map Benefit: Cartilage
High-Value MRI with Deep Learn
qDESS Super-Resolution
Additional Approaches: T2 Shuff
Computer Aided Diagnoses • Variety of algorithms for radiology image interpretation
Replace Radiography?
MRI Around Metallic Implants
Predicting Stroke Outcomes
Breast Cancer Screening
Non-Contrast Breast Cancer Scre
Conclusion


Taught by

Stanford Radiology

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