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Materialise Personalized Guides for Craniomaxillofacial Surgery are intended to guide the marking of bone and or guide surgical instruments in facial surgery.

CMF Titanium Guides are used during bone repositioning/reconstruction surgical operations for orthognathic and reconstruction (including bone harvesting) indications.

CMF Titanium Guides are intended for children, adolescents and adults.

CMF Titanium Guides are intended for single use only.

CMF Titanium Guides are to be used by a physician trained in the performance of maxillofacial surgery.

Materialise Personalized Models for Craniomaxillofacial Surgery are intended for visualization of the patient's anatomy, preparation of surgical interventions and fitting or adjustment of implants or other medical devices such as osteosynthesis plates or distractors, in mandibular and maxillofacial surgical procedures.

CMF Plastic Models are intended for infants, children, adolescents and adults.

CMF Plastic Models are intended for single use only.

CMF Plastic Models are to be used by a physician trained in the performance of maxillofacial surgery.

Materialise Personalized Guides and Models for Craniomaxillofacial Surgery combines the use of 3D preoperative planning software with patient-matched guides and models to improve and simplify the performance of surgical interventions by transferring the pre-operative plan to surgery. Materialise Personalized Guides and Models for Craniomaxillofacial Surgery are used in the facial skeleton or in maxillofacial surgeries.

The surgical planning is based on medical images of the patient that are segmented in order to create a 3D representation of the patient's anatomy. The surgical treatment of the patient is simulated based on instructions provided by the surgeon and the patient-matched devices are tailored to the treatment and the patient's needs. The patient-matched devices are manufactured from commercially pure Titanium, polyamide, or clear acrylic by means of additive manufacturing technologies. The patient-matched devices are provided non-sterile.

Materialise Personalized Guides and Models for Craniomaxillofacial Surgery include CMF Titanium Guides and CMF Plastic Models.

The provided text is a 510(k) summary for the device "Materialise Personalized Guides and Models for Craniomaxillofacial Surgery." It details the device's indications for use, description, comparison to predicate and reference devices, and non-clinical performance data. However, it does not include information about AI/algorithm performance, acceptance criteria for such an algorithm, or a clinical study for proving the device meets those criteria. The document lists "non-clinical testing" and states that "no guide specific mechanical testing is performed but this is covered by mechanical analysis of CMF Titanium Plates."

Therefore, I cannot extract the information required for an AI device acceptance criteria and study from this document. The document primarily focuses on the substantial equivalence of the physical, patient-matched guides and models to existing devices, covering aspects like material compatibility, mechanical properties, biocompatibility, and sterilization.

To answer your request, the ideal information would be present in a document describing an AI/ML medical device, which would typically contain details regarding the algorithm's performance metrics (acceptance criteria), the dataset used for testing, ground truth establishment, and potential MRMC studies. This document does not describe such a device.

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Mimics Enlight CMF is intended for use as a software interface and imaging segmentation system for the transfer of medical imaging information to an output file.

Mimics Enlight CMF is also intended to support the diagnostic and treatment planning process of maxillofacial procedures. For this purpose, Mimics Enlight CMF provides visualization, measurement and design tools.

The Mimics Enlight CMF output file can be used for the fabrication of the output file using traditional or additive manufacturing methods. The fabricated output can be used for diagnostic purposes in the field of maxillofacial applications.

Mimics Enlight CMF should be used in conjunction with other diagnostic tools and expert clinical judgement.

Mimics Enlight CMF is an image processing software for the diagnosis and treatment planning of maxillofacial procedures. Mimics Enlight CMF allows the user to import, visualize and segment medical images. Mimics Enlight CMF also allows the user to perform measurements, treatment planning and occlusal splint design. Mimics Enlight CMF allows the user to output digital 3D models of the anatomy to be used for fabrication of physical anatomical models. Mimics Enlight CMF is structured as a modular package consisting of separate workflows for the diagnosis and treatment planning of various indications within the maxillofacial field. The workflows in Mimics Enlight CMF are built on the Mimics Enlight platform. The workflows in Mimics Enlight CMF cover following steps and functionality in the diagnostic and treatment planning process of maxillofacial procedures:

Digital 3D model creation

• . Importing medical images in DICOM format and other formats
• Viewing images and DICOM data
• Selecting a region of interest using generic segmentation tools
• . Verifying and editing a region of interest
• . Calculating a digital 3D model and editing the model
• . Creating composite models by combining medical image information and dental information using registration tools
• Exporting digital 3D models for additive manufacturing (3D printing) of physical replicas (anatomical models)

Planning

• Indicating nerves and cephalometric landmarks
• . Setting the natural head position
• Planning the treatment by cutting the models and repositioning the parts
• Setting the occlusion digitally or by importing an occlusion model ●
• Measuring on images and digital 3D models
• Simulating the soft tissue of the face after the planned treatment

Design

• Designing personalized digital occlusal splints using generic design and finishing tools ●
  User fabrication using additive manufacturing (3D printing) of physical replicas includes only fabrication of anatomical models and does not include additive manufacturing of occlusal splints.

