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Devices of the i-CAT family consist of an x-ray system that uses a cone beam with a rotational sequence, providing two dimensional images and three dimensional volume reconstructions of the head area, which includes ENT and maxillofacial areas (such as TM Joint studies, mandible & maxilla for implant planning, sinuses, airway), for use in planning and diagnostic support in adult and pediatric care.

Devices of the i-CAT family comprise a package of software modules capable of handling 2D and 3D data. This includes 3D reconstruction, storage, retrieval, viewing, and processing of 2D and 3D-image data.

i-CAT FLX V series / KaVo 3D eXam+ V series manufactured by Imaging Sciences International, is a Cone Beam Volumetric Tomography and Panoramic X-ray dental imaging system that consists of a scanner and a software package for image reconstruction. The two models, i-CAT FLX / KaVo 3D eXam+, are of identical design in the i-CAT Scanner family. The components of the system include the main affixed unit, the overhead, the gantry, the tube head, the X-ray source assembly and collimator, the receptor panel, and software package for image reconstruction. The system is an open design that allows patients to sit upright during a procedure. An electric powered seat is built into the scanner for proper patient positioning. The V series refer to 3 different fieldof-view configurations (V8, V10, V17) available on each model based on licensing of the acquisition software.

The software package includes a device specific software package (SmartScan STUDIO) that is required to operate the i-CAT FLX System through a visual touchscreen interface and a post-processing imaging software. The modules within the device specific software perform the Image Acquisition, Quality Assurance, Device Calibration, and Image Reconstruction and Processing functionalities of the device. The software utilizes a modified Feldkamp algorithm for reconstruction. There is a basic DICOM viewer component (with limited image viewing capabilities) for the operator to ensure that the data collection and image processing are correct. Also provided with the device is a postprocessing imaging software, such as TxSTUDIO marketed under K123519. It is a volumetric imaging software designed specifically for dental clinicians, intended for use as a planning and simulation software in the placement of dental implants, orthodontics and surgical treatment. The imaging software reads DICOM data from dental CT machines, such as devices in the i-CAT family.

Cone Beam Volumetric Tomography is a medical imaging technique that uses X-rays to obtain cross-sectional images of the head or neck. The proposed device is a CBCT dental system with 2 modes of operation: panoramic and CBCT.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text.

Important Note: The provided document is a 510(k) summary from the FDA for a dental imaging system (i-CAT FLX V series / KaVo 3D eXam+ V series). It primarily focuses on demonstrating substantial equivalence to predicate devices rather than providing a detailed clinical study with acceptance criteria for an AI algorithm's performance. Therefore, the information typically requested for AI/algorithm performance (like MRMC studies, specific expert adjudication details, ground truth establishment for a training set) is not present in this type of regulatory submission, as the device is a hardware imaging system with associated software for image acquisition and reconstruction, not an AI-driven diagnostic tool.

The "study" described here is more akin to a verification and validation of the imaging system itself to ensure it produces images of diagnostic quality compared to legally marketed predicate devices.

Acceptance Criteria and Reported Device Performance

1. Table of Acceptance Criteria and Reported Device Performance

Since this is an imaging system and not an AI algorithm with specific performance metrics like sensitivity/specificity, the "acceptance criteria" revolve around demonstrating comparable image quality and functionality to predicate devices. The document implies that the acceptance criteria are met if the device can produce volumetric and panoramic images of the maxillofacial (including ENT) areas in the head, and these images are of equivalent diagnostic quality as the predicate devices. The specific quantitative metrics for image quality are implied through the comparison table and the general statement of "acceptable clinical effectiveness."

"Clinical images acquired using i-CAT FLX/KaVo 3D eXam+ were reviewed by qualified clinicians to be of acceptable clinical effectiveness for the proposed indications for use." No specific quantitative metrics (e.g., SNR, contrast, resolution values) from a comparative study are detailed in this summary. |
| Technological Equivalence/Safety: Minor technological differences do not affect imaging of anatomical structures or raise new safety concerns. | "The minor technological difference in the shape of image volumes does not affect imaging of the intended anatomical structures."

