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Software: The Precision AI Planning Software is intended to be used as a pre-surgical planner for simulation of surgical interventions for shoulder joint arthroplasty. The software is used to assist in the positioning of shoulder components by creating a 3D bone construct of the joint and allows the surgeon to visualize, measure, reconstruct, annotate and edit presurgical 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 Precision AI Shoulder Guide and Biomodels.

Hardware: The Precision AI Planning System Guides and Biomodels are intended to be used as patient-specific surgical instruments to assist in the intraoperative positioning of shoulder implant components used with total and reverse shoulder arthroplasty by referencing anatomic landmarks of the shoulder that are identifiable on preoperative CT-imaging scans. The Glenoid Guide is used to place the k-wire and the Humeral Guide is used to place humeral pins for humeral head resection. The Precision AI Guides and Biomodels are indicated for single use only. The Precision AI Surgical Planning System is indicated for use on adult patients that have been consented for shoulder joint arthroplasty. Both humeral and glenoid guides are suitable for a delto-pectoral approach only. The Precision AI Surgical Planning System is indicated for total and reverse shoulder arthroplasty using the following implant systems and their compatible components: Enovis and Lima.

The Precision AI Surgical Planning 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 guides and models to transfer the plan to surgery. The subject device is a system composed of the following: The Precision AI Surgical Planning System Software will create a 3D construct/render of the patient's shoulder joint for the surgeon to plan the operatively then create a physical Patient Specific Instrument (or Guide), using 3D printing by selective laser sintering. The patient's CT scan images are the design input for this to be created and are auto segmented via a locked, or static, artificial intelligence algorithm. The surgeon can visualise the deformity of the diseased joint, on this 3D render and CT scan images, and determine the inherent deformity of the joint. They are then able to virtually place the artificial implants in an optimal position to correct the measured deformity for that specific patient. The Precision AI Guides, 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 guide and models will be manufactured if the surgeon requests patient-specific guides to transfer the plan to surgery.

The provided text is an FDA 510(k) summary for the Precision AI Surgical Planning System (PAI-SPS). It describes the device and its intended use, but it does NOT contain specific acceptance criteria, detailed study designs, or performance results in terms of metrics like sensitivity, specificity, accuracy, or effect sizes for human reader improvement.

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.' This includes verification against defined requirements and validation against user needs." It also mentions that "Design verification and validation testing demonstrated that the PAI-SPS meets all design requirements and is as safe and effective as its predicate device (K233992)."

However, it does not explicitly lay out the acceptance criteria (e.g., "model must achieve 90% accuracy") or the results against those criteria. It focuses more on demonstrating substantial equivalence to a predicate device (PAI-SPS K233992) by showing that the technology and intended use are similar, with the main differences being the addition of compatibility with more implant systems.

Therefore, I cannot fully complete the requested table and answer all questions based solely on the provided text. I will provide information based on what is available and indicate where information is missing.

Description of Acceptance Criteria and Study to Prove Device Meets Criteria

Based on the provided FDA 510(k) summary, the PAI-SPS device is being cleared primarily through demonstrating substantial equivalence to an already cleared predicate device (PAI-SPS, K233992). The key claim for equivalence rests on similar intended use, fundamental scientific technology, design, functionality, operating principles, and materials, with the primary difference being expanded compatibility with additional implant systems.

The document implicitly suggests that the "acceptance criteria" are tied to demonstrating that these technological differences "do not raise any different questions of safety and effectiveness." The studies cited are primarily focused on software verification and validation, ensuring the new compatible implant systems do not negatively impact the established safety and effectiveness.

Here is a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The provided document does not explicitly state quantitative acceptance criteria (e.g., minimum accuracy percentages, specific error bounds) or detailed performance metrics. The performance is largely framed as demonstrating that the device "meets all design requirements and is as safe and effective as its predicate device."

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

• The document does not specify the sample size for any test set (e.g., for software validation or hardware accuracy).
• Data Provenance: Not explicitly stated for specific test sets. Given the company is "Precision AI Pty Ltd" in Australia, and the document discusses "previous cadaver testing and composite bone model testing," it's likely a mix of lab-based/simulated data and potentially some retrospective clinical imaging data for initial AI development/testing, but this is not detailed. The document implies that new testing was not extensively conducted for this submission, relying heavily on the predicate device's prior validation and the minor changes to compatibility.

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

• The document does not specify the number of experts or their qualifications used to establish ground truth for any test set.
• It mentions that the software allows a "qualified surgeon" to approve pre-surgical plan data, implying that expert surgical review is part of the workflow.

