RSNA 2021 Women's Imaging Preview

Road to RSNA 2021: Women's Imaging Preview

By Amerigo Allegretto, staff writer
November 16, 2021

At RSNA 2021, attendees will have the chance to learn about new and improved ways to detect and diagnose breast cancers, screening methods that combine multiple imaging modalities, the role of artificial intelligence (AI) in reducing false positives and improving accuracy, the continued emergence of digital breast tomosynthesis (DBT), abbreviated breast MRI, and more.

Presentations will highlight the performance of DBT, AI's promise in reducing false positives in interpreting breast ultrasound images, breast density characterization around the world, microwave imaging in breast cancer, and the effectiveness of including breast density in risk models. The effect of the COVID-19 vaccine on adenopathy and how it relates to breast cancer -- a major story in 2021 -- will also be addressed.

It has been more than 10 years since the first commercially available DBT system was launched. While it may be too early to determine the imaging method's long-term impact on breast screening, that isn't stopping researchers from studying it and comparing it with other imaging modalities. Some presentations at RSNA 2021 even address what happens when AI is applied to DBT imaging.

Speaking of AI, the technology continues to make strides toward being a permanent fixture in clinical practice. Presentations will analyze AI's performance when combined with other imaging methods, as well as the technology's potential to reduce false positives and improve lesion detection.

However, this year's women's imaging presentations are not limited to breast cancer. Researchers will also address topics such as vaginal bleeding from gynecological cysts and how radiation therapy can help, as well as follow-up imaging for ovarian cancer.

In addition, the RSNA will host educational courses that address topics such as AI in breast imaging, minimizing treatment in early breast cancer, the effect of COVID-19 on breast imaging and practice, and imaging in gynecologic oncology, to name a few.

Keep reading for highlights of just some of the many research and poster presentations scheduled for this year's meeting. View the complete 2021 scientific and educational program on the RSNA website.

Pandemic affected DBT recall, false-positive rates
Sunday, November 28 | 10:30 a.m.-11:30 a.m. | SSBR01-6 | Room TBA
In this Sunday presentation, researchers will discuss the results of a study measuring how the COVID-19 pandemic affected recall and false-positive rates for digital breast tomosynthesis (DBT) and digital mammography.
DBT continues to show promise a decade after commercial availability
Sunday, November 28 | 10:30 a.m.-11:30 a.m. | SSBR01-2 | Room TBA
Presenters will give the verdict on whether digital breast tomosynthesis (DBT) has been a successful screening method since the first commercially available system was released in 2011.
Combining radiomics, AI with PET/MRI helps assess nodal status
Sunday, November 28 | 10:30 a.m.-11:30 a.m. | SSNMMI01-3 | Room TBA
Here, researchers will talk about how applying radiomics and machine learning to FDG-PET/MRI can noninvasively assess nodal status and treatment planning for breast cancer patients.
PET/MRI shows prowess for nodal staging in breast cancer
Sunday, November 28 | 10:30 a.m.-11:30 a.m. | SSNMMI01-4 | Room TBA
In this presentation, researchers will compare nodal staging between CT, MRI, and FDG-PET/MRI in patients with newly diagnosed breast cancer.
Harmonic, subharmonic ultrasound characterizes breast lesions
Monday, November 29 | 3:00 p.m.-4:00 p.m. | SSBR04-4 | Room TBA
In this presentation, Flemming Forsberg, PhD, from Thomas Jefferson University in Philadelphia will discuss characterizing breast lesions with 3D harmonic and subharmonic ultrasound.
AI reduces false positives on breast ultrasound
Monday, November 29 | 3:00 p.m.-4:00 p.m. | SSBR04-6 | Room TBA
Researchers will present their findings from a clinical trial that used artificial intelligence (AI) in an effort to reduce false positives on breast ultrasound.
Premenopausal women more affected by adding density to risk model
Tuesday, November 30 | 8:00 a.m.-9:00 a.m. | SSBR05-5 | Room TBA
In this presentation, Dr. Stamatia Destounis from Elizabeth Wende Breast Care will talk about the effects of adding mammographic density to the Tyrer-Cuzick risk model.
Consider breast thickness when measuring cancer risk
Tuesday, November 30 | 8:00 a.m.-9:00 a.m. | SSBR05-6 | Room TBA
In this presentation, researchers will talk about their findings on distributing volumetric breast density across screening populations around the world for measuring risk.
Breast volume helps determine radiation dose for spiral breast CT
Tuesday, November 30 | 9:30 a.m.-10:30 a.m. | SSPH09-1 | Room TBA
Radiation dose for a novel spiral breast CT scanner can be determined by measuring breast volume, according to this presentation.
'Plug-and-play' AI method helps with microcalcifications on DBT
Tuesday, November 30 | 9:30 a.m.-10:30 a.m. | SSPH09-6 | Room TBA
Researchers will present results from a "plug-and-play" artificial intelligence (AI) algorithm that they say has the potential to improve detection of microcalcifications on digital breast tomosynthesis (DBT) images.
Photon-counting CT makes modality more effective for breast imaging
Tuesday, November 30 | 9:30 a.m.-10:30 a.m. | SSPH09-5 | Room TBA
In this Tuesday morning presentation, research findings will show how high-resolution photon-counting CT used with deep-learning image processing can expand the modality's role in breast cancer imaging.
Hypofractionated radiation therapy stops vaginal bleeding faster
Wednesday, December 1 | 9:30 a.m.-10:30 a.m. | SSRO03-2 | Room TBA
In this presentation, researchers from the University of Alabama at Birmingham will look at the effects of radiotherapies on vaginal bleeding for women with gynecological tumors.
Deep-learning tool triages women with decreased breast density
Wednesday, December 1 | 3:00 p.m.-4:00 p.m. | SSBR09-4 | Room TBA
In this Wednesday talk, researchers will present findings from their study of nearly 2,700 women that used a convolutional neural network in predicting mammographic density percentage from MRI scans.
AI model shows promise in detecting lesions from DBT data
Wednesday, December 1 | 3:00 p.m.-4:00 p.m. | SSBR09-3 | Room TBA
Finish your RSNA week off right with this presentation, in which researchers will discuss an artificial intelligence (AI) algorithm that detects lesions using datasets from digital breast tomosynthesis (DBT) exams.