(129 days)
HeartFlow FFRct is a coronary physiologic simulation software for the clinical quantitative and qualitative analysis of previously acquired Computed Tomography DICOM data for clinically stable symptomatic patients with coronary artery disease. It provides FFRct a mathematically derived quantity, computed from simulated pressure, velocity and blood flow information obtained from a 3D computer model generated from static coronary CT images. FFRct analysis is intended to support the functional evaluation of coronary artery disease.
The results of this analysis are provided to support qualified clinicians to aid in the evaluation and assessment of coronary arteries. The results of HeartFlow FFRct are intended to be used by qualified clinicians in conjunction with the patient's clinical history, symptoms, and other diagnostic tests, as well as the clinician's professional judgment.
FFRct is coronary physiologic simulation software developed for the clinical quantitative and qualitative analysis of CT DICOM data. It is a tool for the analysis of CT DICOM-compliant cardiac images and data, to assess the anatomy and function of the coronary arteries.
The software displays the anatomy combined with functional information using graphics and text, including computed and derived quantities of blood flow, pressure and velocity, to aid the clinician in the assessment of coronary artery disease.
Here's a breakdown of the acceptance criteria and study information for the HeartFlow FFRct v 2.18 device, based on the provided text:
Acceptance Criteria and Device Performance (Based on K161772 Predicate, as no new data is presented for K182035):
Since the submitted K182035 explicitly states, "There is no change from the performance submitted as part of the predicate K161772" and "No additional pre-clinical or clinical data is being provided with this submission," the acceptance criteria and performance metrics are derived from the previous K161772 submission. The provided document itself does not detail the specific acceptance criteria or reported performance of the device in this text. It only states that the previous validation work for K161772 concluded the device was acceptable for use.
To fully answer this, the K161772 submission document would need to be reviewed. However, based solely on the provided text, we can infer that the device's acceptable performance was established in the prior submission.
| Acceptance Criteria (from K161772 submission) | Reported Device Performance (from K161772 submission) |
|---|---|
| Not specified in the provided text. | Not specified in the provided text. |
| (These would typically include metrics like diagnostic accuracy, sensitivity, specificity, PPV, NPV against a gold standard for detecting hemodynamically significant coronary artery disease, and possibly agreement with invasive FFR values.) | (The previous submission's results would be listed here.) |
Study Details (Inferred from reference to K161772):
The provided text for K182035 does not contain details of the study itself beyond confirming that "Software and medical device design validation was completed and reviewed as part of the predicate review (K161772)." Therefore, the following information is based on the implication that such studies were performed for the predicate device.
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Sample size used for the test set and the data provenance:
- Test Set Sample Size: Not specified in the provided text.
- Data Provenance: The document states that HeartFlow FFRct "is independent of imaging equipment, imaging protocols and equipment vendors; the clinical validation report includes identification of vendors and equipment used in the clinical validation of the product." This implies a varied source, but specific countries or retrospective/prospective nature are not specified in the provided text.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not specified in the provided text. (For the predicate K161772, this would typically involve invasive FFR experts or interventional cardiologists.)
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Adjudication method (e.g., 2+1, 3+1, none) for the test set:
- Not specified in the provided text.
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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:
- Not specified in the provided text. The device's stated indication is to "support qualified clinicians to aid in the evaluation and assessment," which implies it's an assistive tool, but a formal MRMC comparative effectiveness study (human vs. human + AI) is not mentioned.
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If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- The document describes FFRct as a "mathematically derived quantity, computed from simulated pressure, velocity and blood flow information obtained from a 3D computer model generated from static coronary CT images." This suggests the algorithm's performance in deriving FFRct values would be evaluated standalone against a ground truth (likely invasive FFR). The text also mentions "validation studies included stress testing, and repeatability testing to ensure the device performance," which would be standalone algorithm performance. However, specific standalone performance metrics (e.g., accuracy, concordance) and the study results are not detailed in the provided text. The indication for use, "to aid in the evaluation and assessment," also points to a standalone capability being critical before human integration.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
- Not specified in the provided text. For FFRct, the gold standard for clinical validation is typically invasive Fractional Flow Reserve (FFR) measurements.
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The sample size for the training set:
- Not specified in the provided text.
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How the ground truth for the training set was established:
- Not specified in the provided text. (Presumably, this would also rely on invasive FFR data or similar clinically validated measurements.)
Summary of what is explicitly stated regarding studies for K182035:
- The current submission (K182035) does not include new pre-clinical or clinical data.
- The performance claims rely entirely on the validation performed for the predicate device, K161772.
- The K161772 submission included "Software and medical device design validation" and "Validation studies included stress testing, and repeatability testing to ensure the device performance."
- These previous studies "concluded the device was acceptable for use."
To get the specific details requested in points 1-9 for the HeartFlow FFRct device, one would need to consult the original K161772 510(k) submission and its supporting documentation. The provided text is a summary for a new submission that references the predicate's established performance without re-submitting or detailing the original study data.
