The HeartFlow Analysis is an AI-based medical device software for the clinical quantitative and qualitative analysis of previously acquired Computed Tomography DICOM data for patients with suspected coronary artery disease. It provides anatomic data, plaque identification and characterization, as well as the calculations of FFRCT, a coronary physiological simulation, computed from simulated pressure, velocity and blood flow information obtained from a 3D computer model generated from static coronary CT images. The HeartFlow Analysis is intended to support the risk assessment and functional evaluation of coronary artery disease.

The HeartFlow Analysis is provided to support qualified clinicians to aid in the evaluation and risk assessment of coronary artery disease. The HeartFlow Analysis is 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.

Device Description

The HeartFlow Analysis is an Al-based medical device 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 in the risk stratification and evaluation of coronary artery disease.

The software displays coronary and functional information using graphics and text, including computed and derived quantities of percent stenosis, plaque volumes, blood flow, pressure and velocity, to aid the clinician in the assessment and treatment planning of coronary artery disease.

The HeartFlow Analysis is performed on previously physician-acquired image data and is unrelated to acquisition equipment and clinical workstations.

AI/ML Overview

Here's a breakdown of the acceptance criteria and study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not explicitly state specific acceptance criteria with numerical targets or thresholds. It generally discusses "validation studies including stress testing, and repeatability testing to ensure the safety and effectiveness of the device" and that "results concluded the device was acceptable for use."

However, based on the context of the device and its intended use, we can infer general performance areas. Since no specific acceptance criteria are given, the "Reported Device Performance" column will reflect the general conclusion from the document.

Criteria Area (Inferred)	Acceptance Criteria (Not Explicitly Stated)	Reported Device Performance
Safety and Effectiveness	Device is safe and effective for its intended use.	Validation studies included stress testing and repeatability testing. Medical device design validation has been completed, encompassing testing and evaluation using previously acquired diagnostic images from HeartFlow-sponsored clinical trials. Results concluded the device was acceptable for use.
Accuracy of FFRct Calculation	FFRct calculations are accurate.	The device computes FFRct, a coronary physiological simulation, from simulated pressure, velocity, and blood flow information obtained from a 3D computer model generated from static coronary CT images. No specific accuracy metrics are provided in this document, but implies accuracy through its intended use and general validation.
Plaque Identification/Characterization	Plaque identification and characterization is accurate.	The device provides plaque identification and characterization, as well as anatomic data. Supported by comparison to the Autoplaque predicate device. Implies accuracy through intended use and general validation.
Anatomic Data Extraction	Accurate extraction of anatomic data.	The device extracts anatomic data to aid in risk assessment and functional evaluation. Implies accuracy through intended use and general validation.

2. Sample Size for Test Set and Data Provenance

Sample Size for Test Set: The document states that testing and evaluation used "previously acquired diagnostic images received through HeartFlow sponsored clinical trials." However, a specific number for the test set sample size is not provided.
Data Provenance: The data was "previously acquired diagnostic images received through HeartFlow sponsored clinical trials." This suggests the data is retrospective (already acquired) and likely originates from various clinical trial sites, but specific countries are not mentioned.

3. Number of Experts Used to Establish Ground Truth and Qualifications

The document does not specify the number of experts used or their qualifications for establishing ground truth for the test set.

4. Adjudication Method for the Test Set

The document does not describe an adjudication method (e.g., 2+1, 3+1).

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

The provided text does not mention if an MRMC comparative effectiveness study was done, nor does it specify an effect size of human readers' improvement with AI vs. without AI assistance. The focus is on the device's standalone validation.

6. Standalone (Algorithm Only) Performance

Yes, a standalone (algorithm only) performance assessment was done. The document states:

"The software was designed, developed, tested and validated according to written procedures."
"Validation studies included stress testing, and repeatability testing to ensure the safety and effectiveness of the device."
"Medical device design validation has been completed. Medical device design included testing and evaluation using previously acquired diagnostic images received through HeartFlow sponsored clinical trials."
"Summaries of pre-clinical studies were reviewed as part of a prior predicate review (K161772, the original predicate of K182035/K190925/K203329). The results concluded the device was acceptable for use."

This indicates that the device's performance was evaluated independently without human intervention during the "testing and evaluation" phase described, proving its standalone capabilities.

7. Type of Ground Truth Used

The document implies that the ground truth was established through clinical diagnosis and evaluation of the "previously acquired diagnostic images" from HeartFlow-sponsored clinical trials. While it doesn't explicitly state "expert consensus," this is the most likely method for establishing ground truth in clinical trials concerning coronary artery disease diagnoses from images. No mention of pathology or outcomes data as direct ground truth is made in this specific excerpt for the validation studies mentioned.

8. Sample Size for the Training Set

The document states: "The core technology remains unchanged from the primary predicate and continues to be trained using deep learning (AI and machine learning) since 2015, to incorporate learnings from the volumes of CT data and studies."

