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The Caption Guidance software is intended to assist medical professionals in the acquisition of cardiac ultrasound images. Caption Guidance software is an accessory to compatible general purpose diagnostic ultrasound systems.

Caption Guidance software is indicated for use in two-dimensional transthoracic echocardiography (2D-TTE) for adult patients, specifically in the acquisition of the following standard views: Parasternal Long-Axis (PLAX), Parasternal Short-Axis at the Aortic Valve (PSAX-AV), Parasternal Short-Axis at the Mitral Valve (PSAX-MV), Parasternal Short-Axis at the Papillary Muscle (PSAX-PM), Apical 4-Chamber (AP4), Apical 5-Chamber (AP5), Apical 2-Chamber (AP2), Apical 3-Chamber (AP3), Subcostal 4-Chamber (SubC4), and Subcostal Inferior Vena Cava (SC-IVC).

The Caption Guidance software is a radiological acquisition and/or optimization guidance system that provides real-time guidance to the users during acquisition of echocardiography to assist them in obtaining anatomically correct images that represent standard 2D echocardiographic diagnostic views and orientations. Caption Guidance is a software-only device that uses artificial intelligence to emulate the expertise of sonographers.

Caption Guidance is comprised of several different features that, combined, provide expert guidance to the user. These include:

• 1. Quality Meter: The real-time feedback from the Quality Meter advises the user on the expected diagnostic quality of the resulting clip, such that the user can make decisions to further optimize the quality, for example by following the prescriptive guidance feature below.
• 2. Prescriptive Guidance: The prescriptive guidance feature in Caption Guidance provides direction to the user to emulate how a sonographer would manipulate the transducer to acquire the optimal view.
• 3. Auto-Capture: The Caption Guidance Auto-Capture feature triggers an automatic capture of a clip when the quality is predicted to be diagnostic, emulating the way in which a sonographer knows when an image is of sufficient quality to be diagnostic and records it.
• 4. Save Best Clip: This feature continually assesses clip quality while the user is scanning and, in the event that the user is not able to obtain a clip sufficient for Auto-Capture, the software allows the user to retrospectively record the highest quality clip obtained so far, mimicking the choice a sonographer might make when recording an exam.

The Caption Guidance software was trained using echocardiographic clips from studies performed by trained sonographers. The ideal probe pose for each cardiac view was used to determine the Prescriptive Guidance for maneuvering the probe to the ideal pose.

The Caption Guidance software is labeled for use with the Terason uSmart 3200t Plus, an FDA 510(k) cleared (K150533) ultrasound system. Caption Guidance is installed on the third-party ultrasound system. The user has access to both the Terason user interface (UI) and the Caption Guidance UI and will be able to switch between the two.

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

Acceptance Criteria and Device Performance

The primary acceptance criteria for the Caption Guidance device focused on the ability of medical professionals without specialized echocardiography training (represented by Registered Nurses, RNs) to acquire echocardiographic exams of sufficient image quality for clinical assessment.

Table of Acceptance Criteria and Reported Device Performance (Pivotal Study - RN Users):

The text explicitly states: "The four primary endpoints were satisfied and demonstrated the clinical utility of Caption Guidance for users without specialized echocardiography training." This indicates that the reported percentages met their predetermined success criteria.

Study Details: Pivotal (Nurse) Study

2. Sample Size and Data Provenance:
* Test Set Sample Size: 8 Registered Nurses (RNs) each completed scans of 30 patients, resulting in a total of 240 patient studies (8 RNs * 30 patients).
* Data Provenance: The study was a prospective clinical study conducted with US-based participants (implied by the FDA De Novo classification and the mention of Northwestern Memorial Hospital for the Human Factors study, which typically suggests local clinical trials).

3. Number of Experts and their Qualifications for Ground Truth:
* Number of Experts: Five (5) expert cardiologists.
* Qualifications: "Expert cardiologists" are described as providing independent assessments. While specific years of experience aren't stated, the term "expert" implies significant experience and board certification, aligning with qualifications needed for interpreting echocardiograms.

