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The OnDemand3D92 is intended for use as a software package which loads DICOM images from CT, MR, X-Ray, stores those and provides 3D visualization and 2D analysis, various MPR (Multi-Planar Reconstruction) functions for further rapid and precise diagnosis.

It also provides the following functions as shown below.

• 1. Functions for implant surgery planning and fabricating a surgical guide according to the plan
• 2. Functions to combine and show the image data from different modalities such as CT, MRI and PET in one window at the same time
• 3. Functions to create orthodontic analysis using 3D volume data
• 4. Functions to sort and save DICOM files, Project Files and 2D image files from different modality [Panorama, Cephalometric, intraoral] under a single patient name

OnDemand3DS2 is a personal computer based dental imaging software which I oads DICOM images taken from CT, MR and provides 3D visualization and 2D analysis, various MPR (Multi-Planar Reconstruction) functions for further rapid and precise diagnosis. It is also intended to plan an implant surgery, fabricate a surgical guide according to the plan, superimpose and stitch multi DICOM da ta sets, mark anatomical landmark from CT data and provide analyzed data for orthodontic treatment while software provides 2D image viewing module enabli ng 2D image acquisition specialized in 2D scanned image supporting DICOM, BITMAP, JPG, TIF.

OnDemand3D22 is designed to provide with users and familiar user-interface easy. Also OnDemand3D22 makes it possible to manage medical images more easily and provides advanced tools for 2D and 3D analysis with various rendering functions.

The provided text does not contain detailed information about specific acceptance criteria or a dedicated study proving the device meets them. The submission is a 510(k) summary for a Picture Archiving and Communications System (PACS) software, OnDemand3D92, which primarily focuses on demonstrating substantial equivalence to predicate devices rather than proving specific performance metrics against defined acceptance criteria.

However, based on the descriptive sections of the 510(k) summary, we can infer the intent of the device's capabilities. If we were to hypothesize acceptance criteria based on its stated functions, and then describe how the submission generally addresses performance through its claims of substantial equivalence and intended use, we could construct a response.

Therefore, the following table and subsequent sections are hypothetical in terms of explicit acceptance criteria and a detailed study report. They are constructed by interpreting the device's functions and the nature of a 510(k) submission, which relies on demonstrating equivalence rather than presenting an exhaustive performance study against novel criteria.

1. Table of Acceptance Criteria and Reported Device Performance

As the 510(k) summary does not explicitly list acceptance criteria or specific quantitative performance metrics from a dedicated study, the table below provides hypothetical acceptance criteria derived from the device's stated functions and then indicates how the submission implicitly addresses performance through its nature as a PACS system seeking substantial equivalence.

Study Information (Based on 510(k) Summary, which typically relies on substantial equivalence rather than a de novo clinical study):

The provided 510(k) summary does not describe a specific clinical study designed to prove the device meets explicit acceptance criteria. Instead, it leverages the concept of substantial equivalence to predicate devices. This means the manufacturer is asserting that their device is as safe and effective as existing legally marketed devices, and therefore does not require new rigorous clinical testing for each feature.

Therefore, many of the requested details about "the study" are not directly applicable in the context of this 510(k) summary. We will address each point based on what can be inferred or what is typical for a 510(k) submission of this nature.

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

• Sample Size: The 510(k) summary does not specify a "test set" sample size for a performance study. For a PACS system seeking substantial equivalence, testing largely involves software validation (e.g., unit testing, integration testing, system testing for functionality, DICOM conformance) and comparison of specifications and intended use against predicate devices. While internal testing would have occurred, quantitative metrics or specific patient datasets used for such validation are not detailed in this public summary.
• Data Provenance: Not explicitly stated. For internal software validation, proprietary or publicly available DICOM datasets would likely be used, along with data from beta testing sites. The country of origin of the data is not mentioned. It is not specified if the data was retrospective or prospective.

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

• This information is not provided in the 510(k) summary. Given the nature of a PACS software submission focused on substantial equivalence, a formal ground truth establishment by a panel of medical experts for a comparative effectiveness study is not typically included unless new clinical claims are being made.

4. Adjudication Method:

• Not applicable/Not described. Since a formal clinical performance study with expert interpretation and ground truth establishment is not detailed, an adjudication method for such a test set is not presented.

