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The OsteoFab® Suture Anchors are intended to be used for the fixation/reattachment of soft tissue to bone in the shoulder, knee, hand and wrist, elbow, and foot and ankle in the following procedures:

Shoulder: Rotator Cuff Repair, Bankart Repair, SLAP Lesion Repair, Biceps Tenodesis, Acromio-Clavicular Separation Repair, Deltoid Repair, Capsular Shift or Capsulolabral Reconstruction, Anterior Shoulder Instability Repair.

Knee: Extra Capsular Ligament Repair, Patellar Realignment and Tendon Repairs, and Illiotibial Band Tenodesis.

Hand and Wrist: Ulnar or Lateral Collateral Ligament Reconstruction, Collateral Ligament Reconstruction or Repair.

Elbow: Ulnar or Radial Collateral Ligament Reconstruction, Lateral Epicondylitis Repair, Biceps Tendon Repair.

Foot and Ankle: Hallux Valgus Repairs, Medial or Lateral Instability Repairs and Reconstructions, Achilles Tendon Repairs and Reconstructions, Midfoot Reconstructions, Metatarsal Ligament/Tendon Repairs and Reconstructions, Bunionectomy.

The OsteoFab® Suture Anchor is a single procedure suture anchor device for the reattachment of soft tissue to bone in shoulder, knee, hand and wrist, elbow, and foot and ankle procedures. This reattachment of damaged soft tissue is achieved with suture that is threaded through an anchor which is fixated in bone via interference fit between the anchor and bone. The anchor is mounted on a custom inserter and threaded with recommended suture before deployment. The OsteoFab® Suture Anchors are manufactured from polyetherketone (PEKK) polymer in Oxford Performance Materials, Inc.'s proprietary additive manufacturing process. The OsteoFab® Suture Anchors are available in three sizes (4.5, 5.5, ad 6.5mm) and are provided non-sterile.

The provided text describes a medical device (OsteoFab® Suture Anchors) and its performance data submitted to the FDA for 510(k) clearance. This means the primary focus is on establishing substantial equivalence to a predicate device, rather than proving novel efficacy through clinical trials. Therefore, much of the information typically found in an AI/Software as a Medical Device (SaMD) study (like detailed test set specifics, expert qualifications for ground truth, MRMC studies, or training set details) is not present here as it is not applicable to a device like a physical suture anchor.

However, I can extract the relevant information from the document regarding acceptance criteria and the studies performed to demonstrate substantial equivalence.

Acceptance Criteria and Study for OsteoFab® Suture Anchors

The OsteoFab® Suture Anchors are physical medical devices, not an AI/SaMD. As such, the "acceptance criteria" and "study" are focused on mechanical performance, biocompatibility, and substantial equivalence to a legally marketed predicate device, rather than diagnostic accuracy or human reader improvement.

1. Table of Acceptance Criteria and Reported Device Performance

The overarching acceptance criterion for the 510(k) submission is to demonstrate substantial equivalence to the predicate device (K122314 Cayenne Quattro Link Knotless Anchors) in terms of safety and effectiveness. The performance data listed above were presented to support this conclusion.

2. Sample Size Used for the Test Set and the Data Provenance
The document does not specify the exact sample sizes (e.g., number of anchors tested) for the mechanical bench tests or the biocompatibility tests. Product safety and performance tests are typically conducted on a representative sample of finished devices according to validated protocols.

• Data Provenance: The studies were internal company tests ("Performance Bench Testing," "Biocompatibility Testing"). No information is provided regarding the specific geographical origin of data beyond the company's US location.
• Retrospective/Prospective: These are laboratory and bench tests, not clinical studies, so the terms "retrospective" or "prospective" are not applicable in this context.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts
This concept is not directly applicable to the evaluation of a physical medical device like a suture anchor. The "ground truth" for mechanical and biocompatibility testing is established through standardized engineering and biological test methods, often specified by international standards (e.g., ISO standards for biocompatibility). The results are objectively measured (e.g., force, displacement, cellular response) rather than requiring expert consensus on subjective interpretations.

4. Adjudication Method for the Test Set
Not applicable. As described above, these are objective physical and biological tests, not evaluations requiring human adjudication of subjective data.