4. Adjudication Method for the Test Set:
* The panel of five (5) expert cardiologist readers independently provided assessments. The text does not describe an explicit adjudication method like "2+1" or "3+1" to resolve disagreements. Instead, it seems the data presented (e.g., percentages of sufficient quality) are based on a consensus or aggregated proportion from these independent assessments (likely using an MRMC statistical approach, as indicated by "MRMC CI"). "In addition, each of the cardiologist readers were asked to provide a repeat assessment on a certain percentage of the exams or clips they reviewed in order to assess intra-grader variability." This suggests independent review was a cornerstone, with variability being a key consideration rather than forced consensus.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:
* Yes, a MRMC study was done, but not to directly compare human readers with AI vs. without AI assistance regarding effectiveness gains.
* The pivotal study used an MRMC design to evaluate the performance of RNs using Caption Guidance against a control arm where trained sonographers acquired images unassisted. The MRMC primary endpoints focused on the proportion of sufficient quality scans achieved by RNs with Caption Guidance.
* Effect Size of Human Readers Improve with AI vs. without AI Assistance: This specific metric (improvement of human readers who already know how to scan when assisted by AI) was not explicitly reported as a primary endpoint or effect size in the pivotal study results section.
* However, a descriptive "Specialist (Sonographer) Study" was conducted with 3 expert cardiologists. This study indicated that "sonographers obtained diagnostic quality images in a high proportion of clips from both study and control exams, demonstrating comparable image quality in clips acquired using Caption Guidance compared to unassisted acquisition." This implies that for already trained sonographers, the AI did not significantly improve their image quality but maintained comparability. The key benefit demonstrated by the pivotal study was enabling untrained users to achieve high-quality images.
* The pivotal study showed that RNs using Caption Guidance could achieve clinical assessments with high success rates, implicitly demonstrating a significant improvement for these untrained users compared to their performance without the device (which would presumably be very low or non-existent for standard views).

6. Standalone (Algorithm Only) Performance:
* Yes, standalone algorithm performance testing was done. The section "Algorithm Performance Testing" details this:
* "The Caption Guidance algorithm was tested for the performance of the supported features: Quality Meter, Auto-Capture, and Save Best Clip."
* Metrics included "Frame-level prediction of the current pose of the probe, as compared to the ideal pose," "Relative image quality prediction," and "Auto-Capture of clinically-acceptable images and clips."
* It also tested "Frame-level PG prediction of the probe maneuver needed to acquire an image/frame" and "Clip-level PG prediction."
* The text notes these results "provide evidence in support of the functionality of Caption Guidance fundamental algorithms" and "demonstrated a low-level verification of the algorithms."

7. Type of Ground Truth Used:
* For the pivotal study, the ground truth was primarily expert consensus (or independent assessment for subsequent aggregation/MRMC analysis) by expert cardiologists using the American College of Emergency Physicians (ACEP) scale for echocardiography quality for individual clips, and global assessment of "sufficient information to assess ten clinical parameters" for patient studies.
* Additionally, quantitative expert measurements by sonographers ("PLAX Sonographer Measurements") served as ground truth for assessing measurability and variability of linear measurements.
* For the initial algorithm training, "The ideal probe pose for each cardiac view was used to determine the Prescriptive Guidance," implying a form of expert-defined ideal states/positions as ground truth.

8. Sample Size for the Training Set:
* The document states: "The Caption Guidance software was trained using echocardiographic clips from studies performed by trained sonographers." A specific sample size for the training set is not provided in the given text.

9. How the Ground Truth for the Training Set Was Established:
* "The Caption Guidance software was trained using echocardiographic clips from studies performed by trained sonographers."
* "The ideal probe pose for each cardiac view was used to determine the Prescriptive Guidance for maneuvering the probe to the ideal pose."
* This implies the ground truth for training data likely involved:
* Labeled echocardiographic clips: Experts (sonographers) provided the "correct" (diagnostic quality, specific view) clips.
* Expert definition of "ideal probe pose": This would serve as the target for the prescriptive guidance and quality meter. This likely involved expert sonographers demonstrating and labeling ideal probe positions and maneuvers for each cardiac view.

