EchoGo Heart Failure 2.0 is an automated machine learning-based decision support system, indicated as a diagnostic aid for patients undergoing routine functional cardiovascular assessment using echocardiography. When utilised by an interpreting clinician, this device provides information that may be useful in detecting heart failure with preserved ejection fraction (HFpEF).

EchoGo Heart Failure 2.0 is indicated in adult populations over 25 years of age. Patient management decisions should not be made solely on the results of the EchoGo Heart Failure 2.0 analysis.

EchoGo Heart Failure 2.0 takes as input an apical 4-chamber view of the heart that has been captured and assessed to have an ejection fraction ≥50%.

Device Description

EchoGo Heart Failure 2.0 takes as input a 2D echocardiogram of an apical four chamber tomographic view and reports as output a binary classification suggestive of the presence, or absence of heart failure with preserved ejection fraction (HFpEF). EchoGo Heart Failure 2.0 also provides users with an EchoGo Score ranging from 0 to 100% to support the binary classification. The EchoGo Score informs the binary classification when referenced against the pre-determined decision threshold (50%).

To aid in the interpretation of the EchoGo Score, a comparative visual analysis is provided. A histogram format displays the reported EchoGo Score output against a population of patients with known disease status (Independent Testing Dataset). This allows the user to interpret the EchoGo Score relative to the decision threshold of 50%.

EchoGo Heart Failure 2.0 should receive an input echocardiogram acquired without contrast and contain at least one full cardiac cycle.

EchoGo Heart Failure 2.0 is fully automated and does not comprise a graphical user interface.

EchoGo Heart Failure 2.0 is intended to be used by an interpreting clinician as an aid to diagnosis for HFpEF. The ultimate diagnostic decision remains the responsibility of the interpreting clinician using patient presentation, medical history, and the results of available diagnostic tests, one of which may be EchoGo Heart Failure 2.0.

EchoGo Heart Failure 2.0 is a prescription only device.

AI/ML Overview

Here's a breakdown of the acceptance criteria and the study proving the device meets them, based on the provided text:

Acceptance Criteria and Reported Device Performance

Criteria	Acceptance Limit	Reported Device Performance
I. Device Performance (Sensitivity & Specificity)	Implicit within reporting of performance: The device must demonstrate sufficient sensitivity and specificity for detecting HFpEF as a diagnostic aid. The specific acceptance limits are not explicitly stated as numerical thresholds but are demonstrated by the reported performance being "substantively equivalent to the predicate device and met pre-specified levels of performance."	Sensitivity: 90.3% (95% CI: 88.5, 92.4%) when removing "no classification" studies. 84.9% (95% CI: 83.0, 87.5%) when including "no classification" studies. Specificity: 86.1% (95% CI: 83.4, 88.3%) when removing "no classification" studies. 78.6% (95% CI: 75.3, 81.1%) when including "no classification" studies.
II. Accuracy of EchoGo Score (AUROC & Goodness-of-Fit)	Implicit within reporting of performance: The EchoGo Score must be accurate and align with known and expected proportions of HFpEF. Statistical significance (p-value > 0.05) for the Hosmer-Lemeshow Test and a sufficiently high AUROC are expected.	Area Under the Receiver Operating Characteristic Curve (AUROC): 0.947 (95% CI: 0.934, 0.958) when removing "no classification" studies. 0.937 (95% CI: 0.924, 0.949) when considering all studies. Hosmer-Lemeshow Test for goodness-of-fit: p=0.304 (not significant, indicating acceptable fit).
III. Proportion of Non-Diagnostic Outputs	A priori acceptance limits: The proportion of "no classification" outputs must be within pre-specified limits (the exact numerical limit is not provided, but the text states it was "within a priori acceptance limits").	7.4% (116 out of 1,578 studies) were categorized as "No Classification."
IV. Precision (Repeatability and Reproducibility)	Implicit within reporting of performance: The device must demonstrate high repeatability and acceptable reproducibility in its classification output.	Repeatability: 100% in all measures. Reproducibility: 82.6% Positive Agreement and 82.4% Negative Agreement.

