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The Yomi S Robotic System (Yomi S) is a computerized robotic navigational system intended to provide assistance in both the planning (pre-operative) and the surgical (intra-operative) phases of dental implantation surgery. The system provides software to preoperatively plan dental implantation procedures and provides robotic navigational guidance of the surgical instruments. The system can also be used for planning and performing guided bone reduction (also known as alveoplasty) of the mandible and/or maxilla. Yomi S is intended for use in partially edentulous and fully edentulous adult patients who qualify for dental implants.

When YomiPlan software is used for preplanning on third party PCs, it is intended to perform the planning (pre-operative) phase of dental implantation surgery. YomiPlan provides pre-operative planning for dental implantation procedures using the Yomi S Robotic System. The output of YomiPlan is to be used with the Yomi S Robotic System.

The Neocis Yomi S is a modified next iteration of the Yomi Robotic System, designed to provide guidance for a dental surgeon during dental implant surgery. Yomi S is a dental stereotaxic medical device (Product Codes PLV, QRY) regulated under 21 CFR 872.4120. The device includes a YomiLink that is placed on the patient prior to the CT scan, and a fiducial array with fiducial markers that is placed on the YomiLink prior to the CT scan so the virtual plan can be related to the physical space of the system. The Guidance Arm secures a standard dental drill, allowing the surgeon to grip the drill as normal. The Guidance Arm does not move unless the surgeon applies a manual force to the drill. The Guidance Arm will constrain the surgeon to drill according to the prescribed surgical plan, preventing deviation. The surgeon is constantly in control of the drilling. The system has a mechanical feedback system that is connected to the YomiLink on the patient, which relays information to the control software in order to track patient movement. If patient movement occurs during the surgical procedure, the system will respond by altering the prescribed surgical cutting angle and position to accommodate the patient movement, which will maintain the accuracy of the drill placement.

The Yomi S Robotic System allows the user to plan the surgery virtually in YomiPlan, cleared for use alone on third-party PCs for preplanning. The operative plan is based on a cone beam computed tomography (CBCT) scan of the patient, which is used to create a 3-D model of the patient anatomy in the planning software. The plan is used for the system to provide physical, visual, and audible feedback to the surgeon during the implant site preparation. The Yomi S robotic arm holds and guides a standard FDA-cleared third party powered bone cutting instrument.

The patient tracking portion of Yomi S is comprised of linkages from the patient to Yomi S, which include the Patient Splint (YomiLink Teeth or YomiLink Bone), Tracker End Effector (TEE), and the Patient Tracker (PT). In cases where YomiLink Teeth is utilized, it is attached to the contralateral side of the patient's mouth over stable teeth using on-label dental materials prior to the presurgical CBCT scan. In cases where YomiLink Bone is utilized, it is placed using bone screws prior to the presurgical CBCT scan (appropriate local anesthesia is required), or after the scan when using the subject YomiLink Arch device.

The subject of this submission is to: introduce the Yomi S Robotic System, a next-generation modification of the Yomi Robotic System, intended to assist dental surgeons by providing guidance during dental implant procedures.

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The TECHFIT Patient-Specific Cranial System is intended to replace bony voids in the cranial skeleton. The devices are indicated for adults and adolescents from 18 years or older.

The TECHFIT Patient-Specific Cranial System is patient specific devices intended to replace bony voids in the cranial/craniofacial skeleton. The TECHFIT Patient-Specific Cranial System includes a cranial implant, cranial model and a software component for digital planning and visualization named Digitally Integrated Surgical Reconstruction Platform DISRP®.

TECHFIT Patient-Specific Cranial Implants are manufactured from Polyether Ether Ketone (PEEK). The TECHFIT Patient-Specific Cranial Implants are attached to the native bone using commercial plates and screws.

The TECHFIT Patient-Specific Cranial System matches the shape and dimensions of the missing skull bone fragments. The implants are manufactured from PEEK according to ASTM F2026 and are manufactured by machining process.

