Study confirms iCAD's Breast Arterial Calcification AI Algorithm successfully detects calcification of breast vessels, an indicator of cardiovascular disease, from mammograms
NASHUA, N.H., April 08, 2024 (GLOBE NEWSWIRE) -- iCAD, Inc. (NASDAQ: ICAD), a global leader in clinically proven AI-powered cancer detection solutions, announced today that new data indicates its AI-powered solution effectively uncovers calcium deposits in the breast vessels, a sign of possible cardiovascular disease in women. iCAD research collaborator Chirag Parghi, M.D., Chief Medical Officer of Solis Mammography, presented the findings at the American College of Cardiology (ACC) annual meeting taking place April 6 - 8, 2024, in Atlanta, GA.
For the study, Dr. Parghi and his team included mammograms from a multiracial cohort of 117,189 women, using iCAD's ProFound AI Heart Healthi solution, specifically designed for Breast Arterial Calcification (BAC) detection. The 15-site prospective study included 2D screening mammograms from women ages 20 to 100, with a median age of 56.
"The ProFound BAC AI algorithm may provide a critical surrogate biomarker for women at risk of heart disease or stroke," said Dana Brown, president and CEO of iCAD. "We are thrilled to be able to collaborate with Solis Mammography on this state-of-the-art software that gives women the power of knowing—earlier—if they are at potential risk of heart disease during a routine screening mammogram. This provides women valuable information that may lead to obtaining additional cardiovascular screening. We anticipate that ProFound Heart Health will positively impact cardiovascular disease prevention for women as iCAD's ProFound Detection and Risk solutions do for breast cancer."
Analyzing the data of the prospective study involving 117,189 women, Dr. Parghi and his team found the overall prevalence of BAC (score >1) was 14.8%. Prevalence increased with age, with a 4.2% prevalence in women under 50 years old, 9.0% in women aged 50-59, 19.9% in women in the 60-69 year-old age group, and 40.7% in women 70 years and above. Future work includes tracking patients longitudinally to identify associated cardiovascular risk factors and guiding primary care physicians in managing patients with detected BAC. The study also suggests the ProFound Heart Health AI algorithm can standardize BAC detection, potentially improving efficiency and reducing variability among observers. These findings also align with previous literature emphasizing the association between BAC and cardiovascular risk, underscoring potential opportunity of BAC detection on screening mammography for women's health.
"Artificial Intelligence software can be used to detect breast arterial calcifications with high accuracy," said Dr. Parghi. "With this tool, we will be able to identify patients that can benefit from additional cardiovascular screening, potentially intervening before adverse outcomes manifest. To be able to have one screening mammogram unveil meaningful insights for two of the leading causes of death for women – breast cancer and heart disease – is remarkable."
"At present, radiologists must rely on visual detection of breast arterial calcifications, which is time-consuming and leads to consistent underreporting of BAC results," continued Dr. Parghi. "With an AI algorithm accurately identifying BAC, we will see more consistent BAC detection and reporting, which will ultimately benefit patients the most."
Recent research shows that calcium deposits inside the blood vessels of the breast correlate to hardening of the cardiovascular arteries, and women with BAC are 51% more likely to develop heart disease. Early cardiovascular disease detection is key, as among asymptomatic women, the first manifestation of underlying coronary heart disease is often acute myocardial infarction (MI) or sudden death. Although women tend to have a lower burden of obstructive coronary artery disease on angiography, they typically have a worse prognosis after MI compared with men.
研究证实 iCad 的乳房动脉钙化 AI 算法成功地从乳房 X 光检查中检测出乳房血管钙化,这是心血管疾病的指标
新罕布什尔州纳舒厄,2024年4月8日(GLOBE NEWSWIRE)——临床验证的人工智能癌症检测解决方案的全球领导者iCad, Inc.(纳斯达克股票代码:ICAD)今天宣布,新数据表明其人工智能驱动的解决方案可有效发现乳腺血管中的钙沉积,这表明女性可能患有心血管疾病。iCad研究合作者奇拉格·帕尔吉医学博士,Solis首席医学官 Mography在2024年4月6日至8日在乔治亚州亚特兰大举行的美国心脏病学会(ACC)年会上介绍了研究结果。
在这项研究中,帕尔吉博士和他的团队使用iCad专为乳房动脉钙化(BAC)检测而设计的ProFound AI Heart Healthi解决方案,对117,189名多种族女性进行了乳房X光检查。这项15个地点的前瞻性研究包括对20至100岁的女性进行2D筛查的乳房X光检查,中位年龄为56岁。
iCad总裁兼首席执行官达娜·布朗表示:“InforDoun BAC AI算法可以为有心脏病或中风风险的女性提供重要的替代生物标志物。”“我们很高兴能够与Solis Mammography合作开发这种最先进的软件,该软件使女性能够更早地知道自己在常规乳房X光检查中是否有患心脏病的潜在风险。这为女性提供了宝贵的信息,可能有助于获得额外的心血管筛查。我们预计,Inforend Heart Health 将对女性心血管疾病的预防产生积极影响,就像 iCad 的 Inforend 检测和风险解决方案一样,对乳腺癌的预防产生积极影响。”
帕尔吉博士和他的团队分析了涉及117,189名女性的前瞻性研究的数据,发现BAC的总体患病率(分数>1)为14.8%。患病率随着年龄的增长而增加,50岁以下女性的患病率为4.2%,50-59岁的女性为9.0%,60-69岁年龄组的女性为19.9%,70岁及以上的女性为40.7%。未来的工作包括纵向跟踪患者以确定相关的心血管危险因素,以及指导初级保健医生管理检测到的BAC患者。该研究还表明,Inforoud Heart Health AI算法可以标准化BAC检测,从而有可能提高效率并减少观察者之间的变异性。这些发现也与先前强调BAC与心血管风险之间关联的文献一致,突显了BAC检测在筛查乳房X光检查以检查女性健康方面的潜在机会。
帕尔吉博士说:“人工智能软件可用于高精度检测乳房动脉钙化。”“有了这个工具,我们将能够识别出可以从额外心血管筛查中受益的患者,有可能在不良结果出现之前进行干预。能够进行一次乳房X光检查,为女性两个主要死因——乳腺癌和心脏病——揭示有意义的见解,这真是了不起。”
帕尔吉博士继续说:“目前,放射科医生必须依靠目视检测乳房动脉钙化,这非常耗时,而且会导致BAC结果持续低报。”“通过精确识别BAC的人工智能算法,我们将看到更加一致的BAC检测和报告,这最终将使患者受益最大。”
最近的研究表明,乳房血管内的钙沉积与心血管硬化有关,患有BAC的女性患心脏病的可能性要高51%。早期发现心血管疾病是关键,因为在无症状的女性中,潜在冠心病的第一个表现通常是急性心肌梗塞(MI)或猝死。尽管女性接受血管造影检查的阻塞性冠状动脉疾病的负担往往较低,但与男性相比,她们在心肌梗死后的预后通常较差。