The provided text describes the device, Mimics Enlight CMF, and its substantial equivalence to predicate devices, but it does not contain the specific acceptance criteria or detailed study results (like sample sizes, expert qualifications, or MRMC study results) that would typically be found in a detailed performance study section of a 510(k) submission.

The document mainly focuses on:

• Indications for Use
• Comparison of Technological Characteristics with Predicate Device
• Statements about Software Verification and Validation
• Geometrical Accuracy Testing for Virtual Models and Physical Replicas (by reference to the predicate device)
• Soft Tissue Simulation Equivalence

Based on the available text, here's what can be extracted and what information is not present:

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

The document does not provide a specific table with numerical acceptance criteria and reported performance values. It mentions:

• "The results revealed no deviations in the virtual models, demonstrating substantial equivalency between the two devices."
• "The deviations were found to be within the acceptance criteria, indicating that the virtual models can be printed accurately using one of the compatible 3D printers." (This refers to predicate device testing, with the conclusion that it applies to the subject device due to no significant deviations in virtual models).
• "The test demonstrated that the soft tissue simulation in Mimics Enlight CMF is equivalent to the soft tissue simulation in the reference device Proplan CMF (K111641)."

This implies acceptance criteria related to "no deviations" or "deviations within acceptance criteria" and "equivalence," but the specific numerical thresholds are not detailed.

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

• Sample Size for Test Set: Not specified. The document mentions "virtual models were compared" and "soft tissue simulation in the subject device Mimics Enlight CMF" was tested, but no specific number of cases or models used for these comparisons is provided.
• Data Provenance: Not specified. There is no information regarding the country of origin of the data or whether it was retrospective or prospective.

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

Not specified. The document mentions testing for geometrical accuracy and soft tissue simulation equivalence, but it does not describe any expert-based ground truth establishment process involving specific numbers of experts or their qualifications.

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

Not specified. Given that the described tests involve comparisons of virtual models and simulations rather than human interpretation of cases to establish ground truth, an adjudication method in the traditional sense (for clinical interpretation) is not mentioned or implied.

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. The document does not mention an MRMC study. The device, Mimics Enlight CMF, is described as an image processing software for segmentation, visualization, measurement, and design tools, supporting diagnostic and treatment planning. It's not an AI-assisted diagnostic tool in the sense that medical images are interpreted by human readers with or without AI assistance. Therefore, an MRMC study to show human reader improvement with AI assistance is not relevant to the described performance evaluation.

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

Yes, in a sense. The described tests on "geometrical accuracy" of virtual models and "soft tissue simulation" are evaluations of the algorithm's output directly, without a human in the loop for the performance measurement itself. The device is an "image processing software," so its performance is inherently about the quality and accuracy of its processing capabilities. The statement "Mimics Enlight CMF should be used in conjunction with other diagnostic tools and expert clinical judgement" implies that it is not intended for standalone clinical decision-making but rather as a tool within a broader clinical workflow, where the algorithm's output is then used by a human expert.

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

The ground truth for the "geometrical accuracy" appears to be based on:

• Comparison with the predicate device's virtual models ("no deviations in the virtual models").
• Optical scans of physical models (for the predicate device, implying this accuracy carries over to the subject device).

For "soft tissue simulation," the ground truth was equivalence to the reference device Proplan CMF (K111641).

This is a technical ground truth based on direct comparison to a known state (predicate/reference device's output or physical measurements via optical scans), rather than a clinical ground truth like pathology or expert consensus on a diagnosis.

8. The sample size for the training set

Not specified. The document does not provide details about a training set, as it emphasizes verification and validation against requirements and comparison to predicate devices, rather than a machine learning model's training process.

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

Not applicable/Not specified. Since no training set or machine learning model training is described for this device in the provided text, the establishment of ground truth for a training set is not pertinent to the information given. The device appears to be a rule-based or algorithmic image processing software, not a deep learning AI model that requires a labeled training dataset in the traditional sense.

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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'
• GLOBAL® APG+ Shoulder System (K052472)
• DELTA XTEND™ Reverse Shoulder System (K120174, K062250, K183077, K203694)
• GLOBAL® STEPTECH® APG Shoulder System (K092122)
• INHANCE™ Anatomic Shoulder System (K202716)1
• INHANCE™ Reverse Shoulder System (K212737)
• Enovis'2 (DJO)
• Reverse® Shoulder Prosthesis (K051075, K111629, K092873)
• Turon® Shoulder System (K080402)
• AltiVate™ Anatomic Shoulder System (K162024)
• AltiVate™ Anatomic Augmented Glenoid (K213387)
• Smith+Nephew's 3
• Titan™ Total Shoulder System (K100448, K112438, K142413, K152047)
• Titan™ Reverse Shoulder System (K130050, K161189, K173717, K181999)
• Lima's
• SMR™ Shoulder System (K100858)
• SMRTM Reverse Shoulder System (K110598)
• SMRTM Modular Glenoid (K113254) (K143256)
• SMR™ 3-Pegs Glenoid (K130642)
• SMR™ TT Metal Back Glenoid (K133349)
• SMRTM 40mm Glenosphere (K142139)
• SMRTM TT Augmented 360 Baseplate (K220792)
• SMR™ TT Hybrid Glenoid (K220792)
• Stryker's
• ReUnion RSA Reverse Shoulder System (K183039)
• 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 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.