The TECHFIT Patient-Specific Cranial System models are patient specific devices manufactured from clear resin using 3D printing manufacturing process. Those models are a representation of the anatomy of the patient, and they are not indicated to enter to the OR (Operating Room).

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The Yomi Robotic System (Yomi) is a computerized robotic navigational system intended to provide assistance in both the planning (pre-operative) and the surgical (intra-operative) phases of dental implantation surgery. The system provides software to preoperatively plan dental implantation procedures and provides robotic navigational guidance of the surgical instruments. The system can also be used for planning and performing guided bone reduction (also known as alveoplasty) of the mandible and/or maxilla. Yomi is intended for use in partially edentulous and fully edentulous adult patients who qualify for dental implants.

When YomiPlan software is used for preplanning on third party PCs, it is intended to perform the planning (pre-operative) phase of dental implantation surgery. Yomi Plan provides pre-operative planning for dental implantation procedures using the Yomi Robotic System. The output of Yomi Plan is to be used with the Yomi Robotic System.

Yomi Robotic System is a dental stereotaxic instrument and a powered surgical device for bone cutting. Yomi Robotic System is a computerized navigational system intended to provide assistance in both the planning (pre-operative) and the surgical (intra-operative) phases of dental implantation surgery. The system provides software to preoperatively plan dental implantation procedures and provides navigational guidance of the surgical instruments. The Yomi Robotic System is intended for use in partially edentulous and fully edentulous adult patients who qualify for dental implants.

The Yomi Robotic System allows the user to plan the surgery virtually in YomiPlan, cleared for use alone on third-party PCs for preplanning. The operative plan is based on a cone beam computed tomography (CBCT) scan of the patient, which is used to create a 3-D model of the patient anatomy in the planning software. The plan is used for the system to provide physical, visual, and audible feedback to the surgeon during the implant site preparation. The Yomi robotic arm holds and guides a standard FDA-cleared third party powered bone cutting instrument.

The patient tracking portion of Yomi is comprised of linkages from the patient to Yomi, which include the Patient Splint (YomiLink Teeth or YomiLink Bone), Tracker End Effector (TEE), and the Patient Tracker (PT). In cases where YomiLink Teeth is utilized, it is attached to the contralateral side of the patient's mouth over stable teeth using on-label dental materials prior to the presurgical CBCT scan. In cases where YomiLink Bone is utilized, it is placed using bone screws prior to the presurgical CBCT scan (appropriate local anesthesia is required), or after the scan when using the subject YomiLink Arch device.

The subject of this submission is to: Integrating algorithms that provide automatic segmentation of maxillary sinuses, inferior alveolar nerve, and maxillary and mandibular bone. The integrated software, Relu Creator, was cleared in K233925. The software is not adaptive, it is trained at the manufacturer (Relu), and the weights are locked.

Additionally, since the most recent clearance of Yomi Robotic System (K231018), minor modifications to the Yomi System include the following:
• Planning software improvements
• Restorative planning – Features to support customized crown design
• Dual arch planning – Feature to enable the end user to plan multiple arches in a singe case and a singe scan
• Patient work volume guidance improvements – Added guidance for the angulation of the patient chair
• Added patient proximity for baseline
• YomiLink Bone (YLB) planning – improved placement of the YLB
• Added proximity threshold lower limit value
• Improved alignment between CT scans and imported .stl objects
• Added ability for user to designate soft tissue thickness to assist in bone reduction planning
• Added max depth information to the implant cursor hover info
• VTK Off-the-Shelf software version update
• Added model details to implant selection
• Added restorative planning case feedback option
• Added additional implant models to the implant library

• Control software and behavior improvements
• Updates to handpiece interaction gestures, and optimization of the response of the control software to guide arm joint limits, singularities and potential wrist / base collisions.

• Hardware improvements Tracker Arm Joint

• Accessory improvements
• Updates to the YomiLink Teeth and intraoral fiducial array

• Minor bug fixes

All other aspects of the Yomi Robotic System remain unchanged from prior clearances.

