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The LARIAT® RS Suture Delivery Device facilitates suture placement and knot tying for use in surgical applications where soft tissue are being approximated and/or ligated with a pre-tied polyester suture.

The LARIAT® RS Suture Delivery Device is a one-piece, single-use suture delivery and deployment device with a pre-tied size "0" polyester suture loop that is pre-loaded on a retractable Delivery Snare on the distal end of the device. The pre-tied suture loop is held onto the Delivery Snare and allows for multiple opening and closings of the suture loop without release. Upon tightening of the suture loop, the suture is released from the Delivery Snare. An accessory lumen within the LARIAT RS device is designed for aspiration. flushing or to accommodate a guide wire of up to 0.035" diameter. The LARIAT RS device offers the additional feature of allowing the user to release the Delivery Snare from the tissue during device removal from the target location following suture deployment. The LARIAT RS device is compatible with access site diameters of 4.3mm and larger. The suture is itself a cleared medical device as a part of K021019.

The provided document is a 510(k) summary for a medical device called the LARIAT® RS Suture Delivery Device. It describes the device, its intended use, and claims substantial equivalence to a predicate device (LARIAT III Suture Delivery Device). However, the document does not contain information about the acceptance criteria or the study that proves the device meets specific acceptance criteria in the context of AI/ML performance.

This document pertains to the regulatory clearance of a physical medical device based on its substantial equivalence to a previously cleared device, not an AI/ML system's performance. The "testing in support of substantial equivalence determination" listed focuses on mechanical and functional aspects of the physical device (e.g., joint strength, actuation, aspiration, suture properties), typical for a traditional medical device submission.

As such, I cannot extract the requested information (acceptance criteria, device performance table, sample sizes for test/training, expert qualifications, adjudication, MRMC studies, standalone performance, ground truth types) because the document does not describe a study involving an AI/ML algorithm or its performance characteristics.

The specific questions you've asked are relevant to assessing the performance of AI/ML-driven medical devices, which typically involve metrics like sensitivity, specificity, AUC, and rigorous validation studies comparing an algorithm's output to a 'ground truth' established by human experts or pathology. This document does not describe such a validation study.

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The LARIAT® III Suture Delivery Device facilitates suture placement and knot tying for use in surgical applications where soft tissue are being approximated and/or ligated with a pre-tied polyester suture.

The LARIAT® III Suture Delivery Device is a one-piece, single-use suture delivery and deployment device with a pre-tied size "0" polyester suture loop that is pre-loaded on a retractable Delivery Snare on the distal end of the device. The pre-tied suture loop is held onto the Delivery Snare and allows for multiple opening and closings of the suture loop without release. Upon tightening of the suture loop, the suture is released from the Delivery Snare. An accessory lumen within the LARIAT III device is designed for aspiration and flushing. The LARIAT III device is compatible with access site diameters of 4.3mm and larger. The suture is itself a cleared medical device as a part of K021019.

The provided document is a 510(k) premarket notification for the LARIAT® III Suture Delivery Device. It details the device's characteristics, intended use, and claims of substantial equivalence to a predicate device (LARIAT II Suture Delivery Device). This type of submission relies on comparisons to already-cleared devices and bench testing rather than clinical study data for device performance metrics related to diagnostic accuracy or clinical outcomes often seen with AI/ML devices. Therefore, a direct application of typical "acceptance criteria" for AI/ML performance metrics and detailed clinical study information is not present in this document.

However, I can extract the information that is available regarding the device's performance through bench testing in support of its substantial equivalence claims.

1. A table of acceptance criteria and the reported device performance

The document does not explicitly state numerical "acceptance criteria" with thresholds for each test, but rather lists the types of bench tests performed to confirm the device performs "according to the stated intended use." The reported device performance is broadly stated as successful completion of these tests.

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

The document specifies "bench testing" was conducted. This typically refers to laboratory-based tests on physical devices or components, not clinical data. Therefore, details like "country of origin of the data" or "retrospective or prospective" do not apply. The sample size for each specific bench test is not provided in this summary.

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

Not applicable. Bench testing of a mechanical device does not typically involve human experts establishing ground truth in the way it would for an AI diagnostic device. The "ground truth" for these tests would be derived from engineering specifications and widely accepted physical/material science principles.