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.

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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', DJO's, Smith+Nephew's, Lima's, Stryker's.

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 graftspace between implant and bone, based on the pre-operative planning of the surgeon. The graft model serves as a visual reference for the surgeon in the OR.

The provided text is a 510(k) summary for the Materialise Shoulder System™, which includes the Materialise Shoulder Guide and Models (hardware) and the SurgiCase Shoulder Planner (software). This submission is for an extension of compatibility with additional Lima's Implant components, not a new device requiring a full de novo performance study. Therefore, the information regarding acceptance criteria and performance studies is limited and focuses on showing equivalence to the predicate device.

Here's an analysis based on the provided text, highlighting what is (and isn't) present:

1. Table of Acceptance Criteria and Reported Device Performance:

The document describes the performance data in a qualitative manner, emphasizing equivalence to the predicate and existing testing. It does not provide a quantitative table of specific acceptance criteria (e.g., in terms of accuracy metrics, sensitivity, specificity) and corresponding performance outcomes for the newly added functionalities. Instead, it relies on the established performance of the predicate and the assertion that the changes do not affect safety or effectiveness.

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

• Software Validation: 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.'" However, it does not specify the sample size used for the test set (number of cases/patients) or the data provenance (e.g., country of origin, retrospective/prospective). The validation is described as "verification against defined requirements, and validation against user needs," but no details on the specific data used for this validation are provided in this summary.
• Hardware Testing: For hardware, it mentions "simulated surgeries using rapid prototyped bone models and previous cadaver testing on previously cleared devices K153602 and K131559." Again, sample sizes (e.g., number of models or cadavers) are not provided. The data provenance is implied to be from previous testing of predicate/cleared devices, but no specific details are given.

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

This information is not provided in the document. Given that the submission focuses on substantial equivalence for an expanded compatibility, explicit ground truth establishment by experts for specific new performance metrics is not detailed. The "approved glenoid pre-surgical plan" by a "qualified surgeon" for generating guides suggests expert involvement in the planning process, but not in a formal ground truth assessment for a test set.

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

This information is not provided. As no formal multi-reader ground truth establishment is described for a test set, an adjudication method would not be applicable in the context of the information given.

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. The device is a surgical planning tool and patient-specific instrumentation, not an AI diagnostic aid for human readers in the traditional sense. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant to this device's stated purpose and is not included in the submission summary.

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

• The software component, SurgiCase Shoulder Planner, is described as assisting in the positioning of shoulder components and allowing the surgeon to "visualize, measure, reconstruct, annotate and edit pre-surgical plan data." The output is a "pre-surgical plan data file." This indicates a human-in-the-loop process where the surgeon interacts with and approves the plan.
• While software verification and validation were performed, the summary does not explicitly describe a "standalone" performance study of the algorithm only in isolation from human interaction for clinical decision-making. Its function is to facilitate human planning, not replace it.

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

• For the software, the ground truth for validation is implied to be against "defined requirements" and "user needs," which likely translates to the accuracy of planned measurements or component placements compared to a reference standard (e.g., expert-defined ideal parameters, possibly based on anatomical landmarks from CT images). However, the specific type of ground truth (e.g., expert consensus on optimal placement on a gold standard model) is not explicitly stated as pathology or outcomes data.
• For the hardware, "simulated surgeries using rapid prototyped bone models and previous cadaver testing" would involve assessing the accuracy of guide placement and the resulting pin positioning relative to the pre-surgical plan. The "ground truth" here would thus be defined by the pre-surgical plan itself and the anatomical accuracy of the physical model/cadaver.

8. The sample size for the training set:

• The document is a 510(k) summary for a substantial equivalence claim, primarily for extending compatibility. It describes software "design and verification and validation," implying a traditional software development lifecycle. It does not mention a training set in the context of machine learning or AI models, as this is not presented as an AI-driven device with a learning component.

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

• As no training set for a machine learning model is mentioned, this information is not applicable/provided.

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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'
  • GLOBAL® APG+ Shoulder System (K052472)
  • DELTA XTEND™ Reverse Shoulder System (K120174, K062250, K183077, K203694)
  • GLOBAL® STEPTECH® APG Shoulder System (K092122)
  • INHANCETM Anatomic Shoulder System (K202716)
  • INHANCE™ Reverse Shoulder System (K212737)
• DJO's
  • Reverse® Shoulder Prosthesis (K051075, K111629, K092873)
  • Turon® Shoulder System (K080402)
  • AltiVate™ Anatomic Shoulder System (K162024)
• Smith & Nephew's
  • Titan™ Total Shoulder System (K100448, K112438, K142413, K152047)
  • Titan™ Reverse Shoulder System (K130050, K161189, K173717, K181999)
• Lima's
  • SMRTM Shoulder System (K100858)
  • SMRTM Reverse Shoulder System (K110598)
  • SMRTM Modular Glenoid (K113254) (K143256)
  • SMR™ 3-Pegs Glenoid (K130642)
  • SMRTM TT Metal Back Glenoid (K133349)
  • SMR™ 40mm Glenosphere (K142139)
• Stryker's .
  • ReUnion RSA Reverse Shoulder System (K183039)
  • Reunion TSA Total Shoulder Arthroplasty System (K183039)

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 quide 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 quides 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 model serves as a visual reference for the surgeon in the OR.