The provided FDA 510(k) clearance letter for the Yomi Robotic System focuses on the substantial equivalence of the modified device to its predicate. While it mentions the integration of an automatic segmentation algorithm (Relu Creator, K233925), it does not contain the detailed acceptance criteria or the specific study that proves the device meets those criteria for the automatic segmentation algorithm.

The document primarily describes:

• The indications for use.
• A comparison of technological characteristics between the subject device (Yomi Robotic System with Automatic Segmentation Algorithm) and its predicate (Yomi Robotic System K231018) and a reference device (Relu Creator K233925).
• General statements about software, cybersecurity, and usability verification and validation testing, but without specific performance metrics or study details.

Therefore, many of the requested details about acceptance criteria, specific performance results, sample sizes, expert qualifications, and ground truth establishment for the automatic segmentation algorithm are not present in the provided text. The document refers to the Relu Creator (K233925) as having been cleared, implying its own performance evaluations would have been submitted in that separate clearance.

Here's a breakdown of the information that can be extracted or inferred, and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Not explicitly provided for the automatic segmentation algorithm (Relu Creator) in this document. The document states:

• "Yomi Plan 2.7 with Automatic Segmentation Algorithm functionality was successfully verified and user validated."
• "The software has been successfully verified to perform with the PC specifications of the Yomi Robotic System."
• "All changes have been successfully verified and, therefore, not considered to affect the overall safety and efficacy profile of Yomi Plan."
• "The combined testing and analysis of results provides assurance that the device performs as intended."

These are general assurances of performance and validation but do not provide specific quantitative acceptance criteria or reported device performance metrics for the automatic segmentation algorithm itself.

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

Not provided in this document. The document mentions "Software verification and validation testing" and "User Validation testing" but does not specify the sample size of cases or the provenance (country of origin, retrospective/prospective) of the data used for testing the automatic segmentation algorithm.

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

Not provided in this document.

4. Adjudication method for the test set

Not provided in this 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

Not provided in this document. The document does not mention an MRMC study or any results comparing human reader performance with and without AI assistance from the segmentation algorithm. The automatic segmentation algorithm is integrated into the planning software to assist (presumably by providing pre-segmented anatomy), but its impact on human reader performance is not quantified here.

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

Not explicitly detailed for the segmentation algorithm's performance. The document states, "The integrated software, Relu Creator, was cleared in K233925." This implies that the Relu Creator, which performs the automatic segmentation, underwent its own standalone performance evaluation as part of its original clearance (K233925). This current 510(k) focuses on its integration into the Yomi Robotic System, not its primary standalone performance evaluation.

7. The type of ground truth used

Not explicitly provided in this document for the automatic segmentation algorithm. For image segmentation algorithms, ground truth is typically established through manual segmentation by experts, often on a pixel/voxel level, sometimes validated by pathology or clinical outcomes. The document does not specify which method was used for the Relu Creator.

8. The sample size for the training set

Not provided in this document. The document states, "The software is not adaptive, it is trained at the manufacturer (Relu), and the weights are locked." This confirms that training occurred, but the size of the training dataset is not mentioned.

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

Not provided in this document. Similar to item 7, the method for establishing ground truth for the training data is not detailed.

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

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

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

CMF Titanium Guides are intended for single use only.

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

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

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

CMF Plastic Models are intended for single use only.

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

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

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

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

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

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

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

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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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MT-Bone is a piezoelectric ultrasonic device, consisting of handpieces and associated tip inserts, intended for:

• Bone cutting, osteotomy, osteoplasty and drilling in a variety of oral surgical procedures, including implantology, periodontal surgery, surgical orthodontic and surgical endodontic procedures;
• Scaling applications, including:
  Scaling: All general procedures for removal of supragingival and interdental calculus & plaque deposits:
  · Periodontology: Periodontal therapy and debridement for all types of periodontal diseases. including periodontal pocket irrigation and cleaning;
  · Endodontics: All treatments for root canal reaming, irrigation, filling, gutta-percha condensation and retrograde preparation;
  · Restorative and Prosthetics: Cavity preparation, removal of prostheses, amalgam condensation, finishing of crown preparations and inlay/onlay condensation.

