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TECHFIT Digitally Integrated Surgical Reconstruction Platform (DISRP) System is intended for use as a software system and image segmentation system for the transfer of imaging information from a medical scanner such as a CT based system. The input data file is processed by the DISRP System and the result is an outbut data file that may then be provided as digital models or used as input to a rapid prototyping portion of the system that produces physical outputs including surgical guides and splints for use in maxillofacial surgery. The DISRP System is also intended as a preoperative software tool for simulating / evaluating surgical treatment options.

The DISRP system is compatible with the TECHFIT Patient- Specific Maxillofacial System and the TECHFIT Diagnostic Models and should be used in conjunction with expert clinical judgment.

The TECHFIT DISRP SYSTEM is composed by Anatomic Specificx Guiding System and the Digitally Integrated Surgical Reconstruction Platform (DISRP).

• . The Digitally Integrated Surgical Reconstruction Platform (DISRP) is a web-based collaboration software for digital surgery case flow management and Orthognathic surgery planning that reflects the production process and allows for the interaction of multiple users: surgeons, sales representatives, and the TECHFIT case planning staff (case planning assistant, case planners, and operations director), using multiple devices. It allows collaboration in the planning process. Detail description of the software can be found in later in this section.
• Anatomic Specificx Guiding System is a Patient-Specific single-use device designed to ● assist surgeons in transferring the pre-surgical plan to the operation room. This system includes surqical quides intended for Orthognathic and Reconstructive surgeries in adults. The surgical guides have drilling holes and slots to make osteotomies and ensure the correct positioning of bones and implants.

The Anatomic Specificx Guiding System is divided into two categories: Anatomic Specificx Orthognathic Guides and Anatomic Specificx Reconstruction Guides.

Anatomic Specificx Orthognathic Guides are classified into Titanium and Resin Surgical Guides.

Anatomic Specificx Orthognathic Titanium Guides are manufactured from Commercially Pure (CP) Titanium grade 4; they include mandibular and maxillofacial surgical guides (e.q. Le Fort, Genioplasty, etc). Palatal Splints are also part of Anatomic Specificx Orthognathic Titanium Guides, which are optional quides used in orthognathic surgery to quide and support the correct teeth positioning and validate the patient's final occlusion.

Anatomic Specificx Orthognathic Resin Guides are manufactured through rapid prototyping using the Form 3B and Form 4B printers and Biomed Clear Resin from Formlabs. These guides include Le Fort and genioplasty surgical guides. During surgery, resin surgical guides must be used with slot, drill, and screw metal sleeves. Slot sleeves are made from commercially pure grade 4 titanium, while drill and screw sleeves are made from alloyed titanium (Ti6Al4V). All sleeves are manufactured by machining. The resin quides also include splints (intermediate, final, and palatal), which are optional quides used in orthognathic surgery to quide and support the correct teeth positioning and validate the patient's final occlusion.

Anatomic Specificx Reconstruction Guides

The Anatomic Specificx Reconstruction Guides are intended for mandibular and maxillofacial surqical procedures in adults, using patient grafts/flaps for reconstruction. These guides are made from Commercially Pure (CP) grade 4 titanium, produced through machining and finished with an anodizing process. They are intended for use in the anatomical sites of the maxilla, mandible and fibula. The reconstruction guides provide transfer of the pre-surgical plan to the operating room, facilitating placement and fixation of the patient's bone grafts/flaps at the surgical site.

The TECHFIT DISRP® System is cleared based on non-clinical testing. The device is a software system and image segmentation system intended for use in maxillofacial surgery for transferring imaging information from a medical scanner (such as a CT-based system) to create digital models, or to produce physical outputs such as surgical guides and splints. It also serves as a preoperative software tool for simulating and evaluating surgical treatment options.

Here's an overview of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

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

The provided document does not specify the exact sample sizes for the test sets in the dimensional validation, compatibility testing, mechanical testing, or software verification and validation. It only states that these tests were conducted.

The provenance of the data (e.g., country of origin, retrospective or prospective) is not explicitly mentioned for any of the non-clinical tests.

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

This information is not provided in the document. For instance, in the dimensional validation, it does not state how many individuals assessed the comparisons or their qualifications. For software V&V, it does not specify who conducted the testing or their expertise.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication methods (e.g., 2+1, 3+1) for establishing ground truth or evaluating test results. The conclusions appear to be based on direct measurements and adherence to test standards.

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

No, the document does not mention a Multi Reader Multi Case (MRMC) comparative effectiveness study. The studies described are non-clinical hardware and software performance tests, not clinical studies involving human readers or comparative effectiveness with and without AI assistance.

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

The software verification and validation activities (e.g., "DISRP meets the SDS and testing as intended in the intended use environment") represent standalone algorithm performance testing to some extent. The DISRP system, as a software for planning and segmentation, operates on input data files and produces output data files, which is a core standalone function. However, the overall system still anticipates "expert clinical judgment" as stated in the Indications for Use, meaning it's intended to be used with a human in the loop for clinical application. The V&V focuses on the software's functional correctness.