4. Adjudication Method for the Test Set

• The document does not specify any adjudication method (e.g., 2+1, 3+1) for establishing ground truth or evaluating test results.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No, an MRMC comparative effectiveness study was not explicitly mentioned or described. The focus of this 510(k) is substantial equivalence based on technological similarity and expanded compatibility, not a comparative study against human readers or performance improvement with AI assistance.

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

• The document states that the AI algorithm performs "auto segmentation via a locked, or static, artificial intelligence algorithm." While this indicates a standalone AI component, the document does not provide standalone performance metrics for this AI segmentation. The overall system is described as a "pre-surgical planner" where the surgeon can "visualize, measure, reconstruct, annotate and edit pre-surgical plan data," suggesting a human-in-the-loop workflow.

7. The Type of Ground Truth Used

• For software, the implicit ground truth appears to be expert consensus or approved surgical plans for judging the accuracy of the software's representations and planning capabilities. The document states "The software allows a qualified surgeon to visualize, measure, reconstruct, annotate, edit and approve pre-surgical plan data."
• For hardware, "previous cadaver testing and composite bone model testing" were used, implying physical measurements against a known standard or "true" position established in these models.

8. The Sample Size for the Training Set

• The document does not specify the sample size used for the training set for the AI segmentation algorithm.

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

• The document does not specify how the ground truth for the AI training set was established. It only mentions that the AI algorithm for auto-segmentation is "locked, or static," implying it was trained previously.

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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)
• INHANCE™ Hybrid Anatomic Glenoid Implant (K212933)
• INHANCE™ Reverse Glenoid Peripheral Posts (K221467)
• INHANCE Convertible Glenoid (K230831)
• · Enovis'2 (DJO)
• Reverse® Shoulder Prosthesis (K051075, K111629, K092873)
• Turon® Shoulder System (K080402)
• AltiVate™ Anatomic Shoulder System (K162024)
• AltiVate™ Anatomic Augmented Glenoid (K213387, K222592)
• AltiVate™ Reverse Glenoid (K233481)
• · Smith+Nephew's3
• Titan™ Total Shoulder System (K100448, K112438, K142413, K152047)
• Titan™ Reverse Shoulder System (K130050, K161189, K173717, K181999)
• AETOS Total Shoulder System (K220847, K230572)
• AETOS Reverse Shoulder System (K220847, K230572)
• · Lima's
• SMR™ Shoulder System (K100858)
• SMR™ Reverse Shoulder System (K110598)
• SMR™ Modular Glenoid (K113254) (K143256)
• SMR™ 3-Pegs Glenoid (K130642)
• SMR™ TT Metal Back Glenoid (K133349)
• SMR TM 40mm Glenosphere (K142139)
• SMR™ TT Augmented 360 Baseplate (K220792)
• SMR™ TT Hybrid Glenoid (K220792)
• PRIMA TT Glenoid (K222427)

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 quide and models that are based ● on a pre-surgical plan. This pre-surgical plan is generated using the software component. Patientspecific 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 model serves as a visual reference for the surgeon in the OR.

The provided FDA 510(k) summary (K242813) for the Materialise Shoulder System™ describes a submission seeking substantial equivalence to a previously cleared device (K241143). This submission is primarily for adding compatibility with new implant components rather than introducing a completely new AI capability or significant software change that would necessitate extensive new performance data. Therefore, the document does not contain the detailed information typically found in a study proving a device meets acceptance criteria for an AI/ML product.

Specifically, the document states:

• "The non-clinical performance data has demonstrated that the subject software technological differences between the subject and predicate devices do not raise any different questions of safety and effectiveness." (Page 9)
• "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." (Page 10)
• "Previous testing for biocompatibility, sterility, cleaning, debris, dimensional stability and packaging are applicable to the subject device. Testing verified that the accuracy and performance of the system is adequate to perform as intended. The stability of the device placement, surgical technique, intended use and functional elements of the subject device are the same as that of the predicate device of Materialise Shoulder System™ K241143 and previously cleared devices... therefore previous simulated surgeries using rapid prototyped bone models and previous cadaver testing on previously cleared devices K153602 and K131559 are considered applicable to the subject device." (Page 10)

Given this, I cannot provide detailed answers to many of your questions as the submission relies on the substantial equivalence principle and prior testing rather than new, extensive performance studies for AI/ML.

However, I can extract what is available:

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

The document does not provide a specific table of quantitative acceptance criteria and reported device performance for the current submission (K242813), as it relies on the previous clearance and the assessment that the changes (adding implant compatibility) do not raise new safety or effectiveness concerns.