"Based upon an analysis of the technological differences, and the substantiation through design verification and validation, ISI determines that the proposed i-CAT FLX / KaVo 3D eXam+ is substantially equivalent to the predicate devices... and does not raise any new concerns."

Compliance with various IEC standards (IEC 60601-1, 60601-1-2, 60601-1-3, 60601-1-6, 60601-2-63, 62366) and biocompatibility testing was also reported. |
| Functional Equivalence: Device offers similar functionalities to predicate devices. | The device provides "3D reconstruction, storage, retrieval, viewing, and processing of 2D and 3D-image data," similar to its predicates. It supports various imaging procedures (implants, TM Joints, reconstructed panoramic/cephalometrics, airway/sinus, nerve canal, conventional digital panoramic). |

Study Details (as inferable from the document)

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

   • Sample Size: Not specified quantitatively. The document states "Clinical images acquired using i-CAT FLX/KaVo 3D eXam+ were reviewed." This implies a set of clinical images were used, but the number of cases or patients is not provided.
   • Data Provenance: Not specified (e.g., country of origin). It's a general statement about "clinical images." It reads as if the images were likely prospectively acquired using the device itself for testing purposes, rather than being a retrospective dataset.

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

   • Number of Experts: Not specified. The document states "reviewed by qualified clinicians."
   • Qualifications of Experts: "Qualified clinicians" is the only description provided. Specifics like "radiologist with 10 years of experience" are not mentioned.

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

   • Adjudication Method: Not specified. It merely says "reviewed by qualified clinicians." There's no indication of a consensus or adjudication process.

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

   • MRMC Study: No, an MRMC study was not detailed. This submission is for an imaging system hardware/software combination, not an AI-assistance diagnostic tool.
   • Human Reader Improvement with AI: Not applicable, as this device itself is the image acquisition and reconstruction system, not an AI for image interpretation or reader assistance.

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

   • Standalone Performance: Not applicable in the context of an AI algorithm. The "algorithm" here refers to the image reconstruction algorithm (modified Feldkamp algorithm), and its performance is inherently evaluated through the diagnostic quality of the reconstructed images, which were "reviewed by qualified clinicians to be of acceptable clinical effectiveness."

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

   • Type of Ground Truth: The "ground truth" for this type of submission is the diagnostic quality perceived by qualified clinicians when reviewing images produced by the device, implicitly compared against what they would expect from a predicate device. It's not a "ground truth" for a specific disease or condition in the way a pathology report would be.

8. The sample size for the training set:

   • Sample Size: Not applicable. This document does not describe the development or training of a machine learning or AI model; it describes a medical imaging device. The "training set" concept does not apply here.

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

   • Ground Truth Establishment: Not applicable, as there is no "training set" in the context of an AI model's development in this submission. The image reconstruction algorithms are based on physics and mathematical principles, not trained on a dataset with "ground truth" labels.

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Dexis Webview is a web-based software used for general dental and maxillofacial diagnostic image review that allows users alternate access to image data using a common web-browser. It provides the ability to view, enhance, annotate, compare, and export images by accessing an existing image database available in a distributed environment.

Dexis Webview is indicated for use only by prescription and by a trained and qualified dentist or dental technician.

Dexis Webview is a web browser-based accessory software application that allows users to access preexisting imaging data remotely. Users are able to view, enhance, annotate, compare, and export preexisting images using the Dexis Core database using a web-browser. The intended use of the device is to allow dentists to be able to diagnose remotely using a traditional web-browser running on a desktop PC or Apple Mac.

The Dexis Webview Software is a software program for general dental and maxillofacial diagnostic imaging. It provides the ability to view, enhance, annotate, compare, and export images by accessing an existing image database available in a distributed environment. It allows remote access to x-ray digital images acquired from digital imaging systems. It can also handle other types of images acquired by digitizing film with a flatbed scanner, or color images from intraoral dental cameras as long as they are stored in an accessible database.

