CAC Software

by Imbio  · Based in United States → — AI-powered medical imaging analysis for personalized lung and cardiothoracic care.
Cardiology Radiology
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Regulatory Status Disclosed

Overview

Imbio’s CAC Software, now part of 4DMedical’s cardiopulmonary diagnostic suite, is a machine learning-based post-processing tool designed to analyze non-contrast computed tomography (CT) images of the chest. Its primary function is to assess and quantify calcified plaques in the coronary arteries, which are associated with coronary artery disease risk.

This software is intended for use by radiologists, cardiologists, and imaging technologists under physician supervision, within a radiology department setting. It is designed for adult patients aged 29 years or older.

The CAC Software integrates into standard DICOM viewing workflows, providing automated analysis without user intervention. It processes high-resolution CT DICOM images and generates a summary report. This report includes quantitative measures such as the Agatston score, arterial age, and calcified lesion mass and volume metrics for the whole heart and individual coronary arteries (LM, LAD, LCX, RCA). Additionally, the software outputs annotated images that preview the segmentation of calcifications. The results are routed directly to PACS for review.

Notable capabilities include its compatibility with various non-contrast chest CT scans, including new and existing, gated or ungated, standard or low-dose scans. It can be utilized as a component of lung cancer screening programs to opportunistically assess cardiovascular risk.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Automated image post-processing for coronary artery calcification
  • Quantification of calcification within coronary arteries
  • Outputs Agatston score, arterial age, calcified lesion mass and volume
  • Provides 3D visualizations and annotated images
  • Non-invasive analysis from non-contrast chest CT scans
  • Integrates into existing DICOM viewing workflow
  • Supports risk assessment for coronary artery disease
  • Deep-learning based analysis
  • Effective for gated or ungated CT scans, and low-dose CT scans
  • Identifies potential positive CAC findings and false positive artifacts

Use Cases

  • Coronary artery disease risk assessment
  • Evaluation of calcified plaques in coronary arteries
  • Lung cancer screening programs (as a component for low-dose CT scans)
  • Expediting diagnosis and guiding referrals for patients with breathlessness
  • Objective, reproducible quantification for radiologists
  • Distinguishing between cardiac and pulmonary causes of dyspnea

What Physicians Need to Know

ECG/EKG Analysis Capability
AI-powered algorithms can detect a weak heart pump (low ventricular ejection fraction), atrial fibrillation, and other faulty heart rhythms from ECGs, often before symptoms are evident. Some AI tools can also detect structural heart diseases from single-lead ECGs with high accuracy.
Echocardiography AI Features
AI tools can interpret echocardiograms with high accuracy, performing automated measurements of cardiac structures (e.g., ejection fraction, chamber volume, strain), classifying different views, and assisting in diagnosing conditions like severe aortic stenosis, systolic dysfunction, and cardiac amyloidosis. Some platforms can generate comprehensive, guideline-based echocardiographic reports.
Cardiac CT/MRI Analysis
AI algorithms automatically and consistently identify and measure coronary artery calcium (CAC) findings across non-gated, non-contrast CT exams, providing numerical calcium scores and categorization. These tools can also assess coronary artery segmentation, plaque assessment (calcified and non-calcified), and stenosis detection, enhancing diagnostic accuracy and refining risk stratification.
Arrhythmia Detection Accuracy
AI-powered ECG interpretation has shown high accuracy in detecting various arrhythmias, including atrial fibrillation, with some deep-learned algorithms clinically proven to be as accurate as cardiologists. These systems can achieve 95u201399% sensitivity for detecting arrhythmias.
Heart Failure Risk Prediction
AI models can predict heart failure risk years before diagnosis by analyzing extensive datasets, including genetic information, clinical data from electronic health records, ECGs, and CT scans. These tools can identify subtle patterns and risk factors not immediately apparent to clinicians.
Coronary Artery Assessment
AI solutions provide automatic and consistent measurement of CAC, categorizing plaque severity based on methods like Agatston scoring. They can also analyze non-calcified plaque volume and diameter stenosis percentages from CCTA, offering a comprehensive view of coronary artery disease and predicting future cardiovascular events.
Cardiac Monitoring Integration
The software seamlessly integrates with existing Picture Archiving and Communication Systems (PACS) and Electronic Medical Record (EMR) systems. It can also integrate with cardiac implantable electronic devices and wearable devices for continuous, real-time monitoring of ECG signals and other physiological data.
AHA/ACC Guideline Alignment
AI-driven solutions can generate comprehensive echocardiographic reports based on established clinical guidelines from authoritative bodies like the ASE/European Association of Cardiovascular Imaging (EACVI). Guideline integration in AI clinical decision support systems increases protocol adherence by 78%, standardizing care quality.
Real-Time Alert Capability
AI systems provide real-time cardiac risk assessments and intelligent critical alert management. They prioritize urgent clinical situations based on severity and patient-specific risk factors, analyzing multiple data streams to identify critical situations requiring immediate attention, and reducing critical event response time by 45%.
Physician Tip

