(203 days)
CardIQ Suite is a non-invasive software application designed to provide an optimized application to analyze cardiovascular anatomy and pathology based on 2D or 3D CT cardiac non contrast and angiography DICOM data from acquisitions of the heart. It provides capabilities for the visualization and measurement of vessels and visualization of chamber mobility. CardIQ Suite also aids in diagnosis and determination of treatment paths for cardiovascular diseases to include, coronary artery disease, functional parameters of the heart, heart structures and follow-up for stent placement, bypasses and plaque imaging. CardIQ Suite provides calcium scoring, a non-invasive software application, that can be used with non-contrasted cardiac images to evaluate calcified plaques in the coronary arteries, heart valves and great vessels such as the aorta. The clinician can use the information provided by calcium scoring to monitor the progression/regression of calcium in coronary arteries overtime, and this information may aid the clinician in their determination of the prognosis of cardiac disease. CardIQ Suite also provides an estimate of the volume of heart fat for informational use.
CardIQ Suite is a non-invasive software application designed to work with DICOM CT data acquisitions of the heart. It is a collection of tools that provide capabilities for generating measurements both automatically and manually, displaying images and associated measurements in an easy-to-read format and tools for exporting images and measurements in a variety of formats.
CardIQ Suite provides an integrated workflow to seamlessly review calcium scoring and coronary CT angiography (CCTA) data. Calcium Scoring has a fully automatic capability which will detect calcifications within the coronary arteries, label the coronary arteries according to regional territories and generate a total and per territory calcium score based on the AJ 130 and Volume scoring methods. Interactive tools allow editing of both the auto scored coronary lesions and other calcified lesions such as aortic valve, mitral valve as well as other general cardiac structures. Calcium scoring results can be compared with two percentile guide databases to better understand a patient's percentage of risk based on age, gender, and ethnicity. Additionally, for these non-contrasted exams, the heart fat estimation automatically estimates values within the heart that constitute adipose tissue, typically between –200 and –30 Hounsfield Units.
Calcium Scoring results can be exported as DICOM SR, batch axial SCPT, or a PDF report to assist with integration into structured reporting templates. Images can be saved and exported for sharing with referring physicians, incorporating into reports and archiving as part of the CT examination.
The Multi-Planar Reformat (MPR) Cardiac Review and Coronary Review steps provide an interactive toolset for review of cardiac exams. Coronary CTA datasets can be reviewed utilizing the double oblique angles to visually track the path of the coronary arteries as well as to view the common cardiac chamber orientations. Cine capability for multi-phase data may be useful for visualization of cardiac structures in motion such as chambers, valves and arteries, automatic tracking and labeling will allow a comprehensive analysis of the coronaries. Vessel lumen diameter is calculated, and the minimum lumen diameter computed is shown in color along the lumen profile.
Distance measurement and ROI tools are available for quantitative evaluation of the anatomy. Vascular findings of interest can be identified and annotated by the user, and measurements can be calculated for centerline distances, cross-sectional diameter and area, and lumen minimum diameter.
Let's break down the acceptance criteria and study details for the CardIQ Suite device based on the provided FDA 510(k) clearance letter.
1. Table of Acceptance Criteria and Reported Device Performance
The document provides specific acceptance criteria and performance results for the novel or modified algorithms introduced in the CardIQ Suite.
