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The Novasight Hybrid System is intended for intravascular imaging of coronary arteries and is indicated in patients who are candidates for transluminal interventional procedures.

The Novasight™ Hybrid System is intended for real-time, minimally-invasive guidance of transluminal interventional procedures. The system provides image information of coronary vessel anatomic features, spatial relationships of other devices within the coronary arteries, and intra-procedural complications such as perforation. The system is comprised of a catheter and a cart based console. The console includes the Acquisition and Display Module (ADM) for image acquisition, display and manipulation as well as the Patient Interface Module (PIM) which the catheter connects to. The ADM has two monitors to allow for ease of image view and review for both the technologist and the physician users. The technologist user is able to control the system software via an easy to use interface using multiple methods of input including a trackpad, keyboard and/or a touch screen. Casters on the ADM allow easy movement of the system throughout a cath lab which can have a small footprint as well as small obstacles to cross. The PIM has a user interface for the physician to have control over the acquisition. It is also compact such that it can be moved and handled by an able-bodied user. The system includes software build version 2.0 (2.0.6607.31062). The catheter is a 3Fr single use, sterile device, which is able to perform transluminal ultrasound and optical coherence tomography imaging of adults. The catheter is capable of real-time 2D side viewing ultrasound and optical imaging acquired simultaneously providing precisely co-registered images with the ability to produce rapidly post processed rendered longitudinal images of the vessel. The imaging system is able to resolve features within coronary arteries such as healthy tissue and stent struts. The physician user has the ability to manually position the imaging sensor as well as perform pullback (automatically or manually trigger) for defined regions of interest.

The provided text is a 510(k) summary for the Conavi Medical Inc. Novasight Hybrid System. It primarily focuses on demonstrating substantial equivalence to predicate devices based on functional and technological comparisons and non-clinical performance testing.

The document does not include detailed acceptance criteria for standalone device performance nor does it describe a study explicitly proving the device meets said acceptance criteria in a quantitative manner with reported performance metrics, ground truth, or expert consensus.

Instead, the document states:

• "No clinical study is included in the submission. Determination of substantial equivalence Performance is based on an assessment of non-clinical data." (Page 5)
• "Verification and validation test were performed in accordance with the following standards, and test results confirm that results demonstrate that Novasight Hybrid System demonstrate as intended meeting the applicable requirements." (Page 17)

Therefore, I cannot populate the table or provide specific details regarding sample sizes, ground truth establishment, or expert qualifications for performance criteria because this information is not present in the provided document. The document focuses on regulatory compliance through non-clinical testing and comparison to predicate devices, rather than a clinical performance study with defined acceptance criteria and reported outcomes for the device's diagnostic capabilities.

However, based on the non-clinical testing listed, I can infer the types of acceptance criteria the device would have met in terms of safety and technical specifications, as these are the focus of the testing mentioned.

Here's a breakdown of what can be extracted and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

Since no specific performance metrics like sensitivity, specificity, or accuracy for diagnostic tasks are provided, and no quantitative acceptance criteria for such metrics are given, this table cannot be fully populated as requested. The "reported device performance" is broadly stated as meeting "applicable requirements" of various standards.

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

• Not provided. The document states, "No clinical study is included in the submission." The non-clinical tests would have involved specific test samples (e.g., catheters, system components) but the "sample size" in a clinical or diagnostic performance context is not applicable here.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

• Not applicable/Not provided. Since no clinical performance study with ground truth establishment was conducted or submitted, this information is not available.

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

• Not applicable/Not provided. No adjudication method is mentioned as there's no clinical test set for diagnostic performance.

5. 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. The document explicitly states "No clinical study is included in the submission." Therefore, no MRMC study or AI assistance improvement effect size is reported.

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

• No specific standalone diagnostic performance study was reported. The device is an imaging system (hardware and software) intended for real-time guidance. Its "standalone" performance is implicitly covered by its technical specifications and compliance with safety and imaging standards (e.g., acoustic output, image resolution capability, etc., which are compared to predicates and tested non-clinically). However, this is not a diagnostic algorithm performance study.

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

• Not applicable/Not provided. No ground truth for diagnostic performance assessment is mentioned, as no clinical study was performed. The "ground truth" for the non-clinical tests would be the established engineering and safety standards.

8. The sample size for the training set:

• Not applicable/Not provided. There is no mention of a training set, indicating that this submission is not for an AI/ML-based diagnostic algorithm that would typically require a training set for its development. The device is hardware and associated software.

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

• Not applicable/Not provided. As there is no mention of a training set, this information is not available.

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The Foresight Intracardiac Echocardiography (ICE) System is indicated for intraluminal ultrasound visualization of cardiac and great vessel anatomy and physiology as well as visualization of other devices in the heart and great vessels of patients.