The general acceptance criterion mentioned is that the "accuracy and performance of the system is adequate to perform as intended." This was verified through previous testing, including "simulated surgeries using rapid prototyped bone models and previous cadaver testing."

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document mentions "previous simulated surgeries using rapid prototyped bone models and previous cadaver testing on previously cleared devices K153602 and K131559." It does not specify the sample size for these tests, nor 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 (e.g. radiologist with 10 years of experience)

This information is not provided in the document.

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

This information is not provided in the document.

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 such MRMC study is mentioned. The device is a "pre-surgical planner" and "surgical instrument" designed to assist the surgeon, but the provided text does not detail comparative effectiveness studies of human readers (surgeons) with and without the AI (planning software) assistance.

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

The software (SurgiCase Shoulder Planner) generates a pre-surgical plan which the "qualified surgeon" can "visualize, measure, reconstruct, annotate, edit and approve" (Page 9). This indicates a human-in-the-loop process. Standalone performance of the algorithm without human interaction is not discussed as it's not the intended use.

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

The document generally refers to "verification against defined requirements, and validation against user needs" and "accuracy and performance of the system is adequate to perform as intended" based on "simulated surgeries using rapid prototyped bone models and previous cadaver testing." This suggests a ground truth established through expert-defined surgical planning parameters and comparison to physical outcomes in the simulated/cadaveric environment, but specifics on how this ground truth was formalized (e.g., expert consensus on optimal planning, precise measurement validation) are not detailed.

8. The sample size for the training set

This device is a surgical planning tool and guides, not a deep learning AI model that requires a "training set" in the conventional sense for image classification or similar tasks. It is based on algorithms that process CT-imaging scans and anatomical landmarks to generate personalized plans and guides. Therefore, the concept of a "training set" for AI/ML is not applicable here in the way it would be for a pattern recognition AI. The software's robustness and accuracy are likely validated through extensive testing against various patient anatomies and surgical scenarios.

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

As explained above, the concept of a training set as typically understood for AI/ML models is not directly applicable to this device based on the provided information.

Ask a specific question about this device

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)
• INHANCE Hybrid Anatomic Glenoid Implant (K212933)
• INHANCE Reverse Glenoid Peripheral Posts (K221467)
• 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's3
• Titan™ Total Shoulder System (K100448, K112438, K142413, K152047)
• Titan™ Reverse Shoulder System (K130050, K161189, K173717, K181999)
• AETOS Total Shoulder System (K220847, K230572)
• AETOS Reverse Shoulder System (K220847, K230572)
• Lima's
• SMR™ Shoulder System (K100858)
• SMR™ Reverse Shoulder System (K110598)
• SMR™ Modular Glenoid (K113254) (K143256)
• SMR™ 3-Pegs Glenoid (K130642)
• SMR™ TT Metal Back Glenoid (K133349)
• SMR™ 40mm Glenosphere (K142139)
• SMR™ TT Augmented 360 Baseplate (K220792)
• SMR™ TT Hybrid Glenoid (K220792)
• PRIMA TT Glenoid (K222427)

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

The provided text describes a 510(k) submission for the Materialise Shoulder System™, Materialise Shoulder Guide and Models, and SurgiCase Shoulder Planner. It indicates that this is a special 510(k) submission, meaning it's for a modification to a previously cleared device. Therefore, much of the performance data refers back to the predicate device and prior clearances.

Here's an analysis of the acceptance criteria and supporting study information based on the provided text:

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

The document does not explicitly state quantitative acceptance criteria or a direct table showing "acceptance criteria vs. reported device performance" for this specific 510(k) submission. Instead, for this special 510(k), the performance data mainly focuses on demonstrating that the changes (addition of new implant components to the software and hardware compatibility) do not raise new questions of safety and effectiveness compared to the predicate device.

The "performance data (non-clinical)" section highlights that:

• Hardware: Previous testing for biocompatibility, cleaning, debris, dimensional stability, and packaging is applicable. Accuracy and performance of the system were "adequate to perform as intended." Previous simulated surgeries and cadaver testing on earlier cleared devices are considered applicable.
• Software: Software verification and validation were performed "against defined requirements" and "against user needs," following FDA guidance.

