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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%.

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.

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

Study Details

1. 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.

2. 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.

3. 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.

4. 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.

5. 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."

6. 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.

7. 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.

8. 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.

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The Vivio® System is indicated to non-invasively estimate left ventricular end-diastolic pressure (LVEDP) is above or below 18mmHg. This measurement can aid in the diagnosis of heart failure when used by qualified healthcare professionals as an adjunct alongside other clinically relevant information. For use in adults only.

The Vivio System consists of an Arm Cuff system (BP cuff electronics, connection tubinq), EKG patch, and a software application that runs on an off-the-shelf computer tablet. Data is collected non-invasively at the brachial artery and via a single-lead EKG Patch. An off-the-shelf blood pressure arm cuff is attached to the patient's upper arm as if taking a blood pressure measurement. The Arm Cuff is attached to the blood pressure cuff with the quick connect end connected to the pneumatic pump within the Arm Cuff Electronics Enclosure. Two off-the-shelf electrodes are attached to the snap connections on the bottom of the EKG Patch and then connected on the left side of the patient's chest. Both the pneumatic pump attached to the Arm Cuff and EKG Patch are then powered on by pressing and releasing their respective power buttons. The Vivio App is opened on an off-the shelf computer tablet, and the on-screen prompts are followed to connect the Arm Cuff and the EKG Patch. The user is prompted to enter required patient and user data, initiating a patient recording session. Data from the recording session is processed by a proprietary algorithm and results reported on the computer tablet.

The provided document focuses on the 510(k) summary for the Vivio® System, which is an "Adjunctive Cardiovascular Status Indicator" device. It outlines the regulatory classification, device description, indications for use, technological characteristics, and summaries of non-clinical and clinical tests.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided text:

Indications for Use: The Vivio® System is indicated to non-invasively estimate left ventricular end-diastolic pressure (LVEDP) as above or below 18mmHg. This measurement aids in the diagnosis of heart failure when used by qualified healthcare professionals as an adjunct alongside other clinically relevant information, for use in adults only.

1. Table of Acceptance Criteria and Reported Device Performance

The document states "The primary efficacy objectives for the study were met." The acceptance criteria for efficacy are directly linked to diagnostic performance metrics:

Note: The document does not explicitly state these as acceptance criteria but rather as "primary efficacy objectives for the study." In the context of a 510(k) submission, meeting these pre-specified performance thresholds demonstrates the device's ability to achieve its intended use. The LVEDP threshold for diagnosis is 18mmHg.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size (Test Set):

  • Cath Lab Cohort: 195 subjects scheduled for non-emergent left heart catheterization.
  • Non-Aged Healthy Cohort: 101 subjects.
  • Aged Healthy Cohort: 40 subjects.
  • Total Enrolled: 195 + 101 + 40 = 336 subjects.
  • However, the statistical analysis was performed on a "subset of validation data that had passed the completeness and quality requirements outlined in the data management plan and procedure." The exact size of this final validation subset, specifically used for the reported sensitivity and specificity, is not explicitly stated, but it would be derived from the 195 subjects in the "Cath Lab Cohort" used for comparison to invasive LVEDP. The sensitivity and specificity numbers are specifically tied to the LVEDP estimate, which would rely on the cohort with ground truth LVEDP measurements (Cath Lab Cohort).

• Data Provenance:

  • Geographic Origin: The Cath Lab Cohort was enrolled "across 9 sites" (locations not specified, assuming within the US for FDA clearance), and the two Healthy Cohorts were enrolled "at a single site" (location not specified).
  • Nature of Data: Prospective validation study.

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

• The document states that the ground truth for the Cath Lab Cohort was "gold-standard invasive LVEDP obtained via the Millar Mikro-Cath." This is a direct physiological measurement, not established by human experts in a subjective reading context.
• For the "reference-standard non-invasive echocardiographic indices" used for the Aged Healthy Cohort, the document does not specify the number or qualifications of experts involved in establishing these indices. However, echocardiographic indices are objective measurements and calculations, typically performed by trained sonographers and interpreted by cardiologists/echocardiographers.