Leverage AI-powered CAC software to opportunistically screen for cardiovascular risk from routine non-cardiac CT scans, identifying at-risk patients who might otherwise go undiagnosed. Integrate these tools into your workflow to enhance diagnostic accuracy for ECGs and echocardiograms, automate measurements, and predict heart failure risk earlier. Utilize real-time alerts for proactive intervention and to improve adherence to AHA/ACC guidelines, ultimately leading to more personalized and effective preventive care. Remember that while AI offers powerful assistance, clinical judgment remains paramount, especially in interpreting complex cases and considering individual patient contexts.

Seamless integration with existing hospital information systems, including EHR, PACS, and EMR, is crucial for maximizing the utility of CAC software. This allows for automated data flow, incorporation of AI results into patient reports, and efficient patient management and follow-up. Compatibility with various imaging modalities (CT, MRI, ultrasound) and cardiac monitoring devices (wearables, implantables) ensures a comprehensive approach to cardiovascular assessment.

Details

Category Cardiology AI
Pricing Contact for pricing
DeploymentCloud, On-premise, Partner platforms
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status 1 AI-estimated

Imbio CAC Software (K230112) is intended for use as a non-invasive post-processing software to evaluate calcified plaques in the coronary arteries from non-contrast thoracic CT images. It outputs a summary report containing Agatston score, arterial age, and calcified lesion mass and volume metrics.
Integrations
EHR Not specified
Specialties Cardiology, Radiology

What the Web Says

CAC Software, developed by IMBIO, appears to be a relatively new or niche product, as comprehensive reviews from a wide range of sources are limited. Information directly from physicians or extensive tech reviews is scarce. Most available information points to its function within healthcare IT, likely focusing on clinical decision support or data management, but detailed user experiences are not readily found on major review platforms like G2, Capterra, or Reddit.

Overall: Mixed

Strengths

  • Likely designed for specific healthcare IT needs (e.g., clinical data, decision support)
  • Potential for improving clinical workflows or data accuracy
  • Developed by IMBIO, suggesting a focus on medical or biological applications
  • May offer specialized features not found in general software
  • Could be beneficial for organizations seeking tailored healthcare solutions

Limitations

  • Limited public reviews and user feedback available
  • Scarcity of physician-specific opinions or detailed case studies
  • Lack of presence on major review sites (G2, Capterra) makes it hard to gauge user satisfaction
  • No readily available discussions or reviews on platforms like Reddit
  • Difficulty in assessing overall sentiment due to lack of data
  • May have a steep learning curve if specialized

Based on reviews from: IMBIO website, General web searches for 'CAC Software IMBIO reviews', Searches on G2, Capterra, Reddit for 'CAC Software' or 'IMBIO'

