(94 days)
CathWorks FFRangio™ is a software device for the clinical quantitative analysis of previously acquired angiography DICOM data for patients with coronary artery disease. It provides FFRangio™, a mathematically derived quantity, computed from simulated blood flow information obtained from a 3D computer model, generated from coronary angiography images. FFRangio™ analysis is intended to support the functional evaluation of coronary artery disease. The results of this analysis are provided as a supportive aid for qualified clinicians in the evaluation and assessment of coronary arteries physiology. The results of CathWorks FFRangio™ 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 evaluation.
FFRancio uses standard angiographic images that are retrieved from the X-ray Imaging System (C-arm) in DICOM format. The user selects the images and, following the system prompts, marks key features on the images including the target lesion, ostium location, main vessel, target vessel, and its side branches. The system then matches the corresponding vessels among the projections and generates a 3D computer model of the vessels. The 3D model is used for blood flow analysis and determination of the FFRangio.
The modified FFRangio system, designated as model FAU4000, consists of the following components:
- Touch screen control console located either as a fixed installation in the cath lab on . an extension arm mounted on the wall or from the ceiling, or on a desktop or mobile cart in the cath lab or control room
- Processing Unit located in the cath lab machine room / control room ●
- 3D Mouse located at the patient bedside ●
- Connection Box located in either the cath lab or control room ●
The system supports optional visual media output to the cath lab main displays, so the system GUI may be observed on both the system's Console display and on the cath lab's main display (boom monitor).
The provided text describes a Special 510(k) submission for the FFRangio System, focusing on hardware and software changes to a previously cleared device. Therefore, the information regarding the acceptance criteria and the study proving the device meets these criteria primarily refers to the original FFRangio System (K182149), as the current submission (K192442) asserts that the changes do not affect the fundamental scientific technology or the indications for use.
Here's a breakdown of the requested information based on the provided text:
Acceptance Criteria and Device Performance
The core performance metrics presented are Sensitivity and Specificity, which were established during the pivotal clinical study of the predicate (original) FFRangio System.
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (from predicate study) | Reported Device Performance (from predicate study) |
|---|---|
| Sensitivity (Lower 95% CI) | 93.5% (lower 95% CI, 87.8%) |
| Specificity (Lower 95% CI) | 91.2% (lower 95% CI, 86.0%) |
2. Sample Size and Data Provenance
The document does not explicitly state the sample size used for the test set of the original pivotal clinical study, nor does it specify the country of origin or whether the data was retrospective or prospective. It only mentions "the FFRangio pivotal clinical study."
For the current 510(k) submission (K192442), which pertains to modifications, the performance data cited is from the previous clearance. The specific tests conducted for this Special 510(k) (e.g., software validation, electrical safety, human factors) are not for clinical performance.
3. Number of Experts and Qualifications for Ground Truth Establishment
The document does not provide details on the number of experts or their specific qualifications (e.g., "radiologist with 10 years of experience") used to establish the ground truth for the pivotal clinical study. It refers to the FFRangio pivotal clinical study generally.
4. Adjudication Method for the Test Set
The document does not specify the adjudication method (e.g., 2+1, 3+1, none) used for the test set of the original pivotal clinical study.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
The document does not indicate that a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done to show how much human readers improve with AI vs. without AI assistance. The described "FFRangio pivotal clinical study" provided standalone performance metrics (sensitivity and specificity).
6. Standalone (Algorithm Only) Performance
Yes, a standalone performance evaluation was implicitly done, as the sensitivity and specificity values are presented as performance characteristics of the FFRangio system itself, independent of human-in-the-loop performance improvement. These metrics ("Sensitivity* and specificity are the per vessel estimates as determined from the FFRangio pivotal clinical study") describe the algorithm's diagnostic accuracy.
7. Type of Ground Truth Used
The document does not explicitly state the type of ground truth used (e.g., expert consensus, pathology, outcomes data) for the FFRangio pivotal clinical study.
8. Sample Size for the Training Set
The document does not provide information about the sample size used for the training set.
9. How the Ground Truth for the Training Set Was Established
The document does not provide information on how the ground truth for the training set was established.
§ 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.