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Smart SPACE Shoulder 3D Positioners

Smart SPACE Shoulder System instrumentation consists of patient-specific 3D positioners. They have been specially designed to assist in the intraoperative positioning of shoulder components used with total anatomic or reverse shoulder arthroplasty procedures using anatomic landmarks that are identifiable on patient-specific preoperative CT scans.

Smart SPACE Shoulder Planner software

Smart SPACE Shoulder Planner software is a medical device for surgeons composed of one software component. It is intended to be used as a pre-surgical planner for shoulder orthopedic surgery.

The Smart SPACE Shoulder System consists of the Smart SPACE Shoulder Planner software and 3D Positioners which assist the user in planning reverse and anatomic total shoulder arthroplasty and gives the user the ability to translate the surgical plan intraoperatively using 3D positioners for glenoid K-wire placement and humeral head resection.

The provided text is a 510(k) summary for the "Smart SPACE Shoulder System," a medical device used for pre-surgical planning in shoulder orthopedic surgery and for creating patient-specific 3D positioners.

After reviewing the document, it's clear that the included text does not contain the specific information requested regarding acceptance criteria and a detailed study proving the device meets those criteria, especially in the context of an AI/algorithm-based device as implied by the request's structure (e.g., "human readers improve with AI vs without AI assistance," "standalone algorithm only").

The document focuses on the regulatory submission process, comparison to a predicate device, and general performance data (sterilization, biocompatibility, software verification, mechanical, and a cadaveric study for the 3D positioners).

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

Information Present (or implied):

• Device Name: Smart SPACE Shoulder System
• Device Type: Pre-surgical planning software and patient-specific 3D positioners for shoulder arthroplasty.
• Regulatory Class: Class II (Product Codes: OHE, KWS, MBF)
• Performance Data Mentioned (but lacking detail for acceptance criteria):
  • Sterilization & Shelf-life Testing
  • Biocompatibility Testing (ISO 10993-1)
  • Software Verification and Validation Testing (IEC 62304 and FDA guidance documents: General Principles of Software Validation, Off-The-Shelf Software Used in Medical Devices, Cybersecurity for Networked Medical Devices Containing Off-the-Shelf Software, Postmarket Management of Cybersecurity in Medical Devices, Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices)
  • Mechanical and Acoustic Testing (not applicable for this submission)
  • Animal Study (not required)
  • Clinical Studies (Performed on cadaveric specimens, focused on accuracy and precision of humeral head cut using the 3D Positioner. Stated that the device "performs as well as existing traditional instrumentation" and "translated the humeral head resection in a more accurate and precise manner compared to traditional instrumentation.")

Information NOT Present (or not in sufficient detail to answer your specific questions):

The bulk of your questions relate to AI/algorithm performance studies, which are not described in this 510(k) summary. The "Smart SPACE Shoulder Planner software" is described as a "pre-surgical planner" that allows surgeons to "visualize, measure, reconstruct, annotate and edit anatomic data" and "design shoulder patient-specific instrumentation." While this involves computational processing, the document does not depict it as an AI/ML algorithm that requires the types of performance studies you've outlined for diagnostic or AI-assisted interpretation tasks.

Specifically, the following cannot be answered from the provided text:

1. A table of acceptance criteria and the reported device performance: No specific, quantified acceptance criteria (e.g., X% sensitivity, Y% specificity, Z mm accuracy) are provided for the software or the 3D positioners' performance in the summary, other than a general statement about the cadaveric study demonstrating "accuracy and precision" and performing "as well as existing traditional instrumentation."
2. Sample sized used for the test set and the data provenance: The cadaveric study is mentioned, but the number of cadavers/cases used is not specified. Data provenance (country, retrospective/prospective) is not provided.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not mentioned.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not 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 done/Not described. The device is a planning tool and guide, not an AI diagnostic assistant for human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not done/Not described for an AI algorithm. The software is a planning tool for surgeons. The cadaveric study assessed the 3D positioner's performance in executing a plan.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): For the cadaveric study, the "ground truth" for the humeral head cut would likely be based on physical measurements against a predefined surgical plan, but the method is not detailed.
8. The sample size for the training set: This refers to AI model training. Since an AI model is not described, training set size is not applicable.
9. How the ground truth for the training set was established: Not applicable.

In summary: The provided document is a regulatory submission summary for a medical device that includes software for surgical planning and 3D printed guides. It does not present data in the format of an AI/ML performance study as detailed in your questions. The performance data mentioned (cadaveric study) relates to the physical accuracy of the 3D positioners in aiding a surgical cut, not the diagnostic performance or AI-assisted interpretation of medical images.

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