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Software: The Precision AI Planning Software is intended to be used as a pre-surgical planner for simulation of surgical interventions for shoulder joint arthroplasty. The software is used to assist in the positioning of shoulder components by creating a 3D bone construct of the joint and allows the surgeon to visualize, measure, reconstruct, annotate and edit presurgical plan data. The software leads to the generation of a surgery report along with a pre-surgical plan data file which can be used as input data to design the Precision AI Shoulder Guide and Biomodels.

Hardware: The Precision AI Planning System Guides and Biomodels are intended to be used as patient-specific surgical instruments to assist in the intraoperative positioning of shoulder implant components used with total and reverse shoulder arthroplasty by referencing anatomic landmarks of the shoulder that are identifiable on preoperative CT-imaging scans. The Glenoid Guide is used to place the k-wire and the Humeral Guide is used to place humeral pins for humeral head resection. The Precision AI Guides and Biomodels are indicated for single use only. The Precision AI Surgical Planning System is indicated for use on adult patients that have been consented for shoulder joint arthroplasty. Both humeral and glenoid guides are suitable for a delto-pectoral approach only. The Precision AI Surgical Planning System is indicated for total and reverse shoulder arthroplasty using the following implant systems and their compatible components: Enovis and Lima.

The Precision AI Surgical Planning System is a patient-specific medical device that is designed to be used to assist the surgeon in the placement of shoulder components during total anatomic and reverse shoulder replacement surgery. This can be done by generating a pre-surgical shoulder plan and, if requested by the surgeon, by manufacturing a patient-specific guides and models to transfer the plan to surgery. The subject device is a system composed of the following: The Precision AI Surgical Planning System Software will create a 3D construct/render of the patient's shoulder joint for the surgeon to plan the operatively then create a physical Patient Specific Instrument (or Guide), using 3D printing by selective laser sintering. The patient's CT scan images are the design input for this to be created and are auto segmented via a locked, or static, artificial intelligence algorithm. The surgeon can visualise the deformity of the diseased joint, on this 3D render and CT scan images, and determine the inherent deformity of the joint. They are then able to virtually place the artificial implants in an optimal position to correct the measured deformity for that specific patient. The Precision AI Guides, which are a patient-specific guide and models that are based on a pre-surgical plan. This pre-surgical plan is generated using the software component. Patient-specific guide and models will be manufactured if the surgeon requests patient-specific guides to transfer the plan to surgery.

The provided text is an FDA 510(k) summary for the Precision AI Surgical Planning System (PAI-SPS). It describes the device and its intended use, but it does NOT contain specific acceptance criteria, detailed study designs, or performance results in terms of metrics like sensitivity, specificity, accuracy, or effect sizes for human reader improvement.

The document states that "Software verification and validation were performed, and documentation was provided following the 'Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices.' This includes verification against defined requirements and validation against user needs." It also mentions that "Design verification and validation testing demonstrated that the PAI-SPS meets all design requirements and is as safe and effective as its predicate device (K233992)."

However, it does not explicitly lay out the acceptance criteria (e.g., "model must achieve 90% accuracy") or the results against those criteria. It focuses more on demonstrating substantial equivalence to a predicate device (PAI-SPS K233992) by showing that the technology and intended use are similar, with the main differences being the addition of compatibility with more implant systems.

Therefore, I cannot fully complete the requested table and answer all questions based solely on the provided text. I will provide information based on what is available and indicate where information is missing.

Description of Acceptance Criteria and Study to Prove Device Meets Criteria

Based on the provided FDA 510(k) summary, the PAI-SPS device is being cleared primarily through demonstrating substantial equivalence to an already cleared predicate device (PAI-SPS, K233992). The key claim for equivalence rests on similar intended use, fundamental scientific technology, design, functionality, operating principles, and materials, with the primary difference being expanded compatibility with additional implant systems.

The document implicitly suggests that the "acceptance criteria" are tied to demonstrating that these technological differences "do not raise any different questions of safety and effectiveness." The studies cited are primarily focused on software verification and validation, ensuring the new compatible implant systems do not negatively impact the established safety and effectiveness.

Here is a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The provided document does not explicitly state quantitative acceptance criteria (e.g., minimum accuracy percentages, specific error bounds) or detailed performance metrics. The performance is largely framed as demonstrating that the device "meets all design requirements and is as safe and effective as its predicate device."