I am sorry, but the provided text primarily consists of an FDA 510(k) clearance letter and summary for the Materialise Shoulder System. While it describes the device, its indications for use, and technological characteristics compared to a predicate device, crucial details regarding the acceptance criteria and the study proving the device meets those criteria (such as specific performance metrics, sample sizes for test sets, ground truth establishment, or clinical study designs like MRMC studies) are not present in the provided document.

The "Performance Data (non-clinical)" section briefly mentions software verification and validation, but it does not provide the specific "acceptance criteria" for performance or the details of the "study that proves the device meets the acceptance criteria" in the format requested. It mainly relies on demonstrating substantial equivalence to a predicate device based on similar technology and previous testing.

Therefore, I cannot fulfill your request to describe the acceptance criteria and the study proving the device meets them using only the information given in the input text. The information required for the table and the detailed study description is simply not provided in this regulatory document.

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Materialise TKA Guide System consists of hardware (Materialise TKA Guides and Models) and software (SurgiCase Knee Planner) components.

Hardware

· Pin Placement Guides

The Materialise TKA Guides are intended to be used as a surgical instrument to assist in the intra-operative positioning of Total Knee Replacement components and in guiding the marking of bone before cutting.

The Materialise TKA Guides must be used in conjunction with the Zimmer NexGen® CR-Flex fixed bearing, Zimmer NexGen® CR fixed bearing, Zimmer NexGen® LPS-Flex fixed bearing, Zimmer NexGen® LPS fixed bearing, Zimmer Gender Solutions® Natural-Knee® fixed bearing, Zimmer Persona® CR fixed bearing, Zimmer Persona® PS fixed bearing, Vanguard® Complete Knee System, Vanguard® SSK 360, Vanguard® SSK Revision Knee System, Regenerex® Primary Tibial System, Offset & Microplasty® Tibial Systems, Maxim® Complete Knee System, Ascent™ Total Knee System, AGC® Complete Knee system, Lima Physica PS System, Lima Physica CR Knee System, Lima Physica KR Knee System, Omni Apex CR, Ortho Development BKS CR, Ortho Development BKS PS, Ortho Development BKS TriMax CR and Ortho Development BKS TriMax PS prostheses families only.

The Materialise TKA Guides are intended for single use only.

• Cut-Through Guides

The Materialise TKA Guides are intended to be used as a surgical instrument to assist in the intra-operative positioning of Total Knee Replacement components and in guiding the marking of bone before cutting of the bone.

The Materialise TKA Guides must be used in conjunction with the Vanguard® Complete Knee System. Vanguard® SSK 360, Vanguard® SSK Revision Knee System, Regenerex® Primary Tibial System, Offset & Microplasty® Tibial Systems, Maxim® Complete Knee System, Ascent™ Total Knee System and AGC® Complete Knee system prostheses families only

The Materialise TKA Guides are intended for single use only.

• Models

The Materialise TKA Models are intended to be used as a surgical instrument to assist in the intra-operative positioning of Total Knee Replacement components.

The Materialise TKA Models must be used in conjunction with Zimmer NexGen® CR-Flex fixed bearing, Zimmer NexGen® CR fixed bearing, Zimmer NexGen® LPS-Flex fixed bearing, Zimmer NexGen® LPS fixed bearing, Zimmer Gender Solutions® Natural-Knee® fixed bearing, Zimmer Persona® CR fixed bearing, Zimmer Persona® PS fixed bearing, Vanguard® Complete Knee System, Vanguard® SSK 360, Vanguard® SSK Revision Knee System, Regenerex® Primary Tibial System, Offset & Microplasty® Tibial Systems, Maxim® Complete Knee System, Ascent™ Total Knee System, AGC® Complete Knee system, Lima Physica PS System, Lima Physica CR Knee System, Lima Physica KR Knee System, Omni Apex CR, Omni Apex PS , Ortho Development BKS CR, Ortho Development BKS PS, Ortho Development BKS TriMax CR and Ortho Development BKS TriMax PS prostheses families only.

The Materialise TKA Models are intended for single use only.

Software

The SurgiCase Knee Planner is intended to be used as a pre-surgical planner for knee orthopedic surgery. The software is used to pre-operatively plan the positioning of knee components. The SurgiCase Knee Planner allows the surgeon to visualize, measure, reconstruct, annotate and edit pre-surgical plan data. The generation of a surgery report along with a pre-surgical plan data file which is used as input data to design the Materialise Knee Guides and Models.