4. Adjudication method for the test set

Not applicable, as this refers to a method used to resolve discrepancies among human experts during ground truth establishment for clinical/diagnostic performance, which is not relevant for this type of bench testing.

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

Not applicable. This device is a surgical tool, not an AI/ML diagnostic or assistive device that would involve human "readers" or AI assistance.

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

Not applicable. This device is a mechanical surgical tool, not an algorithm.

7. The type of ground truth used

For bench testing, the "ground truth" is typically defined by accepted engineering specifications, material properties, and functionality requirements rather than expert consensus, pathology, or outcomes data. For example, a "suture tensile strength test" would have a specified minimum tensile strength (ground truth) that the suture must meet.

8. The sample size for the training set

Not applicable. This device is not an AI/ML model that requires a training set.

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

Not applicable. This device is not an AI/ML model that requires a training set.

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The LARIAT II Suture Delivery Device facilitates suture placement and knot tying for use in surgical applications where soft tissue are being approximated and/or ligated with a pre-tied polyester suture.

The LARIAT II Suture Delivery Device is a one-piece, single-use suture delivery and deployment device with a pre-tied size 0 polyester suture loop that is pre-loaded on the device. A lumen within the LARIAT II is designed for aspiration, flushing during the delivery, capture or release of the LARIAT II Suture.

The LARIAT II is packaged with a guide cannula and a dilator which may be used for guidance and placement of the LARIAT II, and a surgical blade which is used for cutting excess suture.

The suture is itself a cleared medical device as a part of Pre-Market Notification K021019.

The provided document, K090385, describes the LARIAT II Suture Delivery Device, its intended use, and substantial equivalence to predicate devices. However, it does not contain the detailed information required to fill out all sections of your request regarding acceptance criteria and a specific study proving device performance against those criteria.

The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to legally marketed predicate devices. It states that "Functional testing was conducted to support the claim of substantial equivalence and to demonstrate the LARIAT II is safe and effective for its intended use" and "Results of testing demonstrate the LARIAT II is biocompatible." However, it does not provide the specific acceptance criteria for this functional testing, nor does it detail the study design, sample sizes, ground truth establishment, or expert involvement that you've requested.

Therefore, many of your requested fields cannot be populated from the provided text.

Here's a breakdown of what can and cannot be answered based on the input:

1. A table of acceptance criteria and the reported device performance

• Cannot be provided. The document states "Functional testing was conducted to support the claim of substantial equivalence," but it does not list specific acceptance criteria or the reported performance data against those criteria.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Cannot be provided. The document only mentions "Functional testing" without any details on sample size or data provenance.

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/Cannot be provided. This type of information is typically relevant for studies involving subjective human assessment (like image interpretation). For a suture delivery device, "ground truth" would likely be objective mechanical or functional performance, not expert consensus on an interpretation. The document does not describe any such expert-based ground truth establishment.

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

• Not applicable/Cannot be provided. Similar to point 3, this is not relevant for the type of testing described (functional performance of a mechanical device).

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. This type of study is completely irrelevant for a suture delivery device, which is a physical surgical tool, not an AI-powered diagnostic or assistive reading tool.

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

• No. This is also irrelevant as the device is a manual surgical tool, not an algorithm.

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

• Cannot be provided definitively. Based on the general description of "functional testing," the ground truth would likely be based on objective measurements of mechanical performance (e.g., suture integrity, delivery success, knot security, material strength, biocompatibility), rather than expert consensus, pathology, or outcomes data in the traditional sense of diagnostic devices. However, the specific metrics and how they constitute "ground truth" are not detailed.

8. The sample size for the training set

• Not applicable. The LARIAT II Suture Delivery Device is a physical medical device, not an AI or machine learning model that requires a training set.

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

• Not applicable. As above, no training set for an algorithm exists for this device.

In summary, the provided K090385 document is a regulatory submission focused on substantial equivalence rather than a detailed scientific study report. It states that functional testing was performed but lacks the granular data and methodological details you are seeking.

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The FindrWIRZ System is intended for use in the cardiovascular system for introduction and positioning of over-the-wire catheters and therapeutic devices during interventional procedures. A FindrWIRZ may also be used to manipulate and or reposition another FindrWIRZ. The FindrWIRZ System is not intended for use in the coronary or cerebral vasculature.