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

• No. A MRMC comparative effectiveness study is not mentioned or described in this 510(k) summary. The submission focuses on demonstrating substantial equivalence based on features and functionality aligning with predicate devices, not on proving an improvement in human reader performance with or without AI assistance. The device is primarily a visualization, analysis, and management tool, not an AI-assisted diagnostic aid that directly impacts reader interpretation accuracy in the manner typically assessed by MRMC studies for diagnostic algorithms.

6. Standalone (Algorithm Only) Performance Study:

• No. A standalone performance study of an "algorithm only" component is not described. The OnDemand3D92 is a software package with multiple functions (visualization, analysis, planning, management). Its performance is evaluated in the context of its intended use as a medical device software, which often involves software validation and testing for functionality, accuracy of measurements, and DICOM conformance, rather than a standalone algorithm performance study.

7. Type of Ground Truth Used:

• For the purpose of this 510(k) submission, the "ground truth" implicitly relies on the established performance and safety of the predicate devices. The claim of substantial equivalence suggests that the functionalities of OnDemand3D92 (e.g., rendering, measurements, image registration) are within acceptable clinical parameters, validated by comparison to existing, legally marketed systems. There is no mention of pathology, expert consensus (for a new diagnostic claim), or outcomes data being used as ground truth for a novel performance study.

8. Sample Size for the Training Set:

• Not applicable/Not provided. This is not an AI/Machine Learning diagnostic device that would typically have a "training set" in the context of developing a predictive algorithm. It is a software system for image management, visualization, and analysis. Therefore, a training set as understood in AI/ML development is not relevant here, and no sample size is consequently provided.

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

• Not applicable/Not provided. As there is no described training set or AI/ML algorithm development, the method for establishing its ground truth is not relevant to this submission.

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The OnDemand3D™ is intended for use as a software package which loads DICOM images from CT, MR, X-Ray, stores those and provides 3D visualization and 2D analysis, various MPR (Multi-Planar Reconstruction) functions for further rapid and precise diagnosis.

OnDemand3D™ is a personal computer based dental imaging software which loads DICOM images taken from CT, MR and provides 3D visualization and 2D analysis, various MPR (Multi-Planar Reconstruction) functions for further rapid and precise diagnosis. OnDemand3D™ is designed to provide users easy and familiar user-interface. Also OnDemand3D™ makes it possible to manage medical images more easily and provides advanced tools for 2D and 3D analysis with various rendering functions.

The provided 510(k) summary for CyberMed, Inc.'s OnDemand3D™ device
does not contain information about acceptance criteria or a study that proves the device meets specific performance metrics.

The document is a submission to the FDA for 510(k) clearance, which primarily focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed performance study data against predefined acceptance criteria.

Therefore, I cannot populate the requested table or answer the specific questions about standalone performance, MRMC studies, sample sizes, expert qualifications, or ground truth establishment.

The document states:

• Purpose: "This summary of 510(k) safety and effectiveness information is being submitted in accordance with requirements of 21 CFR Part 807.92."
• Conclusion: "CyberMed, Inc. concludes that OnDemand3D™ is safe and effective and substantially equivalent to predicate devices as described herein."

This indicates that the submission is based on substantial equivalence, which typically does not involve the detailed performance studies with acceptance criteria that would be found for novel devices or those undergoing PMA. If such performance studies were conducted, they are not detailed in this 510(k) summary.

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Use as a software for the display and 3D visualization of dental image files from scanning devices such as CT, MRI for radiologists, dental clinicians and practitioners to acquire, process, render, review, store, print and distribute DICOM 3.0 complaint image studies, utilizing standard PC hardware.

Accurex™ is a dental imaging software which loads DICOM images taken from CT. MR and provides 3D visualization, 2D image reformation and various diagnosis tools for dentists on PC, laptop or PACS Workstation. Dentists can do further precise and accurate pre/post-operative diagnosis by using advanced image reformation and generation functionality of Accurex™ such as Panoramic image and Cephalometric x-ray imaqe as well as 3D volume rendering image.

The provided 510(k) summary for CyberMed, Inc.'s Accurex device (K061126) focuses on demonstrating substantial equivalence to predicate devices (V-works and Vimplant) based on its functional description and intended use. It does not contain information about specific acceptance criteria, a formal study design the proves the device meets the acceptance criteria (beyond functional testing), reader performance, or detailed ground truth establishment for a test set.

