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AI-CVD® is an opportunistic AI-powered quantitative imaging tool that provides automated CT-derived anatomical and density-based measurements for clinician review. The device does not provide diagnostic interpretation or risk prediction. It is solely intended to aid physicians and other healthcare providers in determining whether additional diagnostic tests are appropriate for implementing preventive healthcare plans. AI-CVD® has a modular structure where each module is intended to report quantitative imaging measurements for each specific component of the CT scan. AI-CVD® quantitative imaging measurement modules include coronary artery calcium (CAC) score, aortic wall calcium score, aortic valve calcium score, mitral valve calcium score, cardiac chambers volumetry, epicardial fat volumetry, aorta and pulmonary artery sizing, lung density, liver density, bone mineral density, and muscle & fat composition.

Using AI-CVD® quantitative imaging measurements and their clinical evaluation, healthcare providers can investigate patients who are unaware of their risk of coronary heart disease, heart failure, atrial fibrillation, stroke, osteoporosis, liver steatosis, diabetes, and other adverse health conditions that may warrant additional risk assessment, monitoring or follow-up. AI-CVD® quantitative imaging measurements are to be reviewed by radiologists or other medical professionals and should only be used by healthcare providers in conjunction with clinical evaluation.

AI-CVD® is not intended to rule out the risk of cardiovascular diseases. AI-CVD® opportunistic screening software can be applied to non-contrast thoracic CT scans such as those obtained for CAC scans, lung cancer screening scans, and other chest diagnostic CT scans. Similarly, AI-CVD® opportunistic screening software can be applied to contrast-enhanced CT scans such as coronary CT angiography (CCTA) and CT pulmonary angiography (CTPA) scans. AI-CVD® opportunistic bone density module and liver density module can be applied to CT scans of the abdomen and pelvis. All volumetric quantitative imaging measurements from the AI-CVD® opportunistic screening software are adjusted by body surface area (BSA) and reported both in cubic centimeter volume (cc) and percentiles by gender reference data from people who participated in the Multi-Ethnic Study of Atherosclerosis (MESA) and Framingham Heart Study (FHS). Except for coronary artery calcium scoring, other AI-CVD® modules should not be ordered as a standalone CT scan but instead should be used as an opportunistic add-on to existing and new CT scans.

AI-CVD® is an opportunistic AI-powered modular tool that provides automated quantitative imaging reports on CT scans and outputs the following measurements:

• Coronary Artery Calcium Score
• Aortic Wall and Valves Calcium Scores
• Mitral Valve Calcium Score
• Cardiac Chambers Volume
• Epicardial Fat Volume
• Aorta and Main Pulmonary Artery Volume and Diameters
• Liver Attenuation Index
• Lung Attenuation Index
• Muscle and Visceral Fat
• Bone Mineral Density

The above quantitative imaging measurements enable care providers to take necessary actions to prevent adverse health outcomes.

AI-CVD® modules are installed by trained personnel only. AI-CVD® is executed via parent software which provides the necessary inputs and receives the outputs. The software itself does not offer user controls or access.

AI-CVD® reads a CT scan (in DICOM format) and extracts scan specific information like acquisition time, pixel size, scanner type, etc. AI-CVD® uses trained AI models that automatically segment and report quantitative imaging measurements specific to each AI-CVD® module. The output of each AI-CVD® module is inputted into the parent software which exports the results for review and confirmation by a human expert.

AI-CVD® is a post-processing tool that works on existing and new CT scans.

AI-CVD® passes if the human expert approves the segmentation highlighted by the AI-CVD® module is correctly placed on the target anatomical region. For example, Software passes if the human expert sees the AI-CVD® cardiac chamber volumetry module highlighted the heart anatomy.

AI-CVD® fails if the human expert sees the segmentation highlighted by the AI-CVD® module is not correctly placed on the target anatomical region. For example, Software fails if the human expert sees the AI-CVD® cardiac chamber volumetry module highlighted the lungs anatomy or a portion of the sternum or any adjacent organs. Furthermore, Software fails if the human expert sees that the quality of the CT scan is compromised by image artifacts, severe motion, or excessive noise.

The user cannot change or edit the segmentation or results of the device. The user must accept or reject the segmentation where the AI-CVD® quantitative imaging measurements are performed.

AI-CVD® is an AI-powered post-processing tool that works on non-contrast and contrast-enhanced CT scans of chest and abdomen.

AI-CVD® is a multi-module deep learning-based software platform developed to automatically segment and quantify a broad range of cardiovascular, pulmonary, musculoskeletal, and metabolic biomarkers from standard chest or whole-body CT scans. AI-CVD® system builds upon the open-source TotalSegmentator as its foundational segmentation framework, incorporating additional supervised learning and model training layers specific to each module's clinical task.

The provided FDA 510(k) Clearance Letter for AI-CVD® outlines several modules, each with its own evaluation. However, the document does not provide a single, comprehensive table of acceptance criteria with reported device performance for all modules. Instead, it describes clinical validation studies and agreement analyses, generally stating "acceptable bias and reproducibility" or "acceptable agreement and reproducibility" without specific numerical thresholds or metrics. Similarly, detailed information on sample sizes, ground truth establishment methods (beyond general "manual reference standards" or "human expert knowledge"), and expert qualifications is quite limited for most modules.

