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The Overture Orthopaedics Patellofemoral System is intended to be used in cemented arthroplasty in patients with osteoarthritis limited to the distal patello-femoral joint, patients with a history of patellar fracture, and those patients with failed previous surgery (arthroscopy, tibial tubercle elevation, lateral release, etc.) where pain, deformity or dysfunction persists.

The Overture Orthopaedics Patellofemoral System is comprised of trochlear implants, and a set of ancillary instruments. The trochlear implants are titanium and feature a polished articulating surface with a titanium nitride (TiN) coating. The patellar implants are cross-linked ultra high molecular weight polyethylene (UHMWPE) and feature a titanium pin for X-ray visualization. The trochlear and patellar implants utilize cemented pegs for immediate fixation. The trochlear implants also feature porous titanium bone-contacting surfaces.

The implants are provided in a variety of configurations and sizes to accommodate various patient anatomy. The trochlear implants are offered in long and round geometries. The long implants are offered in lengths ranging 25-40mm and widths ranging 20-35mm. The round trochlear implants are offered in diameters ranging 20-35mm. The patellar implants are offered in a domed geometry in diameters of 25mm and 30mm.

The implants are provided gamma sterilized and individually packaged. The ancillary instruments are provided non-sterile and are to be sterilized by the end user.

This document is a 510(k) summary for the Overture Orthopaedics Patellofemoral System. It describes the device, its indications for use, and a comparison to a predicate device to establish substantial equivalence.

Based on the provided text, the device in question is a medical implant, specifically a patellofemoral system for knee joint arthroplasty. The acceptance criteria and the study that proves the device meets them are described in terms of performance testing for mechanical characteristics, not in terms of diagnostic accuracy or reader performance as the format of the request assumes.

Here's a breakdown of the requested information based on the provided document:

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

   The document does not explicitly list acceptance criteria in a quantitative table with corresponding reported performance for each criterion. Instead, it lists the types of performance testing conducted to demonstrate substantial equivalence. The document states:

   "In summary, rationales and mechanical testing of the Overture Orthopaedics Patellofemoral System indicated there are no new risks and demonstrated substantial equivalence in performance compared to a legally marketed predicate."

   This implies that the acceptance criterion for each test was likely "demonstrates substantial equivalence to the predicate device" or "meets established rationales without new risks." The reported device performance is summarized as having met this overall criterion.

   Acceptance Criteria (Implied)	Reported Device Performance
   Demonstrate substantial equivalence to predicate device in terms of:
   - Patellofemoral Contact Area and Contact Stress	Testing indicated no new risks and substantial equivalence.
   - Patellofemoral Constraint	Testing indicated no new risks and substantial equivalence.
   - Range of Motion	Testing indicated no new risks and substantial equivalence.
   - Fatigue Strength	Rationale adopted, indicating substantial equivalence.
   - Wear	Rationale adopted, indicating substantial equivalence.
   - Additive Manufacturing Characteristics	Rationale adopted, indicating substantial equivalence.
   - Characterization of UHMWPE	Rationale adopted, indicating substantial equivalence.
   - Characterization of Porous Coating	Rationale adopted, indicating substantial equivalence.
   - Modified Metallic Surfaces	Rationale adopted, indicating substantial equivalence.
   Absence of new risks	No new risks indicated.

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

   The document describes "bench testing" and "cadaveric validation lab." It does not specify sample sizes for these tests (e.g., how many implants were tested for fatigue, how many cadavers were used). It also does not mention country of origin or whether the data was retrospective or prospective, as these terms are generally not applicable to bench and cadaveric testing of medical implants.

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)

   This question is not applicable to the type of device and testing described. The "ground truth" for mechanical performance tests is typically measured physical properties, not expert consensus on medical images or diagnoses.

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

   This question is not applicable. Adjudication methods are typically used for establishing ground truth in clinical studies involving interpretation (e.g., by radiologists), not for bench testing of medical implants.

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

   This question is not applicable. An MRMC study with human readers and AI assistance is relevant for diagnostic AI devices. The Overture Orthopaedics Patellofemoral System is a surgical implant undergoing mechanical and material testing, not an AI diagnostic tool.

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

   This question is not applicable. The device is a physical implant, not an algorithm.

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

   For the performance testing mentioned (e.g., contact area, stress, constraint, fatigue), the "ground truth" would be physical measurements and engineering data obtained from standardized mechanical tests or cadaveric studies. The basis for comparison is the performance of the legally marketed predicate device.

