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Navident is a computerized dental navigational system intended to assist preoperative planning and to guide drilling in a patient jaw during implantation surgery, using pre-acquired CT scan of the jaw. The device is intended for use by a qualified dental surgeon in the treatment of partially or fully edentulous jaws.

Navident is an image-guided dental navigational system intended to assist with preoperative planning and real-time positioning of drilling tools during implantation surgery. In particular, Navident provides visual, real-time feedback on the location of the working tip of a dental handpiece. It shows the location and direction of the tip relative to a volumetric CT image of the patient's jaw registered to that anatomy, and, when available, relative to a path planned on that image. Navident is comprised of the following parts: The main system is comprised of a cart that carries a stereoscopic video camera and a laptop with pre-installed proprietary software. The Navident system also includes several types of accessories: Jaw motion Tracking Accessories, Dental Handpiece Tracking Accessories, Registration accessories, Calibrator. Navident's four core functions are: Model, Plan, Register, Guide.

Here's an analysis of the provided text to extract information about the acceptance criteria and the study proving the device meets them:

Device: Navident

Product Code: PLV
Regulation Number: 21 CFR 872.4120
Regulation Name: Bone Cutting Instrument And Accessories
Regulatory Class: Class II

1. Table of Acceptance Criteria and Reported Device Performance

The provided text focuses on the performance data of the device rather than explicit "acceptance criteria" presented as pass/fail thresholds against specific metrics, except for the accuracy at the drill tip. Instead, it describes various validation and testing activities that collectively demonstrate the device's acceptable performance.

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NaviENT is a computerized surgical navigation system intended to guide sinus and trans-nasal skull base endoscopic surgery by dynamically presenting the location of the tip of a surgical instrument mapped to a corresponding location in a pre-acquired CT scan of the patient's head. The device is intended for use by a qualified ENT surgeon (otolaryngologist).

NaviENT is indicated for any medical condition in which the use of stereotactic surgery may be appropriate, and where reference to a rigid anatomical structure, such as the skull, can be identified relative to images of the anatomy. Surgery procedures include but are not limited to the following: transphenoidal procedures, maxillary antrostomnies, ethmoidectomies, sphenoidectomies, sphenoid explorations, turbinate resections, frontal sinusotomnies, intranasal procedures, intranasal tumor resections, and ENT related skull base surgery.

NaviENT is a cart-based, computerized, image-guided navigational system, operating as a combined package for performing guided ENT surgery.

Using pre-acquired CT scan of the sinus, NaviENT provides the surgeon (usually otolaryngologists) with easy-to-use real-time guidance during sinus surgery. The key function performed by NaviENT during navigation is visualization of the instrument tip relative to the surrounding anatomy. This visualization assists the surgeon in performing the surgery.

NaviENT consists of four main components:

1. NaviENT Cart
2. Tracking System
3. Laptop Computer
4. NaviENT Instruments

Here's a breakdown of the acceptance criteria and study information for the NaviENT device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: For accuracy testing, 3 different human head models were used.
• Data Provenance: The testing was conducted in an OR simulated environment. The country of origin of the data is not explicitly stated, but the submission is from ClaroNav Inc. in Toronto, Canada. Given the context of a 510(k) submission, this would be considered a prospective performance study designed for regulatory approval.

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

This information is not explicitly provided in the document. The accuracy testing was done using "human head models," which typically implies a phantom-based or simulated setup for objective measurement rather than expert-derived ground truth on clinical data.

4. Adjudication Method for the Test Set:

This information is not explicitly provided in the document. For benchtop accuracy testing using physical models, an adjudication method like 2+1 or 3+1 by human experts is typically not necessary. The ground truth would be based on precise physical measurements of the models.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance:

An MRMC comparative effectiveness study is not mentioned in the document. The study described is a device performance and accuracy study, not one designed to evaluate the clinical effectiveness of human readers using the device.

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

The study described is a standalone performance study of the NaviENT system's accuracy and various other aspects (software, sterility, electrical safety, biocompatibility, human factors). It evaluates the device's inherent performance characteristics rather than how it performs with a human in a clinical setting. The device itself is described as a "computerized surgical navigation system," implying an algorithmic core.

7. The Type of Ground Truth Used (Expert Consensus, Pathology, Outcomes Data, etc.):

For the accuracy testing, the ground truth was established by physical measurements on human head models within an OR simulated environment. This is a form of engineered or phantom-based ground truth, where the true positions are precisely known or measurable. For other tests (sterilization, biocompatibility, electrical safety), the ground truth is against established ISO and IEC standards and their specific test methodologies.

8. The Sample Size for the Training Set:

This information is not provided in the document. The document describes a medical device with an image guidance component, but it does not detail any machine learning or AI models that would require a separate "training set" in the conventional sense. The "NaviENT software" processes data, but it's not indicated as a learning-based system with a distinct training phase in this submission.

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

As no training set is mentioned (see point 8), this information is not applicable/provided.

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Navident is a computerized dental navigational system intended to assist preoperative planning and to guide drilling in a patient jaw during implantation surgery, using pre-acquired CT scan of the jaw. The device is intended for use by a qualified dental surgeon in the treatment of partial edentulism.

