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Clever One is dental imaging software that is intended to provide tools for supporting diagnosis and treatment. These tools enable end users to view and interpret a series of DICOM compliant medical images and are intended for use by trained medical professionals. Clever One allows users to load, view, and save DICOM images from CT, panoramic, cephalometric, intraoral, and other imaging equipment. It also provides functionalities such as 2D viewing, 2D analysis, 3D visualization, 3D analysis.

Clever One is a dental imaging software designed to acquire, process, view, edit, and analyze medical images for supporting diagnostic and preoperative planning purposes. It supports standard DICOM formats for 2D and 3D image files and enables advanced imaging functionalities for enhanced diagnostic accuracy.

The software provides a range of features, including:

• 2D Imaging: Loading, editing, and viewing 2D dental images in standard formats (e.g., DICOM, JPG, BMP).
• 3D Imaging: Visualization and reconstruction of 3D CT images, including multi-planar views (MPR) and volume rendering.
• Preoperative Planning: Implant position simulation, canal drawing, and bone density analysis to support treatment planning.
• Data Interoperability: Facilitates data transfer and storage using DICOM-compliant workflows, ensuring compatibility with third-party systems and imaging devices.

The software interfaces with dental imaging equipment, such as CT, panoramic, cephalometric, and intraoral X-ray systems, as well as intraoral cameras, for image acquisition. It is designed for use in network environments, allowing users to upload and download clinical diagnostic images and patient data for enhanced collaboration and efficient patient management.

Here's the breakdown of the acceptance criteria and the study information based on the provided FDA 510(k) clearance letter for the "Clever One" device.

Unfortunately, the provided document does not contain detailed information about specific acceptance criteria or a dedicated study proving performance against those criteria in a quantitative manner. The clearance letter primarily focuses on demonstrating substantial equivalence to predicate devices (EzDent-i and Ez3D-i) for a medical image management and processing system. The performance data section is very general.

Therefore, many of the requested fields will state "Not specified in the document" or "Not applicable/provided."

Acceptance Criteria and Reported Device Performance

Given the nature of the device as a "Medical Image Management and Processing System" that provides viewing, analysis, and processing tools, the acceptance criteria are generally focused on functionality, accuracy, interoperability, and cybersecurity rather than diagnostic performance metrics like sensitivity/specificity for disease detection.

Study Details

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

   • Sample Size: Not specified in the document.
   • Data Provenance: Not specified in the document.

2. 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/provided. The document describes a software verification and validation process and "measurement accuracy test," not a clinical study involving ground truth established by experts for diagnostic performance. The device is for "supporting diagnosis and treatment," and "all diagnosis and treatment decisions made are solely up to the user."

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

   • Not applicable/provided, as there is no mention of a test set requiring adjudication in the context of expert ground truth. The V&V process likely involved internal testing against specifications.

4. 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 MRMC comparative effectiveness study was performed or mentioned. The device is described as "dental imaging software that is intended to provide tools for supporting diagnosis and treatment," and is compared to predicate devices for its functionality and technical characteristics, not its impact on human reader performance. Its purpose is "visualizing data," and "visualization results only assist end-users in patient counseling, diagnosis, and treatment planning."

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

   • Not applicable/provided. The device is a software suite with various tools for human users, making a standalone "algorithm only" performance evaluation less relevant in the context of its stated functionality as a viewing and analysis platform for a clinician.

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

   • For the "measurement accuracy test," the ground truth would typically be established against known physical measurements or validated digital standards (e.g., using phantoms or geometrically characterized digital models) rather than clinical ground truth like pathology. For functional V&V, the "ground truth" is adherence to software specifications.

7. The sample size for the training set

   • Not applicable/provided. The document does not describe the use of machine learning that would require a "training set." The device is presented as software that processes and visualizes DICOM images using established algorithms (e.g., for MPR, volume rendering, measurement tools), rather than an AI/ML-driven diagnostic algorithm that learns from data.

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

   • Not applicable/provided, as there is no mention of a training set.