Since this is a special 510(k) for an incremental change (adding compatibility with specific new implants), it's implied that the acceptance criteria are met if these additions do not negatively impact the established safety and effectiveness of the existing device, and the software development process meets regulatory standards.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Hardware (previous testing cited): The document mentions "previous simulated surgeries using rapid prototyped bone models" and "previous cadaver testing on previously cleared devices K153602 and K131559." It does not specify the sample size for these previous studies (e.g., number of bone models or cadavers) or their provenance (country of origin), nor does it state if they were retrospective or prospective.
• Software (verification and validation): The document states "Software verification and validation were performed," but does not specify a separate "test set" in the context of clinical data or specific performance metrics with sample sizes for this particular submission. The V&V activities would involve testing against requirements and user needs, which could include various test cases and scenarios, but these are not quantified here as a "test set" size.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not provided in the document. The studies cited for hardware ("simulated surgeries" and "cadaver testing") and software ("verification and validation") do not detail the involvement of experts in establishing ground truth, their number, or specific qualifications. The software's function is to assist surgeons in planning, implying surgeon input in its use, but not explicitly in establishing a ground truth for a test set described in this submission.

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

This information is not provided in the document.

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

The document does not mention any MRMC comparative effectiveness studies. The device (SurgiCase Shoulder Planner software component and Materialise Shoulder Guide and Models hardware component) is designed to assist surgeons in planning and component positioning, but the provided text does not contain data on whether human readers/surgeons improve with or without this specific AI assistance or effect sizes.

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

The document states that the 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." It also mentions, "SurgiCase Shoulder Planner allows the surgeon to visualize, measure, reconstruct, annotate and edit pre-surgical plan data." This indicates that the software is a human-in-the-loop device, where the surgeon is actively involved in the planning process and responsible for approving the plan. Therefore, a standalone (algorithm only) performance assessment, without human input, is unlikely to be the primary method of evaluation described or required for this type of device. The document does not provide such standalone performance data.

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

The document does not explicitly state the type of ground truth used for any specific test set related to this submission. For the hardware (guides and models), the "accuracy and performance" implies a comparison to a known standard or ideal, perhaps derived from anatomical models or surgical goals. For the software, "verification against defined requirements, and validation against user needs" suggests that the ground truth for V&V would be the successful adherence to these requirements and user expectations, which could involve internal expert review or adherence to pre-defined medical/engineering specifications. However, specific types of ground truth like pathology or long-term outcomes data are not mentioned.

8. The sample size for the training set

This information is not provided in the document. As the submission is for a special 510(k) updating compatibility, it's possible that the core algorithms were developed and trained previously, and details of their original training are not part of this specific submission. The focus here is on the impact of the changes to the device.

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

This information is not provided in the document. Similar to the training set size, the specifics of how the ground truth was established for the original training of any underlying algorithms are not included in this special 510(k).

Ask a specific question about this device

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', Enovis' (DJO), 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 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.

The provided text describes the regulatory clearance for the Materialise Shoulder System™ and mentions performance data, but it does not contain a detailed study proving the device meets specific acceptance criteria in the format requested.

The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than presenting a comprehensive standalone study with detailed effectiveness metrics.

Here's an analysis of the information that can be extracted, and what is missing based on your request:

1. Table of Acceptance Criteria and Reported Device Performance:

• Acceptance Criteria: Not explicitly stated in a quantitative manner for the performance of the AI component (SurgiCase Shoulder Planner) or the hardware (Materialise Shoulder Guide and Models) beyond ensuring it performs "as intended" and maintains accuracy.
• Reported Device Performance: The document states that "Testing verified that the accuracy and performance of the system is adequate to perform as intended." However, no specific performance metrics (e.g., accuracy, precision, sensitivity, specificity, or error margins) are provided for either the software for planning or the hardware for guiding.

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

• Test Set Sample Size: Not specified for the software component (SurgiCase Shoulder Planner).
• Data Provenance: Not specified for any software testing.
• For Hardware: It refers to "simulated surgeries using rapid prototyped bone models and previous cadaver testing." No specific number of models or cadavers is provided, nor is the country of origin 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:

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

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

• Not specified.

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 is mentioned. The document focuses on the planning and guidance aspect for surgeons, but not on a comparative study of human readers (surgeons) with and without AI assistance for diagnosis or planning accuracy.

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

• A standalone performance evaluation of the software's planning functionality is implied through the statement "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, no specific metrics or study details are provided. The software is described as a "planning tool used to generate a pre-surgical plan" and for "assisting the surgeon in positioning shoulder components," suggesting a human-in-the-loop workflow.

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

• Ground Truth Type: Not explicitly stated for the software. For the hardware, the use of "rapid prototyped bone models and previous cadaver testing" implies a physical ground truth for accuracy validation.