7. The Type of Ground Truth Used

The type of ground truth used for the non-clinical tests can be inferred as follows:

• Sterilization: Ground truth is established by adherence to recognized international standards (AAMI/ISO 17665-1, ANSI/AAMI/ISO 14937) and demonstrating the specified SAL.
• Dimensional validation: Ground truth would be the original digital design files against which the scanned physical devices are compared. This is a direct comparison to a digital reference.
• Compatibility testing: Ground truth is defined by the functional requirement for components to work together seamlessly.
• Mechanical testing: Ground truth is established by the specified mechanical properties to be achieved or exceeded, often through direct measurement and comparison with known material properties or predicate device performance.
• Software verification and validation: Ground truth is the Software Design Specification (SDS) and the intended functional requirements of the software.
• Biocompatibility testing: Ground truth is established by the pass/fail criteria defined in the referenced ISO 10993 series standards, indicating the absence of adverse biological reactions.

8. The Sample Size for the Training Set

The document does not provide any information about a training set for an AI/ML algorithm. The device is described as a "software system and image segmentation system," but there's no explicit mention of machine learning or deep learning components requiring a dedicated training set. The development described is more akin to traditional software and CAD/CAM processes.

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

Since no training set is mentioned or implied for an AI/ML component, this information is not applicable and not provided in the document.

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The TECHFIT Diagnostic Models are patient-specific devices intended to be used as a pre-operative planning tool for treatment in the field of maxillofacial surgery.

The input data file (DICOM imaging information from a medical scanner file) is processed by commercial off-the-shelf software, and the result is an output data file that may then be provided as digital models or used as input to produce physical anatomic models using additive manufacturing.

The physical replica can be used for diagnostic purposes in the field of, maxillofacial applications.

TECHFIT Diagnostic Models should be used in conjunction with other diagnostic tools and expert clinical judgment.

TECHFIT Diagnostic Models are not intended to enter the operating room

TECHFIT Diagnostic Models are virtual and additive manufactured anatomic models intended for diagnostic use during maxillofacial surgery planning.

The models are created from a CT scan of the patient's anatomy, which is segmented through Commercial-Off-The-Shelf (COTS) software and converted into virtual 3D models. The surgeon uses these 3D models to make the initial plan/diagnosis based on examination or physical measurement of the patient's anatomy, this includes planning anatomic structures movements (for example, maxilla and mandible movements for occlusion), the resections, measurement of anatomic distances (e.g., the facial symmetry), and determining fixation points and the size and shape of the implants if requested. These functions are those that the surgeon can perform, not functions that the subject device provides by itself.

TECHFIT creates a design proposal for the case based on the information given by the medical professional and the process continues until the final design proposal is approved. Finally, the digital file can be used as an input to produce physical anatomic models through additive manufacturing.

TECHFIT Diagnostic Models are intended for single use only.

The provided text describes the TECHFIT Diagnostic Models, which are patient-specific devices intended for pre-operative planning in maxillofacial surgery. The device processes DICOM imaging data to create virtual 3D models or physical anatomical models through additive manufacturing.

Here's an analysis of the acceptance criteria and study information provided:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Dimensional Validation: "multiple anatomic models from different patients (mandibles and maxilla)" were used. The exact number of patients or models is not specified.
• Diagnostic Qualitative Evaluation: The number of clinicians interviewed is not specified, only referred to as "interviewed surgeons".
• Fidelity Validation of detectable anatomical landmarks: "educational anatomic models" were used. The number of models or specific types is not provided.
• Data Provenance: Not explicitly stated whether the patient data used for dimensional validation was retrospective or prospective, or its country of origin. The use of "educational anatomic models" for landmark fidelity implies a non-clinical, potentially synthetic, origin for that specific test.

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

• Dimensional Validation: The ground truth for dimensional accuracy would likely be the original CAD model or physical measurement of the source object. No human experts are explicitly mentioned for establishing this ground truth, rather the comparison is against the "original model".
• Diagnostic Qualitative Evaluation: "Maxillofacial surgeons" were interviewed. Their specific qualifications (e.g., years of experience, subspecialty) are not provided beyond being maxillofacial surgeons. The number of surgeons is not specified.
• Fidelity Validation of detectable anatomical landmarks: The ground truth would be the known anatomical landmarks on the "educational anatomic models." No experts are explicitly mentioned for establishing this ground truth, as it is inherent to the models.

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

• No specific adjudication method is mentioned for any of the studies. For qualitative evaluations, it sounds like individual surgeon opinions were aggregated, but no formal adjudication process (like consensus reading or tie-breaking) is described.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• No MRMC comparative effectiveness study is mentioned. The qualitative evaluation focused on the perceived utility of the models as a "significant help" to surgeons, rather than quantifying improvement in human reader performance with or without the device. The device itself is described as a "pre-operative planning tool" and "diagnostic models" to be used "in conjunction with other diagnostic tools and expert clinical judgment," implying it's an aid, not a standalone diagnostic tool or an AI for image interpretation.