Study Details

Sample size used for the test set and the data provenance:
- Test Set Sample Size: 1,578 patients (785 controls and 793 cases).
- Data Provenance: Retrospective case:control study. The data was collected from multiple independent clinical sites spanning five states in the US.
Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- The document states that the ground truth was established by "ground truth classifications of cases (HFpEF) or controls," but it does not specify the number or qualifications of experts who established this ground truth for the test set.
Adjudication method for the test set:
- The document does not explicitly describe an adjudication method (e.g., 2+1, 3+1). It only refers to "ground truth classifications," implying these were already established.
If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:
- No, a multi-reader multi-case (MRMC) comparative effectiveness study evaluating human readers with and without AI assistance was not done. The study focuses on the standalone performance of the device. The device is intended as a "diagnostic aid" for use "by an interpreting clinician," but its performance evaluation presented here is not an MRMC study.
If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Yes, a standalone performance study was done. The reported sensitivity, specificity, AUROC, and precision values are for the device (algorithm) itself without human intervention in the classification output for the test set. The device provides a "binary classification suggestive of the presence, or absence of heart failure with preserved ejection fraction (HFpEF)" and an "EchoGo Score."
The type of ground truth used (expert consensus, pathology, outcomes data, etc):
- The ground truth was based on "ground truth classifications of cases (HFpEF) or controls," and "known and expected proportions of HFpEF." While not explicitly stated as "expert consensus," this terminology strongly implies clinical diagnoses were used to establish the HFpEF status for each patient in the dataset. It does not mention pathology or outcomes data specifically for ground truth.
The sample size for the training set:
- The sample size for the training set is not explicitly stated in the provided text. It mentions that the "Subject device AI model was trained on more data and with additional preprocessing steps and data augmentations" compared to the predicate device, and the testing data cohort was a "22.9% increase in data beyond the testing data cohort utilized for the 510k submission of EchoGo Heart Failure 1.0." However, the exact size of the training set is not provided.
How the ground truth for the training set was established:
- The document does not explicitly describe how the ground truth for the training set was established. It only states that the AI model was "trained on more data" with "additional preprocessing steps and data augmentations." It is highly probable it was established similarly to the test set ground truth (i.e., using clinical diagnoses or expert classifications), given the nature of the diagnostic task.

Summary

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September 23, 2024

Ultromics Limited Elena Traistaru Head of Quality and Regulatory Affairs 4630 Kingsgate Cascade Way, Oxford Business Park Oxford, OX4 2SU United Kingdom

Re: K240013

Trade/Device Name: EchoGo Heart Failure (2.0) Regulation Number: 21 CFR 870.2200 Regulation Name: Adjunctive Cardiovascular Status Indicator Regulatory Class: Class II Product Code: OUO Dated: August 23, 2024 Received: August 23, 2024

Dear Elena Traistaru:

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 (the 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 available 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.

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Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).

Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30. Design controls; 21 CFR 820.90. Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).

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 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 Part 803) for devices or postmarketing safety reporting (21 CFR Part 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 (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.

All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-device-advicecomprehensive-regulatory-assistance/unique-device-identification-system-udi-system.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 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 medical devices and radiation-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-regulatory

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assistance/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,

Robert T. Kazmierski -S

for

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

Enclosure

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Indications for Use

Submission Number (if known)

K240013

Device Name

EchoGo Heart Failure (2.0)

Indications for Use (Describe)

EchoGo Heart Failure 2.0 is indicated in adult populations over 25 years of age. Patient management decisions should not be made solely on the results of the EchoGo Heart Failure 2.0 analysis.

EchoGo Heart Failure 2.0 takes as input an apical 4-chamber view of the heart that has been captured and assessed to have an ejection fraction ≥50%.