The FindrWIRZ System consists of the following components: A 0.035" x 90 cm FindrWIRZ A 0.025" x 260 cm FindrWIRZ Guide wire introducer Torque device Each FindrWIRZ is configured with a tapered core wire and a distal coil, the 0.035 FindrWIRZ has a proximal PTFE jacket and both wires have a hydrophilic coating. The distal tip of each wire has an encapsulated magnet of opposite polarization which is used for proximity sensing and connection of the two guide wires to facilitate manipulation and positioning of each other. The FindrWIRZ System is sterilized with 100% ethylene oxide.

The FindrWIRZ Guide Wire System is a medical device intended for use in the cardiovascular system for the introduction and positioning of over-the-wire catheters and therapeutic devices during interventional procedures. The provided document is a 510(k) summary, which outlines the device's safety and effectiveness compared to predicate devices. It does not contain detailed information about specific acceptance criteria or an explicit study that proves the device meets those criteria. Instead, it describes general functional testing and biocompatibility testing to support the claim of substantial equivalence.

Here's a breakdown of the information available and what is not explicitly stated in the provided text, structured as requested:

1. Table of Acceptance Criteria and Reported Device Performance:

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

The document mentions "Functional testing" and "Results of testing" for biocompatibility but does not specify sample sizes for any test sets. It also does not provide any information regarding data provenance (e.g., country of origin, retrospective or prospective) as the testing appears to be primarily bench testing and material testing, not human clinical data.

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

This information is not applicable and not provided in the document. The testing described is for the performance and biocompatibility of a physical medical device, not for an algorithm requiring expert-established ground truth.

4. Adjudication Method for the Test Set:

This information is not applicable and not provided in the document, as it relates to expert review of data, which is not described.

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

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done as this type of study is typically conducted for diagnostic algorithms or imaging interpretation, not for the functional assessment of a guide wire system.

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

A standalone (algorithm only) performance study was not done as the FindrWIRZ Guide Wire System is a physical medical device and not an AI algorithm.

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

The concept of "ground truth" as typically used for AI or diagnostic studies is not applicable here. The "ground truth" for the device's performance would be established through engineering specifications, material standards, and clinical requirements for guide wires, validated through bench testing, material testing, and potentially pre-clinical (animal) studies (though these are not detailed in the summary).

8. The Sample Size for the Training Set:

This information is not applicable and not provided as this device is not an AI algorithm requiring a training set.

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

This information is not applicable and not provided as the device is not an AI algorithm requiring a training set.

In summary: The provided 510(k) summary focuses on demonstrating substantial equivalence to predicate devices through functional and biocompatibility testing. It lacks detailed quantitative data on specific acceptance criteria and study methodologies, which is common for this type of regulatory submission for a physical medical device. The concepts of "ground truth," "expert adjudication," "sample size for test sets," and "AI performance studies" do not directly apply to the information presented for the FindrWIRZ Guide Wire System.

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The SentreHeart Occlusion Balloon Catheter is intended for temporary occlusion of large vessels in applications such as arteriography, preoperative occlusion, and emergency controlled hemorrhage procedures.

The Occlusion Balloon Catheter consists of a catheter shaft with two independent lumens upon which an expandable balloon material is bonded. The "Guide Wire" lumen extends the length of the catheter and is used for placement of guide wires and injection of contrast for angiographic visualization. The "Balloon" lumen is used to inflate and deflate the balloon. Radiopaque markers at the location of the balloon provide fluoroscopic visualization of balloon placement. The outer diameter of the catheter shaft is coated with a hydrophilic polymer that reduces friction during manipulation in the vessel.

The provided text describes a 510(k) summary for the SentreHeart Occlusion Balloon Catheter. However, it does not contain specific details about acceptance criteria for performance, device performance data through a study, sample sizes for testing, ground truth establishment, or human-in-the-loop studies.

Here's a breakdown of what can be extracted and what information is missing based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

Missing Information: The document states that functional testing and biocompatibility testing were performed but does not quantify the acceptance criteria or the results against those criteria. It relies on a general statement of "safe and effective" and "biocompatible."

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

Missing Information: The document does not mention any specific test set, its sample size, or data provenance (e.g., country of origin, retrospective/prospective). The "functional testing" is broadly mentioned without any details.