Therefore, I cannot populate the requested table and details regarding a specific study proving acceptance criteria. The document primarily describes the device's features and its compliance with DICOM 3.0 standards, comparing it generally to predicate devices in terms of functionality for image processing and visualization in a dental context.

However, I can extract information related to the device's capabilities and its intended use, which inherently imply certain functional acceptance.

Here's what can be inferred and what information is missing:

1. Table of Acceptance Criteria and Reported Device Performance

As noted above, no specific quantitative acceptance criteria or reported performance metrics (like sensitivity, specificity, accuracy, or reader agreement statistics) are provided in the document. The document asserts the device's functionality and substantial equivalence to previously cleared devices.

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

• Sample Size: Not specified.
• Data Provenance: Not specified. The document mentions loading DICOM images from CT/MR devices, but does not detail the origin or nature of data used for any testing.
• Retrospective/Prospective: Not specified.

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.
• Qualifications of Experts: Not specified.

4. Adjudication method for the test set

• Adjudication Method: Not specified.

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 is not mentioned or implied. The device is described as an image processing and visualization tool, not an AI diagnostic aid that would directly assist human readers in interpretation or improve their performance. The purpose is to provide "further precise and accurate pre/post-operative diagnosis" by enabling the practitioner to view and manipulate images.

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

• Standalone Performance: Not explicitly detailed with performance metrics. The document describes the algorithm's capabilities (e.g., 3D image construction via Volume Rendering) and states that "3D Algorithm was cleared in Vworks((K013878)." This implies that the core 3D processing algorithms underwent some form of validation in the predicate device, but specific standalone performance metrics for Accurex are not provided.

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

• Type of Ground Truth: Not specified in relation to any formal testing or validation within this document. The device is a display and processing software, implying that the "ground truth" would relate to the accuracy of image rendering, measurements, and reformations compared to the source DICOM data and established imaging principles, rather than a diagnostic outcome.

8. The sample size for the training set

• Training Set Sample Size: Not applicable. The document describes image processing software, not a machine learning or AI algorithm that would typically require a "training set" in the conventional sense for a diagnostic model. While algorithms might have been developed using data, a dedicated "training set" for a submitted AI model is not indicated.

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

• Ground Truth Establishment for Training Set: Not applicable, as no training set for an AI model is indicated.

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The Vimplant is intended for use as a software interface for the transfer of imaging information from a CT scanner and also as a pre-operative software for simulation and evaluation dental implant placement and surgical treatment options.

VImplant™ is a dental implant simulation software for dentists and implantologists. By use of VImplant™, dental practicians can plan and practice their surgery in advance so they can reduce some risks which can happen during their real surgery. Vimplant™ provides very useful and needful functions. It contains functions of implant simulation, manipulation with 2D and 3D mode, nerve identification, and evaluation of bone density. By using Vimplant TM, dental practicians can quickly and easily simulate implant surgery on their desktop PCs. This enables them to conduct implant surgery more effectively by isolating the exact implant position site and angle and to assist in deciding the proper implant diameter, length, etc.

The provided text is a 510(k) summary for the Vimplant™ Dental implant simulation software. It focuses on demonstrating substantial equivalence to predicate devices and describes the software's functionalities and intended use. However, it does not contain the specific information required to answer your questions regarding acceptance criteria, a dedicated study proving device performance against those criteria, or details about ground truth establishment for a test set or training set.

Here's an analysis of what is available and what is missing based on your request:

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

• Missing: The document does not provide a table of acceptance criteria or reported device performance metrics against specific criteria. The submission methodology is one of "substantial equivalence" to existing predicate devices, not performance against pre-defined quantitative acceptance criteria.

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

• Missing: There is no mention of a dedicated test set, its sample size, or the provenance of any data used for testing. The basis of equivalence is functional similarity and technical characteristics to predicate devices.

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

• Missing: As there's no mention of a test set where ground truth was established, this information is not present.

4. Adjudication method for the test set:

• Missing: No specific adjudication method is mentioned as there's no described test set requiring one.

