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Hardware:

The Materialise Shoulder Guide and Models are intended to be used as a surgical instrument to assist in the intraoperative positioning of glenoid components used with total and reverse shoulder arthroplasty by referencing anatomic landmarks of the shoulder that are identifiable on preoperative CT-imaging scans.

The Materialise Shoulder Guide and Models are single use only.

The Materialise Shoulder Guide and Models can be used in conjunction with the following total and reverse shoulder implants systems and their respective compatible components:

· Depuy Synthes'

• o GLOBAL® APG+ Shoulder System (K052472),
• o DELTA XTEND™ Reverse Shoulder System (K120174, K062250, K183077)
• o GLOBAL® STEPTECH® APG Shoulder System (K092122).

• DJO's

• o Reverse® Shoulder Prosthesis (K051075, K111629, K092873).
• o Turon® Shoulder System (K080402)
• o AltiVate™ Anatomic Shoulder System (K162024)
• · Integra's

o Titan™ Total Shoulder System (K100448, K112438, K142413, K152047)

• o Titan™ Reverse Shoulder System (K130050, K161189, K173717, K181999)
• Lima's
  • o SMRTM Shoulder System (K100858),
  • o SMRTM Reverse Shoulder System (K110598),
  • o SMRTM Modular Glenoid (K113254) (K143256),
  • o SMR™ 3-Pegs Glenoid (K130642),
  • o SMR™ TT Metal Back Glenoid (K133349),
  • o SMRTM 40mm Glenosphere (K142139).

· Stryker's

• o ReUnion RSA Reverse Shoulder System (K183039)
• o Reunion TSA Total Shoulder Arthroplasty System (K183039).

Software:

SurgiCase Shoulder Planner is intended to be used as a pre-surgical planner for simulation of surgical interventions for shoulder orthopedic surgery. The software is used to assist in the positioning of shoulder components. SurgiCase Shoulder Planner allows the surgeon to visualize, measure, reconstruct, annotate and edit pre-surgical 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 Materialise Shoulder Guide and Models.

Materialise Shoulder 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 glenoid guide and models to transfer the glenoid plan to surgery. The device is a system composed of the following:

• a software component, branded as SurgiCase Shoulder Planner. This software is a planning tool used to generate a pre-surgical plan for a specific patient.
• Materialise Shoulder Guide and Models, 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 glenoid guide and models will be manufactured if the surgeon requests patient-specific guides to transfer the glenoid plan to surgery. The Materialise Shoulder Guide is designed and manufactured to fit the anatomy of a specific patient. A bone model of the scapula is delivered with the Materialise Shoulder Guide. A graft model can be delivered with the Materialise Shoulder Guide. The graft model visualizes the graft-space between implant and bone, based on the pre-operative planning of the surgeon. The graft serves as a visual reference for the surgeon in the OR.

The Materialise Shoulder Guide and Models must only be used within the intended use of the compatible components.

The provided text does not contain detailed acceptance criteria or a specific study that proves the device meets those criteria in a quantitative research sense. The document is a 510(k) premarket notification summary from the FDA, focusing on demonstrating substantial equivalence to a predicate device rather than presenting formal study results against predefined acceptance metrics.

However, based on the information provided, we can infer some "acceptance criteria" through the lens of substantial equivalence and list reported device performance related to this equivalence.

Here's an attempt to extract and frame the information according to your request, acknowledging the limitations of the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

Since explicit numerical acceptance criteria are not stated, we will infer them based on the substantial equivalence argument made by the manufacturer. The reported performance is based on the claim of similarity to the predicate device and the results of verification and validation activities mentioned.

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

The document mentions "previous simulated surgeries using rapid prototyped bone models and previous cadaver testing on previously cleared devices K153602 and K131559" which are considered applicable to the current device. However, no specific sample sizes (number of bone models or cadavers) for these tests are provided in this summary.

The provenance of this data (e.g., country of origin, retrospective/prospective) is not explicitly stated. It can be inferred that these were laboratory-based tests conducted typically by the manufacturer or a third-party testing facility.