Here's an attempt to extract and synthesize the information based on the provided text, recognizing the gaps:

Acceptance Criteria and Study Details for AI-CVD®

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria for each module. Instead, it describes performance in terms of agreement with manual measurements or gold standard references, generally stating "acceptable bias and reproducibility" or "comparable performance." The table below summarizes what is reported.

2. Sample Size and Data Provenance for the Test Set

• Coronary Artery Calcium (CAC) Score:
  • Sample Size: 913 consecutive coronary calcium screening CT scans.
  • Data Provenance: "Real-world" data acquired across three community imaging centers. This suggests a retrospective collection from a U.S. or similar healthcare system, though the specific country of origin is not explicitly stated. The term "consecutive" implies that selection bias was minimized.
• Other Modules (Aortic Wall/Valve, Mitral Valve, Epicardial Fat, Aorta/Pulmonary Artery, Liver, Lung, Muscle/Visceral Fat):
  • The document refers to "agreement analyses" and "agreement studies" but does not specify the sample size for the test sets used for these individual modules.
  • Data Provenance: The document generally states that "clinical validation studies were performed based upon retrospective analyses of AI-CVD® measurements performed on large population cohorts such as the Multi-Ethnic Study of Atherosclerosis (MESA) and Framingham Heart Study (FHS)." It is unclear if these cohorts were solely used for retrospective analysis, or if the "real-world" data mentioned for CAC was also included for other modules. MESA and FHS are prospective, longitudinal studies conducted primarily in the U.S.

3. Number of Experts and Qualifications for Ground Truth

• Coronary Artery Calcium (CAC) Score:
  • Number of Experts: Unspecified, referred to as "expert manual measurements."
  • Qualifications: Unspecified, but implied to be human experts capable of performing manual Agatston scoring.
• Other Modules:
  • Number of Experts: Unspecified, generally referred to as "manual reference standards" or "manual measurements."
  • Qualifications: Unspecified.

4. Adjudication Method for the Test Set

The document does not describe a specific adjudication method (e.g., 2+1, 3+1) for establishing ground truth on the test set. It mentions "expert manual measurements" or "manual reference standards," suggesting that the ground truth was established by human experts, but the process of resolving discrepancies among multiple experts (if any were used) is not detailed.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• Was an MRMC study done? No, the document does not describe an MRMC comparative effectiveness study where human readers' performance with and without AI assistance was evaluated. The performance data presented focuses on the standalone AI performance compared to human expert measurements.

• Effect Size of Human Reader Improvement: Not applicable, as an MRMC study was not described.

6. Standalone (Algorithm Only) Performance Study

• Was a standalone study done? Yes, the described performance evaluations for all modules (where new performance data was presented) are standalone performance studies. The studies compare the AI-CVD® algorithm's output directly against manual measurements or established reference standards.

7. Type of Ground Truth Used

• Coronary Artery Calcium Score: Expert manual measurements (Agatston scores).
• Aortic Wall and Aortic Valve Calcium Scores: Manual reference standards.
• Mitral Valve Calcium Score: Manual measurements.
• Epicardial Fat Volume: Manual measurements.
• Aorta and Main Pulmonary Artery Volume and Diameters: Manual reference measurements.
• Liver Attenuation Index: (Implicitly) Manual reference measurements or established methods for hepatic attenuation.
• Lung Attenuation Index: (Implicitly) Manual reference measurements or established methods for lung density.
• Muscle and Visceral Fat: (Implicitly) Manual reference measurements.
• Cardiac Chambers Volume & Bone Mineral Density: Leveraged previously cleared predicate devices, suggesting the ground truth for their original clearance would apply.

8. Sample Size for the Training Set

The document provides information on the foundational segmentation framework (TotalSegmentator) and hints at customization for AI-CVD® modules:

• TotalSegmentator (Foundational Framework):
  • General anatomical segmentation: 1,139 total body CT cases.
  • High-resolution cardiac structure segmentation: 447 coronary CT angiography (CCTA) scans.
• AI-CVD® Custom Datasets: The document states that "Custom datasets were constructed for coronary artery calcium scoring, aortic and valvular calcifications, cardiac chamber volumetry, epicardial and visceral fat quantification, bone mineral density assessment, liver fat estimation, muscle mass and quality, and lung attenuation analysis." However, it does not provide the specific sample sizes for these custom training datasets for each AI-CVD® module.

9. How Ground Truth for the Training Set Was Established

• TotalSegmentator (Foundational Framework): The architecture utilizes nnU-Net, which was trained on the described CT cases. Implicitly, these cases would have had expert-derived ground truth segmentations for training the neural network.
• AI-CVD® Custom Datasets: "For each module, iterative model enhancement was applied: human reviewers evaluated model-generated segmentations and corrected any inaccuracies, and these corrections were looped back into the training process to improve performance and generalizability." This indicates that human experts established and refined the ground truth by reviewing and correcting model-generated segmentations, which were then used for retraining. The qualifications of these "human reviewers" are not specified.

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