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

Missing Information: Since no specific test set or clinical study is detailed, there is no mention of experts or how ground truth would have been established. This device is a catheter, not an AI/diagnostic imaging device where expert interpretation is typically a primary ground truth.

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

Missing Information: No information provided.

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

Missing Information: This is not applicable to a device like an "Occlusion Balloon Catheter." MRMC studies are typically for diagnostic imaging devices where human interpretation is involved. This is a medical device for temporary occlusion, not a diagnostic tool assisted by AI.

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

Missing Information: This is not applicable. The device is a physical catheter, not an algorithm.

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

Missing Information: For a medical device like this, "ground truth" would typically relate to the physical and mechanical properties of the device (e.g., balloon inflation pressure, burst pressure, material strength, biocompatibility results) and its ability to achieve its intended function (occlusion) in relevant models (in vitro, animal, or human studies, though clinical efficacy data isn't detailed here for the 510(k)). The document only generally refers to "functional testing."

8. The sample size for the training set

Missing Information: Not applicable. This is not an AI/machine learning device that requires a training set.

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

Missing Information: Not applicable.

Summary of the Study Mentioned in the Document:

The document briefly mentions:

• "Functional testing": Conducted to support substantial equivalence and demonstrate safety and effectiveness.
• "Biocompatibility testing": Conducted for the materials used in the catheter.

Key takeaway: This 510(k) summary is for a medical device (a catheter), not a software or AI-based diagnostic tool. Therefore, many of the requested categories (like ground truth from experts, MRMC studies, training sets, algorithms) are not applicable. The document itself provides a very high-level summary of testing without specific quantitative performance data or detailed study designs. It relies on the concept of "substantial equivalence" to predicate devices rather than novel, extensive performance studies with detailed acceptance criteria for statistical clinical endpoints.

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The LARIAT Loop Applicator facilitates suture placement and knot tying for use in surgical applications where soft tissue are being approximated and/or ligated with a pre-tied polyester suture.

The LARIAT Loop Applicator is a one piece, single-use suture delivery and deployment device with a pre-tied polyester suture loop that is pre-loaded on the device. A central lumen within the LARIAT Loop Applicator is designed for aspiration and stabilization of tissue during the delivery of the LARIAT Suture Loop.

The provided 510(k) notification describes a medical device, the LARIAT Loop Applicator, and its intended use. However, the document does not contain specific acceptance criteria or a detailed study proving the device meets particular acceptance criteria in the manner typically associated with studies for AI/ML devices or diagnostic tools.

Instead, this 510(k) focuses on demonstrating substantial equivalence to predicate devices, primarily through in-vitro testing and assessment of biocompatibility. The information provided is characteristic of a medical device submission that relies on established safety and effectiveness profiles of already cleared devices and materials.

Given this, I cannot fully complete all sections of your request as they are not explicitly addressed in the provided text. I will fill in what is available and indicate where information is missing.

Here's the breakdown based on the provided text:

1. A table of acceptance criteria and the reported device performance

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample Size: Not specified for in-vitro testing.
• Data Provenance: Not specified, but generally, in-vitro testing for 510(k) submissions would be conducted in a controlled lab setting, likely within the US where the applicant is located.
• Retrospective/Prospective: Neither. The testing mentioned is in-vitro performance and biocompatibility testing, not clinical data collection.

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. This device is a surgical applicator, not a diagnostic device requiring expert interpretation of results to establish ground truth. The "ground truth" for its performance would be its mechanical functionality (e.g., suture delivery, knot tying) and material safety, evaluated through engineering and biocompatibility testing.

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

Not applicable. This type of adjudication method is relevant for studies involving human interpretation or clinical endpoints, not for the in-vitro performance and biocompatibility testing described.

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

Not applicable. This device is a surgical tool, not an AI-assisted diagnostic or interpretive system. Therefore, MRMC studies and AI improvement effect sizes are not relevant to this submission.

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

Not applicable. The device is a physical surgical applicator, not an algorithm.

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

The "ground truth" implicitly used for this device involves:

• Engineering specifications and functional requirements for safe suture delivery and deployment.
• Biocompatibility standards and established safety profiles for the materials used and similar predicate devices.
• The effectiveness of the predicate devices in their intended uses.

8. The sample size for the training set

Not applicable. This device is not an AI/ML algorithm that requires a training set.

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

Not applicable.

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