The provided text is a 510(k) summary for the Dexis Webview device. It describes the device, its intended use, and argues for its substantial equivalence to a predicate device (Dexis Software K140445). However, it does not contain the information requested regarding acceptance criteria, a specific study demonstrating performance against criteria, sample sizes, ground truth establishment, or human reader effectiveness studies.

The document discusses "Performance Data" in a general sense, focusing on verification and validation testing, conformance to a risk management standard (ISO 14971), and a claim that the Dexis Webview performs equivalently in functionality to the predicate device for viewing, enhancing, annotating, comparing, and exporting images. It explicitly states: "The safety and effectiveness of the Dexis Webview web-browser software was evaluated via bench testing. verification and validation testing, and conformance to international conformance standards." This is a general statement about software development practices, not a detailed description of a clinical or analytical performance study demonstrating specific acceptance criteria.

Therefore, most of the requested information cannot be extracted from the provided text.

Here's what can be inferred or stated as unavailable:

1. Table of acceptance criteria and reported device performance:

• Not available. The document states "Performance data (Verification and Validation) demonstrate that Dexis Webview web-browser software functions equivalently to the Dexis Software predicate device," but does not list specific acceptance criteria or quantitative performance metrics against them.

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

• Not available. The document mentions "bench testing, verification and validation testing" but does not provide details on sample sizes or data provenance (e.g., country of origin, retrospective/prospective nature of data).

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

• Not available. As no specific performance study with a test set and ground truth is described, this information is absent.

4. Adjudication method for the test set:

• Not available. For the same reasons as above.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and its effect size:

• Not done/Not described. The document focuses on demonstrating substantial equivalence based on technological characteristics and functional equivalence to the predicate device. It does not mention any MRMC study comparing human readers with or without AI assistance. The device is described as an image review software, not an AI-assisted diagnostic tool in the sense of providing automated interpretations.

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

• Not applicable/Not described. The Dexis Webview is a viewing and processing tool for human operators, not an autonomous algorithm that provides diagnostic outputs. Its "performance" would be related to display quality, functionality of tools, and data integrity, rather than standalone diagnostic accuracy.

7. The type of ground truth used:

• Not available. No specific ground truth establishment is described as there is no detailed performance study presented.

8. The sample size for the training set:

• Not applicable/Not available. The Dexis Webview is described as software for viewing, enhancing, annotating, comparing, and exporting images. It is not an AI/ML device that would typically involve a "training set" for model development. Its development would involve software engineering and testing against functional requirements.

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

• Not applicable/Not available. For the same reasons as above.

In summary, the provided 510(k) summary focuses on demonstrating substantial equivalence to a predicate device based on functional and technological characteristics, rather than reporting on a detailed clinical or analytical performance study with specific acceptance criteria and outcome metrics.

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VixWin Platinum is a software program for general dental and maxillofacial diagnostic imaging. It controls capture, display, enhancement, and saving of digital images from various digital imaging systems. It stores and communicates these images within the system or across computer systems at distributed locations.

VixWin Platinum is a software program for general dental and maxillofacial diagnostic imaging. It controls capture, display, enhancement, and saving of digital images from various digital imaging systems. It stores and communicates these images within the system or across computer systems at distributed locations.

VixWin Platinum Software has the following functionality which compares with the functionality provided for VixWin PRO predicate cleared under K060178. The functionality has been updated to remove legacy hardware no longer supported by the VixWin Platinum Software.

• Controls scanning and intake of x-ray images from imaging plates with the Photo-Stimulable ● Phosphor (PSP) scanners.
• Controls the direct capture of x-ray images from intra-oral sensors and extra-oral systems. ●
• Allows View and capture color images from intra-oral and extra-oral cameras. ●
• . Export and import digital images (such as those obtained by scanning a film).
• . Process images with dental specific tools to enhance their diagnostic value.
• . Analyze and enhance images to gather additional diagnostic information which may not be immediately apparent on initial visual inspection.
• Obtaining and storing patient data pertaining to those images
• Both the viewing of the images and storage of the images and their associated data. ●
• Managing (locally and remotely) a database of patients and related data.
• Allows the update of existing patient information and the creation and storage of new patient information in a database over the network.
• . Allows access to patient files from multiple workstations via network connectivity.
• . Allows printing images and image related information over the network.