MT-Bone is a piezoelectric ultrasonic device designed for oral bone surgery.
MT-Bone uses piezoelectric ultrasound technology to generate mechanical micro vibrations that can cut, drill or abrade through mineralized structures using appropriate inserts.
This allows an efficient and safe action which preserves the integrity of the osteotomized surfaces.
The micrometric, ultrasonic vibrations of the inserts provide greater precision and a selective action compared to traditional methods such as drills or oscillating saws (which act with macro vibrations), therefore minimizing traumatic effect on soft tissues. Depending by the Indication for use a lot of different type of inserts are available in Mectron portfolio.

The provided text describes the MT-Bone device and its substantial equivalence to a predicate device (PIEZOSURGERY TOUCH, K122322). However, it does not contain specific acceptance criteria, reported device performance metrics in a table, or details of a study proving the device meets said criteria in the way typically found for AI/ML-based medical devices.

The document primarily focuses on demonstrating substantial equivalence through a comparison of technological characteristics, indications for use, and general safety/performance testing. There is no mention of an algorithm, AI, or machine learning in the context of device function.

Therefore, many of the requested items (e.g., sample size for test set, data provenance, number of experts for ground truth, adjudication method, MRMC study, standalone performance, training set size) are not applicable or cannot be extracted from this document, as they pertain to a different type of device or evaluation method.

Here's a breakdown of what can be extracted based on the provided text, and where information is missing or not applicable:

1. Table of acceptance criteria and the reported device performance:

The document states that a series of non-clinical bench performance tests were conducted to evaluate the efficacy and safety of the device. The "acceptance criteria" are implied by the statement "All tests passed successfully" or "The testing showed that..." without quantitative metrics.

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

• Sample Size for Test Set: Not specified for any of the non-clinical tests. For the cadaver lab, it refers to "clinicians" but no number of cadavers or specific cases is given.
• Data Provenance: Not explicitly stated for any of the tests. It's internal testing by the manufacturer (Mectron S.p.A., Italy).

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):

• Number of Experts: For Usability Testing, it mentions "KOLs feedback and evaluations" (Key Opinion Leaders) but does not specify the number or their qualifications. For the Cadaver Lab, it states "clinicians" but again, no number or qualifications are provided.
• Qualifications of Experts: Not specified.

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

• Not applicable as the tests described are primarily bench, software, and usability/cadaver lab evaluations, not diagnostic accuracy studies requiring adjudication of ground truth by multiple experts.

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, a multi-reader multi-case (MRMC) comparative effectiveness study was not performed. The device described is a surgical instrument (piezoelectric ultrasonic device), not an imaging or diagnostic AI/ML device that assists human readers.

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

• Not applicable. The device is a surgical instrument requiring human operation. There is no mention of a standalone algorithm component that performs autonomously.

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

• For the non-clinical bench tests, "ground truth" is typically defined by engineering specifications, regulatory standards (e.g., IEC, ISO), and performance targets for the device's physical functions (e.g., amplitude, frequency, temperature, cutting efficacy).
• For Usability and Cadaver Lab tests, the "ground truth" or validation came from "KOLs feedback and evaluations" and "evaluation process conducted by clinicians," implying expert assessment of performance, safety, benefits, and usability.

8. The sample size for the training set:

• Not applicable. The document does not describe an AI/ML device that requires a training set.

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

• Not applicable. The document does not describe an AI/ML device that requires a training set.