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The Bay Labs, Inc. EchoMD Automated Ejection Fraction software is used to process previously acquired transthoracic cardiac ultrasound images, to store images, and to manipulate and make measurements on images using a personal computer or a compatible DICOM-compliant PACS system in order to provide automated estimation of left ventricular ejection. This measurement can be used to assist the clinician in a cardiac evaluation.

The EchoMD Automated Ejection Fraction Software is indicated for use in adult patients.

The EchoMD Automated Ejection (AutoEF) software applies machine learning algorithms to process echocardiography images in order to calculate left ventricular ejection fraction. The software operates in between the DICOM source and the DICOM destination. EchoMD AutoEF performs left ventricular ejection measurements using both the apical four chamber and apical two chamber cardiac ultrasound views.

The software selects the image clips to be used, performs the AutoEF calculation, and forwards the results to a destination PACS server for clinician viewing. The output of the Ejection Fraction estimate stated as a percentage, which is displayed via the destination PACS system. The software applies machine learning algorithms to assess image quality and provides this information as qualitative and quantitative user feedback. By automating the estimation of ejection fraction, the EchoMD software is designed to streamline the clinician's calculation of the measurement.

Here's a breakdown of the acceptance criteria and study details for the Bay Labs, Inc. EchoMD Automated Ejection Fraction Software, based on the provided text:

Acceptance Criteria and Reported Device Performance

1. Sample Size and Data Provenance

• Test Set Sample Size: Over 300 previously-acquired studies.
• Data Provenance: Retrospective, non-interventional validation study. The country of origin is not explicitly stated, but given the FDA submission, it's highly likely to be within the US or compliant with US standards.

2. Number of Experts and Qualifications

• Number of Experts: Not explicitly stated for the primary validation study's ground truth establishment. However, an additional study was performed "with a different set of cardiologists" on a subset of the validation patient studies. The specific number of cardiologists for this additional study is also not provided.
• Qualifications of Experts: The experts involved in the "additional study" were "cardiologists." No further details on their experience (e.g., years of experience) are given.

3. Adjudication Method for the Test Set

• The text does not describe an explicit adjudication method (e.g., 2+1, 3+1) for establishing the ground truth EF for the test set. The ground truth was established by "the biplane method of disks ejection fraction reported." It implies that the reported EF values were considered the reference.

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

• Was an MRMC study done? The text states, "An additional study was performed with a different set of cardiologists on a subset of the validation patient studies to further demonstrate the generalizability of the software." This suggests a form of multi-reader study, but it's not explicitly framed as an MRMC comparative effectiveness study in the sense of comparing human readers with AI vs. without AI assistance. The focus seems to be on verifying the generalizability of the software's performance against different cardiologists.
• Effect Size: No effect size or improvement for human readers with AI assistance versus without AI assistance is reported. The study's purpose was to demonstrate the generalizability of the software's performance, not to quantify human reader improvement.

5. Standalone (Algorithm Only) Performance

• Was a standalone performance study done? Yes. The primary endpoint measured the EchoMD AutoEF ejection fraction measurements compared to the biplane method ejection fraction, with a root mean square deviation calculated. This directly assesses the algorithm's performance independent of a human-in-the-loop scenario.
• Performance Metric: Root Mean Square Deviation (RMSD).
• Performance Result: 8.290% RMSD (p-value 0.00052).

6. Type of Ground Truth Used

• Ground Truth: "the biplane method of disks ejection fraction reported." This is a clinical standard for Left Ventricular Ejection Fraction (LVEF) measurement based on echocardiography. While it relies on expert interpretation and measurement, it is not explicitly described as "expert consensus" in the sense of multiple independent readers reaching a consensus. It's more aligned with a established clinical measurement method.

7. Sample Size for the Training Set

• The sample size for the training set is not provided in the document. The text only states that "Test datasets were strictly segregated from algorithm training datasets."

8. How Ground Truth for Training Set was Established

• The method for establishing the ground truth for the training set is not specified. The document only mentions that the software "applies machine learning algorithms to process echocardiography images."

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