The Materialise TKA guide system is a medical device designed to implant total knee prosthesis components during a total knee arthroplasty surgical procedure. This can be done by generating a pre-surgical knee plan and by manufacturing a patient-specific knee guide and models to transfer the knee plan to surgery.

The subject device is a system that consists of the following two functional components:

• l A software component branded as SurgiCase Knee Planner. This software is a planning tool used to generate a pre-surgical TKA plan for a specific patient.
• Hardware components branded as Materialise TKA Guides and Models: which are patient-specific guides and models that are based on a pre-surgical plan. This pre-surgical plan is generated using the software component. Materialise TKA Guides and Models is an instrument set containing a femur and/or tibia guide(s) and bone models (optional). Both femoral and tibial guides are designed and manufactured to fit the anatomy of a specific patient. If the surgeon requests it, a bone model of the femur and/or tibia are delivered with the Materialise TKA Guides. The Materialise TKA Guides and Models assist in the intra-operative positioning of total knee replacement components. The guides assist in guiding the marking of bone before cutting and cutting of the bone. The models serve as a visual reference for the surgeon in the operating room. The Materialise TKA Guides and Models must only be used within the intended use of the compatible components (510(k) cleared, legally marketed prosthesis).

The provided text from the FDA 510(k) summary (K221337) describes the Materialise TKA Guide System, but does not include detailed acceptance criteria or a study proving that the device meets specific performance criteria with quantitative results.

Instead, it relies on substantiating equivalency to a predicate device (K173445) and primarily focuses on verification and validation activities for the software, and re-evaluation/re-testing of hardware characteristics like biocompatibility, cleaning, sterilization, and packaging due to specific updates or extended specifications. It states that "Previous testing for debris, dimensional stability and packaging are applicable to the subject device and demonstrate substantial equivalence with the predicate device. Testing verified that the accuracy and performance of the system is adequate to perform as intended."

Therefore, I cannot provide a table of acceptance criteria and reported device performance, nor detailed information about specific studies to prove device performance against those criteria, as this information is not present in the provided document.

However, I can extract information about the studies and verification activities that were performed, based on the provided text, and address the points that can be answered:

1. Table of Acceptance Criteria and Reported Device Performance:

• This information is NOT PRESENT in the provided document. The document does not specify quantitative acceptance criteria for the accuracy or performance of the TKA Guide System (e.g., specific angular deviation tolerances, linear accuracies, etc.) nor does it report specific performance metrics from a study that demonstrate the device meets such criteria. It generally states that "Testing verified that the accuracy and performance of the system is adequate to perform as intended" and that "the subject device is as safe, as effective, and performs as well as the predicate device."

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

• Test Set Sample Size: Not explicitly stated for performance testing related to accuracy. The document mentions "All samples passed the cleaning test" and "All samples passed the sterilization test," but the number of samples is not specified.
• Data Provenance: Not specified for any performance testing. It is not clear if any in vivo or ex vivo testing of the device's accuracy was performed as part of this submission, or if it relies entirely on the predicate's performance claims. The document mentions "previous simulated surgeries using rapid prototyped bone models and previous cadaver testing are considered applicable to the subject device," implying that these were done for the predicate, not necessarily for the current submission.

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

• This information is NOT PRESENT in the provided document. The document does not describe studies involving experts establishing ground truth for performance evaluation of the device's accuracy.

4. Adjudication Method for the Test Set:

• This information is NOT PRESENT in the provided document. No adjudication method is mentioned as there's no description of a study involving expert assessment of performance.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

• No MRMC comparative effectiveness study is mentioned in the provided document. The document focuses on regulatory clearance based on substantial equivalence, not comparative effectiveness studies with human readers assisting with AI vs. without AI. The device is a planning software and physical guides, not an AI diagnostic tool involving human readers.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

• A "standalone" software verification and validation was performed. The document states, "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." However, specific performance metrics from this standalone validation are not reported. The "human-in-the-loop" aspect for this device is the surgeon using the planning software and then using the physical guides in surgery. The software part itself is a planning tool, and its "standalone" performance would likely refer to its accuracy in generating measurements or plans, which is generally covered by its verification and validation.

7. Type of Ground Truth Used:

• For the software verification and validation, the ground truth would typically be established based on defined requirements and user needs (as stated in the document). For hardware re-evaluations:
  • Biocompatibility: ISO 10993-1:2018 standards (cytotoxicity, sensitization, irritation, systemic toxicity, pyrogenicity).
  • Cleaning: "extended cleaning cycle specifications, including testing of both manual and automated cleaning cycle with both enzymatic and alkaline detergent on a new worst-case design." Ground truth would be cleanliness metrics, though not specified.
  • Sterilization: ISO 17665-1:2006 "overkill method." Ground truth would be sterility assurance level.
  • Packaging: ISO 11607-1:2019, ISTA 3A:2018, ASTM D4169-16. Ground truth would be packaging integrity after simulated distribution.