Type of Use (Select one or both, as applicable)

Prescription Use (Part 21 CFR 801 Subpart D)

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

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1 Submitter

Company	Ultromics Limited4630 Kingsgate Cascade Way, Oxford Business Park South,Oxford, Oxfordshire, United Kingdom, OX4 2SU
Contact	Dr. Elena Traistaru

2 Subject Device

Product Trade Name	EchoGo Heart Failure
Model Number	2.0
510(k)	K240013
Manufacturer	Ultromics Limited
Medical Speciality	Cardiology
Regulation	21 CFR 870.2200 - Cardiovascular Monitoring Devices
Product Code	QUO- Adjunctive Heart Failure Status Indicator
Regulatory Class	II

EchoGo Heart Failure is the product trade name and 2.0 is the model number. For the avoidance of doubt, in this submission we combine the product trade name and model number and refer to the subject device as EchoGo Heart Failure 2.0.

3 Predicate Device

Predicate Device	EchoGo Heart Failure
510(k)	K222463
Manufacturer	Ultromics Limited

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4 Device Description

EchoGo Heart Failure 2.0 should receive an input echocardiogram acquired without contrast and contain at least one full cardiac cycle.

EchoGo Heart Failure 2.0 is fully automated and does not comprise a graphical user interface.

EchoGo Heart Failure 2.0 is a prescription only device.

5 Context

5.1 Intended Use

Providing adjunctive information on a patient's cardiovascular condition (diagnostic aid for Heart Failure with Preserved Ejection Fraction (HFpEF)).

5.2 Intended User

The clinician interpreting the report produced by EchoGo Heart Failure 2.0 and making a diagnostic decision.

5.3 Indications for Use

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clinician, this device provides information that may be useful in detecting heart failure with preserved ejection fraction (HFpEF).

EchoGo Heart Failure 2.0 is indicated in adult populations over 25 years of age. Patient management decisions should not be made solely on the results of the EchoGo Heart Failure 2.0 analysis.

EchoGo Heart Failure 2.0 takes as input an apical 4-chamber view of the heart that has been captured and assessed to have an ejection fraction ≥50%.

5.4 Patient Population

Patients undergoing routine functional cardiovascular assessment using diagnostic echocardiography or those suspected of heart failure.

6 Comparison of Intended Use/Indications for Use

The subject and predicate device have identical intended use for use.

Indications for use of predicate and subject device is identical (unchanged).

7 Comparison of Technological Characteristics

7.1 Subject and predicate device (EchoGo Heart Failure (K222463))

At a high level, the subject and primary predicate device is based on the following same technological elements:

Both device takes as input a DICOM file containing an echocardiogram as input numeric physiological information from medical devices to which it is connected. Both devices therefore receive as input data that is the output of another medical device.
The output of both devices is based on an artificial intelligence (AI) model developed using a convolutional network that produces a classification result.
Both device reports a classification decision as suggestive or not suggestive of the presence of heart failure with preserved ejection fraction (HFpEF). Both devices are adjunctive cardiovascular status indicators.
Subject device includes a class probability score along with comparative analysis to a population of cases with known ground truth (reference dataset) using a histogram display format in the report.

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Subject device includes additional application programming interfaces for input and output expanding the methods of interfacing with external applications and medical devices.
Subject device allows more the deployment options permitting functionality to be distributed and replicated, increasing the scalability, robustness and non-clinical performance of the device.
Subject device AI model was trained on more data and with additional preprocessing steps and data augmentations.

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Any technological differences between the subject and predicate devices raise no new concerns with regards to safety and efficacy. In addition, Ultromics is of the view that general controls alongside special controls introduced under the primary product code of the predicate are sufficient to ensure safety and efficacy of the EchoGo Heart Failure 2.0 device.

8 Special Controls

Special controls for regulation 21 CFR 870.2200 follow. The submission itself contains detailed references to supporting documentation and/or data allowing the verification of the implementation of the associated special controls.

