80 FR 63671 - Medical Devices; Cardiovascular Devices; Classification of the Coronary Vascular Physiologic Simulation Software Device

DEPARTMENT OF HEALTH AND HUMAN SERVICES
Food and Drug Administration

Federal Register Volume 80, Issue 203 (October 21, 2015)

The Food and Drug Administration (FDA) is classifying the coronary vascular physiologic simulation software device into class II (special controls). The special controls that will apply to the device are identified in this order and will be part of the codified language for the coronary vascular physiologic simulation software device's classification. The Agency is classifying the device into class II (special controls) in order to provide a reasonable assurance of safety and effectiveness of the device.

[Federal Register Volume 80, Number 203 (Wednesday, October 21, 2015)]
[Rules and Regulations]
[Pages 63671-63674]
From the Federal Register Online  [www.thefederalregister.org]
[FR Doc No: 2015-26658]


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DEPARTMENT OF HEALTH AND HUMAN SERVICES

Food and Drug Administration

21 CFR Part 870

[Docket No. FDA-2015-N-3387]


Medical Devices; Cardiovascular Devices; Classification of the 
Coronary Vascular Physiologic Simulation Software Device

AGENCY: Food and Drug Administration, HHS.

ACTION: Final order.

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SUMMARY: The Food and Drug Administration (FDA) is classifying the 
coronary vascular physiologic simulation software device into class II 
(special controls). The special controls that will apply to the device 
are identified in this order and will be part of the codified language 
for the coronary vascular physiologic simulation software device's 
classification. The Agency is classifying the device into class II 
(special controls) in order to provide a reasonable assurance of safety 
and effectiveness of the device.

DATES: This order is effective October 21, 2015. The classification was 
applicable on November 26, 2014.

FOR FURTHER INFORMATION CONTACT: Shawn Forrest, Center for Devices and 
Radiological Health, Food and Drug Administration, 10903 New Hampshire 
Ave., Bldg. 66, Rm. 1326, Silver Spring, MD 20993-0002, 301-796-5554.

SUPPLEMENTARY INFORMATION:

I. Background

    In accordance with section 513(f)(1) of the Federal Food, Drug, and 
Cosmetic Act (the FD&C Act) (21 U.S.C. 360c(f)(1)), devices that were 
not in commercial distribution before May 28, 1976 (the date of 
enactment of the Medical Device Amendments of 1976), generally referred 
to as postamendments devices, are classified automatically by statute 
into class III without any FDA rulemaking process. These devices remain 
in class III and require premarket approval, unless and until the 
device is classified or reclassified into class I or II, or FDA issues 
an order finding the device to be substantially equivalent, in 
accordance with section 513(i) of the FD&C Act, to a predicate device 
that does not require premarket approval. The Agency determines whether 
new devices are substantially equivalent to predicate devices by means 
of premarket notification procedures in section 510(k) of the FD&C Act 
(21 U.S.C. 360(k)) and part 807 (21 CFR part 807) of the regulations.
    Section 513(f)(2) of the FD&C Act, as amended by section 607 of the 
Food and Drug Administration Safety and Innovation Act (Pub. L. 112-
144), provides two procedures by which a person may request FDA to 
classify a device under the criteria set forth in section 513(a)(1). 
Under the first procedure, the person submits a premarket notification 
under section 510(k) of the FD&C Act for a device that has not 
previously been classified and, within 30 days of receiving an order 
classifying the device into class III under section 513(f)(1) of the 
FD&C Act, the person requests a classification under section 513(f)(2). 
Under the second procedure, rather than first submitting a premarket 
notification under section 510(k) of the FD&C Act and then a request 
for classification under the first procedure, the person determines 
that there is no legally marketed device upon which to base a 
determination of substantial equivalence and requests a classification 
under section 513(f)(2) of the FD&C Act. If the person submits a 
request to classify the device under this second procedure, FDA may 
decline to undertake the classification request if FDA identifies a 
legally marketed device that could provide a reasonable basis for 
review of substantial equivalence with the device or if FDA determines 
that the device submitted is not of ``low-moderate risk'' or that 
general controls would be inadequate to control the risks and special 
controls to mitigate the risks cannot be developed.
    In response to a request to classify a device under either 
procedure provided by section 513(f)(2) of the FD&C Act, FDA will 
classify the device by written order within 120 days. This 
classification will be the initial classification of the device.
    On November 6, 2013, HeartFlow, Inc. submitted a request for 
classification of the FFRCT v.1.4 under section 513(f)(2) of 
the FD&C Act. The manufacturer recommended that the device be 
classified into class II (Ref. 1).
    In accordance with section 513(f)(2) of the FD&C Act, FDA reviewed 
the request in order to classify the device under the criteria for 
classification set forth in section 513(a)(1). FDA classifies devices 
into class II if general controls by themselves are insufficient to 
provide reasonable assurance of safety and effectiveness, but there is 
sufficient information to establish special controls to provide 
reasonable assurance of the safety and effectiveness of the device for 
its intended use. After review of the information submitted in the 
request, FDA determined that the device can be classified into class II 
with the