| Feature/Algorithm Tested | Acceptance Criteria | Reported Device Performance |
|---|---|---|
| New Heart Segmentation (non-contrast CT exams) | More than 90% of exams successfully segmented. | Met the acceptance criteria of more than 90% of the exams that are successfully segmented. |
| New Heart Fat Volume Estimate (non-deep learning) | Average Dice score $\ge$ 90%. | Average Dice score is greater than or equal to 90%. (Note: Under or over estimation may occur due to inaccurate heart segmentation). |
| New Lumen Diameter Quantification (non-deep learning) | Mean absolute difference between estimated diameters and reference device (CardIQ Xpress 2.0) diameters lower than the mean voxel size. | The mean absolute difference is lower than the mean voxel size, demonstrating sufficient agreement for lumen quantification. |
| Modified Coronary Centerline Tracking | Performance is enhanced when compared to the predicate device. | Proven that the performance of these algorithms is enhanced when compared to the predicate device. |
| Modified Coronary Centerline Labeling | Performance is enhanced when compared to the predicate device. | Proven that the performance of these algorithms is enhanced when compared to the predicate device. |
2. Sample Sizes Used for the Test Set and Data Provenance
- Heart Segmentation (non-contrast CT exams): 111 CT exams
- Heart Fat Volume Estimate: 111 CT exams
- Lumen Diameter Quantification: 94 CT exams with a total of 353 narrowings across all available test sets.
- Coronary Centerline Tracking and Labeling: "a database of retrospective CT exams." (Specific number not provided for this particular test, but it is part of the overall bench testing.)
Data Provenance: The document states that the CT exams used for bench testing were "collected from different clinical sites, with a variety of acquisition parameters, and pathologies." It also notes that this database is "retrospective." The country of origin is not explicitly stated in the provided text.
3. Number of Experts Used to Establish Ground Truth and Qualifications
The document does not explicitly state the number of experts used or their specific qualifications (e.g., radiologist with 10 years of experience) for establishing the ground truth for the test sets. The tests are described as "bench testing" and comparisons to a "reference device" (CardIQ Xpress 2.0) or to an expectation of "successfully segmented."
4. Adjudication Method for the Test Set
The document does not explicitly describe an adjudication method (e.g., 2+1, 3+1). The performance is reported based on comparisons to a reference device or meeting a quantitative metric (e.g., Dice score, successful segmentation percentage, mean absolute difference).
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
The document does not mention or describe that a multi-reader multi-case (MRMC) comparative effectiveness study was done. The focus is on the performance of the algorithms themselves ('bench testing') and their enhancement compared to predicates, rather than human reader improvement with AI assistance.
6. Standalone (Algorithm Only Without Human-in-the-Loop) Performance
Yes, the studies described are standalone performance evaluations of the algorithms. They are referred to as "bench testing" and evaluate the device's algorithms directly against defined metrics or a reference device, without involving human readers in a diagnostic setting for performance comparison.
7. Type of Ground Truth Used
The type of ground truth used varies based on the specific test:
- Heart Segmentation (non-contrast CT exams) & Heart Fat Volume Estimate: The ground truth for these appears to be implicitly established by what constitutes "successfully segmented" or against which the "Dice score" is calculated. A "predefined HU threshold" is mentioned for heart fat, suggesting a quantitative, rule-based ground truth related to Hounsfield Units within segmented regions.
- Lumen Diameter Quantification: The ground truth for this was established by comparison to diameters from the reference device, CardIQ Xpress 2.0 (K073138).
- Coronary Centerline Tracking and Labeling: The ground truth for evaluating enhancement compared to the predicate is not explicitly defined but would likely involve some form of expert consensus or highly accurate manual delineation, which is then used to assess the "enhancement" of the new algorithm.
8. Sample Size for the Training Set
The document does not provide the sample size for the training set. It only mentions that the "new deep learning algorithm for heart segmentation of non-contrasted exams uses the same model as the previous existing heart segmentation algorithm for contrasted exams, however now the input is changed, and the model is trained and tested with the non-contrasted exams." Similarly for coronary tracking, it states the deep learning algorithm was "retrained to a finer resolution." However, no specific training set sizes are given.
9. How the Ground Truth for the Training Set Was Established
The document does not explicitly state how the ground truth for the training set was established. It is noted that the models were "trained," which implies the existence of a ground truth for the training data, but the methodology for its establishment (e.g., expert annotation, semi-automated methods) is not described in the provided text.
§ 892.1750 Computed tomography x-ray system.
(a)
Identification. A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.