VixWin Platinum can be utilized either locally or over a networked environment. If VixWin Platinum is installed on several computers, the patient and image database can be shared among them and used from different workstations.

The provided text describes a 510(k) premarket notification for the device "VixWin Platinum." This document is a regulatory submission for a medical device that aims to demonstrate its substantial equivalence to a legally marketed predicate device, not typically a study proving performance against acceptance criteria for an AI/ML device in the sense of accuracy, specificity, or sensitivity. Therefore, much of the requested information (sample sizes, expert ground truth, adjudication methods, MRMC studies, standalone performance, training set details) is not applicable or not present in this type of regulatory submission.

The document primarily focuses on establishing substantial equivalence based on technological characteristics and intended use, rather than a quantitative performance study.

Here's an analysis based on the provided document:

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

There are no specific quantitative "acceptance criteria" for diagnostic performance (e.g., sensitivity, specificity, AUC) or reported performance metrics against such criteria in this document. The "performance" described relates to the functionality of the software.

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

• Not applicable / Not provided. The document states that "All internal verification and validation has been completed," but does not detail a specific test set, its size, or data provenance for proving diagnostic performance equivalence. The comparison is primarily structural and functional.

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)

• Not applicable / Not provided. Ground truth establishment is not mentioned as part of this type of regulatory submission for a Picture Archiving and Communication System (PACS) software primarily focused on processing and displaying images.

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

• Not applicable / Not provided.

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 / Not provided. This device is a PACS software, not an AI-assisted diagnostic tool.

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

• Not applicable / Not provided. This is a PACS software, not an autonomous algorithm for diagnosis.

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

• Not applicable / Not provided. The "performance data" refers to functional verification and validation that the software operates as intended and equivalently to its predicate, not against a clinical ground truth for diagnostic accuracy.

8. The sample size for the training set

• Not applicable / Not provided. This software is not an AI/ML model that would require a distinct training set in the conventional sense.

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

• Not applicable / Not provided.

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Devices of the i-CAT family consist of an x-ray system that uses a cone beam with a rotational sequence, providing two dimensional images and three dimensional volume reconstructions of the head area, which includes ENT and maxillofacial areas (such as TM Joint studies, mandible & maxilla for implant planning and diagnostic support in adult and pediatic care. Devices of the i-C AT family comprise a package of software modules capable of handling 2D and 3D data. This includes 3D reconstruction, storage, retrieval, viewing, and processing of 2D and 3D-image data.

i-CAT FLX was developed as an upgrade to the existing i-CAT Scanner. i-CAT FLX, manufactured by Imaging Sciences International, is a Cone Beam Volumetric Tomography and Panoramic X-ray dental imaging system that consists of a scanner and a software package for image reconstruction. It is a device in the i-CAT Scanner family. The components of the system include the main affixed unit, the overhead, the gantry, the tube head, the X-ray source assembly and collimator, the receptor panel, and software package for image reconstruction. The system is an open design that allows patients to sit upright during a procedure. An electric powered seat is built into the scanner for proper patient positioning.

Cone Beam Volumetric Tomography is a medical imaging technique that uses X-rays to obtain crosssectional images of the head or neck. The proposed device utilizes cone beam X-ray technology, which generates conical x-ray beams that rotate around the patient's head and incident upon the receptor that generate sufficiently contrasted images. Quality of the images depends on the level and amount of X-ray energy delivered to the tissue. When interpreted by a trained physician, these images provide useful diagnostic information.