Navident is a cart-based, computerized, image-guided dental navigational system, operating as a combined package for performing both pre-operative planning and guided implant insertion. Using preacquired CT scan of the jaw, Navident provides the dentist (usually a GP dentist, prosthodontist, periodontist or dental surgeon) with implantation planning and real-time guidance during dental implants insertion.

The guidance function of Navident is primarily provided using a visualization of the drill pose (tip location and shaft axis direction) relative to the desired pose of the implant, as planned on a preacquired CT image of the jaw. This visualization assists the dentist in implementing their implantation plan.

Navident consists of four main components:

• 1. A notebook computer positioned above the patient's chest. The Navident software running on the computer provides both planning and navigation functionalities.
• 2. A handpiece attachment. The attachment consists of a universal removable metal adapter, and a specially marked plastic part, named DrillTag, which latches on the adapter.
• 3. A customizable patient jaw attachment consisting of a moldable stent part, named NaviStent, and a matching specially marked plastic tag, named JawTag. NaviStent can be formed, customized and tested for fit directly on the patient's jaw or on a plaster model. The patient wears the NaviStent during the CT scan and again during the surgery. Navident is able to continuously register NaviStent's position during surgery with its appearance in the CT scan automatically.
• 4. An optical position sensor which detects high contrast patterns printed on the DrillTag and JawTag and constantly reports their relative positions to the Navident software.

Here's a breakdown of the acceptance criteria and study details for the Navident device, based on the provided text:

Navident Device Performance and Acceptance Criteria

Study Details Proving Acceptance Criteria

Due to the nature of the provided document (a 510(k) summary), specific details for some categories (like distinct training vs. test sets or formal MRMC studies) are not fully separated as might be found in a later clinical trial report. However, the summary describes various performance and clinical evaluations.

1. Table of Acceptance Criteria and Reported Device Performance: (See table above)

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

   • Bench Testing: Performed with various settings and conditions (e.g., different image voxel sizes, distances, lighting, random jaw models). The exact number of "tests" or "samples" for each specific parameter is not quantified.
   • Human Factors/Usability Summative Evaluation: 15 representative users (oral surgeons, general dental practitioners).
   • Clinical Case Data: 21 cases with 36 guided implantations. The geographical provenance (country of origin) is not explicitly stated but implies international, as it mentions "a diverse international group of surgeons." This appears to be retrospective collected over time as "feedback on usage history."
   • Clinical Evaluation (Systematic Feedback): 7 surgeons who treated a total of 150 patients. The provenance is again "diverse international group of surgeons" and appears to be retrospective collection of "usage history and professional impressions."

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

   • For the human factors/usability evaluation, 15 "representative users (i.e., oral surgeons, general dental practitioners)" were observed. Their role was more as "test subjects" or "users" rather than establishing a separate "ground truth" in terms of clinical outcomes, though their feedback contributed to the "usability problems" assessment.
   • For the clinical case data and systematic feedback, the ground truth regarding "accuracy averaging 1.0mm deviation from plan at both entry and apex" was likely established through post-procedure analysis by the "experienced user" (qualified dental surgeon) themselves or by the study investigators. The qualifications of these 7 surgeons and the "diverse international group of surgeons" are defined as "qualified dental surgeon." No specific number of independent experts for ground truth adjudication is given for the accuracy assessment, rather it describes "an experienced user is able to achieve."

4. Adjudication Method for the Test Set:

   • No formal multi-reader adjudication method (e.g., 2+1, 3+1) is described for the clinical accuracy assessment. The summary states, "Accuracy assessment demonstrated that, with Navident's guidance, an experienced user is able to achieve an implant placement accuracy averaging 1.0mm deviation from plan at both entry and apex." This implies a measurement against the pre-planned position, which serves as the "ground truth" for deviation.

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

   • No MRMC comparative effectiveness study, specifically comparing human readers with AI vs. without AI assistance, is mentioned. The device is a "computerized dental navigational system" providing real-time guidance, not an AI diagnostic aid that assists human readers in interpreting images. Its direct comparison is against a predicate surgical navigation system.

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

   • Yes, the "Full system bench testing" (point 3 under SUMMARY OF PERFORMANCE TESTING) evaluates the "Overall accuracy of the system in mapping the drill tip to the CT image" and other operational aspects without direct human surgical intervention as the primary performance metric. This represents the standalone performance of the navigation system's mapping and guidance precision.

7. The Type of Ground Truth Used:

   • Bench Testing: Engineering measurements against known physical standards or simulated conditions.
   • Clinical Cases (Accuracy): Deviation from the "planned pose of the implant" as visualized on the pre-acquired CT image. The pre-planned position serves as the ground truth for measuring positional / angular deviation.
   • Clinical Cases (Outcomes): "No significant patient adverse events or complications were reported." This relies on outcomes data from the surgeons.

8. The Sample Size for the Training Set:

   • The document describes a "510(k) summary," which focuses on demonstrating substantial equivalence and performance testing rather than algorithm development. It does not provide details on a specific "training set" for an AI algorithm. The device is a mechanical/software navigation system, not primarily an AI deep learning model that requires a large training dataset in the conventional sense. The "training" here refers to its design and calibration processes.

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

   • Not applicable in the context of an AI training set. The "ground truth" for the system's design and calibration would have been engineering specifications and physical measurements, ensuring its tracking capabilities (Stereoscopic triangulation of illuminated checker-board patterns) and mapping accuracy.

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