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

• The document does not specify the sample size for any test set (e.g., for software validation or hardware accuracy).
• Data Provenance: Not explicitly stated for specific test sets. Given the company is "Precision AI Pty Ltd" in Australia, and the document discusses "previous cadaver testing and composite bone model testing," it's likely a mix of lab-based/simulated data and potentially some retrospective clinical imaging data for initial AI development/testing, but this is not detailed. The document implies that new testing was not extensively conducted for this submission, relying heavily on the predicate device's prior validation and the minor changes to compatibility.

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

• The document does not specify the number of experts or their qualifications used to establish ground truth for any test set.
• It mentions that the software allows a "qualified surgeon" to approve pre-surgical plan data, implying that expert surgical review is part of the workflow.

4. Adjudication Method for the Test Set

• The document does not specify any adjudication method (e.g., 2+1, 3+1) for establishing ground truth or evaluating test results.

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

• No, an MRMC comparative effectiveness study was not explicitly mentioned or described. The focus of this 510(k) is substantial equivalence based on technological similarity and expanded compatibility, not a comparative study against human readers or performance improvement with AI assistance.

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

• The document states that the AI algorithm performs "auto segmentation via a locked, or static, artificial intelligence algorithm." While this indicates a standalone AI component, the document does not provide standalone performance metrics for this AI segmentation. The overall system is described as a "pre-surgical planner" where the surgeon can "visualize, measure, reconstruct, annotate and edit pre-surgical plan data," suggesting a human-in-the-loop workflow.

7. The Type of Ground Truth Used

• For software, the implicit ground truth appears to be expert consensus or approved surgical plans for judging the accuracy of the software's representations and planning capabilities. The document states "The software allows a qualified surgeon to visualize, measure, reconstruct, annotate, edit and approve pre-surgical plan data."
• For hardware, "previous cadaver testing and composite bone model testing" were used, implying physical measurements against a known standard or "true" position established in these models.

8. The Sample Size for the Training Set

• The document does not specify the sample size used for the training set for the AI segmentation algorithm.

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

• The document does not specify how the ground truth for the AI training set was established. It only mentions that the AI algorithm for auto-segmentation is "locked, or static," implying it was trained previously.

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The SMR Shoulder System is intended for partial or total, primary or revision shoulder joint replacement.

The SMR Anatomic Shoulder System is indicated for partial or total, primary or revision shoulder joint replacement in patients suffering from disability due to:

• non-inflammatory degenerative joint disease including osteoarthritis and avascular necrosis;
• . inflammatory degenerative joint disease such as rheumatoid arthritis;
• treatment of acute fractures of the humeral head that cannot be treated with other fracture fixation methods;
• revision of a failed primary implant; in case of SMR Short Stems only if sufficient bone stock remains); .
• cuff tear arthropathy (CTA Heads only); .
• glenoid arthrosis without excessive glenoid bone loss: A1, A2 and B1 according to Walch classification (SMR TT Hybrid Glenoid only). .

The SMR Reverse Shoulder System is indicated for primary, fracture or revision total shoulder replacement in a grossly rotator coff deficient joint with severe arthropathy (disabled shoulder). The patients joint must be anatomically suited to receive the selected implants and a functional deltoid muscle is necessary to use the device.

The SMR TT Hybrid Glenoid Reverse Baseplate must not be used in cases of excessive glenoid bone loss and/or when bone graft is needed.

The Modular SMR Shoulder System allows the assembly of components in various humeral and glenoid constructs are intended for cemented and uncemented use as specified in the following table.

In the Anatomic shoulder the humeral consists of the humeral stem, the humeral body, the adaptor taper and the humeral head. In the Reverse shoulder the humeral consists of the humeral stem, the reverse humeral body and the reverse liner. On the humeral side the fixation of the humeral stem determines if the construct is cemented or uncemented.

The Anatomic glenoid construct consists of an all polyethylene glenoid with metal peg or a metal back assembled with a liner; the Reverse glenoid consists of a metal back/connector/glenosphere construct or of a peg/baseplate/glenosphere construct. On the glenoid side, the fixation of the all polyethylene glenoid with metal peg or the metal back determines if the construct is cemented or uncemented.

