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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.

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.

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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 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 of calcium in coronary arteries over time, and this information may aid the clinician in their determination of the prognosis of cardiac disease.

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 measurement's 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 the capability to automatically segment and label the calcifications within the coronary arteries, and then automatically compute a total and per territory calcium score. The calcium segmentation/labeling is using a new deep learning algorithm. The calcium scoring is based on the standard Agatston/Janowitz 130 (AJ 130) and Volume scoring methods for the segmented calcific regions. The software also provides the users a manual calcium scoring capability that allows them to edit (add/delete or update) auto scored lesions. It also allows the user to manually score calcific lesions within coronary arteries, aorta, aortic valve and mitral valve as well as other general cardiac structures. Calcium scoring offers quantitative results in the AJ 130 score, Volume and Adaptive Volume scoring methods.

Calcium Scoring results can be exported as DICOM SR 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. Distance measurement and ROI tools are available for quantitative evaluation of the anatomy.

Based on the provided text, here is a description of the acceptance criteria and the study that proves the device meets them:

Device: CardIQ Suite (K233731)
Functionality being assessed: Automated Heart Segmentation, Coronary Tree Segmentation, Coronary Centerline Tracking, and Coronary Artery Labeling (all utilizing new deep learning algorithms).

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance

• Test Set (Reader Study): A "sample of clinical CT images" was used. The exact number of cases is not specified.
• Test Set (Bench Testing): A "database of retrospective CT exams" was used. The exact number of cases is not specified.
• Data Provenance: The text does not explicitly state the country of origin. The bench testing data is described as "representative of the clinical scenarios where CardIQ Suite is intended to be used," suggesting it covers relevant acquisition protocols and clinical indicators. Both studies are retrospective ("retrospective CT exams" for bench testing and "sample of clinical CT images" for the reader study implying pre-existing data).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Number of Experts: A "reader study evaluation was performed," indicating multiple readers. The exact number is not explicitly stated.
• Qualifications of Experts: The text refers to them as "readers." Their specific qualifications (e.g., "radiologist with 10 years of experience") are not detailed.

4. Adjudication method for the test set

The reader study used "Likert Scales and Additional Grading Scales" for evaluation. The specific adjudication method (e.g., 2+1, 3+1 consensus) for establishing a definitive ground truth or resolving discrepancies among readers is not detailed in the provided text. Scores were "to be acceptable by the readers," implying individual reader agreement or perhaps a simple majority/threshold.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

Yes, a reader study was performed, which is a type of MRMC study in a sense.
The study did not directly measure human reader improvement with AI vs. without AI assistance quantitatively (e.g., AUC increase). Instead, it focused on the acceptability of the AI-generated outputs.
However, the conclusion states an perceived improvement in workflow efficiency: "Based on the reader study evaluation, we conclude that the automation of Heart Segmentation, Coronary Tree Segmentation, Coronary Centerline Tracking and Coronary Artery Labeling provides an improvement in workflow efficiency when compared to the predicate and reference devices wherein these functionalities were performed manually by the user or using traditional algorithms."

The effect size (quantification of improvement) in terms of reader diagnostic performance is not provided, only the qualitative statement about workflow efficiency and the acceptability of the AI's outputs.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done

Yes, a standalone evaluation of the algorithms was performed as "Engineering has performed bench testing for the four newly introduced deep learning algorithms... The result of the algorithm validation showed that the algorithm successfully passed the defined acceptance criteria." This bench testing implies an assessment of the algorithm's performance independent of human interaction for its specific outputs against some predefined criteria.

7. The type of ground truth used

• For the Reader Study: The ground truth for evaluating the acceptability of the automated outputs was based on the "scores" given by human "readers" using Likert Scales and Additional Grading Scales. This is a form of expert consensus/reader assessment of the AI's output quality.
• For the Bench Testing for Algorithm Validation: The text states "the algorithm successfully passed the defined acceptance criteria". While the exact nature of this "defined acceptance criteria" is not specified, it would typically involve comparing algorithm output to a reference standard, which could be expert-annotated ground truth, a pre-established gold standard, or other quantitative metrics. The document does not specify if it was pathology, outcomes data, or expert consensus. It likely involved expert-derived annotations or quantitative metrics on the retrospective CT exams.

8. The sample size for the training set

The sample size for the training set is not provided in the given text.

9. How the ground truth for the training set was established

The method for establishing ground truth for the training set is not provided in the given text.

Ask a specific question about this device

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. Calcium Scoring may be used to monitor the progression of calcium in coronary arteries overtime, which may aid in the prognosis of cardiac disease.

CardlQ 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 measurement's 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 the capability to automatically segment and label the calcifications within the coronary arteries, and then automatically compute a total and per territory calcium score. The calcium segmentation/labeling is using algorithm. The calcium scoring is based on the standard Agatston/Janowitz 130 (AJ 130) and Volume scoring methods for the segmented calcific regions. The software also provides the users a manual calcium scoring capability that allows them to edit (add/delete or update) auto scored lesions. It also allows the user to manually score calcific lesions within coronary arteries, aorta, aortic valve as well as other general cardiac structures. Calcium scoring offers quantitative results in the AJ 130 score, Volume and Adaptive Volume scoring methods.