Summary of Performance Data (from the document):

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

Additionally, "comprehensive cybersecurity risk management and verification and validation activities were conducted" and their results "are included in this premarket submission."

The document concludes that the "new device does not introduce a fundamentally new scientific technology, and the device has been validated through system level test."

Ask a specific question about this device

EzDent-i is dental imaging software that is intended to provide diagnostic tools for maxillofacial radiographic imaging. 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-i is intended for use as software to acquire, view, save 2D image files, and load DICOM project files from panorama, cephalometric, and intra-oral imaging equipment.

EzDent-i v3.5 is a device that provides various features to acquire, transfer, edit, display, store, and perform digital processing of medical images. EzDent-i is a patient & image management software specifically for digital dental radiography. It also provides server/client model so that the users upload and download clinical diagnostic images and patient information from any workstations in the network environment.

EzDent-i supports general image formats such as JPG and BMP for 2D image viewing as well as DICOM format. For 3D image management, it provides uploading and downloading support for dental CT Images in DICOM format. It interfaces with a 3D imaging software made by our company, the Ez3D-i (K131616, K150761, K161246, K163539, K173863, K190791, K200178, K211791, K222069, K231757) but the EzDent-i itself does not view, transfer or process 3D radiographs.

EzDent-i supports the acquisition of dental images by interfacing with OpenCV library to import the intra-oral camera images. It also supports the acquisition of CT/Panoramic/Cephalo/Intra-Oral Sensor /Intra-Oral Scanner images by interfacing with Xray capture software.

The provided text is a 510(k) summary for the EzDent-i/E2/Prora View/Smart M Viewer (v3.5) device. It asserts substantial equivalence to a predicate device (EzDent-i/E2/Prora View/Smart M Viewer v3.4). However, the document does not contain any specific acceptance criteria or details of a study proving the device meets acceptance criteria.

The "Performance Data" section (Section 10) only states: "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. Also we have addressed the recommendations in the most recent cybersecurity guidance, "Cybersecurity in Medical Devices Quality System Considerations and Content of Premarket Submissions"."

This statement confirms that tests were conducted and passed, but does not provide the actual acceptance criteria, the reported device performance, sample sizes, details on ground truth establishment, expert qualifications, adjudication methods, or whether MRMC/standalone studies were performed.

Therefore, based solely on the provided text, I cannot complete the requested tables and information. The document confirms that testing occurred and passed, but the specifics required to answer your questions are not present in this 510(k) summary.

Ask a specific question about this device

Ez3D-i is dental imaging software that is intended to provide diagnostic tools for maxillofacial radiographic imaging. 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.

Ez3D-i is intended for use as software to load, view and save DICOM images from CT, panorama, cephalometric and intraoral imaging equipment and to provide 3D visualization, 2D analysis, in various MPR (Multi-Planar Reconstruction) functions.

Ez3D-i v5.5 is 3D viewing software for dental CT images in DICOM format with a host of useful functions including MPR, 2-dimensional analysis and 3-dimensional image reformation. It provides advanced simulation functions such as Implant Simulation, Drawing Canal, and Implant Environ Bone Density, etc. for the benefit of effective doctor and patient communication and precise treatment planning.

Here's an analysis based on the provided FDA 510(k) summary for the Ez3D-i /E3 device, specifically version 5.5:

This document is a 510(k) summary for the Ez3D-i /E3 (v5.5) device, asserting its substantial equivalence to a previously cleared device (Ez3D-i /E3 v5.4, K222069). It does not present a standalone clinical study to prove the device meets specific acceptance criteria based on diagnostic accuracy or clinical outcomes. Instead, it relies on demonstrating that the new version is substantially equivalent to a previously cleared version and that software verification and validation tests were performed.

Here's a breakdown of the information requested:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not contain a table of specific quantitative acceptance criteria related to diagnostic performance or clinical effectiveness, nor does it report such performance metrics. The approval is based on substantial equivalence and software verification/validation.

Instead, the summary implies the "acceptance criteria" are related to successful software verification and validation, ensuring the new features function as intended and the overall device maintains the same functionality and safety profile as its predicate.

