share_log

Innovative Data Featuring Nanox AI Cardiac Solution Showcased at SCCT 2024

Innovative Data Featuring Nanox AI Cardiac Solution Showcased at SCCT 2024

SCCt 2024展示了創新數據,展示了Nanox AI心臟解決方案。
Nano X Imaging ·  07/25 12:00

In a study conducted by Brigham & Women's Hospital, Nanox.AI-Based Analysis helps Reveal Coronary Artery Calcium in over 50% of IMID Patients; Lead author Brittany Weber, MD, PhD, declared as 'Young Investigator Awards' Winner

在Brigham&Women's醫院進行的一項研究中,Nanox.AI基於分析幫助揭示50%以上IMID患者的冠狀動脈鈣化; 領導作者Brittany Weber博士宣佈獲得“青年研究者獎”

In a study conducted by Jefferson Einstein Hospital, Nanox.AI Cardiac Solution Flags CAD High-Risk Patients, Drives Significant Revenue

在Jefferson Einstein醫院進行的一項研究中,Nanox.AI心臟解決方案標記CAD高危患者,推動顯著營收

Additional data presented by Corewell Health, Massachusetts General Hospital and Rabin Medical Center

由Corewell Health、麻省總醫院和Rabin醫療中心提出的額外數據

PETACH TIKVA, Israel, July 25, 2024 (GLOBE NEWSWIRE) -- NANO-X IMAGING LTD ("Nanox" or the "Company," Nasdaq: NNOX), an innovative medical imaging technology company, today announced that the AI Cardiac Solution (HealthCCSng) of its subsidiary, Nanox.AI Ltd., was highlighted in multiple scientific presentations at the 2024 Society of Cardiovascular Computed Tomography (SCCT) Annual Meeting.

以色列PETACH TIKVA,2024年7月25日 (全球新聞社)--醫療影像技術創新公司納斯達克(NNOX)的全資子公司Nanox.AI有限公司的AI心臟解決方案(HealthCCSng)在2024年心血管計算機體層成像協會(SCCT)年會的多個科學演示中得到了突出的介紹。

"We are encouraged by the implementation of our AI cardiac solution at esteemed healthcare systems, along with the continued validation through real-world studies of its potential to promote early detection and preventive care of cardiovascular disease," said Erez Meltzer, Nanox Chief Executive Officer and Acting Chairman. "We would also like to thank SCCT for the opportunity to showcase the outstanding clinical results of our AI cardiac solution."

“我們對我們的AI心臟解決方案在著名醫療系統中的實施以及通過現實世界的研究繼續驗證其促進心血管疾病早期檢測和預防保健的潛力感到鼓舞,” Nаnox首席執行官兼代理主席Erez Meltzer說。 “我們還要感謝SCCt提供展示我們的AI心臟解決方案出色臨床結果的機會。”

Findings presented at SCCT 2024 include:

SCCt 2024展示的研究結果包括:

Prevalence and Prognostic Implications of Incidentally Detected Coronary Artery Calcium Using Artificial Intelligence Analysis Among Individuals with Immune Mediated inflammatory Diseases

人工智能分析在免疫介導的炎症性疾病患者中意外檢測到冠狀動脈鈣化的普遍性及預後影響

  • Abstract Link (2024-A-817-SCCT)
  • Lead author Brittany Weber, MD, PhD, declared as 'Young Investigator Awards Winner' at conference
  • In a study conducted by Brigham & Women's Hospital, HealthCCSng was used to analyze non-cardiac, non-gated chest CT scans of patients with different types of immune mediated inflammatory disease (IMID) – systemic lupus erythematosus, psoriasis, and rheumatoid arthritis – which are associated with increased risk of cardiovascular disease.
  • The study demonstrates that Incidental Coronary Artery Calcification (CAC) on the CT scans of the IMID patients (identified and quantified by HealthCCSng), was found in over 50% of scanned patients and associated with all-cause mortality and adverse cardiovascular outcomes.
  • According to the study, Given the limitations of traditional cardiovascular risk calculators among IMID patients, this data demonstrates the potential of AI-based CAC scoring to offer better guidance for preventative therapies for that patient population.
  • 摘要鏈接(2024-A-817-SCCT)
  • 在會議上宣佈,領導作者Brittany Weber博士獲得“青年研究者獎”
  • 在Brigham&Women's醫院進行的一項研究中,使用HealthCCSng分析了不同類型免疫介導的炎症性疾病(IMID)患者的非心臟,非門控胸部CT掃描 - 系統性紅斑狼瘡,銀屑病和類風溼性關節炎 - 與心血管疾病風險增加有關。
  • 該研究表明,免疫介導性疾病患者CT掃描中意外檢測到的冠狀動脈鈣化(由HealthCCSng識別和量化)在超過50%的掃描患者中發現,並與所有原因的死亡和不良心血管結果有關。
  • 根據該研究,鑑於傳統心血管風險計算器在免疫介導性疾病患者中的侷限性,這些數據表明了基於AI的CAC評分的潛力,爲該患者人群提供更好的預防治療指南。