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The Surgical Drive System (Model: ES70, ES90, E8) is indicated for: drilling, milling, sawing, screwing (for positioning) of osteosynthesis screws, implants and plate systems in soft and hard tissue. Including: ENT surgery and Maxillofacial surgery

The Surgical Drive System is an electrical drive unit, including a motor, power console, foot control, connection cables, and other accessories. It is intended for use in surgical procedures involving incision/cutting, removal, drilling, and sawing of soft and hard tissue and bone. The basic function of the Surgical Drive System is the conversion of electrical energy into a mechanical rotary motion. The control unit is used to control the connected motor and the integrated pump. The integrated touch display is used to monitor the actual settings and to change, within predetermined limits, the operating parameters. The foot control is used for activation of the motor and changing parameters e.g. program, pump state, and motor direction. The motor's function is to provide power for handpieces with the gear ratio (1:1, 1:4.2, 1:5, 3.2:1, 3.4:1, 40:1), the Max. speed of the motor is 40000 min-1, and it is designed with an ISO 3964 Type 3 connector.

This FDA 510(k) summary (K240340) for the Surgical Drive System (Model: ES70, ES90, E8) describes a device that is not an AI/ML-driven medical device. The document focuses on establishing substantial equivalence to a predicate device based on technical design, intended use, and conventional performance and safety testing.

Therefore, the requested information regarding acceptance criteria and studies proving the device meets those criteria, specifically concerning AI/ML performance metrics, cannot be extracted from this document because it does not involve AI/ML.

However, I can provide a summary of the non-clinical performance testing that was conducted to support the substantial equivalence claim for this medical device, which addresses the "study that proves the device meets the acceptance criteria" in a general sense, but not for AI/ML specific criteria.

Non-AI/ML Related Acceptance Criteria and Study Summary (Based on Provided Document):

The acceptance criteria for this non-AI/ML device are primarily related to safety, electromagnetic compatibility, and reprocessing effectiveness, demonstrated through adherence to recognized international standards.

1. Table of Acceptance Criteria and Reported Device Performance (Non-AI/ML):

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

• Test Set Sample Size: Not explicitly stated in terms of number of devices / units. Testing would typically involve a statistically relevant sample of devices or components to demonstrate compliance with standards.
• Data Provenance: Not explicitly stated, but testing is implied to be conducted by the manufacturer (Guangdong Jinme Medical Technology Co., Ltd.) or a contracted testing facility. The nature of these tests (safety, EMC, reprocessing validation) implies prospective testing on manufactured devices to meet specific engineering and regulatory requirements.

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

• This concept is not applicable as this is a non-AI/ML device. "Ground truth" established by expert consensus is typically relevant for evaluating the diagnostic or classification performance of AI/ML algorithms. For this device, compliance is measured against engineering specifications, industry standards, and regulatory requirements, which do not rely on expert "ground truth" in the same way.

4. Adjudication method for the test set:

• Not applicable for a non-AI/ML device. Adjudication methods like 2+1 or 3+1 are used in clinical studies or performance evaluations for diagnostic devices to resolve discrepancies in expert interpretations, particularly for establishing ground truth for AI model training or 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 as this is a surgical drive system, not an AI-driven diagnostic or assistive imaging device involving human readers.

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

• Not applicable as this is a hardware-based surgical drive system, not an AI algorithm.

7. The type of ground truth used:

• For this device, "ground truth" is established by:
  • Engineering Specifications: The device is designed to meet specific performance parameters (e.g., motor speed, power output, operating mode).
  • International Standards: Compliance with established safety (e.g., IEC 60601-1), EMC (e.g., IEC 60601-1-2), and reprocessing (e.g., ISO 17665-1) standards, where the standard itself defines the acceptable criteria and test methods.
  • Software Design Requirements: For the device's control software, compliance is against its own validated design requirements and IEC 62304.

8. The sample size for the training set:

• Not applicable. This device does not use a "training set" in the context of AI/ML.

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

• Not applicable.

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The tmCMF Solution 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 tmCMF Solution, and the result is an output data file that may then be provided as digital models or used as input to a manufacturing portion of the system that produces physical outputs, including anatomical models, surgical guides, dental splints, and implants for use in maxillofacial, midface, and mandibular surgery. Implants are 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, mandible, and chin in adolescents (greater than 12 to 21 years of age) and adults. The tmCMF Solution is also intended as a preoperative software tool for simulating/ evaluating virtual surgical treatment options.