Last updated: 2026-07-18

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Press & Coverage

FDA
CAC Software by Imbio, Inc. receives FDA clearance
Imbio's CAC Software, a machine learning-based post-processing tool for analyzing non-contrast CT images to assess calcified plaques in coronary arteries, received FDA clearance on June 13, 2023. The software quantifies calcification burden by producing scores and metrics to help clinicians evaluate coronary artery disease risk.
2023-06
Physician AI Tools
Imbio CAC Software for Coronary Artery Calcification Assessment
Imbio's CAC Software is highlighted as a tool for automated, quantitative risk assessment for coronary artery disease using non-contrast chest CT scans, providing Agatston scores, arterial age, and 3D visualizations. It is designed for radiologists and cardiologists to aid in patient stratification and treatment planning.
unknown
Innolitics
Command Line as a Medical Device (CLaMD) - Imbio CAC Software
An article discussing Command Line as a Medical Device (CLaMD) mentions Imbio's CAC Software (K230112) as a single command-line executable program with a minimal user interface, outputting DICOM files and PDF reports. This indicates its integration into existing clinical workflows without a separate GUI.
2025-05
4DMedical (User Manual)
Imbio CAC Software User Manual
The Imbio CAC Software user manual details its intended use as a non-invasive post-processing software to evaluate calcified plaques in coronary arteries, utilizing machine learning to analyze non-contrast thoracic CT images. It generates a summary report with Agatston score, arterial age, and calcified lesion metrics.
unknown
FDA
FDA 510(k) Premarket Notification for Imbio CAC Software (K230112)
The FDA 510(k) premarket notification for Imbio CAC Software (K230112) specifies its use for quantifying detected possible calcifications in adult patients u2265 29 years of age, emphasizing that it does not diagnose coronary artery disease and its results are not for standalone clinical decision-making.
2023-06
Radiology AI Directory
Imbio CAC Software listed as FDA-cleared radiology AI for CT/CTA
Imbio's CAC Software is listed as an FDA-cleared radiology AI product for CT/CTA, indicating its official recognition for use in medical imaging for coronary artery calcification assessment.
unknown
FDA
Imbio CAC Software in FDA Total Product Life Cycle (TPLC) database
Imbio, Inc. and its CAC Software (K230112) are listed in the FDA's Total Product Life Cycle (TPLC) database, confirming its regulatory status and ongoing oversight by the FDA.
2026-07
Physician AI Tools
Imbio CAC Software compared to other AI tools
Imbio's CAC Software is noted for its highly specific and quantitative metrics, including Agatston score and arterial age, for coronary artery calcification from non-contrast chest CT scans, offering direct clinical insights for risk assessment. Its enterprise readiness is highlighted by integrations with partner platforms like Nuance and Siemens Syngo.via.
unknown

Videos

Product demos, reviews, and walkthroughs for CAC Software.

View all on YouTube

Frequently Asked Questions

CAC software, utilizing natural language processing (NLP) and machine learning, automates the medical coding process by analyzing clinical documentation and suggesting appropriate CPT and ICD-10 codes for cardiology services. This automation can significantly accelerate claim submission, reduce coding errors, and allow coding staff to focus on more complex tasks, ultimately improving efficiency and revenue cycle management.
CAC software helps ensure accuracy and compliance by interpreting clinical notes and cross-referencing them with extensive coding rules and guidelines specific to cardiology. It can identify potential compliance risks or missing documentation, thereby improving the integrity of claims. However, human oversight by experienced coders is still crucial for validating complex cases and ensuring adherence to evolving guidelines.
Primary alternatives include manual coding by certified professional coders, outsourcing coding to a third-party service, or using simpler encoder tools. While manual coding offers human expertise, it can be slower and more prone to error, whereas outsourcing provides specialized expertise without in-house overhead but may lack direct control. Full CAC systems aim to combine efficiency with accuracy, often with human review.
Pricing models for CAC software often vary, including per-user licenses, per-encounter fees, or subscription-based tiers that depend on the practice's size and required features. Factors influencing the cost typically include the level of integration with existing Electronic Health Records (EHRs), the sophistication of the AI, and the extent of ongoing support and updates provided by the vendor.
CAC software may struggle with highly nuanced or ambiguous clinical documentation, especially for novel cardiology procedures or complex interventional cases that lack clear precedents. It might require human intervention to clarify intent or interpret context that AI cannot fully grasp, and it can sometimes fail to identify vague or uncommon terminology.
CAC software uses AI, specifically Natural Language Processing (NLP) and machine learning, to analyze and understand clinical notes, suggesting codes based on identified patterns and rules. For data privacy and security, robust measures like encryption, strict access controls, and adherence to HIPAA regulations are crucial to protect sensitive patient health information (PHI) processed by these AI systems.
Significant human oversight by experienced cardiology coders or auditors remains essential, even with advanced CAC software. Human experts are needed to review suggested codes, validate complex cases, ensure compliance with payer-specific rules, and adapt to evolving coding guidelines, acting as a critical final check to prevent inaccuracies and potential compliance risks.

Compare CAC Software

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These tools are adjacent in their focus on cardiovascular health but differ significantly in their diagnostic approach. Imbio's CAC Software analyzes CT scans to quantify coronary artery calcification,…
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These tools are adjacent in their focus on cardiology AI but differ significantly in their diagnostic approach. Imbio's CAC Software analyzes CT scans for coronary artery calcification, providing…
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Suggest an Edit → | Last Verified: 2026-04-18 | First Added: 2026-04-18
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