8. The sample size for the training set:

• The document does not mention a training set sample size, which is typical for AI/ML models. This suggests the software functionality described (planning, visualization, measurement) might not be based on deep learning/machine learning that requires explicit training data in the same way as, for example, an image classification algorithm. It seems to be a rules-based or physics-based planning software.

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

• As no training set is mentioned, the method for establishing its ground truth is also not provided.

In summary:

The provided text from the FDA 510(k) summary states that non-clinical performance testing indicates the device is as safe and effective as its predicate. It mentions software verification and validation and previous hardware testing (biocompatibility, sterility, cleaning, debris, dimensional stability, packaging, simulated surgeries, cadaver testing). However, it lacks the specific quantitative acceptance criteria and detailed study results (such as sample sizes, expert qualifications, clear performance metrics, ground truth establishment for software, and formal comparative effectiveness study results) that are typically expected when describing a study proving specific acceptance criteria in detail. This information is usually found in separate, more detailed technical documentation submitted to the FDA, not in the public 510(k) summary.

Ask a specific question about this device

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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The SMR Shoulder System is intended for partial or total, primary or revision shoulder joint replacement.

The SMR Anatomic Shoulder System is indicated for partial or total, primary or revision shoulder joint replacement in patients suffering from disability due to:

• non-inflammatory degenerative joint disease including osteoarthritis and avascular necrosis;
• . inflammatory degenerative joint disease such as rheumatoid arthritis;
• treatment of acute fractures of the humeral head that cannot be treated with other fracture fixation methods;
• revision of a failed primary implant; in case of SMR Short Stems only if sufficient bone stock remains); .
• cuff tear arthropathy (CTA Heads only); .
• glenoid arthrosis without excessive glenoid bone loss: A1, A2 and B1 according to Walch classification (SMR TT Hybrid Glenoid only). .

The SMR Reverse Shoulder System is indicated for primary, fracture or revision total shoulder replacement in a grossly rotator coff deficient joint with severe arthropathy (disabled shoulder). The patients joint must be anatomically suited to receive the selected implants and a functional deltoid muscle is necessary to use the device.

The SMR TT Hybrid Glenoid Reverse Baseplate must not be used in cases of excessive glenoid bone loss and/or when bone graft is needed.

The Modular SMR Shoulder System allows the assembly of components in various humeral and glenoid constructs are intended for cemented and uncemented use as specified in the following table.

In the Anatomic shoulder the humeral consists of the humeral stem, the humeral body, the adaptor taper and the humeral head. In the Reverse shoulder the humeral consists of the humeral stem, the reverse humeral body and the reverse liner. On the humeral side the fixation of the humeral stem determines if the construct is cemented or uncemented.

The Anatomic glenoid construct consists of an all polyethylene glenoid with metal peg or a metal back assembled with a liner; the Reverse glenoid consists of a metal back/connector/glenosphere construct or of a peg/baseplate/glenosphere construct. On the glenoid side, the fixation of the all polyethylene glenoid with metal peg or the metal back determines if the construct is cemented or uncemented.

The SMR 140° Reverse Humeral Bodies (SMR 140° Reverse Humeral Body, SMR 140° Short Reverse Humeral Body, SMR 140° Finned Reverse Humeral Body) are manufactured from Ti6Al4V alloy (ASTM F1472 - ISO 5832-3); they are for tapercoupling with previously cleared Humeral extension (K113523), SMR CTA Head Adaptor for Reverse Humeral Body (K131112), Reverse Liners (K110598, K142139) and Humeral stems (K100858, K101263, K111212, K191963).

This document is a 510(k) premarket notification for the SMR 140° Reverse Humeral Body, a component of a shoulder replacement system. As such, it does not contain information about acceptance criteria or a study proving that an AI device meets acceptance criteria.

The document describes a medical device (SMR 140° Reverse Humeral Body for shoulder replacement) and its substantial equivalence to predicate devices, supported by non-clinical mechanical testing. It explicitly states that clinical testing was not necessary to demonstrate substantial equivalence.

Therefore, the requested information points regarding AI acceptance criteria and studies (sample size, data provenance, expert ground truth, adjudication, MRMC studies, standalone performance, ground truth type for training/test sets, and training sample size) are not applicable to this document.

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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.

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 glenoid 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 Glenoid Positioning Guide and Models.