8. The sample size for the training set

   This question is not applicable. There is no concept of a "training set" for a physical medical implant device in the context of its mechanical performance testing.

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

   This question is not applicable for the same reason as point 8.

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The Episealer Patellofemoral System is intended to be used in patients with osteoarthritis limited to the distal patellofemoral joint, patients with a history of patellar dislocation or patellar fracture, and those patients with failed previous surgery (arthroscopy, tibial tubercle elevation, lateral release, etc.) where pain, deformity or dysfunction persists.

The device is intended for cemented fixation.

The Episealer Patellofemoral System is a patient-individualized arthroplasty device which replaces a damaged patellofemoral joint. The subject device consists of two components:

• . Episealer PF
• Patellar Component ●

The Episealer PF component is implanted centrally in the trochlear area of the distal femur. The Patellar Component is implanted on the backside of the patella and articulates with the Episealer PF.

The provided text describes a 510(k) premarket notification for the Episealer® Patellofemoral System, an orthopedic device. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving a new device's safety and effectiveness through extensive clinical trials with pre-defined acceptance criteria.

As such, detailed information regarding acceptance criteria for a specific performance metric, and a study proving those criteria were met in the same way one would assess an AI/ML algorithm, is not available in this document.

However, I can extract the information that is present regarding performance testing, even though it's not structured around explicit acceptance criteria and corresponding performance metrics in the way you've requested for an AI model.

Here's an attempt to answer your request based on the provided text, highlighting what is included and what is explicitly not mentioned:

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

The document does not explicitly present a table of acceptance criteria with corresponding performance metrics like "sensitivity", "specificity", "AUC", or "agreement" as would be seen for an AI/ML device. Instead, it describes general performance testing and analyses.

Summary of Performance Testing:

The document states: "Performance Testing Summary: Wear testing of the Episealer Patellofemoral System was performed. In addition, analyses of contact area and cantilever bending strength were conducted. A cadaver study was conducted to demonstrate that the components of the patient-matched Episealer Patellofemoral System can be accurately placed relative to the pre-planned position, with proper recession and engagement of the Episealer PF and Patellar components. The testing, engineering analyses, and cadaver study demonstrate the ability of the Episealer Patellofemoral System to perform as intended in the target population."

This section indicates that the device underwent standard engineering and mechanical testing relevant to orthopedic implants, as well as a cadaver study to verify surgical placement. However, specific acceptance criteria (e.g., "wear rate must be less than X," "contact area must be within Y range") and the quantitative results against those criteria are not provided in this 510(k) summary. The conclusion is a qualitative statement: "demonstrate the ability... to perform as intended."

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

• Sample Size for Test Set: Not specified in the provided summary. The text only mentions "wear testing," "analyses of contact area and cantilever bending strength," and "A cadaver study." The number of cadavers or individual test repetitions is not given.
• Data Provenance: Not specified.

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)

This is not applicable in the context of this device. A medical device like the Episealer Patellofemoral System undergoes engineering, mechanical, and cadaveric testing, not evaluation against expert-defined "ground truth" labels in the way an AI/ML diagnostic tool would.

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

This is not applicable for the type of testing described (mechanical testing, cadaver study).

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

This is not applicable. This is an orthopedic implant, not an AI-assisted diagnostic tool.

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

This is not applicable. This is an orthopedic implant, not an algorithm. The device itself is a standalone implant that is surgically placed.

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

The concept of "ground truth" as used for AI/ML evaluation does not directly apply here. Instead, performance is assessed through:

• Engineering measurements (wear, contact area, bending strength) against industry standards or internal specifications.
• Cadaveric surgical validation, where the "truth" would be successful implantation according to surgical protocols and demonstration of intended function.

8. The sample size for the training set

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

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

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

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The Avon Patello-femoral Joint Prosthesis is intended to be used in cemented patellofemoral arthroplasty in patients with degenerative arthritis in the distal femur and patella, patients with a history of patellar dislocation or patella fracture, or patients with failed previous surgery (arthroscopy, tibial tubercle elevation, lateral release) where pain, deformity or dysfunction persists.

These components are single use only and are intended for implantation with bone cement.

This submission covers the Avon femoral and patellar components of the Avon Patello-femoral Joint Prosthesis. The femoral components are manufactured from Cobalt Chrome (CoCr) and the patellar components are manufactured from Ultra-high Molecular Weight Polyethylene (UHMWPE) materials.

