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The MedCAD® AccuShape® Titanium Patient-Specific Cranial Implant is designed individually for each patient and intended to correct defects / replace bony voids in the cranial skeleton.

The MedCAD® AccuShape® Titanium Patient-Specific Cranial Implant is a preformed non-alterable cranioplasty plate that cannot be altered or reshaped at the time of surgery and is designed to be implanted in a patient to repair a skull defect.
The subject device is composed of commercially pure (CP) Grade 2 titanium per ASTM F67. The manufacturing process is subtractive manufacturing (CNC milled) from models created and developed from patient specific CT Scan Data. The software used in this process is identical to the software used in the predicate device (K110684). The device is designed to have, as requested by the physician, drainage holes over the defect void area, fixation holes over an onlay area, and retractions and other features that fall within the approved design envelope. All designs must be approved by the physician prior to manufacture.

The provided document describes the MedCAD AccuShape Titanium Patient-Specific Cranial Implant and its substantial equivalence to a predicate device (MedCAD AccuShape PEEK Patient Specific Cranial Implant) based on non-clinical performance testing.

It is important to note that this document does not describe an AI/ML-driven device or study parameters typical for such devices (e.g., ground truth establishment for a training set, human reader studies, or expert consensus on clinical data). The device described is a physical cranial implant, and the study referenced in the document is a series of non-clinical performance tests designed to assess the physical and mechanical properties of the implant, not its diagnostic or predictive accuracy in an AI context.

Therefore, many of the requested bullet points, particularly those pertaining to AI/ML device evaluation (like sample size for test/training sets of data, number of experts for ground truth, MRMC studies, standalone performance), are not applicable to the information provided in this document.

However, I can extract information relevant to the device's acceptance criteria and the non-clinical performance testing performed for this physical device.

Here's an interpretation of the "acceptance criteria" and "study" as presented for a physical medical device, rather than an AI/ML diagnostic:

Device: MedCAD AccuShape Titanium Patient-Specific Cranial Implant (K220357)

Purpose of the "Study" (Non-Clinical Performance Testing): To demonstrate the substantial equivalence of the MedCAD AccuShape Titanium Patient-Specific Cranial Implant to its predicate device (MedCAD AccuShape PEEK Patient Specific Cranial Implant, K110684) by evaluating its physical and mechanical properties.

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

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

• Sample Size for Test Set:
  • Evaluation of Fit Testing: "3 large defect predicate historical cases (K110684)" were used to generate "worst case CT data". The number of manufactured implants tested is implied to be at least 3 (one for each case). The phrase "All samples" in the result suggests a specific number of manufactured implants were produced and tested, but the exact number isn't quantified beyond the 3 cases used for input data.
  • Comparative Strength: "Identical subject and predicate devices" were used, implying at least one (and likely more for statistical significance, though not stated) of each type (titanium and PEEK) for comparative testing.
  • Screw Fixation: Not explicitly stated, but implies multiple tests to determine "at least as strong as" criteria.
  • MR Compatibility: At least one device (or representative sample) would be tested.
• Data Provenance: The "worst case CT data" for the Evaluation of Fit testing came from "3 large defect predicate historical cases (K110684)". This suggests a retrospective use of previously acquired clinical data (CT scans) from actual patients. The country of origin is not specified but is implicitly USA, given this is an FDA submission.

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

• This concept is not directly applicable in the context of this device's non-clinical testing. The "ground truth" (or reference standard) is based on engineering specifications, material properties, and established test methodologies (e.g., ASTM standards, previous FDA-cleared device performance).
• For the "Evaluation of Fit Testing," "qualified inspectors" performed the evaluation. Their qualifications (e.g., years of experience, specific certifications) are not detailed beyond "qualified".

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

• Not applicable. Adjudication methods are typically used in clinical studies involving multiple human readers interpreting medical images, where discrepancies need to be resolved. This document describes physical, non-clinical tests.

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 implant, not an AI/ML diagnostic tool, and no human reader study was performed.

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

• Not applicable. This is not an AI algorithm. The manufacturing software is mentioned (same as predicate device), but its performance in terms of design output is assessed through the physical device tests (e.g., Evaluation of Fit), not as a standalone AI model.

