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510(k) Data Aggregation
(203 days)
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 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. The constructs are intended for cemented and uncemented use as specified in the following table.
In the Reverse shoulder the humeral construct 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 Reverse glenoid consists of a metal back/connector/glenosphere construct or of a peg/baseplate/glenosphere construct.
The subject SMR Reverse HP Shoulder System is a line extension to the predicate SMR Shoulder System (K223876) consisting of Reverse HP crosslinked UHMWPE glenospheres and Co-Cr-Mo liners. The components are available in one diameter with various options to accommodate varying patient anatomy.
Based on the provided FDA 510(k) clearance letter for the SMR Reverse HP Shoulder System, here's an analysis of the acceptance criteria and the study proving the device meets them:
It's important to note that this document is a 510(k) clearance, which is primarily a declaration of substantial equivalence to a previously cleared predicate device, rather than a full, de novo approval that would detail extensive clinical performance studies with specific statistical acceptance criteria for novel claims. The focus here is on demonstrating that the new device (SMR Reverse HP Shoulder System) is as safe and effective as existing legally marketed devices, rather than proving a new level of clinical efficacy.
Therefore, many of the specific details you've asked for, such as precise quantitative acceptance criteria for clinical performance (e.g., accuracy, sensitivity, specificity, or effect size for AI assistance), adjudication methods, or detailed expert qualifications for ground truth establishment, are typically not found in a 510(k) summary, as they are not generally required for demonstrating substantial equivalence for an orthopedic implant.
The "acceptance criteria" for a 510(k) device primarily revolve around demonstrating that the new device performs as intended and is as safe and effective as its predicate. This is primarily done through non-clinical (mechanical) testing and reference to the predicate's established clinical history.
Acceptance Criteria and Reported Device Performance
The acceptance criteria for the SMR Reverse HP Shoulder System are implicit in the demonstration of substantial equivalence to its predicate devices. The performance testing aims to show that the new components function equivalently to, or better than, the predicate components within the intended use.
1. Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria Category | Specific Test/Area | Acceptance Standard (Implicit from Substantial Equivalence and Standards) | Reported Device Performance (Summary from Document) |
---|---|---|---|
Mechanical Performance | Fatigue Test | Device must withstand anticipated physiological loads and cycles without failure or significant degradation over its intended lifespan, meeting relevant ISO/ASTM standards. | "Mechanical tests demonstrated that device performance fulfilled the intended use and that the devices are substantially equivalent to the predicate devices." |
Push-Out Test | Components must maintain adequate fixation strength against physiological forces. | "Mechanical tests demonstrated that device performance fulfilled the intended use and that the devices are substantially equivalent to the predicate devices." | |
Wear Test | Wear rates of bearing surfaces (UHMWPE, CoCrMo) must be within acceptable limits as defined by relevant ISO/ASTM standards and comparable to predicate devices. | "Mechanical tests demonstrated that device performance fulfilled the intended use and that the devices are substantially equivalent to the predicate devices." | |
Creep and Deformation Test | Materials must exhibit acceptable levels of creep and deformation under sustained loads. | "Mechanical tests demonstrated that device performance fulfilled the intended use and that the devices are substantially equivalent to the predicate devices." | |
Micromotion Test | Interface micromotion between implanted components and bone must be within limits conducive to bone ingrowth and long-term stability. | "Mechanical tests demonstrated that device performance fulfilled the intended use and that the devices are substantially equivalent to the predicate devices." | |
Clean and Abrasive Wear Test | Evaluation of wear under specific conditions, ensuring material integrity. | "Mechanical tests demonstrated that device performance fulfilled the intended use and that the devices are substantially equivalent to the predicate devices." | |
Particle Analysis | Assessment of wear debris generated by the bearing surfaces to evaluate potential biological reactivity and long-term effects. | "Mechanical tests demonstrated that device performance fulfilled the intended use and that the devices are substantially equivalent to the predicate devices." | |
Range of Motion | The system should allow satisfactory physiological range of motion. | "Mechanical tests demonstrated that device performance fulfilled the intended use and that the devices are substantially equivalent to the predicate devices." | |