[[Page 63672]]

establishment of special controls. FDA believes these special controls, 
in addition to general controls, will provide reasonable assurance of 
the safety and effectiveness of the device.
    Therefore, on November 26, 2014, FDA issued an order to the 
requestor classifying the device into class II. FDA is codifying the 
classification of the device by adding 21 CFR 870.1415.
    Following the effective date of this final classification order, 
any firm submitting a premarket notification (510(k)) for a coronary 
vascular physiologic simulation software device will need to comply 
with the special controls named in this final order.
    The device is assigned the generic name coronary vascular 
physiologic simulation software device, and it is identified as 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.
    FDA has identified the following risks to health associated with 
this type of device, as well as the mitigation measures required to 
mitigate these risks, in table 1.

 Table 1--Coronary Vascular Physiologic Simulation Software Device Risks
                         and Mitigation Measures
------------------------------------------------------------------------
              Identified risk                    Mitigation measure
------------------------------------------------------------------------
False negative results improperly           Software verification,
 indicating diseased vessel as low           validation, and hazard
 probability for significant disease leads   analysis.
 to delay of further evaluation/treatment.  Non-clinical performance
                                             testing.
False positive results improperly           Clinical testing.
 indicating diseased vessel as high
 probability for significant disease leads
 to incorrect patient management.
Delayed delivery of results leading to      Consistency (repeatability/
 delay of further evaluation/treatment.      reproducibility)
                                             evaluation.
                                            Labeling.
Failure to properly interpret device        Human factors testing.
 results leads to incorrect patient         Labeling.
 management.
------------------------------------------------------------------------

    FDA believes that the following special controls, in combination 
with the general controls, address these risks to health and provide 
reasonable assurance of safety and effectiveness:
     Adequate software verification and validation based on 
comprehensive hazard analysis with identification of appropriate 
mitigations, must be performed including:
    [cir] Full characterization of the technical parameters of the 
software, including any proprietary algorithm(s) used to model the 
vascular anatomy;
    [ssquf] Adequate description of the expected impact of all 
applicable image acquisition hardware features and characteristics on 
performance and any associated minimum specifications;
    [cir] Adequate consideration of privacy and security issues in the 
system design; and
    [ssquf] 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.
     Adequate non-clinical performance testing must be provided 
to demonstrate the validity of computational modeling methods for flow 
measurement.
     Clinical data supporting the proposed intended use must be 
provided, including the following:
    [cir] 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;
    [cir] Clinical utility of the device measurement accuracy must be 
demonstrated by comparison to that of other available diagnostic tests 
(e.g., from literature analysis);
    [cir] Statistical performance of the device within clinical risk 
strata (e.g., age, relevant comorbidities, disease stability) must be 
reported;
    [cir] 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;
    [cir] Statistical methods must consider the predefined endpoints;
    [ssquf] Estimates of probabilities of incorrect results must be 
provided for each endpoint;
    [ssquf] Where multiple samples from the same patient are used, 
statistical analysis must not assume statistical independence without 
adequate justification;
    [ssquf] The report must provide appropriate confidence intervals 
for each performance metric;
    [cir] Sensitivity and specificity must be characterized across the 
range of available measurements;
    [cir] Agreement of the simulated measure(s) with clinically 
acceptable measure(s) must be assessed across the full range of 
measurements;
    [cir] Comparison of the measurement performance must be provided 
across the range of intended image acquisition hardware; and
    [cir] 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.
     Adequate validation must be performed and controls 
implemented to characterize and ensure consistency (i.e., repeatability 
and reproducibility) of measurement outputs;
    [cir] Acceptable incoming image quality control measures and the 
resulting image rejection rate for the clinical data must be specified;
    [cir] 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;
    [ssquf] 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
    [ssquf] The factors (e.g., medical imaging data set, 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.
     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

