News | Oncology Diagnostics | March 04, 2019

iCAD Partnering With Karolinska Instituet Researchers on AI-based Breast Cancer Risk Prediction

Proposed collaboration seeks to create artificial intelligence-based model to predict a woman’s individual risk of developing breast cancer

iCAD Partnering With Karolinska Instituet Researchers on AI-based Breast Cancer Risk Prediction

March 4, 2019 — iCAD announced their intent to enter an exclusive relationship with two leading researchers at The Karolinska Institutet in Stockholm, Sweden,, to develop an artificial intelligence (AI)-based solution that will identify a women’s individual risk of developing breast cancer.

This partnership builds on an existing research agreement whereby researchers at the Karolinska Institutet developed a breast cancer risk prediction model using information identified in mammography images provided by iCAD’s AI cancer detection and density assessment solutions. Promising early results based on mammography images from more than 70,000 Swedish women enrolled in The Karolinska Mammography Project for Risk Prediction of Breast Cancer (Karma) study were published in Breast Cancer Research in 2017. These data indicated that the model enabled early identification of women who were at a high-risk for breast cancer and it was determined that additional examinations were warranted. Since this publication, these results have been improved upon through the use of iCAD’s latest ProFound AI algorithm. Among other things, the model now takes asymmetry of mammographic features and masking of tumors into consideration.

iCAD and the Karolinska Institutet researchers now intend to collaborate to develop an innovative solution for commercial use to assess an individual’s risk of developing breast cancer. Both parties have agreed to negotiate in good faith with the expectation of entering into an exclusive license agreement for the breast cancer risk assessment model.

According to the World Health Organization, breast cancer is the most prevalent cancer among women worldwide, impacting more than 2 million women each year. Breast cancer screening and early detection are key to improving outcomes and survival rates. However, today, most mammography screening programs are not individualized, so a significant need exists to be able to identify individual risk of the disease in order to most effectively screen for breast cancer.

“Models that accurately predict an individual woman’s risk of developing breast cancer are paramount to transitioning from age-based screening to risk-based screening,” said Per Hall, professor, senior physician, Karolinska Institutet. “Most current risk models are population-based and focus on lifetime or long-term risk. Our research using the iCAD AI technology has shown that by simply using the information available in the mammogram images, we can more accurately stratify women based on short-term risk. Understanding short-term risk will open the door to new paradigms in both the prevention and treatment of breast cancer.”

iCAD announced the commercial availability of its ProFound AI for breast cancer detection in digital breast tomosynthesis in 2018. The algorithm delivers critical benefits, including improvements of cancer detection rates, a decrease in unnecessary patient recalls, and shorter reading times for radiologists.

For more information: www.icadmed.com

Related Content

CoronaCare is designed to help healthcare providers track COVID-19 (coronavirus) related symptoms of potentially infected patients. The platform enables communication with patients outside of facility walls and the ability to request the return of high-risk patients for more in-depth care. #COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2
News | Coronavirus (COVID-19) | March 27, 2020
March 27, 2020 — PaxeraHealth has spent years building and be
AI vendor Infervision's InferRead CT Pneumonia software uses artificial intelligence-assisted diagnosis to improve the overall efficiency of the radiology department. It is being developed in China as a high sensitivity detection aid for novel coronavirus pneumonia (COVID-19). #COVID19 #coronavirus #SARScov2

AI vendor Infervision's InferRead CT Pneumonia software uses artificial intelligence-assisted diagnosis to improve the overall efficiency of the radiology department. It is being developed in China as a high sensitivity detection aid for novel coronavirus pneumonia (COVID-19).

Feature | Coronavirus (COVID-19) | March 27, 2020 | Jilian Liu, M.D., HIMSS Greater China
An older couple walked into the Hubei Provincial Hospital of Integrated Chinese and Western Medicine near their neigh
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2
News | Mammography | March 25, 2020
March 25, 2020 — The...
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2
News | Artificial Intelligence | March 24, 2020
March 24, 2020 — Qure.ai, a leading healthcare...
Instant triage capability could potentially speed up diagnosis of COVID-19 individuals and ensure resources allocated properly.
News | Artificial Intelligence | March 23, 2020
March 23, 2020 — behold.ai announced that its artificial intellige
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2

Representative examples of the attention heatmaps generated using Grad-CAM method for (a) COVID-19, (b) CAP, and (c) Non-Pneumonia. The heatmaps are standard Jet colormap and overlapped on the original image, the red color highlights the activation region associated with the predicted class. COVID-19 = coronavirus disease 2019, CAP = community acquired pneumonia. Image courtesy of the journal Radiology

News | Coronavirus (COVID-19) | March 20, 2020
March 20, 2020 — An arti...
Varian received FDA clearance for its Ethos therapy in February 2020. It is an adaptive intelligence solution that uses onboard AI in the treatment system to take the cone beam CT imaging on the system, compare it to the treatment plan and deliver an entire adaptive treatment plan in a typical 15-minute treatment time slot, from patient setup through treatment delivery.

Varian received FDA clearance for its Ethos therapy in February 2020, shown here displayed for the first time at ASTRO 2019. It is an adaptive intelligence solution that uses onboard AI in the treatment system to take the cone beam CT imaging on the system, compare it to the treatment plan and deliver an entire adaptive treatment plan in a typical 15-minute treatment time slot, from patient setup through treatment delivery.

Feature | Treatment Planning | March 19, 2020 | Dave Fornell, Editor
The traditional treatment planning process takes days to create an optimized radiation therapy delivery plan, but new