§ 870.1415 Coronary vascular physiologic simulation software device.
(a)
Identification. A coronary vascular physiologic simulation software device is a prescription device that provides simulated functional assessment of blood flow in the coronary vascular system using data extracted from medical device imaging to solve algorithms and yield simulated metrics of physiologic information (e.g., blood flow, coronary flow reserve, fractional flow reserve, myocardial perfusion). A coronary vascular physiologic simulation software device is intended to generate results for use and review by a qualified clinician.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Adequate software verification and validation based on comprehensive hazard analysis, with identification of appropriate mitigations, must be performed, including:
(i) Full characterization of the technical parameters of the software, including:
(A) Any proprietary algorithm(s) used to model the vascular anatomy; and
(B) Adequate description of the expected impact of all applicable image acquisition hardware features and characteristics on performance and any associated minimum specifications;
(ii) Adequate consideration of privacy and security issues in the system design; and
(iii) Adequate mitigation of the impact of failure of any subsystem components (
e.g., signal detection and analysis, data storage, system communications and cybersecurity) with respect to incorrect patient reports and operator failures.(2) Adequate non-clinical performance testing must be provided to demonstrate the validity of computational modeling methods for flow measurement; and
(3) Clinical data supporting the proposed intended use must be provided, including the following:
(i) Output measure(s) must be compared to a clinically acceptable method and must adequately represent the simulated measure(s) the device provides in an accurate and reproducible manner;
(ii) Clinical utility of the device measurement accuracy must be demonstrated by comparison to that of other available diagnostic tests (
e.g., from literature analysis);(iii) Statistical performance of the device within clinical risk strata (
e.g., age, relevant comorbidities, disease stability) must be reported;(iv) The dataset must be adequately representative of the intended use population for the device (
e.g., patients, range of vessel sizes, imaging device models). Any selection criteria or limitations of the samples must be fully described and justified;(v) Statistical methods must consider the predefined endpoints:
(A) Estimates of probabilities of incorrect results must be provided for each endpoint,
(B) Where multiple samples from the same patient are used, statistical analysis must not assume statistical independence without adequate justification, and
(C) The report must provide appropriate confidence intervals for each performance metric;
(vi) Sensitivity and specificity must be characterized across the range of available measurements;
(vii) Agreement of the simulated measure(s) with clinically acceptable measure(s) must be assessed across the full range of measurements;
(viii) Comparison of the measurement performance must be provided across the range of intended image acquisition hardware; and
(ix) If the device uses a cutoff threshold or operates across a spectrum of disease, it must be established prior to validation, and it must be justified as to how it was determined and clinically validated;
(4) Adequate validation must be performed and controls implemented to characterize and ensure consistency (
i.e., repeatability and reproducibility) of measurement outputs:(i) Acceptable incoming image quality control measures and the resulting image rejection rate for the clinical data must be specified, and
(ii) Data must be provided within the clinical validation study or using equivalent datasets demonstrating the consistency (
i.e., repeatability and reproducibility) of the output that is representative of the range of data quality likely to be encountered in the intended use population and relevant use conditions in the intended use environment;(A) Testing must be performed using multiple operators meeting planned qualification criteria and using the procedure that will be implemented in the production use of the device, and
(B) The factors (
e.g., medical imaging dataset, operator) must be identified regarding which were held constant and which were varied during the evaluation, and a description must be provided for the computations and statistical analyses used to evaluate the data;(5) Human factors evaluation and validation must be provided to demonstrate adequate performance of the user interface to allow for users to accurately measure intended parameters, particularly where parameter settings that have impact on measurements require significant user intervention; and
(6) Device labeling must be provided that adequately describes the following:
(i) The device's intended use, including the type of imaging data used, what the device measures and outputs to the user, whether the measure is qualitative or quantitative, the clinical indications for which it is to be used, and the specific population for which the device use is intended;
(ii) Appropriate warnings specifying the intended patient population, identifying anatomy and image acquisition factors that may impact measurement results, and providing cautionary guidance for interpretation of the provided measurements;
(iii) Key assumptions made in the calculation and determination of simulated measurements;
(iv) The measurement performance of the device for all presented parameters, with appropriate confidence intervals, and the supporting evidence for this performance. Per-vessel clinical performance, including where applicable localized performance according to vessel and segment, must be included as well as a characterization of the measurement error across the expected range of measurement for key parameters based on the clinical data;
(v) A detailed description of the patients studied in the clinical validation (
e.g., age, gender, race or ethnicity, clinical stability, current treatment regimen) as well as procedural details of the clinical study (e.g., scanner representation, calcium scores, use of beta-blockers or nitrates); and(vi) Where significant human interface is necessary for accurate analysis, adequately detailed description of the analysis procedure using the device and any data features that could affect accuracy of results.