Calcium Scoring results can be exported as DICOM SR 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.

CardlQ Suite provides the Coronary 2D Review toolset which allows interactive 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 such as chambers, valves and arteries in motion. Distance measurement and ROI tools are available for quantitative evaluation of the anatomy.

Here's a breakdown of the acceptance criteria and study details for the CardIQ Suite, based on the provided FDA 510(k) summary:

Acceptance Criteria and Device Performance

Study Details

2. Sample size used for the test set and the data provenance

• Test Set Sample Size: The summary mentions "a representative set of clinical sample images" for the clinical testing. A specific number is not provided.
• Data Provenance: The study used a "database of retrospective CT exams." The country of origin is not specified. It is likely internal data from GE Medical Systems SCS or collaborating institutions.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Number of Experts: Three.
• Qualifications of Experts: "Three board certified radiologists." Specific experience (e.g., years) is not mentioned.

4. Adjudication method for the test set

• The summary states that "Three board certified radiologists manually scored a representative set of clinical sample images using the predicate device." It then compares these manual scores to the automated scores. This implies that the manual scores (generated by the three radiologists using the predicate device) served as the reference standard or ground truth against which the automated algorithm's performance was compared. There is no explicit mention of an adjudication method like 2+1 or 3+1 among the radiologists themselves to reach a single consensus before comparison with the AI.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

• No, a multi-reader multi-case (MRMC) comparative effectiveness study with human readers improving with AI assistance vs. without AI assistance was not explicitly described.
• The clinical study performed was a comparison of the algorithm's standalone performance against manual scoring performed by radiologists using the predicate device. It did not evaluate human reader performance with or without AI assistance.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• Yes, a standalone algorithm performance study was done for the Calcium Scoring algorithm. The study compared the automated score outputted by CardIQ Suite with manual scores provided by radiologists using the predicate device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

• The ground truth used was expert manual scoring (by three board-certified radiologists) using the predicate device (SmartScore 4.0). This serves as a form of expert consensus or reference standard for comparison.

8. The sample size for the training set

• The summary does not provide a specific sample size for the training set. It mentions that the algorithm was validated using "a database of retrospective CT exams" which is "representative of the clinical scenarios" but does not differentiate between training and test sets by size.

9. How the ground truth for the training set was established

• The summary does not explicitly detail how the ground truth for the training set was established. It only describes the validation process (testing set) where radiologists manually scored images. It is generally understood that for deep learning algorithms, training data would also require some form of expert-annotated ground truth, but this document does not provide those specifics for the training phase.

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Syngo.CT Cardiac Function is an image analysis software package for evaluating cardiac CT angiography (CTA) volume data sets. Combining digital image processing and visualization tools (multiplanar reconstruction (MPR) thin/thick, minimum intensity projection (MIP) thin/thick, inverted MIP thin/thick, volume rendering technique (VRT)), evaluation tools (left and right ventricular (LV/RV) volume calculation, left ventricular myocardial wall calculation and visualization of myocardial enhancement by color coding of hypo-/hyperdense areas) and reporting tools (finding location, finding characteristics and key images), the software package is designed to support the physician in determining the functional parameters of the left and right ventricles, confirming the presence of physician-identified myocardial enhancement defects and evaluation, documentation and follow-up of any such finding.

These visualization/evaluation tools allow for quantification of functional parameters and characterization of myocardial enhancements defects over time, helping the physician to assess any changes. It is also designed to help the physician classify conspicuous regions of tissue.

Syngo.CT Cardiac Function is an image analysis software package for evaluating cardiac CT angiography (CTA) volume data sets. Combining digital image processing and visualization tools (multiplanar reconstruction (MPR) thin/thick, minimum intensity projection (MIP) thin/thick, inverted MIP thin/thick, volume rendering technique (VRT)), evaluation tools (left and right ventricular (LV/RV) volume calculation, left ventricular myocardial wall calculation and visualization of myocardial enhancement by color coding of hypo-/hyperdense areas) and reporting tools (finding location, finding characteristics and key images), the software package is designed to support the physician in determining the functional parameters of the left and right ventricles, confirming the presence or absence of physician-identified myocardial enhancement defects and evaluation, documentation and follow-up of any such finding.

These visualization/evaluation tools allow for quantification of functional parameters and characterization of myocardial enhancements defects over time, helping the physician to assess any changes. It is also designed to help the physician classify conspicuous regions of tissue.

I am sorry, but the provided text does not contain specific acceptance criteria or an explicit study proving the device meets those criteria. The document is a 510(k) summary for the Siemens syngo.CT Cardiac Function software, primarily focused on establishing substantial equivalence to previously cleared devices.

It mentions that "The testing results supports that all the software specifications have met the acceptance criteria" in section 10, but it does not detail:

• What those acceptance criteria are.
• The specifics of the study that demonstrates the device meets these criteria (e.g., sample size, data provenance, ground truth establishment, expert qualifications, adjudication methods, or specific performance metrics).
• Any multi-reader multi-case (MRMC) comparative effectiveness studies or standalone performance studies with quantitative results.

Therefore, I cannot provide the requested table and detailed information based on the given input.

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