8. Sample Size for the Training Set:

• The document does NOT mention a training set in the context of machine learning or AI. The software described is a "planning tool" and does not appear to be an AI/ML algorithm that would undergo a distinct training phase.

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

• Not applicable, as no training set for an AI/ML algorithm is mentioned.

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SurgiCase Viewer is intended to be used as a software interface to assist in visualization of treatment options.

SurgiCase Viewer provides functionality to allow visualization of 3D data and to perform measurements on these 3D data, which should allow a clinician to evaluate and communicate about treatment options.

SurgiCase Viewer is intended for use by people active in the medical sector. When used to review and validate treatment options, SurgiCase Viewer is intended to be used in conjunction with other diagnostic tools and expert clinical judgment.

The SurgiCase Viewer can be used by a medical device/service manufacturer/provider or hospital department to visualize 3D data during the manufacturing process of the product/service to the end-user who is ordering the device/service. This allows the end-user to evaluate and provide feedback on proposals or intermediate steps in the manufacturing of the device or service.

The SurgiCase Viewer is to be integrated with an online Medical Device Data System which is used to process the medical device or service and which is responsible for case management, user management, authorization, authentication, etc.

The data visualized in the SurgiCase Viewer is controlled by the medical device manufacturer using the SurgiCase Viewer in its process. The Device manufacturer will create the 3D data to be visualized to the end-user and export it to one of the dedicated formats supported by the SurgiCase Viewer. Each of these formats describe the 3D data in STL format with additional meta-data on the 3D models. The SurgiCase Viewer does not alter the 3D data it imports and its functioning is independent of the specific medical indication/situation or product/service it is used for. It's the responsibility of the Medical device company using the SurgiCase Viewer to comply with the applicable medical device regulations.

The provided text describes the 510(k) submission for the "SurgiCase Viewer" device (K213684). However, it does not contain the specific details required to fully address all parts of your request related to acceptance criteria, test set specifics, expert ground truth establishment, MRMC studies, or training set details. This document primarily focuses on demonstrating substantial equivalence to a predicate device.

The study presented here is a non-clinical performance evaluation comparing the new SurgiCase Viewer with its predicate (K170419) and a secondary reference device (K183105).

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

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of acceptance criteria with numerical performance metrics. Instead, it states that the device was validated to determine substantial equivalence based on:

• Intended Use: "Both the subject device as well as the predicate device have the same intended use; They are both intended to be used as a software interface to assist in visualization and communication of treatment options."
• Device Functionality: The new device was compared to the predicate in terms of features like 3D view navigation, visualization options, measuring, and annotations. For new functionalities (medical image visualization, VR visualization), it states "The abovementioned technological differences do not impact the safety and effectiveness of the subject device for the proposed intended use as is demonstrated by the verification and validation plan."
• Medical Images Functionality (compared to Mimics Medical K183105): "Both functionality produce the same results in: Contrast adjustments, Interactive image reslicing, 3D contour overlay on images."
• Measurement functionality: "Measurement functionality on images was compared with already existing functionality on the 3D models and shown to provide correct results both on images and 3D."

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

• Sample Size: Not explicitly stated. The document refers to "verification and validation" and "performance testing" but does not provide details on the number of cases or images used in these tests.
• Data Provenance: Not explicitly stated (e.g., country of origin). It refers to "medical images functionality" and "3D models" but doesn't specify if these were from retrospective patient data, simulated data, etc. The study is described as "non-clinical testing."

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

• Experts: Not explicitly stated. The validation involved "end-users," but their specific number, roles, or qualifications are not provided.
• Ground Truth Establishment: Not explicitly detailed. The comparison against the predicate and reference device functionalities implies that their established performance served as a form of "ground truth" for the new device's functions.

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

• Not explicitly stated. There is no mention of a formal reader adjudication process.

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 described. This submission focuses on the device's substantial equivalence in functionality and safety, not on human reader performance improvement with AI assistance. The device's stated indication is "to assist in visualization of treatment options," implying a tool for clinicians, but not an AI-driven diagnostic aid that would typically undergo MRMC studies.

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

• The context suggests a standalone functional assessment of the software's capabilities (e.g., whether it correctly performs contrast adjustments, measurement calculations, etc.) in comparison to the predicate and reference device. It's not an AI algorithm with a distinct "performance" metric like sensitivity/specificity, but rather a functional software application.

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

• For the functional comparison: The "ground truth" seems to be the established, correct functioning of the predicate and reference devices for equivalent features, and the defined requirements for new features. For instance, if the Mimics Medical device correctly performs "contrast adjustments," the SurgiCase Viewer needs to produce the "same results." For measurements, it needs to provide "correct results." This isn't a traditional clinical ground truth like pathology for a diagnostic AI.

8. The sample size for the training set:

• Not applicable / Not mentioned. This device description does not indicate the use of machine learning or AI models that require a "training set" in the conventional sense. It's described as a software interface for visualization and measurements.

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

• Not applicable. (See point 8).