The purpose of this submission is to add Magnetic Resonance (MR) Conditional labeling to the labeling of the Avon femoral and patellar components of the Avon Patello-femoral Joint Prosthesis. Additionally, minor labeling and packaging updates, as detailed in the respective sections, are also included in this submission.

The provided text is a 510(k) Summary for a medical device (Avon Patello-femoral Joint Prosthesis) seeking clearance for minor labeling and packaging updates, specifically to add Magnetic Resonance (MR) Conditional labeling. This submission does not describe a study to prove the device meets acceptance criteria related to its clinical effectiveness or performance in a patient.

Instead, it describes non-clinical testing to demonstrate that the device is "MR Conditional" as per relevant ASTM standards. Therefore, many of the requested categories are not applicable to the information provided.

Here's the breakdown of what can be extracted:

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

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

This information is not provided. The testing was non-clinical (laboratory testing of the device components), not involving human subjects or patient data.

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. The ground truth for the MR Conditional testing is established by the ASTM standards themselves, which define methodologies and criteria for measurement. No human experts were involved in establishing "ground truth" for this non-clinical testing.

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

Not applicable. This was non-clinical, objective testing against predefined engineering standards.

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 document is not about AI or diagnostic imaging interpretation. It is for a joint prosthesis and its MR compatibility.

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

Not applicable. This document is not about an algorithm, but a physical medical device.

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

The "ground truth" for the non-clinical testing was defined by adherence to published ASTM standards for MR compatibility. These are objective engineering and physics standards.

8. The sample size for the training set

Not applicable. This was non-clinical testing, not a machine learning study.

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

Not applicable. This was non-clinical testing, not a machine learning study.

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The MOTO PFJ is designed for cemented use in partial knee arthroplasty, if there is evidence of enough sound bone to seat and support the components. Patellofemoral replacement is indicated in the following cases:

Osteoarthritis, post-traumatic arthritis, polyarthritis, severe chondrocalcinosis of the patellofemoral joint.

Previously failed surgical attempts (i.e. arthroscopy, lateral release, tibial tubercle elevation, cartilage transplantation). History of patellar dislocation or fracture, resulting in cartilage degeneration of the patellofemoral joint.

Degeneration induced by dysplasia.

If the surgeon evaluates an unequivocal indication for replacement of the patellofemoral joint, with or without a patella resurfacing, which outweighs the risks associated with the surgery, PFJ replacement may be considered, particularly for young patients.

The MOTO PFJ System, subject of this submission, consists of:

• o Patello Femoral Joint, made of Cobalt-Chromium-Molybdenum alloy
• MOTO Patella, made of UHMWPE ●

The MOTO PFJ System is intended for replacement of the femoral trochlea of the patellafemoral joint affected by injury and/or disease process.

The MOTO PFJ System is intended for cemented use only.

The MOTO PFJ System may be used alone or in combination with the MOTO Partial Knee System Unicompartmental Prosthesis (Medial K161741 and Lateral K183029) and GMK UNI Prosthesis (K162084), to treat multiple conditions of patellofemoral and tibiofemoral regions of the natural knee. The Patello Femoral Joint component is designed to articulate with natural patella or with the dedicated MOTO Patella.

The provided document is a 510(k) summary for the Medacta International SA MOTO PFJ System. It describes the device, its indications for use, and a comparison to predicate devices, along with performance data. However, this document does not describe an AI/ML medical device. It details a knee joint patellofemoral polymer/metal semi-constrained cemented prosthesis.

Therefore, most of the requested information regarding acceptance criteria and studies for an AI/ML medical device (such as sample size for test sets, ground truth establishment, expert adjudication, MRMC studies, and standalone performance) is not applicable or present in this document.

The document focuses on non-clinical performance data to demonstrate substantial equivalence to predicate devices, which is typical for implantable medical devices of this type.

Here's an analysis of what is available and what is not for an AI/ML context:

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

• For an AI/ML device: This would typically involve metrics like sensitivity, specificity, accuracy, F1-score, AUC, etc., with pre-defined thresholds for acceptance.

• For this device: The acceptance criteria are based on mechanical and material performance, and biological safety. The "performance" is demonstrated through various non-clinical tests.

