February 28, 2024 — iCAD, Inc., a global leader in clinically proven AI-powered solutions that enable medical providers to accurately and reliably detect cancer earlier and improve patient outcomes, will highlight scientific presentations, including an award-winning poster at the European Congress of Radiology (ECR) annual meeting in Vienna, Austria, Feb 28 – March 3, 2024. The Company also announced it will highlight a new release for its AI-powered ProFound Detection solution while showcasing its full Breast Health Suite in booth X1 AI-35.
“The data presented at ECR demonstrate the real-world ability to improve efficiency and accuracy in mammography breast screening—from reducing workloads without compromising accuracy to potentially reducing interval cancer rates and expediting diagnosis for true positive cases. These findings underscore ProFound AI’s transformative power to improve breast healthcare,” said Dana Brown, president and CEO of iCAD.
“Furthermore, we are thrilled to showcase new workstation features to improve the readability of iCAD’s primary solution, ProFound Detection,” continued Brown. “This includes limiting lesion marks to the three highest-scoring lesions, which may be color-coded based on lesion score. Additionally, the ProFound Scorecard may be color-coded based on case score categories, with options for score range fine-tuning based on a facility’s real-world data. For radiologists, these latest enhancements further improve and facilitate their reading of mammograms.”
New Research
The following three oral and award-winning poster presentations highlight the clinical research being presented at ECR 2024. Detailed information may be found here.
Friday, March 1, 8:00 – 9:00 am, RPS1202 – Adding Artificial Intelligence (AI) Case Malignancy Scoring in a Breast Screening Program to Reduce Screen-Reading Workload: A Retrospective Study. The study conducted by A. Nitrosi et al. at the Reggio Emilia Breast Screening Program in Italy aimed to assess the integration of iCAD’s artificial intelligence mammography case malignancy scoring (AI-CMS) into a breast screening program to alleviate screen-reading workload without compromising accuracy. Analyzing data from 31,747 screening exams, including 92 proven tumors, the study simulated two integrated AI and human reading protocols (ProFound AI 2D system). Results showed that implementing ProFound AI-CMS could substantially reduce the number of human readings and workload by 24.8% to 30.6%, with a modest improvement in recall rate and no increase in false negatives observed with 10% and 15% Case Score thresholds.
Sunday, March 3, 9:30 – 11:00 am, RPS2305 – Retrospective Evaluation of Interval Breast Cancer: Can the Number of Interval Carcinomas be Reduced Utilizing AI Diagnostic Software? In this study conducted by Jonas Subelack et al., researchers from the University of St. Gallen and Krebsliga Ostschweiz in Switzerland and Radiologie am Theater in Germany assessed whether iCAD’s ProFound AI could help reduce interval carcinomas (ICs). Analyzing data from 151,245 screening mammograms between 2010 and 2019, the study identified 264 ICs where cancer was detected within 24 months after screening that was considered normal. Expected results anticipate improved IC detection rates with the software compared to initial screening, with detection accuracy influenced by set thresholds. The study expects the software to outperform radiologists in IC detection, suggesting potential integration into mammography screening to reduce ICs.
Sunday, March 3, 11:30 am – 12:30 pm - RPS 2405 – Adding Artificial Intelligence (AI) Case Malignancy Scoring in a Breast Screening Program to Overcome Delay in Most Probably True Positive Cases: A Retrospective Study. The retrospective study at the Reggio Emilia Breast Screening Program in Italy led by A. Nitrosi et al. aimed to assess the efficacy of implementing iCAD’s ProFound AI case scoring strategy in a breast screening program to expedite the reading process for potentially true positive cases, ensuring compliance with local regulations requiring readings within two weeks. Analyzing data from 32,012 2D mammography screening exams, the study utilized the ProFound AI 2D system. The AI-generated Case Scores, representing the algorithm's confidence in malignancy, were used to prioritize readings. Results showed that reading screening exams above certain Case Score thresholds identified 61% to 89% of screen-detected cancers while requiring only 5.4% to 20% of screening exams to be read. Notably, prioritizing readings of exams with Case Scores above 40% allowed for the recall of the majority (85%) of true positive cases within a short time frame.
ECR 2024 Awarded - Certificate of Merit
E-Poster Presentation – Breast Arterial Calcification (BAC): A Proxy for Medium and Large Vessel Atherosclerotic Calcium. In this retrospective study by C. Parghi et al., researchers investigated the correlation between breast arterial calcification (BAC) as detected by ProFound AI Heart Health on screening mammograms from Solis Mammography and the extent of atherosclerotic disease observed on CT imaging within 12 months of the mammogram. Analyzing data from 1,449 women, they found that a BAC score of 3 or more was associated with a significantly higher rate of clinically significant atherosclerotic disease in large and medium vessels compared to a BAC score of less than 3. Specifically, the rate increased from 11.0% to 31.0% (p < 0.001). The sensitivity, specificity, and accuracy for detecting clinically significant atherosclerotic disease when the BAC score was 3 or more were 21.8%, 92.9%, and 83.8% respectively. These findings suggest that quantitative BAC assessment could offer insight and potentially identify those who need further cardiovascular screening.
Chirag Parghi, M.D., chief medical officer of Solis Mammography and a pioneer in the use of mammography to assess BAC, won the Certificate of Merit award for this poster presentation. “I am encouraged by our findings, which highlight the potential of Breast Arterial Calcification (BAC) assessment in revolutionizing access to cardiovascular risk assessment. Our research demonstrates the significance of a quantitative BAC score indicating a higher likelihood of clinically significant atherosclerotic disease elsewhere in the body, identifying individuals who may benefit from further cardiovascular screening. These results continue to advocate for screening mammography as a portal to screen for both breast cancer and cardiovascular risk, the top two causes of death in women worldwide."
Enhancements for ProFound Detection for 2D and 3D Mammography
The new workstation features included in the updates to ProFound Detection’s Third Generation solution were designed to improve readability of iCAD results through a configuration option to limit to three lesion marks visible on a 3D view. This refinement ensures that radiologists can interpret the most critical information without multiple markings, streamlining the diagnostic process for more efficient decision-making.
Moreover, the introduction of color-coded lesion marks and case score on the ProFound Scorecard provides an intuitive visual aid, allowing radiologists to discern the suspicion level of detected abnormalities quickly. This color-coded system, based on cancer occurrence per screening population, offers a concise, comprehensive representation of the severity of detected lesions and the overall case, further facilitating accurate diagnosis and prioritization of cases.
Additionally, support for the ability to fine-tune score ranges based on real-world data enables users to customize the detection system according to their specific clinical needs, supporting performance and adaptability to varying patient populations.
Lastly, iCAD will highlight expanded cloud platform and subscription licensing plans marking a significant advancement in deployment flexibility. iCAD’s new Success Program offers a full range of ongoing software updates to ensure customers have the latest version of iCAD’s AI offerings, system maintenance, and customer support.
For more information: www.icadmed.com
April 25, 2024 