However, a specific sample size for the training set is not provided. It only mentions "volumes of CT data and studies."

9. How the Ground Truth for the Training Set Was Established

The document implies that the ground truth for the training set was established through "learnings from the volumes of CT data and studies." Similar to the test set, this would likely involve expert interpretation and analysis of the CT data used for training the deep learning algorithms, reflecting accepted clinical diagnoses and findings within those studies. No further details are given.

Summary

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October 14, 2022

HeartFlow, Inc. Windi Hary Chief Regulatory and Quality Officer 1400 Seaport Boulevard. Building B Redwood City, California 94063

Re: K213857

Trade/Device Name: HeartFlow Analysis Regulation Number: 21 CFR 870.1415 Regulation Name: Coronary Vascular Physiologic Simulation Software Device Regulatory Class: Class II Product Code: PJA, LLZ Dated: October 11, 2022 Received: October 13, 2022

Dear Windi Hary:

We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.

If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.

Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's

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requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (OS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.

For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely,

for

LCDR Stephen Browning Assistant Director Division of Cardiac Electrophysiology, Diagnostics, and Monitoring Devices Office of Cardiovascular Devices Office of Product Evaluation and Ouality Center for Devices and Radiological Health

Enclosure

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Indications for Use

510(k) Number (if known) K213857

Device Name HeartFlow Analysis

Indications for Use (Describe)

Type of Use (Select one or both, as applicable)
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Prescription Use (Part 21 CFR 801 Subpart D)

Over-The-Counter Use (21 CFR 801 Subpart C)

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This 510(k) summary of safety and effectiveness information is submitted in accordance with the requirements of 21 CFR Part 807.87(h).

1 Submitter Information

Submitter / Manufacturer Name:	HeartFlow, Inc.331 E. Evelyn AveMountain View, CA 94041
Primary Contact Person:	Windi Hary, RACChief Regulatory and Quality OfficerHeartFlow, Inc.331 E. Evelyn Ave,Mountain View, CA 94041T +1 (650) 241-1250F +1 (650) 368-2564whary@heartflow.com
Additional Contact Person:	James R. DavisDirector, Regulatory AffairsHeartFlow, Inc.T +1 (650) 241-1250F +1 (650) 368-2564jdavis@heartflow.com
Date Prepared:	April 20, 2022

2 Device Identification

Product Name	HeartFlowAnalysis	Common Name	FFRct
Product Feature Description	Product Code	Classification	Classification Name
FFRct	PJA-Primary	870.1415	Coronary vascular physiologicsimulation software device
PreRead (Anatomy extractedfrom FFRct 3D model) andsystem plaque volumes	LLZ-Secondary	892.2050	Medical image managementand processing system

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Plaque characterizationpresented with FFRct model(automated AI/ML detection)	LLZ-Secondary	892.2050	Medical image managementand processing system
Planner	PJA-Secondary	870.1415	Coronary vascular physiologicsimulation software device

3 Predicates

HeartFlow FFR -- v3 (K203329) is the identified primary predicate and Autoplaque add-on ORS Visual (K122429) is an additional predicate for this submission.

4 Device Description

The HeartFlow Analysis is performed on previously physician-acquired image data and is unrelated to acquisition equipment and clinical workstations.

5 Indications for Use

The HeartFlow Analysis is an Al-based medical device software for the clinical quantitative and qualitative analysis of previously acquired Tomography DICOM data for patients with suspected coronary artery disease. It provides anatomic data, plaque identification and characterization, as well as the calculations of FFRCT, a coronary physiological simulation, computed from simulated pressure, velocity and blood flow information obtained from a 3D computer model generated from static coronary CT images. The HeartFlow Analysis is intended to support the risk assessment and functional evaluation of coronary artery disease.

6 Technological Characteristics of Device

The HeartFlow Analysis is a software medical device that allows for the quantitative analysis of Coronary Computed Tomography (cCTA). The predicates and this product have the same technological characteristics.

The core technology remains unchanged from the primary predicate and continues to be trained using deep learning (Al and machine learning) since 2015, to incorporate learnings from the volumes of CT data and studies. All algorithms are then frozen and validated prior to product release. There are no differences between the subject device and the predicates with respect to intended use.