4. Adjudication Method for the Test Set

• Since the primary ground truth for LVEDP was an invasive, objective measurement (Millar Mikro-Cath), no expert adjudication method (like 2+1 or 3+1) would have been necessary for this part of the ground truth establishment.
• For the echocardiographic indices, the document does not provide details on adjudication, but as noted above, these are typically objective measurements.

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

• The document does not indicate that an MRMC comparative effectiveness study was done to show how human readers improve with AI vs. without AI assistance.
• The Vivio System is described as a device that "estimates LVEDP" and "aids in the diagnosis of heart failure when used by qualified healthcare professionals as an adjunct." It provides a calculated clinical parameter, not necessarily an AI-driven image interpretation system that assists human readers.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• Yes, the reported "sensitivity of 80% (64-91), and specificity of 80% (73-86)" appear to be a measure of the Vivio System's (algorithm's) standalone performance in classifying LVEDP as above or below 18mmHg against the invasive gold standard. The device generates the estimate, and these metrics directly assess its accuracy.

7. Type of Ground Truth Used

• Primary Ground Truth: "Gold-standard invasive LVEDP obtained via the Millar Mikro-Cath" for the Cath Lab Cohort. This is direct physiological outcomes data.
• Reference Standard: "Reference-standard non-invasive echocardiographic indices" for the Aged Healthy Cohort. This relies on established clinical measurements, not subjective expert consensus.

8. Sample Size for the Training Set

• The document does not specify the sample size used for the training set. It mentions a "proprietary algorithm" and a "fixed parameter model" (as opposed to AI/machine learning), but no details on its development data are provided.

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

• The document does not specify how the ground truth for the training set was established. Given the device uses a "fixed parameter model" rather than a machine learning model, it implies that the algorithm's parameters were likely determined based on physiological principles and pre-existing clinical data/models, rather than a large-scale data-driven training process with established ground truth labels in the same way as an AI model.

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EchoGo Heart Failure 1.0 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 1.0 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 1.0 analysis.

EchoGo Heart Failure 1.0 takes as input an apical 4-chamber view of the heart that has been captured and assessed to have an ejection fraction ≥50%.

EchoGo Heart Failure 1.0 is a software-only medical device manufactured by Ultromics Limited and granted breakthrough status by the FDA under Q212613.

EchoGo Heart Failure 1.0 takes as input a DICOM file containing an echocardiogram and reports a classification decision suggestive of the presence or absence of heart failure with preserved ejection fraction (HFpEF). The output of this device is based on an artificial intelligence (Al) model developed using a convolutional neural network that produces the classification result. The model takes as input a 2D echocardiogram in which an apical 4-chamber view of the heart has been captured and assessed to have an ejection fraction ≥50% (this would normally be computed using a medical device for the assessment of cardiac function of the left ventricle, for example K213275). The echocardiogram should be acquired without contrast and contain at least one full cardiac cycle.

Independent training, validation and test datasets were used for training and performance assessment of the device. EchoGo Heart Failure 1.0 is fully automated and does not comprise a user interface.

EchoGo Heart Failure 1.0 produces a report containing the result of the classification, and this report is intended to be used by an interpreting clinician as an aid to diagnosis for HFpEF. The results are intended as an additional input to standard diagnostic pathways and should only be used by an interpreting clinician. The device is a diagnostic aid and thus according to common medical sense and the principles of differential diagnosis any diagnostic finding derived from usage of this product must be confirmed by additional diagnostic investigations, if in doubt. 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 1.0.

EchoGo Heart Failure 1.0 is a prescription only device.

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

1. Table of Acceptance Criteria and Reported Device Performance

The provided text only explicitly states the reported device performance and the p-values for one-sided binomial exact tests against a priori acceptance criteria. The specific numerical acceptance criteria (e.g., minimum sensitivity and specificity thresholds) are not directly stated in the document. However, since the p-values are reported as p

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