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 suture anchor, not an AI/SaMD designed to assist human readers or provide diagnostic information.

6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This device is a physical suture anchor, not an AI algorithm.

7. The Type of Ground Truth Used
The "ground truth" for this device consists of:

• Mechanical performance standards: Established engineering principles and, likely, comparison against the predicate device's known mechanical properties. The goal is to demonstrate that the new device meets or exceeds appropriate strength and durability.
• Biocompatibility standards: International standards (e.g., ISO 10993 series) for evaluating biological response to medical devices.
• Predicate device performance: The performance of the legally marketed predicate device (K122314 Cayenne Quattro Link Knotless Anchors) serves as a benchmark for demonstrating substantial equivalence.

8. The Sample Size for the Training Set
Not applicable. As a physical medical device, there is no "training set" in the context of machine learning or AI.

9. How the Ground Truth for the Training Set was Established
Not applicable. As a physical medical device, there is no "training set" or "ground truth" in the AI/ML sense.

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The OsteoFab Patient Specific Cranial Device (OPSCD) is intended for the replacement of bony voids in the cranial skeleton. OPSCDs may be used to fit pre-planned virtual defects in the instance of single stage cranioplasty procedures.

An OsteoFab® Patient Specific Cranial Device (OPSCD) is built individually for each patient to correct defects in cranial bone. OPSCDs are constructed with the use of the patient's CT scan and computer aided design is used to determine the geometry of each implant. OPSCDs are built by laser sintering polyetherketone (PEKK) polymer in Oxford Performance Materials' OsteoFab® process. OPSCDs are attached to native bone with commercially available cranioplasty fixation systems and are a non-load bearing, single use device. OPSCDs are provided non-sterile.

Here's a breakdown of the acceptance criteria and study information for the OsteoFab Patient Specific Cranial Device (K180064), based on the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: "Worst-case, representative cranial cases were selected for end-to-end simulation testing." The document does not specify a numerical sample size for the test set (number of cases/implants tested).
• Data Provenance: The study was a "bench test" simulation. The specific country of origin for the "worst-case, representative cranial cases" or skull models is not mentioned. It is a prospective test, as it was conducted to demonstrate the device's performance for this specific 510(k) submission.

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

• The document does not mention the use of experts to establish ground truth for the bench testing. The "acceptance criteria included meeting existing product release criteria, successful shipment... successful fixation... and satisfactory fit." This suggests a set of objective, measurable criteria rather than expert consensus on subjective aspects.

4. Adjudication method for the test set

• Adjudication methods like 2+1 or 3+1 (typically used for expert reviews) are not applicable here, as expert ground truth establishment is not described for the bench test. The acceptance was based on meeting predefined objective criteria.

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 involving human readers or AI assistance was not done. This device is a physical implant, 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

• This question is not applicable to the OsteoFab Patient Specific Cranial Device. It is a physical medical device, not an algorithm. The "design process" does use computer-aided design, but the "performance" discussed is related to the physical fit and functionality of the implant, not an algorithm's classification accuracy.

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

• The ground truth for the bench testing was based on pre-defined, objective engineering and fit criteria ("existing product release criteria, successful shipment without damage, successful fixation, and satisfactory fit"). It's a form of objective performance criteria met in a simulated environment, rather than clinical ground truth like pathology or patient outcomes.

8. The sample size for the training set

• The concept of a "training set" is not applicable in the context of this device's performance testing. This device is a custom-manufactured implant based on patient-specific CT data and a cleared manufacturing process, not a machine learning model that requires a training set.

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

• Not applicable, as there is no training set for this type of device.

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The OsteoFab® Patient Specific Facial Device (OPSFD) is designed individually for each patient for enhancement, to correct trauma, and/or to correct defects in facial bone. The OPSFD is also designed individually for non-load bearing enhancement of mandibular bone.