[[Page 63673]]

measurements require significant user intervention.
     Device labeling must be provided that adequately describes 
the following:
    [cir] 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;
    [cir] 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;
    [cir] Key assumptions made in the calculation and determination of 
simulated measurements;
    [cir] 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;
    [cir] 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
    [cir] 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.
    A coronary vascular physiologic simulation software device is not 
safe for use except under the supervision of a practitioner licensed by 
law to direct the use of the device. As such, the device is a 
prescription device and must satisfy prescription labeling requirements 
(see 21 CFR 801.109, Prescription devices).
    Section 510(m) of the FD&C Act provides that FDA may exempt a class 
II device from the premarket notification requirements under section 
510(k) of the FD&C Act if FDA determines that premarket notification is 
not necessary to provide reasonable assurance of the safety and 
effectiveness of the device. For this type of device, FDA has 
determined that premarket notification is necessary to provide 
reasonable assurance of the safety and effectiveness of the device. 
Therefore, this device type is not exempt from premarket notification 
requirements. Persons who intend to market this type of device must 
submit to FDA a premarket notification, prior to marketing the device, 
which contains information about the coronary vascular physiologic 
simulation software device they intend to market.

II. Environmental Impact, No Significant Impact

    The Agency has determined under 21 CFR 25.34(b) that this action is 
of a type that does not individually or cumulatively have a significant 
effect on the human environment. Therefore, neither an environmental 
assessment nor an environmental impact statement is required.

III. Paperwork Reduction Act of 1995

    This final order establishes special controls that refer to 
previously approved collections of information found in other FDA 
regulations. These collections of information are subject to review by 
the Office of Management and Budget (OMB) under the Paperwork Reduction 
Act of 1995 (44 U.S.C. 3501-3520). The collections of information in 
part 807, subpart E, regarding premarket notification submissions have 
been approved under OMB control number 0910-0120, and the collections 
of information in 21 CFR part 801, regarding labeling have been 
approved under OMB control number 0910-0485.

IV. Reference

    The following reference has been placed on display in the Division 
of Dockets Management (HFA-305), Food and Drug Administration, 5630 
Fishers Lane, Rm. 1061, Rockville, MD 20852, and may be seen by 
interested persons between 9 a.m. and 4 p.m., Monday through Friday, 
and is available electronically at http://www.regulations.gov.

1. DEN130045: De Novo Request from HeartFlow, Inc., dated November 
1, 2013.

List of Subjects in 21 CFR Part 870

    Medical devices.

    Therefore, under the Federal Food, Drug, and Cosmetic Act and under 
authority delegated to the Commissioner of Food and Drugs, 21 CFR part 
870 is amended as follows:

PART 870--CARDIOVASCULAR DEVICES

0
1. The authority citation for 21 CFR part 870 continues to read as 
follows:

    Authority:  21 U.S.C. 351, 360, 360c, 360e, 360j, 371.


0
2. Add Sec.  870.1415 to subpart B to read as follows:


Sec.  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);

[[Page 63674]]

    (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.

    Dated: October 14, 2015.
Leslie Kux,
Associate Commissioner for Policy.
[FR Doc. 2015-26658 Filed 10-20-15; 8:45 am]
 BILLING CODE 4164-01-P