  • Acceptance Criteria (Implied from tests): The device must demonstrate sufficient fatigue endurance under walking and squatting scenarios, proper articular surface congruence, acceptable range of motion, comparable constraints to predicate, comparable contact pressure and areas to predicate, and acceptable wear behavior. Biocompatibility (pyrogenicity, LAL test) is also an acceptance criterion.
  • Reported Device Performance:
    • Non-Clinical Studies (Validation & Characterization):
      • Shape and Dimension Validation
      • Cadaveric workshop validation
      • Fatigue Endurance Test (Walking Scenario) - Test Reports A3
      • Fatigue Endurance Test (Squatting Scenario) - Test Reports A4
      • Articular Surface Fully Congruent - Test Report B1
      • Range of Motion - Test Report B2
      • Comparison within Medacta MOTO Patella and Zimmer NexGen Patella Constraints - Test Report B3
      • Comparison within Medacta MOTO Patella and Zimmer NexGen Patella in relation to Contact Pressure and Areas - Test Report B4
      • Wear Behaviour - Test Report B5
      • Bacterial Endotoxin Test (LAL test) - passed (equivalent to USP chapter )
      • Pyrogen test - passed (according to USP )

  Table (Reinterpreting for this hardware device):

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

• For an AI/ML device: This would refer to the number of cases/images in the independent test set.
• For this device: The "test set" here refers to the number of physical devices or components subjected to mechanical and biological testing. The document does not specify the exact number of samples for each test (e.g., how many femoral components were tested for fatigue), nor the specific origin of these physical samples beyond being manufactured by Medacta International SA (Switzerland). The testing is "prospective" in the sense that the tests were performed on newly manufactured devices.

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

• For an AI/ML device: This refers to human expert annotations.
• For this device: "Ground truth" is established by engineering specifications, biomechanical principles, and established international standards (e.g., ISO, ASTM, Pharmacopoeia) for material properties and mechanical performance. Experts would be engineers, material scientists, and toxicologists interpreting these results. The document does not list the number or qualifications of these experts analyzing the test results, as it's typically part of the company's internal quality system.

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

• For an AI/ML device: This refers to resolving disagreements between human annotators.
• For this device: Not applicable. Performance is measured against physical and chemical standards, not subjective human interpretations.

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

• For an AI/ML device: Refers to studies evaluating AI's impact on human performance.
• For this device: Not applicable, as this is a physical implant, not a diagnostic AI. The document explicitly states: "No clinical studies were conducted."

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

• For an AI/ML device: Refers to algorithm performance metrics without human interaction.
• For this device: Not applicable. There is no algorithm. The performance is the inherent mechanical and biological performance of the device itself.

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

• For an AI/ML device: Refers to the definitive determination of the condition being detected/diagnosed.
• For this device: The 'ground truth' is based on engineering and material science standards and protocols. For example, fatigue endurance is measured against a specific load cycle standard, wear is measured according to a wear test standard, and biocompatibility is measured against pharmacopoeia standards. There is no "disease state" ground truth for this type of device.

8. The sample size for the training set

• For an AI/ML device: Refers to the data used to train the algorithm.
• For this device: Not applicable, as there is no AI/ML algorithm requiring a training set. The "training" for such devices would be the iterative design and manufacturing process, and knowledge gained from previous designs, but not in the context of data used to train a machine learning model.

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

• For an AI/ML device: Refers to how training data was annotated or labeled.
• For this device: Not applicable.

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Intended to be used in cemented arthroplasty in patients with osteoarthritis limited to the distal patello-femoral joint, patients with a history of patellar dislocation or patellar fracture, and those patients with failed previous surgery (arthroscopy, tibial tubercle elevation, lateral release, etc.) where pain, deformity or dysfunction persists.

The Patello-Femoral Wave《hung Arthroplasty System is a line extension to the Sponsor's previously cleared and commercially marketed HemiCAP™ Patello-Femoral Resurfacing System.

The line extension consists of a larger femoral component for increased coverage of the trochlear groove. The additional sizes will address larger defects of the superior aspect of the trochlea and provide greater coverage superiorly. The system also includes larger mating UHMWPE patella components as described within.

The larger PF Kahuna trochlear Patello-Femoral Wave"«ከ«ባ articular component is designed to mate with the currently marketed Arthrosurface Patello-Femoral fixation component.

The majority of the implantation technique steps are the same. The PF Kahuna trochlear component is implanted using the same Instrumentation Set as with the HemiCAP™ Patello-Femoral Resurfacing System, with the addition of a reaming operation to create the superior ream. The reamers, associated implant trials etc. are contained within an adjunct Patello-Femoral WaveKahuna Instrumentation Kit.

The provided text is a 510(k) premarket notification letter and summary for a medical device, the "Patello-Femoral Wave (Kahuna) Arthroplasty System." This document primarily focuses on demonstrating the device's substantial equivalence to a legally marketed predicate device (HemiCAP Patello-Femoral Resurfacing Prosthesis K071413) based on its design, materials, indications for use, and testing.