The SMR 140° Reverse Humeral Bodies (SMR 140° Reverse Humeral Body, SMR 140° Short Reverse Humeral Body, SMR 140° Finned Reverse Humeral Body) are manufactured from Ti6Al4V alloy (ASTM F1472 - ISO 5832-3); they are for tapercoupling with previously cleared Humeral extension (K113523), SMR CTA Head Adaptor for Reverse Humeral Body (K131112), Reverse Liners (K110598, K142139) and Humeral stems (K100858, K101263, K111212, K191963).

This document is a 510(k) premarket notification for the SMR 140° Reverse Humeral Body, a component of a shoulder replacement system. As such, it does not contain information about acceptance criteria or a study proving that an AI device meets acceptance criteria.

The document describes a medical device (SMR 140° Reverse Humeral Body for shoulder replacement) and its substantial equivalence to predicate devices, supported by non-clinical mechanical testing. It explicitly states that clinical testing was not necessary to demonstrate substantial equivalence.

Therefore, the requested information points regarding AI acceptance criteria and studies (sample size, data provenance, expert ground truth, adjudication, MRMC studies, standalone performance, ground truth type for training/test sets, and training sample size) are not applicable to this document.

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The SMR Shoulder System is intended for partial or total, primary or revision shoulder joint replacement.

The SMR Anatomic Shoulder System is indicated for partial or total, primary or revision shoulder joint replacement in patients suffering from disability due to:

• non-inflammatory degenerative joint disease including osteoarthritis and avascular necrosis;
• inflammatory degenerative joint disease such as rheumatoid arthritis;
• treatment of acute fractures of the humeral head that cannot be treated with other fracture fixation methods;
• revision of a failed primary implant;
• cuff tear arthropathy (CTA Heads only);
• glenoid arthrosis without excessive glenoid bone loss: A1, A2 and B1 according to Walch classification (SMR Hybrid Glenoid only).

The SMR Reverse Shoulder System is indicated for primary, fracture or revision total shoulder replacement in a grossly rotator cuff deficient joint with severe arthropathy (disabled shoulder). The patient's joint must be anatomically and structurally suited to receive the selected implants and a functional deltoid muscle is necessary to use the device. The Hybrid Glenoid Reverse Baseplate must not be used in cases of excessive glenoid bone loss and/or when bone graft is needed.

The Modular SMR Shoulder System allows the assembly of components in various humeral and glenoid constructs. The constructs are intended for cemented and uncemented use as specified in the following table.

The SMR Connectors are used to couple the glenosphere to the metal-backed glenoid. Connectors are made from Ti6Al4V alloy (ASTM F1472 - ISO 5832-3) and are characterized by a double male taper. To increase the solidity of the system, a screw is used to link the glenosphere to the glenoid component. No.5 additional sizes (Lateralized connectors) are available in both Small-STD and Small-R configuration to allow lateralization of Center of Rotation.

The provided document is a 510(k) premarket notification for a medical device called "SMR Lateralized Connectors with screws". This type of submission focuses on demonstrating substantial equivalence to a predicate device already on the market, rather than proving efficacy or safety through extensive clinical trials. Therefore, much of the information requested about acceptance criteria and detailed study designs (especially relating to AI or expert adjudication) is not applicable or present in this document.

However, I can extract the relevant information regarding the non-clinical testing performed to establish substantial equivalence.

Here's a breakdown of the available information:

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

The document does not provide a specific table of numerical acceptance criteria or reported device performance in the format typically seen for novel device performance claims. Instead, it states that mechanical tests "demonstrated device performances fulfill the intended use and are substantially equivalent to the predicate devices." This implies that the performance met predefined internal criteria for equivalence, but these criteria are not explicitly detailed.

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

The document mentions "Mechanical testing was performed on worst case components or constructs." It does not specify the exact sample size for these mechanical tests. The data provenance is internal to Limacorporate S.p.A. and the tests are non-clinical (experimental/lab-based), not derived from patient data.

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

This is not applicable as the study described is non-clinical mechanical testing, not a study involving human interpretation or ground truth establishment by experts for diagnostic or prognostic purposes.

4. Adjudication method for the test set

This is not applicable for the same reason as point 3.

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 study was not done. The device is a mechanical 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

No, a standalone AI algorithm performance study was not done. The device is a mechanical implant.

7. The type of ground truth used

For the non-clinical mechanical testing, the "ground truth" would be the engineering specifications and performance benchmarks derived from the predicate devices and relevant ASTM/ISO standards (e.g., ASTM F2028-18). The device's performance was compared against these established standards and predicate device characteristics to demonstrate substantial equivalence.

