Multimodality Imaging Markers for Gauging Breast Cancer Risk

Targeted CE per ARRT’s Discipline, Category, and Subcategory classification:
[Note: Discipline-specific Targeted CE credits may be less than the total Category A credits approved for this course.]

Breast Sonography: 2.50
Patient Care: 2.00
Patient Interactions and Management: 2.00
Procedures: 0.50
Anatomy and Physiology: 0.50

Mammography: 2.50
Patient Care: 0.75
Patient Interactions and Management: 0.75
Procedures: 1.75
Anatomy, Physiology, and Pathology: 0.50
Mammographic Positioning, Special Needs, and Imaging Procedures: 1.25

Magnetic Resonance Imaging: 1.00
Procedures: 1.00
Body: 1.00

Registered Radiologist Assistant: 2.50
Procedures: 2.50
Thoracic Section: 2.50

Sonography: 1.00
Procedures: 1.00
Superficial Structures and Other Sonographic Procedures: 1.00

Radiation Therapy: 1.00
Patient Care: 1.00
Patient and Medical Record Management: 1.00

Outline

1. Introduction
2. DM and DBT
   1. Mammographic Density
   2. Augmenting Epidemiologically Based Models with Breast Density
   3. Assessing Breast Texture with Radiomic Features
   4. Deep Learning in Breast Cancer Risk Assessment
   5. Digital Breast Tomosythesis
3. Breast US
   1. Tissue Composition of Breast US: BI-RADS Classification
   2. Internal Echogenicity Patterns of Fibroglandular Tissue
   3. Internal Echogenicity Patterns and Breast Cancer Risk
   4. Future Directions for Breast Cancer Risk Assessment Using Breast US
4. Breast MRI
   1. MRI Overview
   2. Biologic Underpinnings
   3. BPE and Breast Cancer Risk
   4. BPE in Women with Elevated Risk
   5. BPE in Women with Average Risk
   6. Future directions in MRI
5. Future Directions and Clinical Implementation
6. Conclusion

Objectives

Upon completion of this course, students will:

1. describe what type of breast tissue places individuals at a higher risk for breast cancer
2. review the meaning of fibroglandular as it pertains to breast density
3. describe the appearance of fibroglandular tissue as it appears on two-dimensional digital mammography and digital breast tomosynthesis
4. list factors that tend to decrease breast density
5. state the prevalence of mammographically dense breasts in women aged 40-74 years in the United States
6. recall the breast anatomy where breast cancer most frequently arises
7. distinguish between how breast imaging modalities demonstrate breast cancer
8. list the early works in mammography that were used to assess breast cancer risk
9. recall what agency developed the BIRADS system
10. interpret categories of the BI-RADS assessment of mammographic breast density
11. recall the method that has been utilized to standardize BI-RADS risk assessment
12. explain the difference between BI-RADS 4th and 5th edition as it relates to breast tissue density
13. state the software utilized to calculate area-based percent of breast density
14. state the number U.S. Food and Drug Administration–approved density assessment methods for DM, DBT, and synthetic mammography using artificial intelligence
15. choose the study that found that volumetric percent density at DM offered stronger association with breast cancer risk than total dense volume
16. list the risk assessment models that include breast density in risk calculation
17. explain how parenchymal complexity can be assessed
18. list the way in which parenchymal complexity can be visualized at digital mammography
19. choose the study that created a lattice of windows for radiomic feature extraction
20. choose the study that used a convolutional neural network–based pixel wise risk model to identify women at high-risk by analyzing negative mammograms from at least 2 years prior to cancer
21. choose the study that developed the mammography-based deep learning model known as Mirai
22. explain what type of image digital breast tomosynthesis uses for reconstruction
23. choose the study that compared DM, DBT, and SM in terms of density assessment
24. note how many images are performed at digital breast tomosynthesis examinations
25. explain breast tissue composition at breast ultrasound according to BI-RADS 5th edition
26. note how dense breast tissue on mammograms is categorized according to BI-RADS 5th edition
27. list the four types of sonographic parenchymal patterns classified by Hou et al
28. describe how sonographic glandular tissue component classification can be estimated more easily at automated breast ultrasound
29. state the primary anatomic source of breast cancer
30. recall the most sensitive imaging modality for the detection of breast cancer
31. list the qualitatively assessed BPE levels as demonstrated at MRI