(128 days)
HeartFlow Analysis is a coronary physiologic simulation software for the clinical quantitative and ysis 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.
The HeartFlow Analysis is a coronary physiological simulation software developed for the clinical quantitative and qualitative analysis of CT DICOM data. It is a tool for the analysis of CT DICOMcompliant cardiac images and data, to assess the anatomy and function of the coronary arteries.
The software displays the anatomy combined with function using graphics and text, including computed and derived quantities of blood flow, pressure and velocity, to aid the clinician in the assessment (diagnosis and treatment planning) of coronary artery disease.
HeartFlow FFR analyses are performed on previously physician-acquired image data and are unrelated to acquisition equipment and clinical workstations.
The new planner feature is also software, and uses as input the anatomic FFRct model, and an idealized model generated from the FFRct model. Just as a CFD solution is run on the anatomic FFRct model to get the color-coded FFRct Analysis, the planner feature runs a reduced order CFD solution for user selected combinations of the anatomic FFRct model and the idealized model.
Here's a breakdown of the HeartFlow Analysis device's acceptance criteria and the study information, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The provided 510(k) summary does not explicitly list quantitative acceptance criteria for the device's performance. Instead, it focuses on demonstrating that the device's new "Planner" feature, which uses a reduced-order CFD solution for user-selected combinations of anatomic and idealized models, produces FFRct results equivalent to those achieved with the existing FFRct solver for a given modified anatomy.
Therefore, accepting this interpretation, here's a table based on the information provided:
| Acceptance Criterion | Reported Device Performance |
|---|---|
| For a given modified anatomy (combinations of anatomic and idealized model), the FFRct results achieved with the Delta-solver are equivalent to those achieved with the FFRct solver. | The design verification test (DVT) ensured this equivalency. The results of all current and previously referenced testing conclude the device is acceptable for use. |
2. Sample Size Used for the Test Set and Data Provenance
The document does not specify the exact sample size used for the test set specifically for the Planner feature. It mentions "testing of various FFRct model modifications to represent a variety of vessel and lesion morphologies and their idealized state."
Regarding data provenance, the document states: "Summaries of pre-clinical studies were reviewed as part of a prior predicate review (K161772, the predicate to K182035). The results concluded the device was acceptable for use. The applicability of the clinical data is not effected by the changes proposed under the predicate K182035 nor this 510(k). No additional pre-clinical data is being provided with this submission." This indicates that previous clinical data was used, but details on country of origin or retrospective/prospective nature are not provided for the current submission's evaluation.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Experts
The document does not provide information on the number of experts or their qualifications used to establish ground truth for the test set of the Planner feature. The assessment appears to be a technical comparison between the two CFD solvers rather than a clinical ground truth adjudicated by experts.
4. Adjudication Method for the Test Set
The document does not describe an adjudication method for the test set, as the evaluation focuses on the technical equivalency of two computational solvers rather than subjective human assessment.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size
No MRMC comparative effectiveness study is mentioned for the current submission's evaluation of the Planner feature. The text highlights that "No additional pre-clinical data is being provided with this submission," suggesting the focus is on the technical changes rather than a new clinical trial.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done
Yes, a standalone evaluation was performed. The "design verification test (DVT)" focused on comparing the FFRct results produced by the Delta-solver (used by the "Planner" feature) with those from the FFRct solver (the existing algorithm) for a given modified anatomy. This is an algorithm-only comparison.
7. The Type of Ground Truth Used
For the evaluation of the Planner feature, the "ground truth" was effectively the output of the established FFRct solver for a modified anatomy. The goal was to demonstrate that the new "Delta-solver" within the Planner feature could produce equivalent results to this existing, validated computational model.
8. The Sample Size for the Training Set
The document does not provide information about the sample size of the training set.
9. How the Ground Truth for the Training Set Was Established
The document does not provide information about how the ground truth for the training set was established. The submission focuses on the new feature of the HeartFlow Analysis software and references previous predicate reviews for the underlying FFRct technology.
§ 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.