8. The sample size for the training set

This is not applicable as there is no AI algorithm being trained.

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

This is not applicable as there is no AI algorithm being trained.

Summary of Relevant Information from the Document:

While the document doesn't fit the typical structure for AI/diagnostic device evaluation, it does provide clear information about the type of acceptance criteria and study performed for this medical device:

• Acceptance Criteria (Implied): Substantial equivalence to predicate devices, fulfilling intended use, and meeting relevant mechanical testing standards (e.g., ASTM F2028-18 for dynamic evaluation of glenoid loosening and dissociation, and standards for fatigue-fretting behavior and endurance stability of taper connections).
• Study Type: Non-clinical mechanical testing.
• Specific Tests Mentioned:
  • Dynamic evaluation of glenoid loosening and dissociation per ASTM F2028-18.
  • Fatigue-fretting behavior.
  • Endurance stability of the taper connection, followed by evaluation for corrosion.
• Sample Size for Testing: "worst case components or constructs" (specific number not provided).
• Data Provenance: Laboratory testing (non-clinical).
• Ground Truth for Testing: Engineering specifications, performance benchmarks of predicate devices, and relevant international standards (ASTM, ISO).
• Clinical Testing: "Clinical testing was not necessary to demonstrate substantial equivalence of the new sizes of SMR Connectors to the predicate devices."

The document primarily focuses on demonstrating that the new SMR Lateralized Connectors with screws are safe and effective because their design, materials, and mechanical performance are equivalent to predicate devices already cleared for market, negating the need for novel clinical data.

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The AltiVate Anatomic™ to Reverse Conversion Module is indicated for revision surgeries in patients with a grossly rotator cuff deficient shoulder joint with severe arthropathy or a previously failed joint replacement with a grossly rotator cuff deficient shoulder joint. The patient's joint must be anatomically and structurally suited to receive the selected implant(s), and a functional deltoid muscle is necessary to use the device. The conversion module is only indicated for use with a well fixed AltiVate Anatomic Humeral Stem.
Humeral components with a porous coated surface are indicated for either cemented or uncemented applications. The glenoid baseplate is intended for cementless application with the addition of screws for fixation.

In cases of revision surgeries to a well fixed AltiVate Humeral Stem, a reverse conversion module can be mated with the AltiVate stem to convert to a reverse shoulder application.
The currently cleared AltiVate™ Anatomic humeral stem will a conversion module to provide an option to revise a failed traditional total shoulder arthroplasty to a reverse shoulder arthroplasty without the need to remove a well fixed humeral stem.

The provided text describes a 510(k) premarket notification for the "AltiVate Anatomic to Reverse Conversion Module," a medical device. The document states that clinical testing was not required or performed for this submission. Therefore, it does not contain information regarding acceptance criteria, device performance from clinical studies, sample sizes, ground truth establishment, or multi-reader multi-case studies.

The document primarily focuses on non-clinical testing and substantial equivalence to predicate devices.

Here's a breakdown of the available information based on the provided input and the limitations due to the absence of clinical testing:

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

• No clinical acceptance criteria or reported clinical device performance are provided as clinical testing was not performed.
• Non-clinical testing: FEA analysis for stress analysis was conducted, determining the subject device is similar to the evaluated predicate device. Bacterial endotoxin testing was also conducted and met expected limits. However, specific numerical acceptance criteria or performance metrics for these non-clinical tests are not detailed in the provided text.

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

• Not applicable as no clinical test set was used.

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

• Not applicable as no clinical test set was used.

4. Adjudication method for the test set:

• Not applicable as no clinical test set was used.

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 medical implant, not an AI diagnostic tool.

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

• Not applicable. This device is a medical implant, not an AI algorithm.

7. The type of ground truth used:

• For the non-clinical tests, the "ground truth" would be engineering specifications and established standards for mechanical performance and sterility (endotoxin levels). The document states the FEA analysis found the device "similar to the evaluated predicate device" and endotoxin testing "met the expected endotoxin limits."

8. The sample size for the training set:

• Not applicable as this is not an AI/algorithmic device and no clinical "training set" was used.

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

• Not applicable as this is not an AI/algorithmic device and no clinical "training set" was used.

In summary, the FDA cleared this device based on non-clinical testing (FEA analysis, endotoxin assessment) and demonstration of substantial equivalence to predicate devices, without requiring or performing clinical trials.

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