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K Number
K231112
Device Name
Materialise Shoulder System™, Materialise Shoulder Guide and Models, SurgiCase Shoulder Planner
Manufacturer
Materialise NV
Date Cleared
2023-09-12

(146 days)

Product Code
QHE,KWS,PHX
Regulation Number
888.3660
Type
Traditional
Panel
OR
Reference & Predicate Devices
K230315,K220452
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

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:

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.

Device Description

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 patientspecific 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 preoperative planning of the surgeon. The graft model serves as a visual reference for the surgeon in the OR.
AI/ML Overview

This document is a 510(k) premarket notification for the Materialise Shoulder System™, Materialise Shoulder Guide and Models, and SurgiCase Shoulder Planner. It asserts substantial equivalence to a previously cleared predicate device (K220452).

The provided text does not contain detailed acceptance criteria or the specific study that proves the device meets those criteria for the software component (SurgiCase Shoulder Planner) in the context of AI/ML performance metrics.

The document primarily focuses on demonstrating substantial equivalence based on:

  • Intended Use: The device is a patient-specific medical device to assist in shoulder component placement during total anatomic and reverse shoulder replacement surgery. The software component, SurgiCase Shoulder Planner, is a pre-surgical planner for simulation and assistance in positioning shoulder components.
  • Technological Characteristics: The subject device has similar fundamental technologies, device functionality, and software technology (same code base, design, verification, and validation methods) as the predicate device.
  • Performance Data (Non-Clinical):
    • Hardware: States previous testing for biocompatibility, cleaning, debris, dimensional stability, and packaging are applicable and demonstrate substantial equivalence. Mentions testing verified accuracy and performance, and applicability of simulated surgeries and cadaver testing from previous clearances.
    • Software: 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."

Therefore, it is not possible to extract the requested information regarding AI/ML-specific acceptance criteria and performance study details from this document. The document describes a traditional 510(k) clearance process, not one with specific AI/ML performance metrics as would be expected for an AI-driven diagnostic or prognostic device. The software "assists" in planning and visualization, it does not appear to perform automated diagnostic or prognostic functions for which detailed performance metrics (like sensitivity, specificity, AUC) would typically be required for FDA clearance.

Based on the provided text, I can only provide the following information as much as possible:

1. A table of acceptance criteria and the reported device performance:
* Acceptance Criteria: Not explicitly stated in the document in terms of quantitative performance metrics for the software's "assistance" function. The acceptance criteria seem to be related to demonstrating substantial equivalence in intended use, technological characteristics, and non-clinical performance (including verification and validation against defined requirements and user needs for the software).
* Reported Device Performance:
* Hardware: "Testing verified that the accuracy and performance of the system is adequate to perform as intended." No quantitative metrics are provided.
* Software: "Software verification and validation were performed... This includes verification against defined requirements, and validation against user needs." No quantitative metrics are provided. The document highlights that the software technology differences (addition of one implant component, easier visualization of muscle elongation) "do not affect the safety or effectiveness, or that they do not raise any new issues regarding to the safety and effectiveness compared to the predicate device."

2. Sample size used for the test set and the data provenance:
* Sample Size: Not specified for software performance validation.
* Data Provenance: Not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
* Not specified. The software is a planning tool to which a surgeon provides input and approves. Ground truth in the context of AI/ML models (e.g., for diagnosis) is not applicable here as the software's function is not a diagnostic one based on the description.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
* Not applicable as no such study is described for the software.

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 described. The software's role is described as assisting in planning and visualization, not as an AI providing interpretations that would be compared to human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
* Not applicable. The software is explicitly described as a "pre-surgical planner" that "allows the surgeon to visualize, measure, reconstruct, annotate and edit pre-surgical plan data." It's a human-in-the-loop system for planning, not a standalone diagnostic algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
* Not applicable in the AI/ML diagnostic sense. The "ground truth" for the software's functionality would be its adherence to specified design requirements and user needs, ensuring it accurately represents anatomical structures and allows for proper planning as intended, rather than a clinical ground truth for a diagnostic output.

8. The sample size for the training set:
* Not specified. The document does not describe a machine learning model that would require a distinct training set in the conventional sense. The "training" for such software would typically involve its development and internal testing against requirements.

9. How the ground truth for the training set was established:
* Not applicable, as no external training set with established ground truth (e.g., clinical labels) is mentioned for a machine learning model.

§ 888.3660 Shoulder joint metal/polymer semi-constrained cemented prosthesis.

(a)
Identification. A shoulder joint metal/polymer semi-constrained cemented prosthesis is a device intended to be implanted to replace a shoulder joint. The device limits translation and rotation in one or more planes via the geometry of its articulating surfaces. It has no linkage across-the-joint. This generic type of device includes prostheses that have a humeral resurfacing component made of alloys, such as cobalt-chromium-molybdenum, and a glenoid resurfacing component made of ultra-high molecular weight polyethylene, and is limited to those prostheses intended for use with bone cement (§ 888.3027).(b)
Classification. Class II. The special controls for this device are:(1) FDA's:
(i) “Use of International Standard ISO 10993 ‘Biological Evaluation of Medical Devices—Part I: Evaluation and Testing,’ ”
(ii) “510(k) Sterility Review Guidance of 2/12/90 (K90-1),”
(iii) “Guidance Document for Testing Orthopedic Implants with Modified Metallic Surfaces Apposing Bone or Bone Cement,”
(iv) “Guidance Document for the Preparation of Premarket Notification (510(k)) Application for Orthopedic Devices,” and
(v) “Guidance Document for Testing Non-articulating, ‘Mechanically Locked’ Modular Implant Components,”
(2) International Organization for Standardization's (ISO):
(i) ISO 5832-3:1996 “Implants for Surgery—Metallic Materials—Part 3: Wrought Titanium 6-aluminum 4-vandium Alloy,”
(ii) ISO 5832-4:1996 “Implants for Surgery—Metallic Materials—Part 4: Cobalt-chromium-molybdenum casting alloy,”
(iii) ISO 5832-12:1996 “Implants for Surgery—Metallic Materials—Part 12: Wrought Cobalt-chromium-molybdenum alloy,”
(iv) ISO 5833:1992 “Implants for Surgery—Acrylic Resin Cements,”
(v) ISO 5834-2:1998 “Implants for Surgery—Ultra-high Molecular Weight Polyethylene—Part 2: Moulded Forms,”
(vi) ISO 6018:1987 “Orthopaedic Implants—General Requirements for Marking, Packaging, and Labeling,” and
(vii) ISO 9001:1994 “Quality Systems—Model for Quality Assurance in Design/Development, Production, Installation, and Servicing,” and
(3) American Society for Testing and Materials':
(i) F 75-92 “Specification for Cast Cobalt-28 Chromium-6 Molybdenum Alloy for Surgical Implant Material,”
(ii) F 648-98 “Specification for Ultra-High-Molecular-Weight Polyethylene Powder and Fabricated Form for Surgical Implants,”
(iii) F 799-96 “Specification for Cobalt-28 Chromium-6 Molybdenum Alloy Forgings for Surgical Implants,”
(iv) F 1044-95 “Test Method for Shear Testing of Porous Metal Coatings,”
(v) F 1108-97 “Specification for Titanium-6 Aluminum-4 Vanadium Alloy Castings for Surgical Implants,”
(vi) F 1147-95 “Test Method for Tension Testing of Porous Metal,”
(vii) F 1378-97 “Standard Specification for Shoulder Prosthesis,” and
(viii) F 1537-94 “Specification for Wrought Cobalt-28 Chromium-6 Molybdenum Alloy for Surgical Implants.”