It is important to note that this document does NOT describe the acceptance criteria or a study that proves the device meets specific performance metrics in the way that an AI/ML medical device submission would. This is a traditional medical device (implant) 510(k) submission, and the "tests" mentioned are primarily about material compatibility, mechanical performance (e.g., contact area, subluxation testing), and sterility rather than a performance study involving diagnostic accuracy or clinical outcomes in the sense of an AI/ML device.

Therefore, most of the requested information regarding acceptance criteria, study sample sizes, expert involvement, ground truth, and AI/ML specific studies (MRMC, standalone performance) for an AI/ML device is not applicable or present in this document.

However, I can extract the information that is present:

Summary of Device Performance and Equivalence (based on the provided text):

The "Patello-Femoral Wave (Kahuna) Arthroplasty System" is a line extension of a previously cleared device. Its approval is based on demonstrating substantial equivalence to the predicate device by showing:

• Same Indications for Use
• Same operating principle
• Manufactured using the same implant grade orthopedic materials
• Utilizes similar instrumentation for proper placement
• Packaged and sterilized using the same materials and processes

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

(Not directly applicable in the AI/ML context, but here's what's presented for this traditional medical device):

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

• Sample Size: Not specified in terms of patient or case numbers for clinical tests. The "tests" listed are bench-top mechanical and material characterization tests.
• Data Provenance: Not applicable in the context of clinical data for this type of submission. The tests are laboratory-based.

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 document does not describe a study involving expert readers or ground truth establishment for a diagnostic or AI/ML performance evaluation. The "experts" would be the engineers and scientists conducting the described non-clinical tests.

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

• Not applicable. This is not a study assessing diagnostic accuracy or clinical outcomes via human interpretation.

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 document does not mention or present any MRMC study, nor is it an AI/ML device.

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

• No. This document describes a physical implant, not an algorithm.

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

• Not applicable in the AI/ML sense. The "ground truth" for this device's approval relates to established engineering and material science standards (e.g., USP chapters, AAMI standards for endotoxins, mechanical test methodologies) and comparison to the predicate device's known characteristics.

8. The sample size for the training set

• Not applicable. There is no "training set" as this is not an AI/ML device.

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

• Not applicable. There is no "training set" or corresponding ground truth establishment for this traditional medical device.

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When used concurrently, the Arthrex iBalance UKA and PFJ systems create the Arthrex iBalance BiCompartmental Arthroplasty System. The Arthrex iBalance BiCompartmental Arthroplasty System is intended to be used as a multi-compartmental knee arthroplasty in patients with:

• Moderately disabling joint disease of the knee resulting from painful osteoarthritis or post traumatic arthritis;
• Correction of functional deformities;
• Revision of previous unsuccessful partial knee replacement or other procedure;
  The BiCompartmental Arthroplasty System is not intended to be used as a dual-condyle or tri-compartmental knee.
  These components are single use only and are intended for implantation with bone cement

The Arthrex iBalance BiCompartmental Arthroplasty System is comprised of a unicompartmental implant system (Arthrex iBalance UKA) and a patellofemoral implant system (Arthrex iBalance PFJ). The Arthrex iBalance UKA and Arthrex iBalance PFJ systems may be used in conjunction to create a bicompartmental patellofemorotibial replacement for the medial or lateral side of the knee.

The provided document is a 510(k) premarket notification for the Arthrex iBalance BiCompartmental Arthroplasty System. It states that the device is substantially equivalent to legally marketed predicate devices and does not describe actual acceptance criteria or a study proving that the device meets specific acceptance criteria in the context of device performance metrics commonly associated with AI/software devices.

Instead, this document focuses on demonstrating substantial equivalence to predicate devices based on intended use, design, size ranges, materials, and biomechanical testing, rather than reporting on specific performance metrics against an acceptance criterion in a clinical study.

Here's a breakdown of the requested information based on the provided text, and where it is not applicable or not found in this specific document:

1. Table of Acceptance Criteria and the Reported Device Performance

This document does not specify quantitative acceptance criteria (e.g., sensitivity, specificity, accuracy thresholds) or provide a table of reported device performance against such metrics. The clearance is based on substantial equivalence.

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

• Sample size for the test set: Not applicable/not provided. The document states, "Clinical data and conclusions are not needed for this device." The evaluation was based on biomechanical testing and comparison to predicates, not a clinical test set with patient data.
• Data provenance: Not applicable/not provided for a clinical test set. The biomechanical testing would have been conducted in a lab setting.

