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EzDent Web is a dental imaging software that is intended to provide viewer and image processing tools for maxillofacial radiographic images. These tools are available to view and interpret a series of DICOM compliant dental radiology images and are meant to be used by trained medical professionals such as radiologist and dentist.

EzDent Web is intended for use as software to acquire, view, and save 2D and 3D image files, to load DICOM project files from panorama, cephalometric, and intra-oral imaging equipment, and to provide 3D visualization and 2D analysis.

EzDent Web v1.2 is a dental imaging software that enables you to save, manage, view and process patients' images. EzDent Web is equipped with management and processing system for various 2D and 3D images. In addition, EzDent Web provides media contents for patient consultation and user friendly instruction to assist your use of the software.

EzDent Web provides you with the following functions using patient images in 2D and 3D.

• . Manage patient information
• View patient images in 2D/3D using tools for image processing and view function.
• . Use high resolution 3D volume rendering to view 3D images in the optimized view for user intent.
• . Consult patients using media contents provided for patient consultation.

EzDent Web can be used in a networked environment. If EzDent Web is installed in several computers, the patient and image database can be shared among them and used on different workstations.

The software level of concern is Moderate.

The provided FDA 510(k) summary for EzDent Web (K230468) indicates that the device has the same indications for use and technical characteristics as its predicate device (K211700). The submission focuses on demonstrating substantial equivalence for software modifications and does not contain information about a study proving the device meets specific acceptance criteria related to AI/ML performance, diagnostic accuracy, or human interpretability studies (e.g., MRMC).

The changes described are primarily feature upgrades for user convenience and system requirements, not changes to core diagnostic capabilities or the introduction of AI/ML algorithms that would necessitate the types of performance studies you are asking about (e.g., sensitivity, specificity, human reader improvement with AI assistance).

Therefore, based on the provided text, I cannot fill out the requested table or answer most of your detailed questions about acceptance criteria and study proving device performance in the context of AI/ML or comparative diagnostic accuracy.

Here's a breakdown of what can be inferred from the provided text, and what cannot:

Information that CANNOT be Extracted from the Provided Text:

• A table of acceptance criteria and reported device performance (in terms of diagnostic accuracy/AI performance): The document does not define such criteria or report on diagnostic accuracy metrics (e.g., sensitivity, specificity, AUC) for the device's performance. The "performance data" section briefly mentions "SW verification/validation and the measurement accuracy test," but does not provide details of what was measured, the criteria, or the results beyond "passed all of the tests based on pre-determined Pass/Fail criteria." This refers to software functionality and measurement accuracy of existing tools, not AI/ML performance.
• Sample size used for the test set and data provenance: No information on a test set for diagnostic performance.
• Number of experts used to establish ground truth & qualifications: Not applicable for this type of submission focused on substantial equivalence of software features.
• Adjudication method for the test set: Not applicable.
• Multi-Reader Multi-Case (MRMC) comparative effectiveness study, including effect size: Not applicable. The device is described as "viewer and image processing tools," not an AI-powered diagnostic assist tool that would typically undergo MRMC studies.
• Standalone (algorithm only) performance: Not applicable as it's not an AI algorithm.
• Type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable.
• Sample size for the training set: Not applicable as it's not an AI model.
• How the ground truth for the training set was established: Not applicable.

Information that CAN be Inferred or Directly Stated from the Provided Text (regarding software changes, not diagnostic performance):

1. Acceptance Criteria & Reported Performance:

   • Acceptance Criteria (Implied for Software Functionality): The device "passed all of the tests based on pre-determined Pass/Fail criteria." These tests relate to "SW verification/validation and the measurement accuracy test" for the modified features.
   • Reported Device Performance: The modifications are described as "additional features for user convenience" and "do not affect the device safety or effectiveness." This implies that the software performed as intended for these new convenience features and that existing functionalities (e.g., image viewing, manipulation, measurement) maintained their accuracy. No quantitative performance metrics are provided for the "measurement accuracy test" beyond a pass/fail.

2. Sample Size and Data Provenance:

   • Not applicable for diagnostic performance studies. The submission is about software functionality updates.

3. Experts and Ground Truth Establishment for Test Set:

   • Not applicable as this is a software update for an existing image management system, not a diagnostic AI system requiring expert-adjudicated ground truth. The device is
     "meant to be used by trained medical professionals such as radiologist and dentist."

4. Adjudication Method for Test Set:

   • Not applicable.

5. MRMC Comparative Effectiveness Study:

   • No MRMC study was done. The document does not describe the device as providing AI assistance to human readers for diagnostic interpretation. Its function is "viewer and image processing tools."

6. Standalone (Algorithm Only) Performance:

   • No standalone algorithm performance was done. This device is an image management and processing system, not a standalone diagnostic algorithm.