In summary, the provided document demonstrates that the SurgiCase Viewer is substantially equivalent to existing cleared devices based on a functional and software validation process. It assures that new functionalities do not negatively impact safety or effectiveness and that shared functionalities perform comparably. However, it does not detail the type of rigorous clinical performance study (e.g., with patient data, expert readers, and quantitative statistical metrics) that would be common for AI/ML-driven diagnostic devices.

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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, K203694)
o GLOBAL® STEPTECH® APG Shoulder System (K092122)
o Ignite Anatomic Shoulder System (K202716) (rebranded to INHANCE™ Anatomic Shoulder System))
• DJO's
o Reverse® Shoulder Prosthesis (K051075, K111629, K092873),
o Turon® Shoulder System (K080402)
o AltiVate™ Anatomic Shoulder System (K162024)
· Smith & Nephew's (Integra's)2
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 SMR™ 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).

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 is a 510(k) summary from the FDA for a medical device called the "Materialise Shoulder System™". While it describes the device, its intended use, and states that non-clinical performance data indicates substantial equivalence to a predicate device, it does not contain the specific details required to answer all parts of your request regarding acceptance criteria and a study proving device performance.

Here's an analysis of what can be extracted and what is missing:

What's Available:

• Device Name: Materialise Shoulder System™, Materialise Shoulder Guide and Models, SurgiCase Shoulder Planner
• Purpose of the "Study": The document focuses on demonstrating substantial equivalence to a predicate device (K193560), rather than a specific clinical study with defined acceptance criteria for novel claims. The performance data presented are primarily non-clinical tests to support this substantial equivalence.
• Type of Ground Truth: For the "Hardware," it mentions "simulated surgeries using rapid prototyped bone models and previous cadaver testing." For the "Software," it mentions "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 implies validation against defined requirements and user needs, but not necessarily a clinical ground truth like pathology or outcomes data.
• Data Provenance (Implied): The company, Materialise N.V., is based in Belgium. The non-clinical tests mentioned would likely have been conducted by or for the manufacturer. The previous cadaver testing would likely have been retrospective or specifically for previous clearances.

What's Missing (and why based on the document type):

The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a legally marketed predicate device. For this type of submission, extensive clinical studies with new acceptance criteria, expert adjudication, MRMC studies, or large training datasets for AI (if applicable, though this device seems more rule-based/software-assisted planning) are often not required if substantial equivalence can be demonstrated through non-clinical means and comparison to established predicate devices.

Therefore, the following information is not provided in the document:

1. A table of acceptance criteria and the reported device performance: The document states that testing "verified that the accuracy and performance of the system is adequate to perform as intended" and that the subject device "is as safe, as effective, and performs as well as the predicate device," but it does

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Hardware

· Guides

The Materialise PKA Guides are intended to be used as a surgical instrument to assist in the intra-operative positioning of Partial Knee Replacement components and in guiding the marking of bone before cutting of the bone.

The Materialise PKA Guides must be used in conjunction with the compatible prostheses families only: ZUK UNI. JOURNEY™ UNI, JOURNEY II UNI, JZ (Hybrid) UNI knee systems, Vanguard™ M Unicompartmental Knee System, Oxford® Partial Knee System and Persona® Partial Knee System.

The Zimmer Biomet Patient Specific Instruments are compatible for use with the Oxford® Partial Knee System as approved in P010014.

The Materialise PKA Guides are intended for single use only.

• Models

The Materialise PKA Models are intended to be used as a surgical instrument to assist in the intra-operative positioning of Partial Knee Replacement components.

The Materialise PKA Models must be used in conjunction with the compatible prostheses families only: ZUK UNI, JOURNEY™ UNI, JOURNEY II UNI, JZ (Hybrid) UNI knee systems, Vanguard™ M Unicompartmental Knee System, Oxford® Partial Knee System and Persona® Partial Knee System.

The Zimmer Biomet Patient Specific Instruments are compatible for use with the Oxford® Partial Knee System as approved in P010014.

The Materialise PKA Models are intended for single use only.

Software

The SurgiCase Knee Planner is intended to be used as a pre-surgical planner for knee orthopedic surgery. The software is used to pre-operatively plan the positioning of knee components. The SurgiCase Knee Planner allows the surgeon to visualize, measure, reconstruct, annotate and edit pre-surgical plan data. The generation of a surgery report along with a pre-surgical plan data file which is used as input data to design the Materialise Knee Guides and Models.

The Materialise PKA guide system is a medical device designed to implant a partial knee prosthesis during partial knee arthroplasty surgical procedures.

The device is a system that consists of the following two functional components:

• . A software component, branded as SurgiCase Knee Planner. This software is a planning tool used to generate a pre-surgical PKA plan for a specific patient.
• . A hardware component, branded as Materialise PKA Guides and Models, which are patientspecific guides and models that are based on a pre-surgical plan. This pre-surgical plan is generated using the software component. Materialise PKA Guides and Models is an instrument set containing a femur and/or tibia guide (s) and bone models (optional). Both femoral and tibial guides are designed and manufactured to fit the anatomy of a specific patient. If the surgeon requests it, a bone model of the femur and tibia is delivered with the Materialise PKA Guides. The Materialise PKA Guides and Models assist in the intra-operative positioning of partial knee replacement components. The guides assist in guiding the marking of bone before cutting and cutting of the bone. The models serve as a visual reference for the surgeon in the operating room.