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. No clinical test set or ground truth established by experts is mentioned for this 510(k) submission.

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

Not applicable/not provided. No clinical test set requiring adjudication is mentioned.

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/not provided. This is a medical device (knee arthroplasty system) and not an AI or imaging diagnostic software. Therefore, an MRMC study related to human reader performance with or without AI assistance is not relevant to this submission.

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

Not applicable/not provided. This is a physical medical implant device, not a standalone algorithm.

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

Not applicable/not provided. For this type of device, "ground truth" would typically relate to mechanical performance or biocompatibility. The document mentions "biomechanical testing data" which demonstrated the "system worked well."

8. The sample size for the training set

Not applicable/not provided. This is a physical medical device, not a machine learning algorithm that requires a training set.

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

Not applicable/not provided.

Summary of the Study that Proves the Device Meets Acceptance Criteria (as per this document):

The "study" or justification for clearance in this 510(k) submission relies on substantial equivalence to existing predicate devices. The document explicitly states:

• "The submitted biomechanical testing data demonstrated the system worked well and the two systems did not impinge on one another."
• "Mechanical data is unchanged from the original clearances; no further mechanical testing is necessary to demonstrate that the iBalance BiCompartmental Arthroplasty System is adequate for its intended use."
• "Clinical data and conclusions are not needed for this device."

Therefore, the device meets its "acceptance criteria" by demonstrating that it is as safe and effective as previously cleared devices based on its intended use, design, materials, and biomechanical performance, without the need for new clinical data or specific quantitative performance metrics against acceptance thresholds in a clinical study.

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The Prelude™ PF Resurfacing Knee System is intended to be used in cemented patellofemoral arthroplplasty in patients with degenerative arthritis in the distal femur and patients with a history of patellar dislocation or patella fracture, or patients with failed previous surgery (arthroscopy, tibial tubercle elevation, lateral release) where pain, deformity or dysfunction persists.

The patella components are to be used with the existing Prelude PF Knee Resurfacing System. The components manufactured from polyethylene (UHMWPE) conforming to ASTM F-648 with a stainless steel x-ray wire and consist of larger sized patella options.

This document is a 510(k) premarket notification for a medical device called "Prelude PF Patellae", a new component for the existing "Prelude PF Knee Resurfacing System". The submission claims substantial equivalence to previously marketed predicate devices.

Here's an analysis of the provided text in relation to your request about acceptance criteria and supporting studies:

1. Table of Acceptance Criteria and Reported Device Performance:

   The document does not provide a specific table of acceptance criteria or quantitative performance metrics for the Prelude PF Patellae. Instead, it relies on demonstrating substantial equivalence based on a comparison to predicate devices across several characteristics.

   Acceptance Criteria (Implied)	Reported Device Performance
   Identical Intended Use to predicate devices	Met: The proposed Prelude PF Knee Resurfacing System patellae devices have the identical intended use as the predicate.
   Identical Indications for Use to predicate devices	Met: The proposed Prelude PF Knee Resurfacing System patellae devices have identical indications for use as the predicate.
   Identical Materials to predicate devices	Met: The proposed and predicate Prelude PF Knee Resurfacing System patellae devices are manufactured from UHMWPE conforming to ASTM F648.
   Identical Design Features to predicate devices	Met: The proposed and predicate patellae devices incorporate identical design features. (The change is the addition of larger sized patella options, but the fundamental design features are stated as identical).
   Identical Sterilization Methods to predicate devices	Met: The proposed and predicate Prelude PF Knee Resurfacing System patellae devices are provided sterile via identical sterilization methods for single-use.
   No new risks compared to predicate devices (Engineering Analysis)	Met: "Engineering Analysis of the larger patellae demonstrate that the proposed additional sizes to the Prelude PF Knee Resurfacing System patellae do not raise any new risks compared to the predicate Prelude PF Knee Resurfacing System patellae." This is the key performance claim from non-clinical testing.

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

   • Test Set Sample Size: Not explicitly stated. The "Engineering Analysis" would have likely involved simulations or bench testing, but the number of prototypes or simulations is not mentioned.
   • Data Provenance: The study described is an "Engineering Analysis," which implies in-house testing/simulation by Biomet Inc. The country of origin for this data is implicitly USA (where Biomet is located). It is retrospective in the sense that it's comparing a new size to an existing, already-approved design, rather than a de novo clinical trial.