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Control	Description
1	Software description, verification, and validation based on comprehensivehazard analysis:
a	Full characterization of technical parameters ofthe software, including any proprietaryalgorithm(s)	Control implemented
b	Description of the expected impact of allapplicable acquisition hardware characteristicson performance and any associated hardwarespecifications.	Control implemented
C	Specification of acceptable data quality controlmeasures.	Control implemented
d	Mitigation of impact of user error or failure ofany components (data detection and analysis,data display, and storage) on accuracy ofpatient reports.	Control implemented
2	Scientific justification for the validity of thestatus indicator algorithm(s) must be provided.Verification of algorithm calculations andvalidation testing of the algorithm using a dataset separate from the training data mustdemonstrate the validity of modelling.	Control implemented
3	Usability assessment must be provided todemonstrate that risk of misinterpretation ofthe status indicator is appropriately mitigated.	Control implemented
4	Clinical data must be provided in support of the intended use and include thefollowing:
a	Output measure(s) must be compared to anacceptable reference method to demonstratethat the output measure(s) represent(s) thepredictive measure(s) that the device providesin an accurate and reproducible manner.	Control implemented
Control	Description
b	The data set must be representative of theintended use population for the device. Anyselection criteria or limitations of the samplesmust be fully described and justified.	Control implemented
c	Agreement of the measure(s) with the referencemeasure(s) must be assessed across the fullmeasurement range.	Control implemented
d	Data must be provided within the clinicalvalidation study or using equivalent datasets todemonstrate the consistency of the output andbe representative of the range of data sourcesand data quality likely to be encountered in theintended use population and relevant useconditions in the intended use environment.	Control implemented
5	Labelling must include the following:
a	The type of input data used, includingspecification of compatible hardware for dataacquisition.	Control implemented
b	A description of what the device measures andoutputs to the user.	Control implemented
c	Warnings identifying acquisition or other factorsthat may impact output measures.	Control implemented
d	Guidance for interpretation of the outputmeasures, including warning(s) specifyingadjunctive use of the results.	Control implemented
e	Key assumptions made in the calculation anddetermination of results.	Control implemented
f	The measurement performance of the devicefor all presented parameters, with appropriateconfidence intervals, and the supportingevidence for this performance.	Control implemented
Control	Description
g	A detailed description of the patients studied inthe clinical validation (e.g., age, gender, race/ethnicity, clinical stability) as well as proceduraldetails of the clinical study.	Control implemented

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9 Consensus Standards

The following consensus standards were used in the design and manufacture of EchoGo Heart Failure 2.0.

Standard	Recognition Number
ISO 14971:2019 - Medical Devices - Application of RiskManagement to Medical Devices	5-125
IEC 62304:2015 - Medical Device Software - Software Life CycleProcesses	13-79
IEC 62366-1:2020 - Medical Devices - Application of UsabilityEngineering to Medical Devices	5-129
NEMA PS 3.1 - 3.20 2021e - Digital Imaging and Communicationsin Medicine (DICOM) Set	12-342
IEC ISO 10918-1:1994 - Digital Compression and Coding ofContinuous-tone Still Images	12-261
ISO 14155:2020 - Clinical investigation of medical devices forhuman subjects - Good clinical practice	2-282

Ultromics Limited cites conformity to the voluntary standards above. In addition, EchoGo Heart Failure 2.0 was designed and manufactured under a QMS that fully conforms to ISO 13485:2016 and FDA 21 CFR Part 820 Compliance.

10 Performance Data

10.1 Software Verification and Validation

EchoGo Heart Failure 2.0 software was developed and tested in accordance with Ultromics' Design Control processes and has been subjected to extensive safety and

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performance testing. Non-clinical verification and validation test results established that the device meets its design requirements and intended use.

Specifically, software verification was conducted at unit, module, and system integration levels. Risk management analysis generated multiple risk mitigation measures and verification activities. Regression- and numerical stability testing were conducted to ensure the device meets algorithmic specifications. Formative and summative usability assessments were conducted to validate labelling and mitigate against the device outputs being misinterpreted by the clinical user. Cybersecurity and data security testing were conducted to verify that data and patient protected health information security measures are included in the design of the software.

Software verification and validation testing were conducted, and documentation was provided as recommended by FDA's Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices. The software for this device is considered as a moderate level of concern since a failure or latent design flaw could indirectly result in minor injury to the patient through incorrect or delayed information or through the action of a care provider.