Materialise Glenoid Positioning System is a patient-specific medical device that is 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 a patientspecific guide and models to transfer the 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.
• a hardware component, branded as the Materialise Glenoid Positioning System™ Guide and Models, which is 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 guide and models will be manufactured if the surgeon requests patient-specific guides to transfer the plan to surgery. The Materialise Glenoid Positioning System 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 provided document (K190286) is a 510(k) Premarket Notification for the Materialise Glenoid Positioning System. This document describes the device, its intended use, and claims substantial equivalence to a predicate device (K172054). However, it does not contain the detailed acceptance criteria and the study results proving the device meets these criteria in the format requested.

The "Performance Data" section (page 5-6) explicitly states:
"Previous testing for biocompatibility, cleaning, 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. The stability of the device placement, surgical technique, intended use and functional elements of the same as that of the predicate Materialise Glenoid Positioning System K172054 and previously cleared devices K170893, K1536559, and therefore previous cadaver testing on previously cleared devices K153602 and K131559 is considered applicable to the subject device."

This statement indicates that performance testing was conducted, and its results were deemed adequate. However, the details of those tests, including specific acceptance criteria, reported performance values, sample sizes, ground truth establishment, expert qualifications, and adjudication methods, are not present in this document. The document primarily relies on demonstrating substantial equivalence to previously cleared devices and states that "previous cadaver testing on previously cleared devices K153602 and K131559 is considered applicable to the subject device." This suggests that the detailed study results might be found in the 510(k) submissions for those predicate devices, rather than being explicitly laid out in this current submission.

Therefore, I cannot populate the table or provide specific details for most of your questions based solely on the text provided in K190286. The document focuses on regulatory justification for substantial equivalence, not a detailed scientific report of device performance trials.

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The SMR Shoulder System is intended for partial or total, primary or revision shoulder joint replacement.

The SMR Anatomic Shoulder System is indicated for partial or total, primary or revision shoulder joint replacement in patients suffering from disability due to:

• non-inflammatory degenerative joint disease including osteoarthritis and avascular necrosis;
• inflammatory degenerative joint disease such as rheumatoid arthritis;
• treatment of acute fractures of the humeral head that cannot be treated with other fracture fixation methods;
• revision of a failed primary implant;
• cuff tear arthropathy (CTA Heads only);
• glenoid arthrosis without excessive glenoid bone loss: A1, A2 and B1 according to Walch classification (SMR Hybrid Glenoid only).

The SMR Reverse Shoulder System is indicated for primary, fracture or revision total shoulder replacement in a grossly rotator cuff deficient joint with severe arthropathy (disabled shoulder). The patient's joint must be anatomically and structurally suited to receive the selected implants and a functional deltoid muscle is necessary to use the device. The Hybrid Glenoid Reverse Baseplate must not be used in cases of excessive glenoid bone loss and/or when bone graft is needed.

The Modular SMR Shoulder System allows the assembly of components in various humeral and glenoid constructs. The constructs are intended for cemented and uncemented use as specified in the following table.

The SMR Connectors are used to couple the glenosphere to the metal-backed glenoid. Connectors are made from Ti6Al4V alloy (ASTM F1472 - ISO 5832-3) and are characterized by a double male taper. To increase the solidity of the system, a screw is used to link the glenosphere to the glenoid component. No.5 additional sizes (Lateralized connectors) are available in both Small-STD and Small-R configuration to allow lateralization of Center of Rotation.

The provided document is a 510(k) premarket notification for a medical device called "SMR Lateralized Connectors with screws". This type of submission focuses on demonstrating substantial equivalence to a predicate device already on the market, rather than proving efficacy or safety through extensive clinical trials. Therefore, much of the information requested about acceptance criteria and detailed study designs (especially relating to AI or expert adjudication) is not applicable or present in this document.

However, I can extract the relevant information regarding the non-clinical testing performed to establish substantial equivalence.

Here's a breakdown of the available information:

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

The document does not provide a specific table of numerical acceptance criteria or reported device performance in the format typically seen for novel device performance claims. Instead, it states that mechanical tests "demonstrated device performances fulfill the intended use and are substantially equivalent to the predicate devices." This implies that the performance met predefined internal criteria for equivalence, but these criteria are not explicitly detailed.

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

The document mentions "Mechanical testing was performed on worst case components or constructs." It does not specify the exact sample size for these mechanical tests. The data provenance is internal to Limacorporate S.p.A. and the tests are non-clinical (experimental/lab-based), not derived from patient data.

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

This is not applicable as the study described is non-clinical mechanical testing, not a study involving human interpretation or ground truth establishment by experts for diagnostic or prognostic purposes.