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

The document does not specify the number of experts used or their qualifications for establishing ground truth in the context of the simulated surgeries or cadaver testing. The software validation involved "validation against user needs," implying input from intended users (surgeons), but the details are absent.

4. Adjudication Method for the Test Set

The document does not describe any adjudication method used for evaluating the performance of the device in the context of the "simulated surgeries" or "cadaver testing."

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

No Multi-Reader Multi-Case (MRMC) comparative effectiveness study is mentioned in the provided text. The submission focuses on substantial equivalence based on technological similarity and prior testing, not on human reader performance improvement with AI assistance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

The software component, "SurgiCase Shoulder Planner," is a planning tool that assists a surgeon. It "allows the surgeon to visualize, measure, reconstruct, annotate and edit pre-surgical plan data." This implies a continuous "human-in-the-loop" interaction for final plan approval. While software verification and validation were performed, the reported performance is within the context of assisting a surgeon, not as a standalone diagnostic or treatment decision-making algorithm. Therefore, a purely standalone (algorithm only without human-in-the-loop performance) study is not explicitly described or claimed. The software verification and validation would involve assessing the algorithm's output accuracy against its intended function (e.g., measurements, reconstructions), but this is not directly presented as "standalone performance" in the clinical decision-making sense.

7. The Type of Ground Truth Used

For the hardware (guidance system), the ground truth for "accuracy and performance" would likely be established through:

• Measurement against physical standards: For dimensional accuracy.
• Intraoperative positioning verification: During simulated surgeries or cadaver tests, assessing how well the guide facilitates the intended pin placement relative to anatomical landmarks. This would be a technical ground truth based on the precision of the physical guides.

For the software (SurgiCase Shoulder Planner), the ground truth for "validation against user needs" would likely involve:

• Expert Consensus/Clinical Expertise: Surgeons reviewing the generated plans, measurements, and reconstructions against their professional judgment and potentially 3D models or other imaging data to deem them clinically acceptable and accurate. This would involve expert consensus on the correctness of the planning outputs.

8. The Sample Size for the Training Set

The document describes premarket notification for a medical device cleared via substantial equivalence, not an AI/ML algorithm that undergoes explicit "training." While the software component has a "code base," it is described as using "exactly the same methods for design and verification and validation as the predicate device" rather than being a deep learning model trained on a dataset. Therefore, the concept of a "training set" in the context of machine learning does not apply as described in this document.

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

As the concept of a "training set" for a machine learning model is not applicable here, the question of how its ground truth was established is not relevant to this document. The software's "ground truth" (i.e., correctness of its functions and outputs) is established through traditional software verification and validation against defined requirements and user needs, as mentioned in point 7.

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Hardware

The Materialise Glenoid Positioning System is intended to be used as a surgical instrument to assist in the intraoperative positioning of glenoid components used with total and reverse shoulder arthroplasty by referencing anatomic landmarks of the shoulder that are identifiable on preoperative CT-imaging scans.

The Materialise Glenoid Positioning System can be used in conjunction with Stryker's ReUnion RSA Reverse Shoulder System (K130895) and its respective components, with DJO's following total and reverse shoulder implant systems and their respective compatible components: the Reverse® Shoulder Prosthesis (K051075, K111629, K092873, K112069), the Turon® Shoulder System (K080402, K123982), and the AltiVate™ Anatomic Shoulder System (K162024), and Lima's SMR Shoulder System (K100858), SMR Reverse Shoulder System (K110598), SMR Modular Glenoid (K113254), SMR 3-Pegs Glenoid (K130642), SMR TT Metal Back Glenoid (K133349), SMR 40mm Glenosphere (K142139) and SMR Modular Glenoid (K143256) and their respective components and Depuy Synthes' GLOBAL® APG+ Shoulder System (K052472), the DELTA XTEND™ Reverse Shoulder System (K120174, K062250) and the GLOBAL® STEPTECH® APG Shoulder System (K092122) and their respective components. The Materialise Glenoid Positioning System guide is single use only.

