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

The 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 computer assisted acquisition guidance system that provides real-time user quidance during acquisition of echocardiography to assist the user 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 quidance to the user. These include:

• 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.
• 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.
• 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.
• 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.

Here's a breakdown of the acceptance criteria and the study details for the Caption Guidance software, based on the provided text.

Note: The provided document is a 510(k) summary for a modification to an already cleared device (K201992, which is predicated on K200755). Therefore, the document primarily focuses on demonstrating substantial equivalence to the previous version of the device and outlining a modification to a predetermined change control plan (PCCP). It does not detail a new clinical study to prove initial performance against acceptance criteria for the entire device, but rather refers to the established equivalence and the PCCP.

However, based on what's typically expected for such devices, and inferring from the description of the device's capabilities, I will construct a plausible set of acceptance criteria and discuss what can be gleaned about the study from the provided text, while acknowledging its limitations for providing full study details.

Acceptance Criteria and Reported Device Performance

Given the device's function (assisting with cardiac ultrasound image acquisition by guiding users to obtain specific standard views and optimizing quality), the acceptance criteria would likely revolve around the accuracy of its guidance, the quality of the "auto-captured" views, and its ability to help users acquire diagnostically relevant images.

Since this document is a 510(k) for a modification and states "The current iteration of the Caption Guidance software is as safe and effective as the previous iteration of such software," and "The Caption Guidance software has the same intended use, indications for use, technological characteristics, and principles of operation as its predicate device," the specific performance metrics from the original predicate device's clearance are not explicitly stated here.

However, a hypothetical table of common acceptance criteria for such a device and inferred performance (based on the device being cleared and performing "as safe and effective as the previous iteration") would look something like this:

Study Details (Based on available information in the document)

1. Sample size used for the test set and the data provenance:

• Sample Size: Not explicitly stated in this 510(k) summary. Given this is for a PCCP modification, new clinical test data for this submission is not provided, but rather relies on the predicate's performance.
• Data Provenance: Not explicitly stated for either the training or test sets in this document. It's common for such data to come from multiple sites and locations to ensure generalizability, but the document doesn't specify. The document refers to the previous iteration's performance, which would have had this data.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not explicitly stated in this 510(k) summary. This information would be present in the original 510(k) for the predicate device (K200755). Typically, a panel of board-certified radiologists or cardiologists with expertise in echocardiography would be used.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

• Not explicitly stated. This detail would be found in the original 510(k) submission for the device that established its initial substantial equivalence. Common methods include majority rule (e.g., 2 out of 3 or 3 out of 5 experts agreeing), or a senior expert adjudicating disagreements.

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:

• The document implies that the device "emulates the expertise of sonographers" and "provides real-time user guidance." This strongly suggests that the original predicate submission would have included a study (likely an MRMC-type study or a study comparing guided vs. unguided acquisition) to demonstrate that the system assists users in acquiring better images.
• Effect Size: Not provided in this summary. Such a study would likely show improvements in metrics like:
  • Percentage of standard views successfully acquired.
  • Time taken to acquire optimal views.
  • Image quality scores (e.g., higher proportion of "diagnostic quality" images).
  • Reduction in inter-user variability for image acquisition.
  • Potentially, images acquired were more similar to those obtained by expert sonographers.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

• Yes, implicitly. The very nature of the "Quality Meter," "Auto-Capture," and "Prescriptive Guidance" features means the AI must perform standalone assessments (e.g., classifying views, assessing quality) to provide its guidance. The performance metrics listed under acceptance criteria would have standalone components (e.g., accuracy of the AI's view classification vs. ground truth).

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

• Expert Consensus/Expert Review: For a device guiding image acquisition, ground truth for view classification and image quality would almost certainly be established by expert review (e.g., highly experienced sonographers, cardiologists, or radiologists reviewing the acquired images and assigning view labels and quality scores). This is standard for image guidance systems.

7. The sample size for the training set:

• Not explicitly stated. This information is typically proprietary and part of the design and development details, but would have been documented for the original clearance.

8. How the ground truth for the training set was established:

• Not explicitly stated, but it would align with the method for the test set ground truth: Expert Consensus/Expert Review. The training data (images and associated metadata) would be meticulously labeled by qualified experts (e.g., specifying which view each image represents, and potentially assigning quality scores) to enable the AI to learn.

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

The 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 computer assisted acquisition guidance system that provides real-time user guidance during acquisition of echocardiography to assist the user 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:

• 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.
• 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.
• 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.
• 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 provided text describes the Caption Guidance software, an updated version of a previously cleared device. The submission focuses on demonstrating substantial equivalence to its predicate device rather than presenting a new clinical study with specific acceptance criteria and performance metrics for the updated features in a comparative effectiveness study.