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

• The "ground truth" for these tests is based on:
  • Engineering Specifications/Standards: e.g., ASTM F2503-20 for MR compatibility.
  • Predicate Device Performance: For comparative strength, the performance of the legally marketed predicate device (K110684 PEEK implant) served as the benchmark.
  • Established Biomechanical Principles: For screw fixation, comparison to "axial pullout forces measured in prior testing of FDA-cleared neuro screws in an established cortical bone model" serves as the reference.
  • 3D Digital Models/Physical Prototypes: For "Evaluation of Fit," the 3D digital model of the implant and representative anatomical models served as the reference for fit.

8. The sample size for the training set

• Not applicable. This device is not an AI/ML system that requires a "training set" of data in the machine learning sense. The manufacturing process uses patient-specific CT scan data as input for design, but this is not a training set for an AI model.

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

• Not applicable, as there is no AI/ML training set in this context.

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The TruMatch CMF Titanium 3D Printed Implant is a patient specific implant and is intended for bone fixation and reconstruction, restoration of bone defects and intended to provide continuity in regions where the bone is missing and/or to augment the bone by means of an onlay device in the maxillofacial skeleton, midface and chin.

The TruMatch CMF Titanium 3D Printed Implant is a patient specific implant and is intended for bone fixation and reconstruction, restoration of bone defects and intended to provide continuity in regions where the bone is missing and/or to augment the bone by means of an onlay device in the maxillofacial skeleton, midface and chin.

The implants feature a mesh-like structure. The mesh-like structures are designed with the same elementary pattern. This pattern was designed to obtain implants with mechanical properties close to those of bone and to allow for osseointegration.

The TruMatch CMF Titanium 3D Printed Implant can be used in combination with TruMatch CMF Titanium 3D Printed Accessories (patient-specific guides), cleared as SurgiCase guides (K103136) and TruMatch CMF Titanium 3D Printed Implant System (K170272). The guides are intended to aid with implant positioning.

The TruMatch CMF Titanium 3D Printed Implant provides surgeons with a patient-specific implant solution for plastic and reconstructive surgery. The device is constructed based on the patient's CT imaging data.

The TruMatch CMF Titanium 3D Printed Implant is designed to fit the patient's anatomy and is not contoured manually by the surgeon. The TruMatch CMF Titanium 3D Printed Implant is designed and manufactured with integrated screw holes to fixate the bone using: MatrixMIDFACE (K050608), MatrixMANDIBLE (K063790, K121574), MatrixORTHOGNATHIC (K083388), MatrixNEURO screws (K123723, K042365), and Synthes Craniofacial Screw System (K050608).

The TruMatch CMF Titanium 3D Printed Implant contains the following applications:

Reconstruction applications: Orbital
Brand name: TruMatch CMF Ti 3D-Printed Implants
Material: Commercially pure titanium
Type of design: Patient Specific
Type of application: Implant thickness: 0.4-1.5mm
Patient specific associated instrument: Orbital guide

Reconstruction applications: Mandible, midface
Brand name: TruMatch CMF Ti 3D-Printed Implant
Material: Commercially pure titanium
Type of design: Patient Specific
Range of length: 10-294mm
Curvature: 0°-12°/mm length
Type of application: Range of shapes:
Midface reconstruction: Mesh-shaped, contoured to the patient's anatomy One/multi piece One/multi layered
Implant thickness: 0.8-10mm
Patient specific associated instrument: Midface guide
Mandibular reconstruction: Mesh-shaped, contoured to patient's anatomy Single/double strut Straight Curved/crescent Subcondylar Plated extensions One/multi layered Combinations of the above
Implant thickness: 1.2-10mm
Patient specific associated instrument: Mandibular guide

This is a 510(k) summary for a medical device called the "TruMatch CMF Titanium 3D Printed Implant" (K173039). The document focuses on demonstrating that this new device is substantially equivalent to existing, legally marketed predicate devices.

Let's break down the information regarding acceptance criteria and the supporting study, based on the provided text.