Biocompatibility | Biological Safety Evaluation | Biocompatibility (cytotoxicity, sensitization, irritation, etc.) must be established according to ISO 10993-1. | "A biological safety evaluation was conducted per FDA Guidance and ISO 10993-1." (Implicitly met acceptance criteria) |
Material Compliance | Material Standards (e.g., Ti6Al4V, CoCrMo, UHMWPE) | All materials must conform to specified international standards (ISO, ASTM) for medical implants. | "Ti6Al4V (ISO 5832-3 - ASTM F1472) – Ti6Al4V 3D printed (to meet the mechanical and chemical requirements of ISO 5832-3) - CoCrMo (ISO 5832-12 - ASTM F1537) – UHMWPE (ISO 5834-2 - ASTM F648) - LimaVit™ (Vitamin E highly crosslinked UHMWPE) (ISO 5834-2 - ASTM F648 - ASTM F2695 – ASTM F2565) - PoroTi Titanium Coating (ASTM F1580) - Ta (ISO13782 - ASTM F560)" (Confirmed compliance) |
Sterility, Packaging, Shelf Life, Reprocessing | Validation against established standards. | Must be adequately validated. | "Previously completed sterility, packaging, shelf life and reprocessing validations from the predicate system were leveraged for the subject devices." (Implicitly met acceptance criteria by leveraging predicate data) |
Clinical Performance (Substantial Equivalence) | Equivalence in safety and effectiveness to predicate device, as demonstrated through post-market data. | Clinical outcomes for the subject device (or its components) must be consistent with the known performance and safety profile of the predicate device. | "Post-market clinical data from outside the United States on the subject and predicate device were provided in this submission, including patient-level radiographs, outcome measures, and safety data. The data supported a determination of substantial equivalence." (Implicitly met acceptance criteria) |
Study Proving Device Meets Acceptance Criteria
The study described is primarily a non-clinical performance study combined with a post-market clinical data review for demonstrating substantial equivalence.
2. Sample Size Used for the Test Set and Data Provenance:
- Test Set (Non-clinical): The document states "Mechanical testing was performed on worst case components or constructs." This implies a limited sample size based on engineering principles (e.g., statistical power calculations for specific test types or industry standards for mechanical testing). Specific numbers are not provided, as is typical for 510(k) engineering tests.
- Data Provenance (Clinical): "Post-market clinical data from outside the United States on the subject and predicate device were provided in this submission." This indicates a retrospective collection of data from clinical use, not a prospective, controlled clinical trial specifically designed for this submission. The exact country of origin within "outside the United States" is not specified, nor is the specific sample size, though it is described as "patient-level radiographs, outcome measures, and safety data."
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:
- Non-clinical: Ground truth is established by engineering standards and specifications (e.g., ISO, ASTM). The "experts" would be the engineers and technicians performing and assessing the mechanical tests against these predefined standards. Their qualifications are implicit in their ability to conduct and interpret these tests, but not explicitly stated in terms terms like "mechanical engineer with 10 years experience."
- Clinical: For the post-market clinical data, the "ground truth" refers to patient outcomes and safety information. This data is observed in real-world clinical practice, typically by treating physicians. There is no mention of a separate panel of experts specifically adjudicating this post-market data for "ground truth" purposes in the context described.
4. Adjudication Method for the Test Set:
- Non-clinical: The "adjudication" is against the pre-defined engineering standards and performance specifications for each mechanical test. This is typically a pass/fail determination based on quantitative measurements. No human-expert consensus "adjudication method" (like 2+1, 3+1) is described or typically applicable to component mechanical testing.
- Clinical: For the post-market clinical data, there's no mention of an adjudication method by external experts. The data would have been collected as part of routine clinical care or existing registries, and then compiled and analyzed by the manufacturer for the submission.
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 an orthopedic implant, not a diagnostic imaging AI algorithm. Therefore, MRMC studies and the concept of "human readers improving with AI assistance" are not applicable to the SMR Reverse HP Shoulder System.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Not applicable. As stated above, this is an orthopedic implant, not an AI algorithm.
7. The Type of Ground Truth Used:
- Non-clinical: The ground truth for mechanical testing is based on established engineering principles and international standards (ISO, ASTM) for orthopedic implants. These standards define the expected performance and limits for various mechanical properties.
- Clinical: The "ground truth" for the clinical data is real-world patient outcomes, safety events, and radiographic assessments collected during post-market use of the predicate device and the subject device (where applicable) outside the US. These are actual clinical observations rather than expert consensus on a test set.
