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The restor3d rTSA System is indicated for use in patients whose shoulder joint has a grossly deficient rotator cuff with severe arthropathy and/or previously failed shoulder joint replacement with a grossly deficient rotator cuff. The patient must be anatomically and structurally suited to receive the implants and a functional deltoid muscle is necessary.

The restor3d rTSA System is indicated for primary, fracture, or revision total shoulder replacement for the relief of pain and significant disability due to gross rotator cuff deficiency.

Glenoid component with porous surface is indicated for uncemented biological fixation application only. The restor3d rTSA System glenoid baseplate components are intended for cementless application with the addition of screw fixation.

Humeral components with porous surface are indicated for either cemented or uncemented applications.

The restor3d Reverse Total Shoulder Arthroplasty System is intended for patients requiring a reverse shoulder replacement for patients with a functional deltoid muscle and with a deficient rotator cuff. The restor3d Reverse Total Shoulder Arthroplasty System consists of the glenoid baseplate, glenosphere intraoperatively affixed to the baseplate, humeral stem, and polymer bearing component affixed to the humeral stem. Additionally, the system includes supporting standard instrument trays and all required accessories (e.g., security screws, peripheral screws).

The provided text is a 510(k) clearance letter for a medical device: the restor3d Reverse Total Shoulder Arthroplasty System. This document focuses on demonstrating substantial equivalence to a predicate device through non-clinical testing. It explicitly states, "The restor3d Reverse Total Shoulder Arthroplasty System was subject to the following non-clinical performance tests to support the assertion of substantial equivalence."

Therefore, the document describes engineering and material performance testing, not a clinical study involving human patients or analysis of clinical images/data using an AI algorithm. The questions posed in your prompt (e.g., acceptance criteria for device performance/accuracy, sample size for test set/training set, number of experts for ground truth, MRMC study, standalone performance) are typically relevant for AI/ML-enabled medical devices or devices requiring clinical performance studies.

Since the provided text does not describe an AI/ML-enabled device or a clinical study that would generate "device performance" in terms of accuracy, sensitivity, specificity, etc., against a clinical ground truth, I cannot fill out the requested table or answer most of the specific questions.

Here's an explanation based on the provided text, highlighting why the requested information isn't present:

Context from the document:

• Device Type: Reverse Total Shoulder Arthroplasty System (a physical implant)
• Regulatory Pathway: 510(k) (seeking substantial equivalence to a legally marketed predicate)
• Testing Described: "Non-Clinical Testing" which includes:
  • Glenoid Baseplate Loosening per ASTM F2028
  • Glenoid Baseplate Fatigue and corrosion analysis
  • Morse Taper Disassembly Strength per ASTM F2009
  • Humeral Stem Fatigue and corrosion analysis
  • Bone Screw Testing per ASTM F543
  • Poly Liner Performance Tests per ASTM F1820
  • Range of Motion Analysis per ASTM F1378
  • Wear Analysis

These are all benchtop, mechanical, and material science tests designed to show that the new device performs similarly from an engineering standpoint to the predicate and meets established ASTM standards for orthopedic implants. They do not involve "device performance" in terms of clinical accuracy or an AI algorithm's predictive capability.

Therefore, I cannot fulfill your request as it pertains to acceptance criteria and studies typically associated with AI/ML or diagnostic devices that produce "performance" metrics against clinical ground truth.

However, if we interpret "acceptance criteria" and "device performance" within the context of mechanical/material testing as presented in the document, here's what could be inferred, though it won't directly answer your specific table columns:

The "acceptance criteria" for this device would be implicit in meeting the requirements of the cited ASTM standards, such as surviving a certain number of fatigue cycles at a given load, or meeting specific wear rates, or exhibiting particular disassembly strengths. The "reported device performance" would be the results from these bench tests, demonstrating that the device did indeed meet those standard specifications.

To directly address your prompts based on the absence of the requested information in the provided document:

Description of Acceptance Criteria and Study to Prove the Device Meets Them (Based on provided document)

The provided FDA 510(k) clearance letter for the restor3d Reverse Total Shoulder Arthroplasty System primarily relies on non-clinical bench testing to demonstrate substantial equivalence to a predicate device. This submission does not describe a clinical study of diagnostic or predictive performance, nor does it discuss AI model performance. Therefore, the requested information regarding AI/ML-specific acceptance criteria, test set details, expert involvement for ground truth, or MRMC studies is not present in this document.

The "acceptance criteria" for this device are implicitly tied to its ability to meet the performance requirements of established ASTM (American Society for Testing and Materials) standards for orthopedic implants, and to demonstrate comparable mechanical and material characteristics to its predicate device. The "study that proves the device meets the acceptance criteria" refers to a series of non-clinical benchtop tests.

1. Table of Acceptance Criteria and Reported Device Performance:

Note: The provided 510(k) summary only lists the types of tests performed and states they support substantial equivalence. It does not provide the specific numerical acceptance thresholds or the detailed numerical results from these non-clinical tests. This level of detail would typically be found in the full 510(k) submission not in the public clearance letter summary.

Regarding other specific questions (not applicable based on the document's content):

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

• Not applicable. The "test set" here refers to physical implant samples subjected to bench testing, not a dataset of clinical cases for an AI algorithm. The document does not specify the number of physical samples used for each test. Data provenance (country, retrospective/prospective) is not relevant for bench testing of a physical implant.

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

• Not applicable. Ground truth in this context is established by engineering standards (e.g., ASTM specifications, material properties) and physical measurements on the device, not by expert medical review of clinical data.

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

• Not applicable. This method applies to expert review of clinical cases, not mechanical testing.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• Not applicable. An MRMC study is for evaluating human performance (often with or without AI assistance) in interpreting clinical data. This document describes a physical 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 refers to AI algorithm performance. No AI algorithm is described.

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

• Not applicable in the clinical sense. Ground truth for this device is based on engineering standards (ASTM), material specifications, and physical measurements demonstrating the device's mechanical and material properties are equivalent to the predicate and meet safety requirements.

8. The sample size for the training set:

• Not applicable. This refers to AI model training data. No AI model is described.

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

• Not applicable. This refers to AI model training data. No AI model is described.

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