7. Type of Ground Truth Used:

   • Not applicable for this type of software modification. The existing "measurement accuracy test" for tools like linear distance, angle, etc., would rely on known measurements in test images, but details are not provided.

8. Sample Size for Training Set:

   • Not applicable. This is not an AI/ML device that requires a training set.

9. How Ground Truth for Training Set was Established:

   • Not applicable.

Summary of the Study (Based on Provided Text):

The study described in the 510(k) summary for EzDent Web (K230468) was a software verification and validation effort. Its purpose was to demonstrate that the updated version of EzDent Web (v1.2) is substantially equivalent to its predicate device (EzDent Web v1.0, K211700).

The "study" assessed the performance, functionality, and reliability of the modified device through "SW verification/validation and the measurement accuracy test." The primary conclusion was that the device "passed all of the tests based on pre-determined Pass/Fail criteria." The changes were identified as "additional features for user convenience" and enhancements to "PC System Requirement Information," "EzDent Web Settings," "PATIENT Page," and "VIEWER Page," rather than fundamental changes impacting diagnostic accuracy or introducing new AI capabilities. No clinical study involving human readers or diagnostic performance metrics was conducted or required for this type of submission.

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EzDent Web is a dental imaging software that is intended to provide viewer and image processing tools for maxillofacial radiographic images. These tools are available to view and interpret a series of DICOM compliant dental radiology images and are meant to be used by trained medical professionals such as radiologist and dentist.

EzDent Web is intended for use as software to acquire, view, and save 2D and 3D image files, to load DICOM project files from panorama, cephalometric, and intra-oral imaging equipment, and to provide 3D visualization and 2D analysis. EzDent Web is not for use for diagnostic purposes.

EzDent Web is a dental imaging software that enables you to save, manage, view and process patients' images. EzDent Web is equipped with management and processing system for various 2D and 3D images. In addition. EzDent Web provides media contents for patient consultation and user friendly instruction to assist your use of the software.

EzDent Web provides you with the following functions using patient images in 2D and 3D.

• Manage patient information
• View patient images in 2D/3D using tools for image processing and view function.
• Use high resolution 3D VR to view 3D images in the optimized view for user intent.
• Consult patients using media contents provided for patient consultation.

EzDent Web can be used in a networked environment. If EzDent Web is installed in several computers, the patient and image database can be shared among them and used on different workstations.

The provided text describes EzDent Web, a dental imaging software, and its substantial equivalence to predicate devices (EzDent-i and Ez3D-i v5.2). However, it does not contain specific acceptance criteria, detailed study designs, or performance metrics that would allow for a comprehensive answer to all parts of the request.

Here's a breakdown of what can be extracted and what is missing based on the provided document:

Description of Acceptance Criteria and Proving Device Adherence

The document states that "SW verification/validation and the measurement accuracy test were conducted to establish the performance, functionality and reliability characteristics of the modified devices. The device passed all of the tests based on pre-determined Pass/Fail criteria."

However, the specific "pre-determined Pass/Fail criteria" (acceptance criteria) and the "reported device performance" are not detailed in the provided text. Therefore, a table explicitly outlining these cannot be generated from this document.

Detailed Information about the Study:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: Not specified in the document.
• Data Provenance: Not specified in the document (e.g., country of origin, retrospective or prospective).

3. Number of Experts and their Qualifications for Ground Truth Establishment:

• Not specified in the document. The document mentions the software is "meant to be used by trained medical professionals such as radiologist and dentist," but it does not describe their involvement in establishing ground truth for testing.

4. Adjudication Method for the Test Set:

• Not specified in the document.

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

• Was it done? No, the document does not mention an MRMC study or any comparison of human readers with or without AI assistance.
• Effect Size: Not applicable, as no MRMC study is reported.

6. Standalone (Algorithm Only) Performance Study:

• Was it done? The document describes "SW verification/validation and the measurement accuracy test" and that the "device passed all of the tests." This suggests a standalone performance evaluation of the software's functionalities. However, specific details of this standalone performance (e.g., accuracy, precision for specific tasks) are not provided. The device is purely software, so its "performance" would inherently be standalone in its function.

7. Type of Ground Truth Used:

• Not specified in the document. Given the context of dental imaging software for viewing and processing, potential ground truths could include expert consensus on image quality, accurate measurement validation, or comparison to established benchmarks for image processing functions. However, the document does not elaborate.

8. Sample Size for the Training Set:

• The document describes a "verification/validation" study for the modified device and states its similarity to predicate devices. It does not mention a "training set" in the context of an AI/machine learning model, which this device, as described, does not appear to be. It's a medical image management and processing system.

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

• Not applicable, as a "training set" in the context of machine learning is not mentioned or implied for this device. The document describes a software system for viewing and processing images, not an AI diagnostic tool that requires a training phase.

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