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a 510(k) submission, the "acceptance criteria" are primarily based on demonstrating performance equivalent to or non-inferior to predicate devices, rather than strict pre-defined numerical thresholds for a novel diagnostic accuracy claim. The performance data presented is focused on various engineering and biological tests.

• Sensitization: In compliance with ISO 10993-10 guidelines.
• Intra-cutaneous reactivity: In compliance with ISO 10993-10 guidelines.
• Systemic toxicity: Test passed and considered negative.
• Chemical characterization: As per report.
• Leachable substances: No toxicological concern remains, further biological testing not justified. |

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

The provided document describes testing for a physical implant, not an AI/ML device that would typically have a "test set" of data. Therefore, the concepts of "sample size used for the test set" and "data provenance (e.g., country of origin of the data, retrospective or prospective)" are not applicable in this context. The "test set" here refers to the physical devices (implants, packaging, materials) that were subjected to the various engineering and biological tests. The document does not specify the exact number of implants or material samples tested for each category (e.g., how many implants for mechanical testing).

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

This section is not applicable as the document describes a physical medical device (implant) and its performance through engineering and biological testing, not a diagnostic or AI/ML device requiring expert-established ground truth. The "ground truth" for these types of tests is generally defined by the standards themselves (e.g., ASTM F382, ISO 10993 series), which specify acceptable performance limits.

4. Adjudication Method for the Test Set

This is not applicable for the same reasons as points 2 and 3. Adjudication methods like 2+1 or 3+1 are used in scenarios where multiple human readers assess a case and their interpretations need to be reconciled, typically in AI/ML performance studies.

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

An MRMC comparative effectiveness study is not applicable as this document describes a physical medical implant, not an AI medical device.

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

A standalone performance study of an algorithm is not applicable as this document describes a physical medical implant, not an AI medical device.

7. The Type of Ground Truth Used

The "ground truth" for the tests performed on the TruMatch CMF Titanium 3D Printed Implant is based on:

• Established Industry Standards and Specifications: For mechanical properties (ASTM F382) and biocompatibility (ISO 10993 series), the acceptance criteria are defined by these internationally recognized standards.
• Sterility Assurance Levels (SAL): For sterilization, the ground truth is a demonstrated SAL of 10^-6, which is a standard regulatory requirement.
• Functional Compatibility: For compatibility with fixation systems, the ground truth is that the device works with the specified Synthes systems.

8. The Sample Size for the Training Set

This is not applicable as the document describes a physical medical implant, not an AI medical device that requires a "training set." The implants are patient-specific and manufactured based on individual patient CT scan data, but this is a manufacturing process, not a machine learning training process.

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

This is not applicable for the same reasons as point 8.

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PEEK Customized Cranial Implant Kit is intended to be used to replace bony voids in the cranial and the craniofacial skeleton.

The PEEK Customized Cranial Implant Kit is indicated for filling bony voids in the cranial and craniofacial skeleton in patients 12 years of age and older.

PEEK Customized Implant Kit consists of the PEEK Customized Cranial Implant or the PEEK Customized Craniofacial Implant, the Host Bone Model, and the Design Proposal.

PEEK Customized Cranial Implant: The PEEK Customized Cranial Implant is a customized patient-specific implant based on CT-data and input by the surgeon. The implant is fabricated from polyetheretherketone (PEEK) and is intended to be used to fill bony voids in the cranial skeleton. It is delivered non-sterile.

PEEK Customized Craniofacial Implant: The PEEK Customized Craniofacial Implant is a customized patient-specific implant based on CT-data. The implant is fabricated from polyetheretherketone (PEEK) and is intended to be used to fill bony voids in the craniofacial region (orbital rim, zygoma, and adjacent bone). The implant matches the shape and dimensions of the missing bone fragments. It is delivered non-sterile.