Optimizing Preventive Cardiology: Harnessing AI for Early Detection of Coronary Artery Disease

優化預防性心臟病學:利用AI早期檢測冠狀動脈疾病

  • Abstract Link (2024-A-573-SCCT)
  • Corewell Health reported that in the first full year of implementing HealthCCSng in its electronic medical records (EMR) system, HealthCCSng analyzed 32,650 chest CT scans and helped identify 3,721 new patients with medium or high CAC – a thirteen-fold increase over the 268 patients reported in the previous two years.
  • Corewell also reported decreased time to treatment, increased statin prescription rate, increased patient satisfaction with the actionable data concerning their cardiac risk, and improved patient compliance in treatment.
  • This observational study demonstrated that the Nanox.AI algorithm is useful in the process of identifying patients with undiagnosed Coronary Artery Disease (CAD) and that AI integrated into the EMR can positively impact population health goals.
  • 摘要鏈接(2024-A-573-SCCT)
  • Corewell Health報道,在其電子病歷(EMR)系統中第一完整年實施HealthCCSng後,HealthCCSng分析了32,650個胸部CT掃描,並幫助識別了3,721個CAC中等或高風險患者 - 是前兩年報告的268名患者的十三倍。
  • Corewell還報告了減少治療時間,增加他汀類處方率,增加患者對有關其心臟風險的可操作數據的滿意度和改善患者治療遵守的數據。
  • 這項觀察性研究表明,Nanox.AI算法在識別未診斷冠狀動脈疾病(CAD)的患者過程中很有用,並且將AI集成到EMR中可以積極影響人群健康目標。

AI Empowering Early Detection of CAD Patients for Improved Cardiac Care

AI賦能早期檢測CAD患者,改善心臟醫療保健

  • Abstract Link (2024-A-641-SCCT)
  • After being installed and implemented at Jefferson Einstein Hospital, HealthCCSng helped identify 757 patients aged 30 or above with CAC levels higher than 100 Agatston units.
  • Of these 757 identified patients, 179 met eligibility criteria to be automatically flagged for follow-up consultation and treatment.
  • Of these 179 eligible patients, 97 returned to Jefferson Einstein for visits totaling 308 total touchpoints.
  • The above-mentioned touchpoints generated up to $130,000 in revenue for the hospital.
  • This analysis shows both the clinical and economic effects of implementing an AI solution (HealthCCSng, Nanox.AI) to opportunistically screen large populations.
  • 摘要鏈接(2024-A-641-SCCT)
  • 在被安裝和實施於Jefferson Einstein醫院後,HealthCCSng幫助識別了757名年齡在30歲或以上的CAC水平超過100 Agatston單位的患者。
  • 在識別出的757名患者中,有179名符合自動標記後續隨訪諮詢和治療的資格要求。
  • 在這179名符合資格的患者中,有97人返回Jefferson Einstein進行了308次接觸。
  • 上述接觸產生了醫院高達130,000美元的營業收入。
  • 本分析展示了實施人工智能解決方案(HealthCCSng, Nanox.AI)進行大規模篩查的臨床和經濟效果。

Artificial–Intelligence-based Detection of Coronary Artery Calcium on Chest CT to Enhance Cardiovascular Risk Assessment of Individuals with Elevated Lipoprotein (a)

基於人工智能的冠狀動脈鈣化檢測可通過胸部CT以加強具有升高的脂蛋白(a)個體的心血管風險評估

  • Abstract Link (2024-A-820-SCCT)
  • In a study conducted by Massachusetts General Hospital and Brigham & Women's Hospital, HealthCCSng was used to analyze non-contrast chest CT scans of 260 patients who had measurements of lipoprotein a (Lp(a)), as part of clinical care.
  • A statistically significant correlation was found between levels of CAC and Lp(a) – a risk factor for coronary atherosclerosis – suggesting that this approach may be used to identify at-risk patients.
  • Such an approach may be used to identify higher risk individuals and screen patients for future clinical trials.
  • 摘要鏈接(2024-A-820-SCCT)
  • 在一項由馬薩諸塞州普通醫院和布里格姆女士醫院進行的研究中,使用HealthCCSng分析對260名進行臨床醫療的磁共振成像患者的非造影胸腔CT掃描圖像。
  • 發現CAC水平和Lp(a)(冠狀動脈粥樣硬化的危險因素)之間存在顯著相關性,表明該方法可以用於識別高危人群。
  • 這種方法可用於識別高風險個體並篩選未來的臨床試驗患者。

Opportunistic Screening of Coronary Artery Calcification on Non-gated Conventional CT scans Using Artificial Intelligence