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

• Test Set Sample Size: Not explicitly stated for any clinical performance or diagnostic accuracy test. The document refers to "SW verification/validation and the measurement accuracy test," implying internal testing rather than a clinical study with a patient dataset.
• Data Provenance: Not specified, as no clinical study with patient data is detailed. The tests mentioned are likely internal software tests.

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

Not applicable / Not specified. Since no clinical study or diagnostic performance assessment is detailed, there's no mention of experts establishing a ground truth for a test set. The device is a viewing and analysis tool, and its outputs are for interpretation by trained medical professionals.

4. Adjudication Method for the Test Set

Not applicable / Not specified. No clinical test set requiring adjudication is described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not reported in this 510(k) summary. The submission focuses on substantial equivalence based on technical characteristics and software changes, not on comparing human reader performance with and without the AI (or specific features) of the device.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

No. The device, Ez3D-i /E3, is described as "dental imaging software that is intended to provide diagnostic tools" and "meant to be used by trained medical professionals such as radiologist and dentist." It is explicitly stated that "Results produced by the software's diagnostic, treatment planning and simulation tools are dependent on the interpretation of trained and licensed radiologists, clinicians and referring physicians as an adjunctive to standard radiology practices for diagnosis." This confirms it is not intended for standalone, algorithm-only performance.

7. The Type of Ground Truth Used

Not applicable / Not specified for any diagnostic performance. The ground truth for the software's functionality would be its design specifications, against which its operational performance was verified.

8. The Sample Size for the Training Set

Not applicable / Not specified. This device is described as "dental imaging software" with "diagnostic tools" and "advanced simulation functions" primarily for viewing, analysis, and processing. There is no mention of machine learning or AI that would require a "training set" in the context of deep learning algorithms. It appears to be a rule-based or conventional image processing software.

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

Not applicable / Not specified, as there is no mention of a training set for machine learning.

Ask a specific question about this device

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.

Ask a specific question about this device

EzDent-i is dental imaging software that is intended to provide diagnostic tools for maxillofacial radiographic imaging. 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-i is intended for use as software to acquire, view, save 2D image files, and load DICOM project files from panorama, cephalometric, and intra-oral imaging equipment.

EzDent-i v3.4 is a device that provides various features to acquire, transfer, edit, display, store, and perform digital processing of medical images. EzDent-i is a patient & image management software specifically for digital dental radiography. It also provides server/client model so that the users upload and download clinical diagnostic images and patient information from any workstations in the network environment.

EzDent-i supports general image formats such as JPG and BMP for 2D image viewing as well as DICOM format. For 3D image management, it provides uploading and downloading support for dental CT Images in DICOM format. It interfaces with a 3D imaging software made by our company, the Ez3D-i (K131616, K150761, K161246, K163539, K173863, K190791, K200178, K211791, K222069) but the EzDent-i itself does not view, transfer or process 3D radiographs. None of the changes to the predicate software are related to the 3D functions.

EzDent-i supports the acquisition of dental images by interfacing with OpenCV library to import the intra-oral camera images. It also supports the acquisition of CT/Panoramic/Cephalo/Intra-Oral Sensor /Intra-Oral Scanner images by interfacing with Xray capture software.

The software level of concern is Moderate.

The provided document is a 510(k) summary for the EzDent-i / E2 / Prora View / Smart M Viewer software. It describes the device, its intended use, and argues for its substantial equivalence to a predicate device.

However, the document does not contain the detailed information necessary to answer all parts of your request, specifically regarding acceptance criteria, reported device performance, sample sizes, expert qualifications, adjudication methods, MRMC studies, standalone performance, or training set details.

This 510(k) submission primarily focuses on demonstrating that the updated software version (v3.4) is substantially equivalent to a previous cleared version (v3.3) by highlighting that the changes are for "user convenience and do not affect the device safety or effectiveness". It therefore does not provide a comprehensive study report with quantified performance metrics against specific acceptance criteria for diagnostic accuracy, which would typically be found in direct performance studies for devices with diagnostic claims.