The host bone model is provided as a preoperative guide to demonstrate orientation and fit of the Peek Customized Cranial Implant. The Design Proposal is a presentation of virtual 3-dimensional models of the implant design. The PEEK Customized Cranial Implant is offered in different sizes based on the size of the cranial defect. Depending on the surgeon's preference, the PEEK Customized Cranial Implant may be constructed in varying thicknesses, wall designs, number of dura suture holes and dura suture hole diameters. The PEEK Customized Cranial Implant is fixated to the native bone with Stryker Neuro, Midface or Upperface self-tapping screws. The PEEK Customized Cranial and Craniofacial Implant Kit is bundled with an online ordering system called "eRequest Lifecycle", whereby the user can initiate a case request, upload the patient specific image data, download the Design Proposal and approve the implant design.

This document describes the PEEK Customized Cranial Implant Kit, a custom patient-specific implant intended to replace bony voids in the cranial and craniofacial skeleton. The submission focuses on demonstrating substantial equivalence to predicate devices rather than proving independent performance against specific acceptance criteria. Therefore, several requested details about acceptance criteria, study design, and ground truth are not explicitly provided in the document as it's a 510(k) submission for a medical device, not an AI/ML algorithm.

However, based on the provided text, the following information can be extracted or inferred:

1. Table of Acceptance Criteria and Reported Device Performance:

Since this is a 510(k) submission for a physical medical implant, the "acceptance criteria" are primarily related to mechanical properties, material compatibility, and fit, rather than performance metrics like sensitivity or specificity typically seen in AI/ML performance studies. The "reported device performance" refers to the results of various physical tests.

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

The document mentions a "Cadaver Lab" for handling tests and various "performance tests" (stability, trimming, drilling, screw insertion, screw pull-out). However, the specific sample sizes for these tests are not provided. Similarly, the data provenance (e.g., country of origin, retrospective or prospective) for these physical tests is not specified.

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

For the "handling test performed in a Cadaver Lab," it states that "surgeons demonstrated that the implants met the user needs and fit the defects."

• Number of experts: Not explicitly stated, but implies multiple surgeons were involved.
• Qualifications of experts: Identified as "surgeons." No further specific qualifications (e.g., years of experience, subspecialty) are provided.

4. Adjudication Method for the Test Set:

Given the nature of the tests, a formalized adjudication method like 2+1 or 3+1 is not applicable. The "handling test" involved surgeons demonstrating fit and meeting user needs, implying a qualitative assessment of suitability. The mechanical tests would have objective pass/fail criteria based on quantitative measurements.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done:

No, an MRMC comparative effectiveness study was not done. This type of study is typically conducted for diagnostic devices or AI algorithms where human reader performance is a key metric. This submission is for a physical implant.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

Yes, in the context of the device's design process. The document describes a "Virtual Implant Design Process (VIDP)" using CT-data to generate a 3D model and design the implant. This design process, which is an algorithm-driven component, is described as "validated." The performance data for the physical implant itself (mechanical strength, integrity) would be considered "standalone" as it's testing the final product independent of the human intervention during design approval.

7. The Type of Ground Truth Used:

• For mechanical tests (stability, trimming, drilling, screw insertion, screw pull-out): The ground truth would be based on engineering specifications and established mechanical properties of native bone (implicitly, as the device aims for "comparable to native skull" strength).
• For the handling test in the Cadaver Lab: The ground truth was based on expert consensus/qualitative assessment from surgeons regarding fit and user needs.

8. The Sample Size for the Training Set:

This question primarily applies to AI/ML algorithms that learn from data. While the device design uses patient CT data, the document does not describe it as a "training set" in the machine learning sense. The "Virtual Implant Design Process (VIDP)" is described as "validated," implying that the rules, algorithms, and processes for custom implant design were developed and verified, but it doesn't refer to a statistical "training set" of patient cases for an AI model to learn from.

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

Again, this question is not directly applicable in the AI/ML sense to this 510(k) submission. The "ground truth" for the "Virtual Implant Design Process" would refer to the accuracy and validity of the 3D modeling and design algorithms in replicating the desired anatomical structures and ensuring proper fit based on CT data. This would be established through engineering validation, potentially against known anatomical models or validated software outputs, during the development of the VIDP itself. The document states a "validated 'Virtual Implant Design Process' (VIDP)" is used, but doesn't elaborate on the validation specifics.

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