8. The Sample Size for the Training Set:
- Not applicable for a 510(k) orthopedic implant. Training sets are relevant for machine learning algorithms. The design and validation of this mechanical implant do not involve "training sets" in this context. The "training" for the device would be the iterative design and development process, informed by biomechanical principles and material science, leading up to the final testing.
9. How the Ground Truth for the Training Set Was Established:
- Not applicable. See point 8.
In summary, the FDA 510(k) clearance for the SMR Reverse HP Shoulder System relies heavily on demonstrating engineering equivalence and material compliance through non-clinical testing, supplemented by a review of existing post-market clinical data for the predicate and related devices. It is a process focused on showing that the new device is "substantially equivalent" to an already cleared device, rather than a de novo approval process that would require extensive novel clinical efficacy studies with sophisticated statistical methodologies often seen for new drug or AI algorithm approvals.
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(29 days)
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."
Acceptance Criteria (Implied) | Reported Device Performance |
---|---|
Software: | |
Functions as a pre-surgical planner for shoulder joint arthroplasty (visualization, measurement, reconstruction, annotation, editing of plan data). | "The planning functionality, including visualization, measurement, reconstruction, annotation, and editing of pre-surgical plan data, is the same in the subject and predicate device." |
"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.'" | |
"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)." | |
Automated segmentation via artificial intelligence algorithm is locked/static and accurate for 3D bone construct creation. | "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." |
(No specific numerical accuracy or precision metrics are reported for segmentation). | |
Expanded compatibility with new Enovis and Lima implant systems does not introduce new safety/effectiveness concerns. | "The non-clinical performance data has demonstrated that the subject software technological differences between the subject and predicate device do not raise any different questions of safety and effectiveness." |
Hardware (Guides & Biomodels): | |
Assists in intraoperative positioning of shoulder implant components by referencing anatomic landmarks. | "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 Precision AI Surgical Planning System (K233992) and therefore previous cadaver testing and composite bone model testing on the previously cleared device are considered applicable to the subject device." | |
Expanded compatibility with new Enovis and Lima implant systems does not introduce new safety/effectiveness concerns. | "The main difference between the subject device hardware and the predicate device is the extension of compatibility of the Precision AI Guides and Models with additional Enovis' and Lima's implant systems and their compatible components... [demonstrated not to raise new safety/effectiveness questions based on previous testing for predicate]." |
Biocompatibility, sterility, cleaning, debris, dimensional stability, and packaging are adequate. | "Previous testing for biocompatibility, sterility, cleaning, debris, dimensional stability and packaging are applicable to the subject device." (Implies these aspects were re-verified or deemed unchanged/covered by predicate testing). |
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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(30 days)
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
(27 days)
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).
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(34 days)
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.
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(98 days)
In Anatomic:
The stem and head may be used by themselves, as a hemiathroplasty, if the natural glenoid provides a sufficient bearing surface, or in conjunction with the glenoid, as a total replacement.
The AETOS Shoulder System is to be used only in patients with an intact or reconstructable rotator cuff, where it is intended to provide increased mobility and to relieve pain. The AETOS Shoulder System is indicated for use as a replacement of shoulder joints disabled by:
- Rheumatoid arthritis
- Non-inflammatory degenerative joint disease
- Correction of functional deformity
- Fractures of the humeral head
- Traumatic arthritis
- Revision of other devices if sufficient bone stock remains
The coated humeral component is intended for uncement is intended for cement is intended for cemented use only.
In Reverse:
The AETOS Shoulder System is indicated for use as a replacement of shoulder joints for patients with a functional deltoid muscle and with massive and non-repairable rotator cuff-tear with pain disabled by:
- Rheumatoid arthritis
- Non-inflammatory degenerative joint disease
- Correction of functional deformity
- Fractures of the humeral head
- Traumatic arthritis
- Revision of devices if sufficient bone stock remains
The humeral liner component is indicated for use in the AETOS Shoulder System as a primary reverse total shoulder replacement and for use when converting an anatomic AETOS Shoulder System into a reverse shoulder construct. This facilitates the conversion without the removal of the humeral stem during revision surgery for patients with a functional deltoid muscle. The component is permitted to be used in the conversion from anatomic to reverse if the humeral stem is well fixed, the patient has a functional deltoid muscle; the arthroplasty is associated with a massive and non-repairable rotator cuff tear.