	FFRCT v3 (primarypredicate)	Autoplaque (predicate)	FFRCT v3.plus
510(k)	K203329	K122429	K213857
	FFRCT v3 (primarypredicate)	Autoplaque (predicate)	FFRCT v3.plus
Manufacturer	HeartFlow, Inc.	Object Research Systems,Inc.	HeartFlow, Inc.
RegulationNumber	870.1415	892.2050	870.1415
RegulationName	Coronary PhysiologicSimulation SoftwareDevice	System, Image Processing,Radiological	Coronary PhysiologicSimulation Software Device
Classification	Class II	Class II	Class II
Device CommonName	HeartFlow FFRCT	Image ProcessingSystem,Radiology,SoftwarePACS	HeartFlow Analysis
Product Code	PJA	LLZ	PJA
Functions	-Extract anatomic datafrom digital cardiacimages for the displayand visualization of theanatomy of patient'scoronary arteries-Compute FFRct	-Users of Autoplaque canedit the lumen andvessel walls of thesuggestedsegmentation.-Users are provided withimage viewing tools toaid in their analysis.-Plaque and stenosismeasurements areoutput based on thecombination of fullyuser-editablesegmentation and user-placed demarcations ofcoronary arterycharacteristics.	-Extract anatomical andplaque data from digitalcardiac images for thedisplay and visualizationof the anatomy ofpatient's coronaryarteries-Compute FFRct
Intended use	-Review of CTangiographic imagesto confirm thecoronary vessels-Semi-automated toolsfor extraction ofanatomic data(including heartstructures) forcoronary physiologicsimulation to aid indiagnosis of coronaryartery disease	-Provide a non-invasiveapplication to analyzecoronary anatomy andpathology-Post processingapplication option forthe ORS visual platform(K100335).-A non-invasivediagnostic readingsoftware add-onintended for use bycardiologists andradiologists as an	-Review of CTangiographic images toconfirm the coronaryvessels-Semi-automated toolsfor extraction of anatomicdata (including heartstructures) for coronaryphysiologic simulation toaid in diagnosis ofcoronary artery disease-Centerline detection
	FFRCT v3 (primarypredicate)	Autoplaque (predicate)	FFRCT v3.plus
	-Centerline detection-Provides additionaldata derived fromcoronary CT anatomyand pathology-Provide simulatedhemodynamicinformation	interactive tool forviewing and analyzingcardiac CT data fordetermining thepresence and extent ofcoronary plaques.-ORS Visual software(K100335) and theAutoplaque add-on mustbe installed on a suitablecommercial computerplatform.	-Provides additional dataderived from coronary CTanatomy and pathology-Provide simulatedhemodynamicinformation
Data source(input)	CT	CT	CT
Output/Accessibility	Graphic and textresults of coronaryanatomy andsimulated data areaccessed via a devicewith internetconnectivity	Graphic and text resultsprovided on a suitablecommercial computerplatform. It is the user'sresponsibility to ensure themonitor quality and ambientlight conditions areconsistent with the clinicalapplications.	Graphic and text results ofcoronary anatomy andsimulated data are accessedvia a device with internetconnectivity
Physicalcharacteristics	-Non-invasive softwarepackage-DICOM compatible	-Software installed andused by the user-Suitable commercialcomputer platform	-Non-invasive softwarepackage-DICOM compatible
Safety	Clinician review andassessment of analysisprior to use assupplementaldiagnostic aid	Clinician review, and assessment of analysisprior to use as supplementaldiagnostic aid	Clinician review andassessment of analysis priorto use as supplementaldiagnostic aid

Table 5-1. Predicate Device Comparison

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Table 5-2. Predicate Device Feature Comparison

Feature	FFRct v3(primarypredicate)	Autoplaque(predicate)	FFRctv3.plus(subject)
Presentation of CT images for confirmation ofextracted model	x		x
Automatic extraction of anatomic data from CTimages for analysis	x	x	x
Modeled stenosis and plaque* information		x (user edit)	x

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Volume rendering based on centerlines	x		x
Automatic/Semi-automatic lumen boundarydetermination	x	x (user edit)	x
Annotate, tag, measure and record selected views	x	x (user edit)	x
View the coronary vessels	x	x (user edit)	x
Modify anatomic model to remove luminalnarrowing(s)	x		x
Expose interim calculations used as input of FFRct(e.g., mass and volume)	x		x
Calculate functional parameters of the heart (e.g.,Fractional Flow Reserve, %myo)	x		x
Visualize plaque information*		x (user edit)	x
Graphic and text results	x	x	x

*Anatomical plaque calculation and visualization is supported by comparison to the Autoplaque predicate device

7 Summary of Studies

The software was designed, developed, tested and validated according to written procedures. These procedures specify individuals within the organization responsible for developing and approving product specifications, coding, testing, validating and maintenance.

Validation studies included stress testing, and repeatability testing to ensure the safety and effectiveness of the device. Software and medical device design validation has been completed. Medical device design included testing and evaluation using previously acquired diagnostic images received through HeartFlow sponsored clinical trials.

Summaries of pre-clinical studies were reviewed as part of a prior predicate review (K161772, the original predicate of K182035/K190925/K203329). The results concluded the device was acceptable for use.

Results of all current and previously referenced testing conclude the device is acceptable for use.

8 Conclusion

The conclusions drawn from the testing demonstrate that the device is as safe, as effective, and performs as well as the legally marketed devices identified in section 2 above.

Regulation Number and Section

§ 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.