3. Number of experts used to establish the ground truth for the test set and their qualifications:
   This information is not provided as there wasn't a human-centric study (like a clinical trial or expert review of images) for the "Engineering Analysis." The "ground truth" for this engineering analysis would be the established material properties (ASTM F-648) and biomechanical principles used in the analysis.

4. Adjudication method for the test set:
   Not applicable, as this was an engineering analysis, not a clinical study requiring expert adjudication.

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 MRMC study was done. This device is a knee joint patellofemoral prosthesis, not an AI-powered diagnostic or assistive tool for human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
   Not applicable, as this is a physical medical device (implant), not a standalone algorithm. The "Engineering Analysis" could be considered "standalone" in mechanical terms, as it assesses the physical device's properties.

7. The type of ground truth used:
   For the non-clinical "Engineering Analysis," the "ground truth" would be based on:

   • Established material properties (UHMWPE conforming to ASTM F-648).
   • Biomechanical principles and engineering standards relevant to prosthetic design.
   • Performance characteristics of the legally marketed predicate devices.

8. The sample size for the training set:
   Not applicable. This is a physical device being compared for substantial equivalence, not a machine learning model requiring a training set.

9. How the ground truth for the training set was established:
   Not applicable (no training set).

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The Prelude™ PF Resurfacing Knee System is intended to be used in cemented patella-femoral arthroplasty in patients with degenerative arthritis in the distal femur and patella, patients with a history of patellar dislocation or patella fracture, or patients with failed previous surgery (arthroscopy, tibial tubercle elevation, lateral release) where pain, deformity or dysfunction persists.

The Prelude™ Patellofemoral (PF) Resurfacing Knee System is a patellofemoral resurfacing prosthesis incorporating a distal femoral trochlear surface articular component and a patella component. The cast femoral component is manufactured from CoCrMo (ASTM F-75) and the MIM femoral component is manufactured from CoCrMo (ASTM F-2886) both with a porous undersurface coating of titanium from polyethylene (UHMWPE) conforming to ASTM F-648 with a stainless steel x-ray wire. The implant system is intended to be implanted with bone cement.

The provided document is a 510(k) Summary for the Biomet Manufacturing Corp. "Prelude™ PF Resurfacing Knee System." This document describes a medical device submission seeking clearance for a new knee implant, and as such, it does not contain information about clinical studies involving AI, human readers, or performance metrics like accuracy, sensitivity, or specificity for diagnostic purposes.

Instead, the document focuses on demonstrating substantial equivalence to existing legally marketed devices (predicates) through non-clinical testing and shared technological characteristics.

Therefore, most of the requested information regarding acceptance criteria, device performance metrics, sample sizes for test/training sets, expert qualifications, adjudication methods, MRMC studies, standalone performance, and ground truth types cannot be extracted from this document, as it is not relevant to this type of device submission.

Here's what can be extracted based on the nature of the document:

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

The document does not present quantitative acceptance criteria or device performance in terms of diagnostic accuracy, sensitivity, or specificity. Instead, the "acceptance criteria" are implied by demonstrating substantial equivalence to predicate devices, meaning the device should perform "within the intended use" and "not raise any new safety and efficacy issues" as determined by non-clinical tests.

• Contact Area
• Fatigue Strength
• Surface Finish
• Magnetic Resonance rationale

Results indicate that the subject construct is substantially equivalent to legally marketed devices, performs within the intended use, and does not raise any new safety and efficacy issues. |

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

Not applicable. This device submission did not involve clinical studies with human subjects or data sets in the context of diagnostic performance. The "tests" mentioned are non-clinical (mechanical, material, etc.).

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. There was no "ground truth" establishment by experts for a test set in the context of diagnostic performance as described in the prompt. The device is a knee implant, and its equivalence is based on engineering and material characteristics, not diagnostic interpretation.

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

Not applicable. No adjudication methods were mentioned as there were no clinical or diagnostic test sets involving expert evaluation.

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. An MRMC comparative effectiveness study was not done. This device is a knee implant, not an AI diagnostic tool. No AI assistance or human reader involvement is part of this submission's evaluation.

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

No. A standalone algorithm performance study was not done. This device is a physical knee implant, not an algorithm.

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

Not applicable in the context of diagnostic performance. The "truth" for this device's evaluation is primarily based on established engineering standards, material specifications, and comparative analyses with predicate device designs and performance under non-clinical conditions.

8. The sample size for the training set

Not applicable. There was no "training set" for an algorithm involved in this submission.