Software

Surgicase Planner is intended to be used as a pre-surgical planner for surgical interventions for shoulder orthopedic surgery. The software is used to assist in the positioning of glenoid components. SurgiCase Planner allows the surgeon to visualize, measure, reconstruct, annotate and edit pre-surgical 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 Materialise Glenoid Positioning Guide.

Materialise Glenoid Positioning Guides are patient-specific medical devices that are designed to assist the surgeon in the placement of glenoid components.

This can be done by generating a pre-surgical plan or by generating a pre-surgical plan and manufacturing patientspecific guides to transfer the plan to surgery. The device is a system composed of the following:

• . a software component, branded as SurgiCase Planner. This software is a planning tool used to generate a pre-surgical plan for a specific patient.
• a hardware component, branded as the Materialise Glenoid Positioning System™ guide, which is a patient specific guide that is based on a pre-surgical plan. This pre-surgical plan is generated using the software component. Patient-specific guides will be manufactured if the surgeon requests patient-specific guides to transfer the plan to surgery. The guide is designed and manufactured to fit the anatomy of a specific patient. A bone model of the scapula is delivered with the Materialise Glenoid Positioning System guide. A graft model can be delivered with the Materialise Glenoid Positioning System guide.

The Materialise Glenoid Positioning Guides must only be used within the intended use of the compatible components.

The provided text describes the Materialise Glenoid Positioning System and its clearance by the FDA (K172054). However, it does not explicitly detail a separate study proving the device meets specific acceptance criteria with reported device performance metrics in a tabular format. Instead, it refers to previous testing and substantial equivalence to predicate devices.

Based on the information provided, here's a breakdown of what can be extracted and what is not explicitly stated:

Acceptance Criteria and Reported Device Performance

The document does not explicitly state acceptance criteria in a table format with specific performance metrics. It generally mentions that "Testing verified that the accuracy and performance of the system is adequate to perform as intended." without providing quantitative values for accuracy or other performance measures.

Study Details

The document refers to prior testing, but not a specific new study with detailed methodology and results for the K172054 submission. Instead, it leverages the substantial equivalence to predicate devices and previously conducted cadaver testing.

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

   • Acceptance Criteria: Not explicitly stated with quantitative values in this document. The general criteria seem to be that "accuracy and performance of the system is adequate to perform as intended" and that it is "as safe, as effective, and performs as well as the predicates."
   • Reported Device Performance: No specific quantitative performance metrics (e.g., accuracy, precision, sensitivity, specificity) are reported for this specific submission (K172054). The document relies on previous testing for predicate devices.

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

   • Sample Size: Not explicitly stated for a new test set. The document refers to "previous cadaver testing on previously cleared devices K153602 and K131559." The sample size for these previous cadaver tests is not provided.
   • Data Provenance: Not explicitly stated (e.g., country of origin). The previous testing mentioned was "cadaver testing."

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 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:

   • No MRMC comparative effectiveness study is mentioned. This device is a surgical instrument and planning software, not an AI-assisted diagnostic tool for human readers in the typical sense.

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

   • This is partially addressed. The "Performance Data" section states, "Testing verified that the accuracy and performance of the system is adequate to perform as intended." This implies some level of standalone technical verification. However, no specific details on how this "accuracy and performance" was measured for the algorithm alone are provided, nor are any quantitative results. The software's function is to generate a pre-surgical plan, which is then inspected, fine-tuned, and approved by a qualified surgeon, indicating a human-in-the-loop process for clinical use.

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

   • The document implies that "previous cadaver testing" was used, which would typically involve physical measurements on cadaveric specimens, possibly treated as the ground truth for validating instrument placement accuracy. More specific details are not provided.

8. The sample size for the training set:

   • Not mentioned. The document primarily focuses on the device cleared under K172054 and its substantial equivalence, not on the training of its underlying algorithms (if applicable, beyond general software development).

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

   • Not mentioned.

In summary, the provided FDA 510(k) summary focuses on demonstrating substantial equivalence to predicate devices rather than detailing a new, comprehensive study with specific acceptance criteria and detailed performance results for the K172054 submission itself. It leverages prior testing and clearances.

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