4. Adjudication method for the test set

This is not applicable for the same reason as point 3.

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, an MRMC study was not done. The device is a mechanical implant, not an AI-powered diagnostic or assistive tool for human readers.

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

No, a standalone AI algorithm performance study was not done. The device is a mechanical implant.

7. The type of ground truth used

For the non-clinical mechanical testing, the "ground truth" would be the engineering specifications and performance benchmarks derived from the predicate devices and relevant ASTM/ISO standards (e.g., ASTM F2028-18). The device's performance was compared against these established standards and predicate device characteristics to demonstrate substantial equivalence.

8. The sample size for the training set

This is not applicable as there is no AI algorithm being trained.

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

This is not applicable as there is no AI algorithm being trained.

Summary of Relevant Information from the Document:

While the document doesn't fit the typical structure for AI/diagnostic device evaluation, it does provide clear information about the type of acceptance criteria and study performed for this medical device:

• Acceptance Criteria (Implied): Substantial equivalence to predicate devices, fulfilling intended use, and meeting relevant mechanical testing standards (e.g., ASTM F2028-18 for dynamic evaluation of glenoid loosening and dissociation, and standards for fatigue-fretting behavior and endurance stability of taper connections).
• Study Type: Non-clinical mechanical testing.
• Specific Tests Mentioned:
  • Dynamic evaluation of glenoid loosening and dissociation per ASTM F2028-18.
  • Fatigue-fretting behavior.
  • Endurance stability of the taper connection, followed by evaluation for corrosion.
• Sample Size for Testing: "worst case components or constructs" (specific number not provided).
• Data Provenance: Laboratory testing (non-clinical).
• Ground Truth for Testing: Engineering specifications, performance benchmarks of predicate devices, and relevant international standards (ASTM, ISO).
• Clinical Testing: "Clinical testing was not necessary to demonstrate substantial equivalence of the new sizes of SMR Connectors to the predicate devices."

The document primarily focuses on demonstrating that the new SMR Lateralized Connectors with screws are safe and effective because their design, materials, and mechanical performance are equivalent to predicate devices already cleared for market, negating the need for novel clinical data.

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The AltiVate Anatomic™ to Reverse Conversion Module is indicated for revision surgeries in patients with a grossly rotator cuff deficient shoulder joint with severe arthropathy or a previously failed joint replacement with a grossly rotator cuff deficient shoulder joint. The patient's joint must be anatomically and structurally suited to receive the selected implant(s), and a functional deltoid muscle is necessary to use the device. The conversion module is only indicated for use with a well fixed AltiVate Anatomic Humeral Stem.
Humeral components with a porous coated surface are indicated for either cemented or uncemented applications. The glenoid baseplate is intended for cementless application with the addition of screws for fixation.

In cases of revision surgeries to a well fixed AltiVate Humeral Stem, a reverse conversion module can be mated with the AltiVate stem to convert to a reverse shoulder application.
The currently cleared AltiVate™ Anatomic humeral stem will a conversion module to provide an option to revise a failed traditional total shoulder arthroplasty to a reverse shoulder arthroplasty without the need to remove a well fixed humeral stem.

The provided text describes a 510(k) premarket notification for the "AltiVate Anatomic to Reverse Conversion Module," a medical device. The document states that clinical testing was not required or performed for this submission. Therefore, it does not contain information regarding acceptance criteria, device performance from clinical studies, sample sizes, ground truth establishment, or multi-reader multi-case studies.

The document primarily focuses on non-clinical testing and substantial equivalence to predicate devices.

Here's a breakdown of the available information based on the provided input and the limitations due to the absence of clinical testing:

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

• No clinical acceptance criteria or reported clinical device performance are provided as clinical testing was not performed.
• Non-clinical testing: FEA analysis for stress analysis was conducted, determining the subject device is similar to the evaluated predicate device. Bacterial endotoxin testing was also conducted and met expected limits. However, specific numerical acceptance criteria or performance metrics for these non-clinical tests are not detailed in the provided text.

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

• Not applicable as no clinical test set was used.

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

• Not applicable as no clinical test set was used.

4. Adjudication method for the test set:

• Not applicable as no clinical test set was used.

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 was done. This device is a medical implant, not an AI diagnostic tool.

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

• Not applicable. This device is a medical implant, not an AI algorithm.

7. The type of ground truth used:

• For the non-clinical tests, the "ground truth" would be engineering specifications and established standards for mechanical performance and sterility (endotoxin levels). The document states the FEA analysis found the device "similar to the evaluated predicate device" and endotoxin testing "met the expected endotoxin limits."