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:

• Missing: This 510(k) summary does not describe an MRMC study. The device is software for planning and simulation, not an AI diagnostic aid that would typically undergo such a study to evaluate reader performance improvement.

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

• Missing: While the device is a standalone software, the document does not describe "standalone performance" in the context of a rigorous, quantitative study with metrics like sensitivity, specificity, etc. It focuses on the capabilities and functions of the software.

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

• Missing: No ground truth is mentioned as there's no performance study described. The "reliability and validity" of the 3D image construction method were "already verified in Vworks™" (a predicate device by the same manufacturer), suggesting reliance on prior work rather than a new ground truth establishment process for Vimplant.

8. The sample size for the training set:

• Missing: This document focuses on the software's features and its substantial equivalence to predicate devices. It does not contain information about a training set, which would typically be relevant for machine learning or AI algorithms that undergo a training phase.

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

• Missing: As there's no training set mentioned, this information is not provided.

Summary of available information:

• Device Name: Vimplant™ Dental implant simulation software
• Intended Use: As a software interface for transferring imaging information from a CT scanner, and as pre-operative software for simulation and evaluation of dental implant placement and surgical treatment options.
• Key Functions: Import DICOM 3.0 data, 2D image reformation (panoramic, cross-sectional), 3D image construction (Surface rendering, verifiable through Vworks™), nerve creation and display, implant simulation (placement, manipulation, property changes), collision detection, sinus bone graft volume estimation, measurement functions (bone density, length, angle, 3D distance), report and image library.
• Predicate Devices: SimPlant System (MATERIALISE N.V., K033849) and V-works™ (CyberMed, Inc., K013878).
• Basis for Clearance: Substantial equivalence to the predicate devices, implying similar safety and effectiveness based on similar technological characteristics and intended use. The 3D image construction's reliability and validity were already verified in the predicate V-works™ system.

The 510(k) summary provided here is characteristic of a submission for a software device that relies on functional equivalence to established technology rather than a novel AI algorithm requiring extensive performance studies with ground truth data.

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The V-works is a software application for the display and 3D visualization of medical image files from scanning devices, such as CT, MRI or 3D Ultrasound. It is intended for use by radiologists, clinicians and referring physicians to acquire, process, render, review, store, print and distribute DICOM 3.0 compliant image studies, utilizing standard PC hardware.

The V-works™ is a software application for the display and 3D visualization of medical image files from scanning devices, such as CT, MRI or 3D Ultrasound. It is intended for use by radiologists, clinicians and referring physicians to acquire, mocess, render, review, store, print and distribute DICOM 3.0 complaint image process, reliaer, 101107, 1011, 1978, dware. All of the functions are supported on standard personal computer platform for ease of cost and maintenance. The use of Microsoft personal compacer pratessional/NT 4.0 operating system makes the V-works™ software easy to use and capable of being integrated with other computer needs.

The provided text is a 510(k) Summary for the CyberMed Inc., V-works™ device. It describes the device, its intended use, and its substantial equivalence to a predicate device (Voxar Limited Plug'n View 3D). However, it does not contain information about acceptance criteria, device performance studies, sample sizes, ground truth establishment, or expert qualifications in the way a clinical validation study typically reports it.

The document focuses on establishing substantial equivalence based on technical characteristics and intended use, rather than presenting a performance study with specific acceptance criteria and results.

Therefore, I cannot fulfill your request for:

• A table of acceptance criteria and the reported device performance: This information is not present in the document.
• Sample sized used for the test set and the data provenance: This information is not present in the document.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: This information is not present in the document.
• Adjudication method for the test set: This information is not present in the document.
• If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and if so, what was the effect size: This information is not present in the document.
• If a standalone performance (i.e. algorithm only without human-in-the loop performance) was done: This information is not present in the document.
• The type of ground truth used: This information is not present in the document.
• The sample size for the training set: This information is not present in the document.
• How the ground truth for the training set was established: This information is not present in the document.

The document mainly emphasizes that the V-works™ software is "designed, developed, tested and validated according to written procedures" and that "hazard analysis on this product has been performed throughout the definition, design, coding and testing phases." It concludes that the "Level of Concern" is "Minor" and that potential hazards are similar to other PACS components and unlikely to result in patient death or injury. This reflects a software development and risk management approach, not a clinical performance study as typically seen for AI/CAD devices.

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