Therefore, the information for some of your requested points is not explicitly detailed in the provided text, as the submission relies on demonstrating that the modifications to the device do not raise new questions of safety or effectiveness and that the overall functionality remains substantially equivalent to the predicate.

Here's a breakdown of the information available based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state a table of specific acceptance criteria with numerical targets for the reported device performance related to the updated features of Caption Guidance (e.g., a specific recall or precision for Auto-Capture). Instead, it describes general performance testing and verification activities to ensure the software performs as expected and is substantially equivalent to the predicate.

The "Performance Data" section details that:

• "Extensive algorithm development and software verification testing assessed the performance of the software."
• "The Caption Guidance algorithm was tested for the performance of the modified Auto-Capture feature in recording clinically-acceptable images and clips."
• "Furthermore, the subject device's algorithm was tested for the performance of providing Prescriptive Guidance (PG), using the following tasks:
  • 1. Frame-level PG prediction of the probe maneuver needed to acquire an image/frame of heart, for a specific view.
  • 2. Clip-level PG prediction of the probe maneuver needed to acquire a diagnostic quality clip for a specific view."

The conclusion is that "Overall, the non-clinical performance testing results provide evidence in support of the functionality of Caption Guidance fundamental algorithms."

For Human Factors Testing, the results conclude:

• "Summative testing has been completed with 16 users without prior scanning experience and 9 users with prior experience)."
• "The summative human factors testing concluded that there were no use errors associated with critical tasks likely to lead to patient injury."
• "Additionally, although the testing was not comparative in nature, when viewed in context of the testing provided in the original De Novo, the enhanced product appears to provide optimization of usability."

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

The document does not specify a separate "test set" sample size for evaluating clinical performance in the traditional sense for this 510(k) submission. The focus was on software verification and validation, and human factors testing.

• Human Factors Testing:
  • Sample Size: 16 users without prior scanning experience and 9 users with prior experience (total 25 users).
  • Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). This was likely prospective testing conducted with study participants.

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

This information is not provided in the document. As the submission focuses on software verification and human factors for an updated version of a device, the establishment of ground truth by multiple experts for a clinical "test set" in the context of diagnostic accuracy is not detailed for this specific submission. The initial De Novo submission (DEN190040) would likely contain this information for the predicate device.

4. Adjudication Method for the Test Set

This information is not provided in the document.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

A formal multi-reader multi-case (MRMC) comparative effectiveness study was not done for this 510(k) submission. The document explicitly states for the human factors testing: "although the testing was not comparative in nature...". The comparison is mainly against the predicate device's established performance and the demonstration that the enhancements do not introduce new risks or diminish performance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

The document states: "Extensive algorithm development and software verification testing assessed the performance of the software." and "The Caption Guidance algorithm was tested for the performance of the modified Auto-Capture feature... Additionally, the subject device's algorithm was tested for the performance of providing Prescriptive Guidance (PG)..."

This indicates that standalone algorithm performance testing was conducted for the Auto-Capture and Prescriptive Guidance features. However, specific metrics (e.g., accuracy, sensitivity, specificity) for this standalone performance are not provided. The human factors testing then evaluates the human-in-the-loop performance of the entire system.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.)

For the algorithm testing of Auto-Capture and Prescriptive Guidance, the ground truth would likely be based on:

• Expert Consensus/Clinical Acceptability: For Auto-Capture, the "recording clinically-acceptable images and clips" implies expert assessment of image quality.
• Expert Knowledge of Optimal Probe Maneuvers: For Prescriptive Guidance, the ground truth for "probe maneuver needed to acquire an image/frame of heart" or "diagnostic quality clip" would stem from expert sonographer knowledge and established echocardiography guidelines.

The document does not explicitly state the methodology for establishing this ground truth (e.g., specific number of sonographers or cardiologists, their qualifications).

8. The Sample Size for the Training Set

The document does not provide a specific sample size for the training set used for the Caption Guidance algorithms. It mentions "Extensive algorithm development..." but does not detail the training data sets.

9. 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. However, given the nature of the device (guidance for cardiac ultrasound acquisition), it would typically involve:

• Expert Sonographer/Cardiologist Annotation: Labeling of optimal probe positions, image quality assessments, and identification of standard views in echocardiogram clips.
• Adherence to Clinical Guidelines: Ensuring annotations align with established protocols for acquiring diagnostic quality echocardiograms.

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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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