The Foresight ICE System is intended to be used for real-time, minimally-invasive guidance of several different intracardiac procedures including, but not limited to, atrial ablation procedures and transseptal punctures. The system will provide image information of cardiovascular anatomic features, spatial relationships of other devices within the heart and great vessels, physiological information of cardiovascular structures and features, and intra-procedure complications including pericardial effusions. The system will be comprised of catheter and a cart based console. The console includes the Acquisition and Display Module (ADM) for image display and manipulation as well as the Patient Interface Module (PIM) which the catheter connects to. The ADM will have two monitors to allow for ease of image view and review for both the technician and physician user. The technician user will be able to control the system software via an easy to use interface using multiple methods of input including a mouse, keyboard and/or a touch screen. Casters on the ADM will allow easy movement of the system throughout an EP Lab which can have a small footprint as well as small obstacles to cross. The catheter will be a 10.3F single use, sterile device, which will be able to perform intracardiac and intraluminal ultrasound imaging of adults. The catheter will be capable of real-time 2D side and forward viewing imaging with the ability to produce rapidly post processed 3D rendered images as well as ECG gated 3D images to reduce motion artifacts. The imaging system will be able to resolve and measure features such as the inferior and superior vena cava, ascending and descending aorta, left and right atria, left and right ventricle, fossa ovalis, aortic valve, mitral valve and tricuspid valves. It will display / measure flow velocities using Color and PW Doppler. The physician user will have easy steering maneuverability of the catheter via deflection and rotation, as well as having control over the position of the transducer to allow for multiple angles of images.

The provided document is a 510(k) premarket notification for a medical device (Foresight Intracardiac Echocardiography (ICE) System). It focuses on demonstrating substantial equivalence to predicate devices, rather than establishing acceptance criteria and proving performance against them in the way modern AI/ML device submissions might.

Therefore, many of the requested details, such as specific acceptance criteria for algorithm performance, performance metrics, sample sizes for test sets, data provenance, expert ground truth establishment, adjudication methods, MRMC studies, standalone performance, and training set details, are not present in this document.

The document primarily relies on non-clinical data (bench-top evaluations, animal testing, biological safety, electrical safety, acoustic output testing, packaging validation, and compliance with various IEC/ISO standards) to demonstrate substantial equivalence to previously cleared ICE systems. It explicitly states: "No clinical testing is included in the submission. Determination of substantial equivalence Performance is based on an assessment of non-clinical data."

However, I can extract and infer some information based on the type of submission and the data that is provided.

Acceptance Criteria and Study for Foresight Intracardiac Echocardiography (ICE) System

Based on the provided 510(k) summary (K162789), the device is a diagnostic ultrasound system (ICE) intended for visualization of cardiac and great vessel anatomy. The "acceptance criteria" in this context are not quantitative performance metrics for an AI algorithm, but rather the demonstration of substantial equivalence to predicate devices through engineering and non-clinical testing. The study supporting this is a series of non-clinical tests and comparisons.

1. Table of Acceptance Criteria and Reported Device Performance

As this is a 510(k) for an ultrasound imaging system without specific AI algorithms requiring performance metrics like sensitivity/specificity for disease detection, the "acceptance criteria" are related to product specifications, safety, and functionality, demonstrating equivalence to the predicate.

2. Sample Size for Test Set and Data Provenance:

• Test Set Sample Size: Not applicable in the context of typical AI/ML validation with a "test set" of patient data. The "test set" here refers to physical devices undergoing various engineering and safety tests. The document does not specify the number of devices or components tested, but implies standard engineering testing practices.
• Data Provenance: The data comes from non-clinical testing conducted by Conavi Medical Inc. (Canada-based). It is not patient data (retrospective or prospective), but rather lab, benchtop, and animal model data.

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

• Not applicable. This submission does not involve an AI algorithm where human experts establish ground truth from patient data. The "ground truth" for the device's functionality is established by engineering specifications, relevant IEC/ISO standards, and the performance of predicate devices.

4. Adjudication Method for the Test Set:

• Not applicable. There is no "adjudication" in the sense of resolving discrepancies in expert labeling of medical images. Testing involves objective measurements against engineering specifications and safety standards.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

• No. The document explicitly states: "No clinical testing is included in the submission." Therefore, no MRMC study was conducted comparing human readers with and without AI assistance, as there is no AI component being evaluated for diagnostic assistance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done:

• Not applicable. This device is an imaging system, not a standalone algorithm. Its performance is inherent to its ability to generate images, which are then interpreted by a human user.

7. The Type of Ground Truth Used:

• The "ground truth" is established by engineering specifications, international safety and performance standards (IEC, ISO, NEMA), and the established performance characteristics of the predicate devices. For example, the "ground truth" for acoustic output is derived from regulatory limits and safe operation ranges for diagnostic ultrasound. "Animal testing" contributes to safety and functional verification, but not to establishing a diagnostic "ground truth" on patient cases.

8. The Sample Size for the Training Set:

• Not applicable. This device does not use machine learning algorithms that require a "training set" of data.

9. How the Ground Truth for the Training Set was Established:

• Not applicable. See point 8.

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