The coated humeral stem is indicated for uncemented use. The coated glenoid baseplate is intended for cementless application with the addition of screws for fixation.
Note: All implant components are single use.
The AETOS Shoulder System consists of:
In an anatomic configuration: A humeral stem (Titanium) with a plasma spray coating (Titanium), a compatible humeral head (CoCr) with a compatible glenoid (UHMWPE). The AETOS Shoulder System stem and head may be used by themselves for hemiarthroplasty.
In a reverse configuration: A humeral stem (Titanium) with a plasma spray coating (Titanium), a compatible liner (UHMWPE), glenoid baseplate (Titanium with Titanium plasma spray), glenosphere (CoCr with Titanium retaining component), peripheral screws (Titanium), center screw (Titanium), optional humeral spacer (Titanium), and optional post extension (Titanium with Titanium plasma spray).
This document is a 510(k) Premarket Notification from the FDA regarding the AETOS Shoulder System. It is primarily concerned with establishing substantial equivalence to previously cleared devices based on non-clinical performance data and technological similarities/differences.
Therefore, a study proving the device meets acceptance criteria related to AI/algorithm performance (as described in your prompt, e.g., sensitivity, specificity, human reader improvement) was not performed nor is it relevant to this specific FDA submission.
The document explicitly states: "Clinical performance data were not necessary to demonstrate substantial equivalence of the subject device."
Instead, the acceptance criteria for this device are established through engineering and mechanical testing, ensuring the physical device components meet design specifications and performance standards comparable to legally marketed predicate devices.
Here's how to interpret the available information in the context of your request:
1. A table of acceptance criteria and the reported device performance:
The acceptance criteria are implied by the non-clinical performance data testing listed, which assess the mechanical integrity and function of the shoulder system components. The "reported device performance" is that the device met these standards, demonstrating substantial equivalence to the predicate devices. This type of submission relies on the device performing as well as the predicate in relevant mechanical and material property tests to prove safety and effectiveness.
Acceptance Criteria (Implied) | Reported Device Performance |
---|---|
Construct fatigue | Met standards |
Dynamic glenoid loosening / dissociation per ASTM F2028 | Met standards |
Range of motion evaluation | Met standards |
Scapular notching evaluation | Met standards |
Construct disassembly evaluation | Met standards |
Total humeral offset evaluation | Met standards |
2. Sample size used for the test set and the data provenance:
- Sample Size: Not explicitly stated in terms of patient data. The "test set" here refers to the physical components of the shoulder system subjected to mechanical testing. The sample size for these engineering tests would typically be a specific number of manufactured components.
- Data Provenance: This is not patient- or human-read data. It's likely from internal laboratory testing conducted by the manufacturer (Smith & Nephew, Inc. at Cordova, Tennessee). It's not retrospective or prospective clinical 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. The "ground truth" for mechanical performance of an orthopedic implant is established through standardized engineering tests (e.g., ASTM standards) and material science principles, not expert consensus from medical professionals. The "experts" would be engineers, material scientists, and quality assurance personnel.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:
Not applicable, as this refers to human expert review of clinical data, which was not the basis of this submission. The "adjudication" is met by demonstrating compliance with established engineering and material standards through testing.
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 applicable. This device is a physical orthopedic implant, not an AI/software as a medical device (SaMD) that assists human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
Not applicable. This is not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
The "ground truth" for this device's acceptance is established through compliance with existing engineering standards and successful completion of specified mechanical and material property tests. These tests are designed to simulate physiological loads and conditions to ensure the device's durability and performance.
8. The sample size for the training set:
Not applicable. This device does not involve a training set for an algorithm.
9. How the ground truth for the training set was established:
Not applicable.
In summary: The provided document is a 510(k) clearance for a physical medical device (shoulder system). The "acceptance criteria" and "study" details you requested are tailored to AI/software products. For this device, acceptance is based on non-clinical (engineering) performance data demonstrating substantial equivalence to older, already cleared devices, rather than clinical trials or AI performance metrics.
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(181 days)
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 .
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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(161 days)
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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(147 days)
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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(84 days)
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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