The Materialise PKA Guides and Models must only be used within the intended use of the compatible components (510(k) cleared, legally marketed prosthesis).

The provided text is a 510(k) Premarket Notification summary for the Materialise PKA Guide System. It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed study proving the device meets specific acceptance criteria in the manner requested (e.g., in terms of sensitivity, specificity, or human improvement with AI assistance).

The document states that the new device is an update to an existing one (K173970) and primarily incorporates compatibility with additional knee implant systems (Persona® Partial Knee). It emphasizes that the device shares the same fundamental scientific technology, intended use, and software codebase as the predicate.

Therefore, many of the requested details, such as specific acceptance criteria for performance metrics like sensitivity/specificity, sample sizes for test sets, data provenance, expert ground truth establishment, or human-in-the-loop study results, are not present in this document. The document relies on the prior clearance of the predicate device and the claim that the changes do not raise new issues of safety or effectiveness.

However, based on the information provided, here's what can be extracted and inferred:

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

The document does not provide a quantitative table of acceptance criteria and reported device performance in terms of typical AI/medical device evaluation metrics (e.g., accuracy, sensitivity, specificity). Instead, the performance evaluation is framed as demonstrating substantial equivalence to the predicate device.

The performance aspects highlighted are:

• Hardware:
  • Applicability of previous testing for cleaning, debris, dimensional stability, and packaging.
  • Verification that "accuracy and performance of the system is adequate to perform as intended." (No specific metrics or thresholds provided).
  • Stability of device placement, surgical technique, intended use, and functional elements are similar to the predicate.
  • Biocompatibility re-evaluation: Shown to be non-cytotoxic, non-sensitizing, non-irritant, non-systematically toxic (acute), and non-pyrogenic according to ISO 10993-1:2008. (This is a qualitative acceptance of safety).
  • Sterilization re-evaluation: All samples passed the sterilization parameters in accordance with ISO 17665-1:2006. (This is a qualitative acceptance of safety).
• Software:
  • "New software validation/verification testing of the SurgiCase Knee Planner was done in support of this premarket notification in the form of end-user evaluations." (No specific metrics or quantitative performance results for these evaluations are provided).
  • The software technology is stated to have the same codebase and use the "exact same methods for design and verification and validation as the predicate device."
  • The "subject software technology differences have been demonstrated to not affectiveness or raise new issues of safety or effectiveness compared to the predicate device."

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

• Test Set Sample Size: Not specified. The document mentions "end-user evaluations" for software and "simulated surgeries using rapid prototyped bone models" and "cadaver testing" (from the predicate device) for hardware, but no specific sample sizes for these test cases are given.
• Data Provenance: Not specified. It's implied some internal "end-user evaluations" were done. The document does not indicate the country of origin of the data or whether it was retrospective or prospective.

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

This information is not provided. The document states that "end-user evaluations" were performed but does not elaborate on the nature of these evaluations, who performed them, or how ground truth was established, particularly for performance metrics beyond basic functionality.

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

This information is not provided.

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 or implied. The device is a surgical guide system and planning software, not a diagnostic AI tool where human reader improvement is typically measured. The focus is on the hardware's ability to assist in positioning and guiding, and the software's ability to plan.

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

The software component (SurgiCase Knee Planner) is described as a "pre-surgical planner" that allows the surgeon to "visualize, measure, reconstruct, annotate and edit pre-surgical plan data." It explicitly states that the surgeon inspects, fine-tunes, and approves the pre-surgical plan. Therefore, it is inherently a human-in-the-loop system, and a standalone algorithm-only performance assessment (in the sense of a fully automated diagnosis or measurement) is not the primary mode of evaluation described. The "new software validation/verification testing... in the form of end-user evaluations" would likely involve human interaction with the software.

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

This is not explicitly stated in the provided text. For hardware performance, the "accuracy and performance" would likely be judged against technical specifications for guide fit and alignment, possibly through physical measurements on bone models or cadavers. For software, "end-user evaluations" might involve assessing the accuracy of measurements, reconstruction, or the usability of the planning interface against known anatomical landmarks or surgical objectives, likely established by expert surgeons. However, the exact method for establishing this "ground truth" is not detailed.

8. The sample size for the training set:

The document describes a 510(k) submission for a medical device (surgical guides and planning software), not an AI model that undergoes a distinct "training" phase with a large dataset. The software is built based on established algorithms and presumably validated against engineering specifications and clinical use cases, but there's no mention of a "training set" in the context of machine learning.

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

As there is no mention of a "training set" in the context of machine learning, this information is not applicable/provided. The software is described as having the "same code base as the predicate device and uses exactly the same methods for design and verification and validation."

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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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