8. The sample size for the training set:

• Not applicable as this is not an AI/algorithmic device and no clinical "training set" was used.

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

• Not applicable as this is not an AI/algorithmic device and no clinical "training set" was used.

In summary, the FDA cleared this device based on non-clinical testing (FEA analysis, endotoxin assessment) and demonstration of substantial equivalence to predicate devices, without requiring or performing clinical trials.

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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 AltiVate Anatomic Shoulder (K162024), Encore Shoulder System (K051075), Turon™ to RSP Conversion Shell (K111629), Turon™ Shoulder System (K080402) and Reverse® Shoulder prosthesis (K092873) and their respective components, 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.

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.

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

The provided text describes the 510(k) premarket notification for the Materialise Glenoid Positioning System. It claims substantial equivalence to a predicate device (K153602) and mentions performance data from previous testing. However, it does not contain the detailed acceptance criteria or the study that directly proves the device meets specific acceptance criteria in terms of quantitative performance metrics.

The text states: "Previous testing for biocompatibility, cleaning, debris, dimensional stability and packaging are applicable to the subject device and demonstrate squivalence with the predicate device. Testing verified that the accuracy and performance of the system is adequate to perform as intended. The stability of the device placement, surgical technique, intended use and functional elements of the same as that of the predicate Materialise Glenoid Positioning System (K153602), and therefore previous cadaver testing on predicate device K153602 and previously cleared device K131559 (which is the predicate for K153602) is considered applicable to the subject device."

This indicates that some performance evaluation was done for the predicate devices, and that information is being leveraged for the current submission. However, the specific acceptance criteria (e.g., maximum allowable deviation, accuracy thresholds) and the results of a study against those criteria for the current device are not presented in this document.

Therefore, I cannot provide a complete answer to your request based solely on the provided text. I will, however, outline what information is available and explicitly state what is missing.

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

This information is not explicitly provided in the document. The text states: "Testing verified that the accuracy and performance of the system is adequate to perform as intended." This is a qualitative statement, not a quantitative table of acceptance criteria and performance against those criteria.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document mentions "previous cadaver testing on predicate device K153602 and previously cleared device K131559".

• Sample size: Not specified.
• Data provenance: Cadaver testing. Country of origin not specified.
• Retrospective/Prospective: Not specified, but cadaver testing is typically prospective for the purpose of the study.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This information is not provided in the document.

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

This information is not provided in the document.

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

• MRMC study: Not mentioned. The device is a surgical instrument/guide, not typically an AI-driven image interpretation system that would involve "human readers" in the sense of diagnostic interpretation. It assists surgeons in positioning glenoid components based on preoperative planning.
• Effect size: Not applicable given the nature of the device and the lack of an MRMC study.

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

The device is a "patient specific guide that is based on a pre-surgical plan" and a "software component, branded as SurgiCase Planner. This software is a planning tool used to generate a pre-surgical plan for a specific patient." The "Materialise Glenoid Positioning System guides are patient specific templates which transfer the pre-operatively determined pin positioning to the patient intraoperatively, assisting the surgeon."

This indicates a human-in-the-loop process where a qualified surgeon inspects, fine-tunes, and approves the pre-surgical plan generated by the software. Therefore, a purely standalone algorithm-only performance as an output without human involvement is not the intended use model described. However, the accuracy of the output of the software (the surgical plan and subsequent guide design) would have been validated, which is essentially a standalone performance evaluation of the software component's mathematical and geometrical accuracy. The details of this validation are not in the document.

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

Given the "cadaver testing" and the nature of the device (positioning guide), the ground truth for measuring accuracy would likely be physical measurements against an intended planned position or anatomical landmark, potentially established by expert surgeons or precise measurement tools. However, the specific method of establishing this ground truth is not detailed in the document.

8. The sample size for the training set

The document describes premarket notification for a medical device that includes "a software component" for planning and "a hardware component" (patient-specific guide). It mentions "previous cadaver testing" which sounds more like a validation/testing stage rather than training for a machine learning model. If the software component involves machine learning or AI, the training set details are not provided. The text focuses on the device being "substantially equivalent" to a predicate, implying that much of the foundational validation comes from the predicate's testing.

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

As described in point 8, a "training set" in the context of machine learning is not explicitly mentioned, and thus how its ground truth was established is not provided. If the software uses algorithms that are not machine learning-based, then the concept of a training set as typically defined for AI may not apply. The emphasis is on the software generating a "pre-surgical plan" and its accuracy.

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