EchoGo Heart Failure 2.0 passed all software verification and validation tests.

10.2 Essential Performance

Device performance was validated using bench- and clinical performance testing.

An independent clinical validation study was conducted on a clinical data set representative of the intended use population and containing a range of data sources and data quality likely to be encountered in the intended use population and relevant use conditions in the intended use environment. The study was used to demonstrate consistency of the device output as well as to assess agreement with reference ground truth.

Device performance was determined according to a retrospective case:control study including multiple sites spanning five states in the final testing data cohort amounted to 1,578 patients, comprising 785 controls and 793 cases. The final testing data represents a 22.9% increase in data beyond the testing data cohort utilized for the 510k submission of EchoGo Heart Failure 1.0.

1. To assess sensitivity and specificity, we compared the device output for a single echocardiogram videoclip per patient to the ground truth classifications of cases (HFpEF) or controls. EchoGo Heart Failure 2.0 correctly identified 673 true positives, and 617 true negatives, alongside 100 false positives, 72 false negatives, and 116 no classification outputs (48 cases, 68 controls). This equated to a sensitivity of 90.3% (95% Cl: 88.5, 92.4%) and a specificity of 86.1% (95% Cl: 83.4, 88.3%) when removing the no classification studies from the calculation, as per the intended use of the

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device. When including the no classification studies in the calculation, sensitivity was 84.9% (95% Cl: 83.0, 87.5%) and specificity was 78.6% (95% Cl: 75.3, 81.1%).

1. To determine the accuracy of the EchoGo Score, we compared the EchoGo Score to known and expected proportions of HFpEF. The p value for the Hosmer-Lemeshow Test for goodness-of-fit was not significant (p=0.304), indicating acceptable fit between observed and known probabilities. The area under the receiver operator characteristic curve (AUROC) was 0.947 (95% Cl: 0.934, 0.958) when removing no classification studies, and 0.937 (95% Cl: 0.924, 0.949) when considering all studies and ignoring uncertainty and instability metrics. When classification statistics are examined across decile cut-offs for the EchoGo Score (0.1 or 10%, to 0.9 or 90%), instead of the default 0.5 (50%) used to determine classification output, we observe high sensitivity and specificity across most decision thresholds (minus the most extreme cut-offs; 0.9 and 0.1 for sensitivity and specificity, respectively). Similarly, when EchoGo Scores are separated into 5 stratum, post-test risk increases with increasing stratum, with 0% and 100% risk for the lowest, and highest stratum (respectively). Finally, a flexible calibration curve with non-parametric loess smoothing results in an intercept close to 0, slope close to 1, and ECI close to 0.
1. The proportion of non-diagnostic (i.e., "No classification") outputs of the device were within a priori acceptance limits. Of the 1,578 studies analysed by the device, 116 (7.4%) were categorized as "No Classification".
1. The device output classification from a single Digital Imaging and Communications in Medicine (DICOM) clip analysed twice (repeatability), and the device output classification from different DICOM clips from the same individual (reproducibility) was assessed for precision. The device demonstrated 100% repeatability in all measures and 82.6% Positive Agreement and 82.4% Negative Agreement for reproducibility.

All measurements produced by EchoGo Heart Failure 2.0 were deemed to be substantively equivalent to the predicate device and met pre-specified levels of performance. We therefore consider EchoGo Heart Failure 2.0 to be substantively equivalent to the predicate device and is therefore deemed to be safe and effective.

11 Conclusions

The subject device, EchoGo Heart Failure 2.0 is as safe and as effective as the predicate device, EchoGo Heart Failure, previously cleared under K222463.

Ultromics concludes that the predicate and subject devices have the same intended use as well as similar technological characteristics. Any minor differences between the subject and the predicate device, as described above, do not alter the intended use of the device, and do not raise new or different questions regarding its safety and effectiveness.

