[Federal Register Volume 80, Number 203 (Wednesday, October 21, 2015)]
[Rules and Regulations]
[Pages 63671-63674]
From the Federal Register Online via the Government Publishing Office [www.gpo.gov]
[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
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Identified risk Mitigation measure
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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.
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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