TechMah CMF (tmCMF) Solution is a family of personalized product solutions for Reconstructive, Orthognathic, Trauma, and Augmentation procedures in the mandible and midface (including orbital floor, medial and lateral orbital walls). The solution is comprised of Surgeon Review Tool (SRT) software and maxillofacial and mandibular surgical instruments (surgical guides, anatomical models, and dental splints) and implants. The surgical instruments and implants are patient-specific devices and are designed utilizing CT and dental scan patient image data.

Surgical guides are patient-specific devices or templates based on pre-operative software planning designed to fit a specific patient. These guides are used to assist a surgeon in transferring the pre-operative plan to the surgery by guiding the marking/drilling of bone for plate fixation screws and the position of the osteotomy marking/cutting slots. Guides can be used in conjunction with anatomical models to verify anatomical positioning and fit. Surgical guides can be used with either tmCMF Solution patient-specific implants or compatible off-the-shelf DePuy Synthes implants.

Anatomical models are patient-specific models that are based on pre-operative anatomy and surqical planning specific to a patient. These models are used to assist a surgeon in transferring the pre-operative plan to the surgery by representing pre-operative, intra-operative, and post-operative anatomical models as quidance. Anatomical models can be used to check quide fit and facilitate the pre-bending of a non-patient-specific off-the-shelf plate.

Dental splints are patient-specific devices or templates based on pre-operative software planning designed to fit a specific patient. These templates are used to assist a surgeon in transferring the pre-operative plan to the surgery by guiding the dental alignment of bone and teeth.

Implants are patient-specific devices that are based on pre-operative software planning designed to fit a specific patient. These implants are integral components for CMF (craniomaxillofacial) procedures, facilitating bone repositioning, fixation, reconstruction, and the restoration of bone defects. They are designed according to the pre-operative surgical plan to ensure continuity in regions where bone is absent and to provide structural integrity to the maxillofacial skeletal components, midface, mandible, and chin. This could include stabilizing fractured or intraoperatively cut bone, fixating harvested graft segments, or augmenting bone defects. Implants can be used in conjunction with surgical guides and anatomical models to assist with anatomical positioning and fit.

The Surgeon Review Tool (SRT) software is used by surgeons for the review of surgical plans, surgical instruments, and implant designs. The SRT software is accessed through a web interface.

tmCMF Solution supports the following maxillofacial, midface (including orbital floor, lateral and medial orbital wall), and mandibular surgical procedures:

• . Reconstructive
• Orthognathic
• Trauma
• Augmentation ●

The provided text describes the tmCMF Solution device and its substantial equivalence to predicate devices, but it does not contain the specific acceptance criteria or the study details proving the device meets those criteria, particularly for performance metrics like accuracy, sensitivity, or specificity for the software components.

The "Benchtop Performance" section mentions that "Testing demonstrated that the tmCMF Solution and substantial equivalence with the predicate device" and lists several "Performance verification" items, but these are high-level statements rather than detailed acceptance criteria and reported performance values. For example, "Testing demonstrated that the surgical guide and implants meets the predetermined acceptance criteria" indicates that acceptance criteria exist but doesn't provide them or the specific performance results.

Therefore, I cannot fulfill all parts of your request with the given input. I will extract the information that is present and indicate where information is missing.

Here's a summary of what can be extracted based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Not explicitly provided with specific numerical acceptance criteria or reported performance values in the document. The document generally states that "Testing demonstrated that... meets the predetermined acceptance criteria" for various aspects.

Note: The document only states that the device "meets" or is "compliant" with predetermined acceptance criteria, without providing the specific quantitative or qualitative criteria themselves, nor the specific performance values (e.g., accuracy percentages, error margins).

2. Sample Size for the Test Set and Data Provenance

This information is not provided in the document. The document refers to "testing" but does not specify the sample size for any test set or the provenance (country of origin, retrospective/prospective) of data used for performance validation.

3. Number of Experts and Qualifications for Ground Truth

This information is not provided in the document.