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Furthermore, Ultromics believe special controls introduced under the 21 CFR 870.2200 regulation are sufficient to ensure safety and effectiveness. These include software verification and validation including a comprehensive hazard analysis; validation testing of the AI algorithm using a data set separate from the training data to demonstrate the validity of the device output; a usability assessment; clinical data in support of the intended use; as well as labelling consistent with the intended use. Performance data is provided as part of this PMN application to demonstrate that EchoGo Heart Failure 2.0 performs as intended in the specified use conditions and that it is as safe and effective as the predicate device and therefore substantially equivalent to K222463.

Regulation Number and Section

§ 870.2200 Adjunctive cardiovascular status indicator.

(a)
Identification. The adjunctive cardiovascular status indicator is a prescription device based on sensor technology for the measurement of a physical parameter(s). This device is intended for adjunctive use with other physical vital sign parameters and patient information and is not intended to independently direct therapy.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Software description, verification, and validation based on comprehensive hazard analysis must be provided, including:
(i) Full characterization of technical parameters of the software, including any proprietary algorithm(s);
(ii) Description of the expected impact of all applicable sensor acquisition hardware characteristics on performance and any associated hardware specifications;
(iii) Specification of acceptable incoming sensor data quality control measures; and
(iv) Mitigation of impact of user error or failure of any subsystem components (signal detection and analysis, data display, and storage) on accuracy of patient reports.
(2) Scientific justification for the validity of the status indicator algorithm(s) must be provided. Verification of algorithm calculations and validation testing of the algorithm using a data set separate from the training data must demonstrate the validity of modeling.
(3) Usability assessment must be provided to demonstrate that risk of misinterpretation of the status indicator is appropriately mitigated.
(4) Clinical data must be provided in support of the intended use and include the following:
(i) Output measure(s) must be compared to an acceptable reference method to demonstrate that the output measure(s) represent(s) the predictive measure(s) that the device provides in an accurate and reproducible manner;
(ii) The data set must be representative of the intended use population for the device. Any selection criteria or limitations of the samples must be fully described and justified;
(iii) Agreement of the measure(s) with the reference measure(s) must be assessed across the full measurement range; and
(iv) Data must be provided within the clinical validation study or using equivalent datasets to demonstrate the consistency of the output and be representative of the range of data sources and data quality likely to be encountered in the intended use population and relevant use conditions in the intended use environment.
(5) Labeling must include the following:
(i) The type of sensor data used, including specification of compatible sensors for data acquisition;
(ii) A description of what the device measures and outputs to the user;
(iii) Warnings identifying sensor reading acquisition factors that may impact measurement results;
(iv) Guidance for interpretation of the measurements, including warning(s) specifying adjunctive use of the measurements;
(v) Key assumptions made in the calculation and determination of measurements;
(vi) The measurement performance of the device for all presented parameters, with appropriate confidence intervals, and the supporting evidence for this performance; and
(vii) A detailed description of the patients studied in the clinical validation (
e.g., age, gender, race/ethnicity, clinical stability) as well as procedural details of the clinical study.

