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aview: CAC

AI-Driven Coronary Calcification Detection

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Radiology

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Coronary Artery
Calcification
Analysis Solution

Coronary Artery Disease is the Leading Global Cause of Mortality.

It Can Be Detected by Calcification Analysis from CT examination.

Medical AI Technology Achieves high accuracy of 99.2% in Coronary Artery Calcification Detection.

 

Conformity Certifications

MFDS

Republic of Korea

FDA

USA

PMDA

Japan

TFDA

TaIwan

CE

Europe

TGA

Australia

HSA

Singapore

ANVISA

Brazil

HC

Canada

 

Automate workflows

Reduce Work Fatigue and Save Time.

Medical AI Technology Replaces Cumbersome Manual Tasks.

Medical AI automatically segments and labels cardiac structures.
In complex cardiac structures, only the calcifications within the coronary arteries can be clearly detected, thereby improving the accuracy of cardiovascular disease analysis.
The task is completed quickly and accurately with low interreader variation.

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Analysis of chest CT images

Detect and analyze calcium within the coronary arteries from cardiac exams and chest CT images.

Proprietary kernel conversion technology improves accuracy and performance for quick analysis.

Identifying calcium on low-dose chest CT images can be challenging with the naked eye.Medical AI assists in detecting even those cardiovascular conditions that might be overlooked.

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Reading Assistance and Communication


Communication with patients becomes easier.

Accurate reading and swift processing.
Quantified 'Coronary Artery Calcium Score' makes diagnosis results easily comprehensible.

Patients and medical professionals can communicate more effectively and precisely with quantified results during consultations.

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Optimize the Utilization of Diagnosis Analysis Results

Are you working on a clinical study? Use rich results for your research.

An automated report is generated, providing accurate and detailed results.

The results include a calcification score, along with a detailed risk and age analysis by vessel, to assist patients in understanding their diagnosis. The analyzed result values are extracted as CSV files and PDF files and can be found within the PACS System.

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Validations

Our solution demonstrates remarkable concordance,not just in cardiac CT scans but also in low-dose CT (LDCT) scans.

cardiac CT imaging study
1
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Kappa
 

0.87

Risk Classification
Consistency

1
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ICC
 

0.958

Consistency

1
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Drug Treatment Target
Screening

99.2%

Accuracy

2
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R2
 

0.996

Correlation

  • Vonder M, Zheng S, Dorrius MD, van der Aalst CM, de Koning HJ, Yi J, Yu D, Gratama JWC, Kuijpers D, Oudkerk M. Deep Learning for Automatic Calcium Scoring in Population-Based Cardiovascular Screening. JACC Cardiovasc Imaging. 2022 Feb;15(2):366-367. doi: 10.1016/j.jcmg.2021.07.012. Epub 2021 Aug 18.
  • Aldana-Bitar J, Cho GW, Anderson L, Karlsberg DW, Manubolu VS, Verghese D, Hussein L, Budoff MJ, Karlsberg RP. Artificial intelligence using a deep learning versus expert computed tomography human reading in calcium score and coronary artery calcium data and reporting system classification. Coron Artery Dis. 2023 May 1. doi: 10.1097/MCA.0000000000001244. Epub ahead of print.
LowDose CT Imaging Study
3
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ICC
 

0.989

Consistency

  • Suh YJ, Kim C, Lee JG, Oh H, Kang H, Kim YH, Yang DH. Fully automatic coronary calcium scoring in non-ECG-gated low-dose chest CT: comparison with ECG-gated cardiac CT. Eur Radiol. 2023 eb;33(2):1254-1265. doi: 10.1007/s00330-022-09117-3. Epub 2022 Sep 13.
 

References:

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Fully automatic coronary calcium scoring in non-ECG-gated low-dose chest CT: comparison with ECG-gated cardiac CT

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Deep Learning for Automatic Calcium Scoring in Population-Based Cardiovascular Screening

 
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