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

• The studies described are primarily focused on the physical and qualitative aspects of the generated models. The device's function involves human input (processing DICOM by "commercial off-the-shelf software" and subsequent human interaction for planning) and the output (digital or physical models) is for a human surgeon to use in conjunction with their judgment. Therefore, a standalone algorithm-only performance study in the sense of a purely interpretative AI is not applicable or described. The "Fidelity Validation" and "Dimensional Validation" assess the accuracy of the output product (models) in replicating anatomical features, which is a form of standalone performance for the manufacturing process, but not for diagnostic interpretation by an AI.

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

• Dimensional Validation: Original digital model or measured physical dimensions.
• Diagnostic Qualitative Evaluation: Clinical experience and qualitative assessment by maxillofacial surgeons.
• Fidelity Validation of detectable anatomical landmarks: Known anatomical landmarks on educational models.
• No mention of pathology or outcomes data being used for ground truth.

8. The sample size for the training set:

• The document describes the device as processing "DICOM imaging information" through "commercial off-the-shelf software" (Mimics Medical, K183105) and then having "biomedical engineers" work with surgeons for planning. It also states that the "anatomic models are created by TechFit versus the end user" and that they use "the same segmentation/3D reconstruction software to create 3D anatomic models Mimics Medical (K183105)."
• This suggests that the core segmentation and 3D reconstruction is performed by a previously cleared software (Mimics Medical). The "TECHFIT Diagnostic Models" appear to be the output of a service that utilizes this software, along with human expertise, to create patient-specific models.
• Therefore, there isn't a "training set" for the "TECHFIT Diagnostic Models" in the typical AI/ML sense, as the core algorithms for image processing and segmentation likely belong to the COTS software (Mimics Medical) and would have their own validation. The TECHFIT process leverages this and human expertise.

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

• As elaborated in point 8, a dedicated training set for "TECHFIT Diagnostic Models" is not described as it is not a de novo AI/ML algorithm being trained by TECHFIT. The ground truth establishment for the underlying COTS software (Mimics Medical) would be relevant here, but is not detailed in this document.

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AFFINITY Proximal Tibia System is intended to treat fractures, nonunions of the proximal tibia including simple, comminuted, lateral wedge, depression, medial wedge, bicondylar combination of lateral wedge and depression, periprosthetic, and fractures with associated shaft fractures.

• · Simple metaphyseal fractures (Classification AO 41-A2)
• · Multifragmentary metaphyseal fractures (Classification AO 41-A3)
• · Simple bicondylar fractures (Classification AO41-C1, 41-C2)
• Multifragmentary bicondylar fractures (Classification AO 41-C3)
• · Simple joint, simple metaphyseal fractures (Classification AO 41-C1)
• · Diaphisary fractures (Classification AO 42A and 42B)

AFFINITY Proximal Tibia System consists of anatomical plates and screws for the placement of the proximal tibial condyles, improving the restoration of the original structure. Similarly, in combination with the variable angle technique, it allows for the placement of screws in different configurations providing appropriate support for the correct healing of fractures.
AFFINITY Proximal Tibia System consists of pre-contoured bone fixation plates and screws. The plates are made from biocompatible commercially pure titanium grade 4 according to ISO 5832-2 and ASTM F67 standard. The screws are made from biocompatible titanium alloy (Ti6Al4V) according to ISO 5832-3 and ASTM F136 standard.
The AFFINITY Proximal Tibia System plates can be fixed with variable angle technique.

The provided text is an FDA 510(k) summary for the AFFINITY Proximal Tibia System. This document describes a medical device (a bone plate and screw system for tibial fractures) and its claim of substantial equivalence to existing predicate devices.

Crucially, the document states that "Clinical testing was not necessary for the substantial equivalence determination." This means that the device's acceptance criteria and the proof it meets them do NOT involve human clinical studies or AI-driven performance metrics such as accuracy, sensitivity, specificity, or human-in-the-loop improvements.

Therefore, I cannot fulfill the request to describe the acceptance criteria and study that proves the device meets the acceptance criteria in the context of AI/machine learning performance. The provided text details non-clinical performance testing for a medical implant, focusing on mechanical, biocompatibility, and sterilization aspects.

Here's why I cannot provide the requested information based on the given text:

• No AI or algorithm present: There is no mention of any AI component, algorithm, or software in the device description or its testing.
• No clinical performance data (e.g., accuracy, sensitivity): The document explicitly states "Clinical testing was not necessary." The performance testing described is mechanical (bend, torsion, pullout strength), biocompatibility, and sterilization, which are relevant for physical implants, not AI diagnostic or assistive devices.
• No human reader studies (MRMC): Since no AI is involved, there are no studies assessing how human readers improve with AI assistance.
• No ground truth establishment for diagnostic performance: The "ground truth" mentioned in your prompt (expert consensus, pathology, outcomes data) is typically for validating diagnostic or classification algorithms. For a bone plate, ground truth relates to its mechanical integrity and biological safety, which were assessed through laboratory tests.

In summary, the provided document describes the regulatory approval of a physical medical device (a bone plate and screw system) through established non-clinical testing and comparison to predicates, not the validation of an AI/ML medical device.

If you have a document describing an AI/ML medical device's performance study, I would be happy to analyze it according to your detailed criteria.

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