4. Adjudication Method

This information is not provided in the document.

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

This information is not provided in the document. The document focuses on the device's technical specifications and substantial equivalence to predicate devices, not on comparative effectiveness with human readers.

6. Standalone (Algorithm Only) Performance Study

The document does not explicitly present a standalone performance study with specific metrics (e.g., accuracy, sensitivity, specificity) for the imaging or segmentation algorithms. It mentions tmCMF Solution is "a software system and image segmentation system," and that "Software Verification and Validation Testing was conducted," but focuses on compliance with software standards (IEC 62304) and general system functionality rather than detailed standalone performance metrics against ground truth for clinical tasks.

7. Type of Ground Truth Used

The specific type of ground truth (e.g., expert consensus, pathology, outcomes data) used for the software's performance assessment is not explicitly stated in the document. It generally refers to "predetermined acceptance criteria" for various verification items.

8. Sample Size for the Training Set

This information is not provided in the document.

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

This information is not provided in the document.

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

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

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

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

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

Digital 3D model creation

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

Planning

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

Design

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

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

The document mainly focuses on:

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

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

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

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

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

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

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

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

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

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

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

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

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

No. The document does not mention an MRMC study. The device, Mimics Enlight CMF, is described as an image processing software for segmentation, visualization, measurement, and design tools, supporting diagnostic and treatment planning. It's not an AI-assisted diagnostic tool in the sense that medical images are interpreted by human readers with or without AI assistance. Therefore, an MRMC study to show human reader improvement with AI assistance is not relevant to the described performance evaluation.

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

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

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

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

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

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

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

8. The sample size for the training set

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

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

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

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The X-Guide® Surgical Navigation System is a computerized navigational system intended to provide assistance in both the preoperative planning phase and the intra-operative surgical phase of dental implantation procedures and/or endodontic access procedures.
The system provides software to preoperatively plan dental implantation procedures and/or endodontics access procedures and provides navigational guidance of the surgical instruments.
The device is intended for use for partially edentulous adult and geriatric patients who need dental implants as a part of their treatment plan. The device is also intended for endodontic access procedures (i.e., apicoectomies and/or access of calcified canals) where a CBCT is deemed appropriate as part of their treatment plan.

The X-Guide® Surgical Navigation System is a cart mounted mobile system utilizing video technology to track position and movement of a surgical instrument (Dental Hand-Piece) during surgical procedures.
The X-Guide® Surgical Navigation System consists of a Mobile Cart, equipped with an LCD Monitor, Boom Arm, Navigation Assembly, Keyboard, Mouse and an Electronics Enclosure.
The Electronics Enclosure contains the system power supplies, data processing hardware, and electronics control circuitry for coordinating operation of the X-Guide® Surgical Navigation System.
A LCD Monitor, Keyboard, and Mouse serve as the main user interface for the surgeon. The Go-Button serves as an additional form of input by providing virtual buttons that a user can activate by touching them with the surgical instrument tip.
The Boom Arm allows the operator to manipulate the Navigation Assembly position for optimal distance and alignment to patterns located with the surgical region (Navi-Zone) for tracking purposes.
The Navigation Assembly contains two cameras oriented in a stereo configuration, along with blue lighting for illuminating the patterns and mitigating ambient lighting noise.
This electro-optical device is designed to improve dental surgical procedures by providing the surgeon with accurate surgical tool placement and guidance with respect to a surgical plan built upon Computed Tomographic (CT scan) data.
The surgical process occurs in two stages. Stage 1 is the pre-planning of the surgical procedure. The dental surgeon plans the surgical procedure in the X-Guide System Planning Software. A virtual implant or endodontic trajectory is aligned and oriented to the desired location in the CT scan, allowing the dental surgeon to avoid interfering with critical anatomical structures during surgery. Once an implant or trajectory has been optimally positioned, the plan is transferred to the X-Guide Surgical Navigation System in preparation for surgery.
In Stage 2 the system provides accurate guidance of the dental surgical instruments according to the preoperative plan.
As the dental surgeon moves the surgical instrument around the patient anatomy, 2D barcode tracking patterns on the Handpiece Tracker and the Patient Tracker are detected by visible light cameras in a stereo configuration and processed by data processing hardware to precisely and continuously track the motion of the dental handpiece and the surgically-relevant portion of the patient.
The relative motion of the dental handpiece and the patient anatomy, captured by the tracking hardware, is combined with patient-specific calibration data. This enables a 3D graphical representation of the handpiece to be animated and depicted in precise location and orientation relative to a 3D depiction of the implant target, along with depictions of the patient anatomy, and other features defined in the surgical plan. This provides continuous visual feedback that enables the dental surgeon to manewer the dental handpiece into precise alignment.
During execution of the surgical procedure, the X-Guide® Surgical Navigation System correlates between the surgical plan and the surgeon's actual performance. If significant deviations in navigation between the plan and the system performance occur, the system will alert the user.