Characteristic	Subject DeviceEchoGo Heart Failure 2.0	Predicate DeviceEchoGo Heart Failure(K222463)
Regulation	21 CFR 870.2200	21 CFR 870.2200
Generic Device Type	Adjunctive cardiovascularstatus indicator	Adjunctive cardiovascularstatus indicator
SaMD	Yes	Yes
Intended Use	Providing adjunctiveinformation on a patient'scardiovascular condition(diagnostic aid for HeartFailure with PreservedEjection Fraction (HFpEF)).	Providing adjunctiveinformation on a patient'scardiovascular condition(diagnostic aid for HeartFailure with PreservedEjection Fraction (HFpEF)).
Characteristic	Subject DeviceEchoGo Heart Failure 2.0	Predicate DeviceEchoGo Heart Failure(K222463)
Indications for Use	EchoGo Heart Failure 2.0 isan automated machinelearning-based decisionsupport system, indicatedas a diagnostic aid forpatients undergoing routinefunctional cardiovascularassessment usingechocardiography. Whenutilised by an interpretingclinician, this deviceprovides information thatmay be useful in detectingheart failure with preservedejection fraction (HFpEF).EchoGo Heart Failure 2.0 isindicated in adultpopulations over 25 yearsof age. Patientmanagement decisionsshould not be made solelyon the results of theEchoGo Heart Failure 2.0analysis.EchoGo Heart Failure 2.0takes as input an apical 4-chamber view of the heartthat has been captured andassessed to have anejection fraction ≥50%.	EchoGo Heart Failure 1.0 isan automated machinelearning-based decisionsupport system, indicatedas a diagnostic aid forpatients undergoing routinefunctional cardiovascularassessment usingechocardiography. Whenutilised by an interpretingclinician, this deviceprovides information thatmay be useful in detectingheart failure with preservedejection fraction (HFpEF).EchoGo Heart Failure 1.0 isindicated in adultpopulations over 25 yearsof age. Patientmanagement decisionsshould not be made solelyon the results of theEchoGo Heart Failure 1.0analysis.EchoGo Heart Failure 1.0takes as input an apical 4-chamber view of the heartthat has been captured andassessed to have anejection fraction ≥50%.
Population	Adults over the age of 25	Adults over the age of 25
Anatomical Site	Cardiovascular	Cardiovascular
Users	Interpreting clinician	Interpreting clinician
Machine Learning-BasedAlgorithm	Yes	Yes
Characteristic	Subject DeviceEchoGo Heart Failure 2.0	Predicate DeviceEchoGo Heart Failure(K222463)
Operating platform	Hosted on Ultromics'platform or on third partyinfrastructure.	Hosted on Ultromics'platform or on third partyinfrastructure.
Interoperability	Interoperability testingconducted with devicecapable of calculating anejection fraction on theapical 4 chamber view.	Interoperability testingconducted with devicecapable of calculating anejection fraction on theapical 4 chamber view.
Software	Complies with IEC62304:2015 and GPSV.Developed under an FDAQSR and ISO 13485:2016compliant QMSincorporating riskmanagement per ISO14971:2019. Softwareverification and validationtesting conducted.	Complies with IEC62304:2015 and GPSV.Developed under an FDAQSR and ISO 13485:2016compliant QMSincorporating riskmanagement per ISO14971:2019. Softwareverification and validationtesting conducted.
Risk Management	In accordance with ISO14971:2019	In accordance with ISO14971:2019
Cybersecurity	Post-market Managementof Cybersecurity in MedicalDevices.Content of PremarketSubmissions forManagement ofCybersecurity in MedicalDevices.Cybersecurity forNetworked Medical DevicesContaining Off-the-Shelf(OTS) Software: Guidancefor Industry.	Post-market Managementof Cybersecurity in MedicalDevices.Content of PremarketSubmissions forManagement ofCybersecurity in MedicalDevices.Cybersecurity forNetworked Medical DevicesContaining Off-the-Shelf(OTS) Software: Guidancefor Industry.
Characteristic	Subject DeviceEchoGo Heart Failure 2.0	Predicate DeviceEchoGo Heart Failure(K222463)
Usability	Complies with IEC62366-1:2020 and generaluse of FDA guidancedocuments on usabilityengineering. Formativeevaluations conducted withaccredited cardiacphysiologists (N=2) andcardiologists (N=5). Formalsummative human factorstesting was conducted with15 users (Board certifiedclinicians with experiencein Echocardiography).	Complies with IEC62366-1:2020 and generaluse of FDA guidancedocuments on usabilityengineering. Formative andsummative evaluationsconducted with accreditedcardiac physiologists (N=2)and cardiologists (N=5).
Pre-clinical PerformanceTesting	No animal studies wereconducted.	No animal studies wereconducted.
Bench Performance Testing	Technical validation,numerical stability, andregression testing.	Technical validation,numerical stability, andregression testing.
Clinical PerformanceTesting	Validated on a US cohortpopulation, comprising 8independent clinical sitesrepresentative of theintended use population.	Validated on a US cohortpopulation, comprising 8independent clinical sitesrepresentative of theintended use population.