利用人工智能對非標記常規CT掃描機上的冠狀動脈鈣化進行機會篩查

  • Abstract Link (2024-A-532-SCCT)
  • In a study conducted by Rabin Medical Center, HealthCCSng was used to analyze non-gated, non-contrast chest CT scans of 631 patients.
  • 84 clinically relevant patients were classified as having high CAC levels and invited to a dedicated outpatient preventive cardiology clinic.
  • 20 patients were referred to myocardial perfusion imaging and 2 were referred for invasive coronary angiography.
  • This data suggests that AI-based CAC evaluation can help identify patients who may benefit from preventive cardiology services.
  • Using HealthCCSng, Rabin Medical Center was able to identify new patients with severe CAC who were previously unknown to the health system and as a result, these patients were scheduled to visit the preventive cardiology clinic.
  • 摘要鏈接(2024-A-532-SCCT)
  • 在一項由Rabin醫療中心進行的研究中,使用HealthCCSng分析了631名患者的非標記、非造影胸腔CT掃描圖像。
  • 分類爲CAC水平高的84名臨床相關患者被邀請參加專門的門診預防心臟病診所。
  • 20名患者被轉介入行心肌灌注成像檢查,2名患者被轉介入行侵入性冠狀動脈造影。
  • 這些數據表明基於人工智能的CAC評估可以幫助識別需要預防心臟病服務的患者。
  • 通過使用HealthCCSng,Rabin醫療中心能夠識別出先前未知於醫療系統的嚴重CAC的新患者,從而爲這些患者安排訪問預防心臟病診所。

About Nanox.AI
Nanox.AI is the deep-learning medical imaging analytics subsidiary of Nanox. Nanox.AI's solutions are developed to target highly prevalent chronic and acute diseases affecting large populations around the world. Leveraging AI technology, Nanox.AI helps clinicians extract valuable and actionable clinical insights from routine medical imaging that otherwise may go unnoticed, potentially initiating further medical assessment to establish individual preventative care pathways for patients. For more information, please visit .

關於Nanox.AI
Nanox.AI是Nanox的深度學習醫學圖像分析子公司。Nanox.AI的解決方案是爲了針對全球大規模影響的慢性和急性疾病而開發的。藉助人工智能技術,Nanox.AI幫助臨床醫生從常規醫學成像中提取有價值和可操作的臨床見解,否則這些可能會被忽視,從而可能引發進一步的醫學評估,爲患者建立個體化的預防護理路徑。有關更多信息,請訪問。

About Nanox
Nanox (NASDAQ: NNOX) is focused on applying its proprietary medical imaging technology and solutions to make diagnostic medicine more accessible and affordable across the globe. Nanox's vision is to increase access, reduce costs and enhance the efficiency of routine medical imaging technology and processes, to improve early detection and treatment, which Nanox believes is key to helping people achieve better health outcomes, and, ultimately, to save lives. The Nanox ecosystem includes Nanox.ARC— a multi-source Digital Tomosynthesis system that is cost-effective and user-friendly; an AI-based suite of algorithms that augment the readings of routine CT imaging to highlight early signs often related to chronic disease (Nanox.AI); a cloud-based infrastructure (Nanox.CLOUD); and a proprietary decentralized marketplace, through Nanox's subsidiary, USARAD Holdings Inc., that provides remote access to radiology and cardiology experts; and a comprehensive teleradiology services platform (Nanox.MARKETPLACE). Together, Nanox's products and services create a worldwide, innovative, and comprehensive solution that connects medical imaging solutions, from scan to diagnosis. For more information, please visit .

關於Nanox
Nanox(納斯達克:NNOX)致力於應用其專有的醫學成像技術和解決方案,使全球診斷醫學更爲普及和經濟實惠。 Nanox的願景是提高運用醫學成像技術和處理流程的效率,降低成本,提高早期檢測和治療效率,從而幫助人們實現更好的健康成果,最終拯救生命。 Nanox生態系統包括多源數字斷層攝影系統Nanox.ARC——成本效益高、易於使用;一個基於人工智能的算法套裝,用於增強常規Ct成像的閱讀,以突出與慢性疾病相關的早期跡象(Nanox.AI);以及雲基礎設施(Nanox.CLOUD)。通過Nanox的子公司USARAD Holdings Inc提供遠程訪問放射學和心臟病學專家的專有分散式市場;以及一個全面的遠程放射學服務平台(Nanox.MARKETPLACE)。 Nanox的產品和服務共同創造了一個連接醫學影像解決方案從掃描到診斷的全球創新全面解決方案。有關更多信息,請訪問。

Contacts

聯繫方式

Media Contact:
Ben Shannon
ICR Westwicke
NanoxPR@icrinc.com

媒體聯繫人:
本·香農
ICR Westwicke
NanoxPR@icrinc.com

Investor Contact:
Mike Cavanaugh
ICR Westwicke
mike.cavanaugh@westwicke.com

投資者聯繫人:
邁克·卡瓦諾
ICR Westwicke
mike.cavanaugh@westwicke.com


譯文內容由第三人軟體翻譯。


以上內容僅用作資訊或教育之目的,不構成與富途相關的任何投資建議。富途竭力但無法保證上述全部內容的真實性、準確性和原創性。
    搶先評論