The provided text describes the X-Guide Surgical Navigation System, which includes a new feature: Automatic Image Processing (AIP) software integration (IconiX) using machine learning. This software is designed to segment and identify anatomical structures in maxillofacial CT scans and IntraOral Scans (IOS).

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

1. Table of Acceptance Criteria and Reported Device Performance

The FDA 510(k) summary does not explicitly list "acceptance criteria" in a quantitative, pass/fail format with reported performance for EACH of the new ML-driven features. Instead, it states that "software verification and validation testing were conducted and documented" and that the "combined testing and analysis of results provides assurance that the device performs as intended."

However, the "Technology Performance Characteristics" table (pages 12-14) implicitly presents several performance characteristics that would have acceptance criteria for the base device, which are maintained. For the new ML features, the validation tests described aim to demonstrate "correct segmentations and visualizations," "automatically create a pan curve," "register (superimpose) the IOS over the CT," and "generate the X-Guide SurfiX."

Given the information, a table focusing on the new ML features would look like this:

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

The 510(k) summary does not explicitly state the sample size used for the test set. It mentions "varied CT data" for training (page 5) but does not provide specifics for the validation/test set.

Similarly, the data provenance (e.g., country of origin, retrospective or prospective) for the test set is not specified in the provided document.

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

The document does not specify the number or qualifications of experts used to establish ground truth for the test set. It mentions that users can "view and confirm the correctness and completeness of [ML] results and, if desired, replace or augment them with conventional tools/methods" (page 5), implying a human expert review process is part of the clinical workflow, but this does not detail how ground truth for the test set was established for regulatory validation.

4. Adjudication Method for the Test Set

The document does not describe an adjudication method (e.g., 2+1, 3+1) for the test set.

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

The document explicitly states: "No clinical studies were performed for the submission of this 510(k)." (page 19) Therefore, no MRMC study was conducted, and no effect size regarding human reader improvement with AI assistance is provided.

6. Standalone (Algorithm Only) Performance Study

The summary describes "Machine Learning Outputs Validation" and "Machine Learning Software Verification" (page 20).

• Machine Learning Outputs Validation: "This validation test demonstrates that the machine learning software outputs correct segmentations and visualizations for the expected patient population." This suggests an assessment of the algorithm's performance in generating segmentations in a standalone context (i.e., whether the outputs themselves were correct compared to ground truth).
• Machine Learning Software Verification: "This verification test demonstrates that the machine learning software meets specifications and requirements when integrated with the X-Guide System software..." This part focuses on the integrated performance.

While the details of the "Machine Learning Outputs Validation" are not provided, its description implies a standalone assessment of the ML algorithm's output accuracy against some form of ground truth.

7. Type of Ground Truth Used

The document does not explicitly state the type of ground truth used for validating the machine learning outputs (e.g., expert consensus, pathology, outcomes data).

8. Sample Size for the Training Set

The document mentions that the machine learning software is "trained on varied CT data" (page 5) but does not specify the sample size for the training set.

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

The document does not describe how the ground truth for the training set was established.

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