Here's an analysis of the provided text regarding the acceptance criteria and study for the i-CAT FLX Cone Beam 3D and 2D Panoramic Dental Imaging System:

The provided document is a 510(k) summary for the i-CAT FLX system, rather than a detailed study report with specific acceptance criteria metrics. In 510(k) submissions, the primary goal is to demonstrate "substantial equivalence" to a legally marketed predicate device, not necessarily to meet pre-defined quantitative acceptance criteria against a specific benchmark. Therefore, the "acceptance criteria" discussed here are focused on demonstrating equivalence in performance, safety, and effectiveness.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify a distinct "test set" in the context of an algorithm's performance evaluation. The testing described is more akin to design verification and validation for a hardware/software system.

• "Clinical Test Data" for "acceptable clinical effectiveness": The document states "Sample clinical images acquired using i-CAT FLX were reviewed to be of acceptable clinical effectiveness for the proposed indications for use."
  • Sample Size: Not specified. It refers to "Sample clinical images," implying a subset, but no number is given.
  • Data Provenance: Not specified (e.g., country of origin, retrospective or prospective). It only states images were "acquired using i-CAT FLX."

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

• Number of Experts: Not specified. The document mentions "When interpreted by a trained physician, these images provide useful diagnostic information" but does not detail the number or role of experts in the "acceptable clinical effectiveness" review.
• Qualifications of Experts: Not specified. It generally refers to "trained physician."

4. Adjudication Method for the Test Set

• Adjudication method: Not specified. The phrase "reviewed to be of acceptable clinical effectiveness" suggests an expert review process, but details of how disagreements or consistency were handled are not provided.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

• MRMC Study: No, an MRMC comparative effectiveness study, especially one involving human readers with and without AI assistance, was not described. The goal of this submission was to demonstrate substantial equivalence of a new imaging system to existing ones, not to evaluate an AI's impact on human performance. The "AI" would be the image reconstruction software, which is intrinsic to the device, not an add-on for comparative effectiveness with human readers.

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

• Standalone Performance: The "algorithm" in this context refers to the image reconstruction software within the i-CAT FLX system. Its "standalone performance" is implicitly evaluated through the "Design Verification and Validation" which determined that the system "can produce volumetric and panoramic images... and they are of equivalent diagnostic quality as GALILEOS." This is a system-level performance evaluation, not a focused algorithm-only study against a specific metric.

7. The Type of Ground Truth Used

• Type of Ground Truth: For the "acceptable clinical effectiveness" of sample images, the ground truth appears to be expert consensus/interpretation by unspecified "trained physician(s)" that the images provided "useful diagnostic information" and were of "acceptable clinical effectiveness." This is inferred, as no explicit ground truth methodology is detailed. For the physical and technical performance (e.g., image quality compared to a predicate, biocompatibility, electrical safety), the ground truth is based on compliance with established standards and direct comparison to a predicate device's known performance.

8. The Sample Size for the Training Set

• Sample size for training set: Not applicable and not specified. This document describes an imaging system, not a machine learning model developed with a distinct "training set" in the modern AI sense. The software package for image reconstruction is an integral part of the device.

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

• Ground truth for training set: Not applicable and not specified, as there is no separate "training set" for an AI algorithm described in this submission. The software development and verification would have relied on engineering principles and established image processing techniques, rather than a labeled training dataset in the context of supervised machine learning.

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The DEXIS software is a software program for general dental and maxillofacial diagnostic imaging. It controls capture, display, enhancement and saving of X-ray digital imaging systems. It can also handle other types of images acquired by digitizing film with a flat bed scanner, or color images from intra-oral and extra-oral dental cameras.

The DEXIS software is a software program for general dental and maxillofacial diagnostic imaging. It controls capture, display, enhancement and saving of X-ray digital imaging systems. It can also handle other types of images acquired by digitizing film with a flat bed scanner, or color images from intra-oral and extra-oral dental cameras.

The provided text is a 510(k) premarket notification approval letter for the "DEXIS Software." This document primarily focuses on the regulatory approval process and does not contain the detailed study information required to answer your specific questions about acceptance criteria and device performance.

Therefore, I cannot provide the information requested from the given text. The document confirms that the device is substantially equivalent to legally marketed predicate devices, but it does not include the results of performance studies, acceptance criteria, sample sizes, ground truth establishment, or expert qualifications.

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