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

Not applicable. There was no "training set" for an algorithm involved in this submission.

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The replacement of the patellofemoral joint with the KNEETEC PFJ device is indicated in the case of symptoms and serious signs affecting daily activities involving the joint:

• Serious degenerative arthritis of the patellofemoral joint,
• Failure of conservative procedures (realignment, arthroscopy, transfer of the tibial tuberosity) with the persistence of joint pain or dysfunction,
• Patellofemoral dislocation (dysplastic or other origin),
• Post-traumatic arthritis (patellar fracture),

The KNEETEC PFJ patellofemoral prosthesis is intended for cemented use only.

When used in association with the KNEETEC PFJ prosthesis, the patellar component of the HLS KNEETEC has the above mentioned indications for use.

The Kneetee PFJ is a semiconstrained resecting prosthesis intended for replacement of the patellofemoral joint. The prosthesis consists of two components, both for cemented use only: a femoral implant and a patella. The patella of the knee joint may be resurfaced with the HLS KNEETEC patellar component and a substantially equivalent in K094013) or KNEETEC PFJ patellar implant.

This document is a 510(k) premarket notification for the KNEETEC PFJ and HLS KNEETEC patellar component, which are patellofemoral knee prostheses. A 510(k) submission demonstrates that a new device is substantially equivalent to a legally marketed predicate device. This process does not typically involve clinical studies with human subjects or AI performance evaluations as described in your request. Instead, it relies on demonstrating equivalence through non-clinical (engineering) testing and comparison of technological characteristics.

Therefore, many of the requested categories are not applicable to this type of submission.

Here's an analysis based on the provided text:

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

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

• Sample size for test set: Not applicable in the context of a 510(k) for this type of device. The "test set" here refers to the actual physical devices undergoing non-clinical engineering tests (e.g., specific components for contact area, pressure, subluxation force). The document states "The following non-clinical testing has been performed on the smallest components of the ranges (worst case)." This implies a limited number of physical prototypes or manufactured components were tested, focusing on the worst-case scenario (smallest size).
• Data provenance: Not explicitly stated, but these were engineering studies performed by the manufacturer, Tornier (based in France for regulatory affairs contact, and USA for applicant). This is not data from human patients.
• Retrospective or prospective: Not applicable, as this refers to engineering tests, 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. Ground truth as typically understood for AI devices (e.g., expert consensus on medical images) is not relevant here. The "truth" in this context is established by engineering standards and measurements.

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

Not applicable. Adjudication methods are typically for clinical studies involving human interpretation or diagnoses, not for engineering performance tests.

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 physical knee prosthesis, not an AI or imaging device that would involve human readers or AI assistance in diagnosis.

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

Not applicable. This is a physical medical device (implant), not an algorithm or software.

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

The "ground truth" for the non-clinical testing was based on engineering standards and direct physical measurements. The performance of the KNEETEC PFJ was compared against the measured performance of predicate devices based on parameters like contact area, contact pressure, and subluxation force.

8. The sample size for the training set

Not applicable. This is not an AI/machine learning device.

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

Not applicable. This is not an AI/machine learning device.

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The MAKO Surgical Corp. Patellofemoral Knee Implant System II is intended to be used in cemented patello-femoral arthroplasty in patients with degenerative arthritis in the distal femur and patella, patients with a history of patellar dislocation or patella fracture, or patients with failed previous surgery (arthroscopy, tibial tubercle elevation, lateral release) where pain, deformity or dysfunction persists. These components are single use only and are intended for implantation with bone cement.

This device consists of a CoCrMo patellofemoral component and an ultra-high molecular weight polyethylene patella components are intended for cemented, one-time use only. The anterior surface of the patellofemoral component is polished and features a trochlear groove. The posterior surface of the patellofemoral and patella component employ features such as cement pockets and pegs for enhanced stability of the prosthesis when cemented onto the femur and patella, respectively.

The provided text describes the MAKO Surgical Corp. Patellofemoral Knee Implant System II and its regulatory clearance, but it does not contain information about acceptance criteria, device performance metrics, or study details (like sample size, ground truth establishment, expert qualifications, or comparative effectiveness studies).

Therefore, I cannot fulfill your request for a table of acceptance criteria and reported device performance, nor can I provide information about the study design elements you requested, as this information is not present in the provided document.

This document is a 510(k) summary and FDA clearance letter, which focuses on demonstrating substantial equivalence to previously marketed devices rather than presenting detailed clinical study results or performance metrics against specific acceptance criteria for a new AI/software-based medical device.

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