HTR-PEKK is a custom implant and the shapes and sizes vary within the following specifications: (1) maximum diameter is 20cm (2) minimum thickness is 1mm (2mm in areas of fixation), (3) maximum thickness is 20mm and the maximum thickness for holes is 10mm, (4) maximum open density is 25%, (5) minimum as designed through-hole diameter is 3mm, (6) maximum as designed though-hole size must meet these specifications (7) minimum distance from the edge of an as designed through-hole (for a cluster of perfusion-holes) to the edge of a device is 15mm, (8) minimum distance from the center of an as designed dimple to the edge for plating is 2.5mm for a 1.5mm diameter screw, (9) minimum distance from the center of an as designed dimple to the edge for lagging is 2.5mm for a 1.5mm diameter screw, (10) minimum distance between two lag holes is 3.25mm for a 1.5mm diameter screw, (11) minimum distance from the center of an as designed dimple to the edge for lagging is 3.75mm for a 2mm diameter screw, and (12) minimum distance between two lag holes is 3.75mm for a 2mm diameter screw.

The OPSFD is constructed with the use of the patient's CT imaging data and computer aided design to determine the dimensions of each implant. The OPSFD is built by a LASER sintering machine. The OPSFD is attached to native bone with commercially available fixation systems. The OPSFD is a non-load bearing single use device and it is shipped non-sterile.

The provided text describes a 510(k) submission for the "OsteoFab Patient Specific Facial Device" (OPSFD), which is an update to an existing device (K133809). This document is an FDA letter and a 510(k) summary, primarily focused on modifications to device specifications and labeling, rather than a comprehensive, standalone clinical study proving the device's overall effectiveness or safety from scratch.

Therefore, the information regarding acceptance criteria and a study proving those criteria is limited to changes related to implant thickness and fixation mechanisms, as these were the only areas where "new non-clinical performance data" was deemed necessary based on risk analysis.

Here's an attempt to answer your questions based on the provided text, highlighting where information is not available:

1. Table of Acceptance Criteria and Reported Device Performance

The text does not explicitly define acceptance criteria as pass/fail values for the new performance data. Instead, it states that "The data obtained was proof of performance" for the changes. The changes themselves relate to specific dimensions and fixation guidelines.

Note: The document explicitly states "New performance data was not required" for some changes, indicating that for those, the previous data for the predicate device was considered sufficient or the change was purely administrative/clarifying. For the thickness and fixation changes, new non-clinical performance data was required and submitted, and deemed "proof of performance."

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

• Sample Size for Test Set: Not specified. The text only refers to "new non-clinical performance data" and "performance testing" related to changes in implant thickness and fixation. It does not provide details on the number of samples or tests conducted.
• Data Provenance: The study was "new non-clinical performance data" suggesting it was generated in a lab setting rather than from patient data. The origin is implied to be from Oxford Performance Materials, Inc. (South Windsor, CT, USA). It is a prospective test in the sense that it was specifically conducted to address the changes in device specifications.

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

• Not applicable / Not specified. This was a non-clinical performance study, meaning it likely involved engineering tests (e.g., mechanical strength, durability simulations) rather than expert review of clinical cases. Therefore, the concept of "ground truth established by experts" in a clinical diagnostic sense does not apply here.

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

• Not applicable / Not specified. Given it was a non-clinical performance study, an adjudication method for reconciling expert opinions on clinical cases is not relevant. The verification and validation would have involved engineering and quality assurance 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

• No. This was a submission for a patient-specific physical implant, not an AI diagnostic or assistance tool. Therefore, an MRMC study or AI-related effectiveness study was not conducted or mentioned.

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

• No. This device is a physical implant, not an algorithm. The design process does involve "computer aided design" based on patient CT imaging data, but there's no mention of a standalone algorithm performance study in the context of typical AI device evaluations. The "device" is the final physical product.

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

• The "ground truth" for the non-clinical performance data would be based on engineering standards, material science properties, and mechanical test results. For example, the ground truth for "minimum thickness for screws" would be whether a sample implant of that thickness can reliably hold a screw under specified forces without failure, as determined by laboratory testing and industry standards for implant fixation. It's not clinical "ground truth" like pathology or expert consensus on a diagnosis.

8. The sample size for the training set

• Not applicable / Not specified. As this is not an AI/machine learning device, there is no "training set." The device is designed for individual patients based on their specific CT data.

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

• Not applicable / Not specified. No training set was used.

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