Here's what can be extracted and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not specified.
• Data Provenance (e.g., country of origin of the data, retrospective or 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.
  • The Indications for Use state the device is "meant to be used by trained medical professionals such as radiologist and dentist." This implies the target users, but not the experts for ground truth.

4. Adjudication method (e.g., 2+1, 3+1, none) 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 comparative effectiveness study is not mentioned. The device is described as "dental imaging software that is intended to provide diagnostic tools" and its results are "dependent on the interpretation of trained and licensed radiologists, clinicians and referring physicians as an adjunctive to standard radiology practices for diagnosis." This suggests it is a viewing and processing tool, not a diagnostic AI that would typically undergo an MRMC study to show improvement in human reader performance.

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

• Standalone Performance Study: No, a standalone performance study is not described. Given the device's function as an image management and processing system used "as an adjunctive to standard radiology practices for diagnosis," it is not presented as an AI algorithm providing standalone diagnoses.

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

• Type of Ground Truth: Not specified, as specific performance tests against diagnostic ground truth are not detailed. The performance data section broadly mentions "SW verification/validation and the measurement accuracy test were conducted," implying functional and technical testing rather than a clinical performance study with established ground truth for diagnostic accuracy.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable/Not specified. The document describes software with various image processing and management features, rather than a machine learning or AI algorithm that would require a distinct "training set."

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

• Ground Truth for Training Set: Not applicable/Not specified, as no training set for a machine learning model is mentioned.

Summary of what the document implies about performance testing:

The "Performance Data" section states: "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."

This indicates that Ewoosoft performed internal validation testing to ensure the software met its specified functional and technical requirements (e.g., correct image display, accurate measurements for linear distance and angle, proper functioning of new features like "Image Share" and "IO sensor image Preview"). However, these are not detailed clinical performance metrics for diagnostic efficacy or accuracy that would typically be associated with AI-driven diagnostic devices. Since the device is presented as substantially equivalent to a predicate device for managing and processing images, the focus of the 510(k) is on the safety and effectiveness of the software updates rather than demonstrating novel diagnostic performance.

Ask a specific question about this device

Ez3D-i is dental imaging software that is intended to provide diagnostic tools for maxillofacial radiographic imaging. 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.

Ez3D-i is intended for use as software to load, view and save DICOM images from CT, panorama, cephalometric and intraoral imaging equipment and to provide 3D visualization, 2D analysis, in various MPR (Multi-Planar Reconstruction) functions.

Ez3D-i is 3D viewing software for dental CT images from CT, panorama, cephalometric and intraoral image equipment in DICOM format with a host of useful functions including MPR, 2-dimensional analysis and 3-dimensional image reformation. It provides advanced simulation functions such as Implant Simulation, Drawing Canal, and Implant Environ Bone Density, etc. for the benefit of effective doctor and patient communication and precise treatment planning.

Ez3D-i's main functions are:

• Image adaptation through various rendering methods such as Teeth/Bone/Soft tissue/MIP
• Versatile 3D image viewing via MPR Rotating, Curve mode
• "Sculpt" for deleting unnecessary parts to view only the region of interest.
• Implant Simulation for efficient treatment planning and effective patient consultation
• Canal Draw to trace alveolar canal and its geometrical orientation relative to teeth.
• "Bone Density" test to measure bone density around the site of an implant(s) .
• Various utilities such as Measurement, Annotation, Gallery, and Report
• 3D Volume function to transform the image into 3D Panorama and the Tab has been optimized for Implant Simulation.
• Provides the Axial View of TMJ, the Condyle/Fossa images in 3D and the Section images, and supports functions to separate the Condyle/Fossa and display the bone density
• STO/VTO Simulation to predict orthodontic treatment/ surgery results with 3D Photo image.
• Segmentation function to get tooth segmentation data from CT, label each segmented tooth data as an object and utilize them in simulation such as tooth extraction, implant simulation, etc.

The provided text describes a 510(k) summary for the Ez3D-i/E3 device, primarily focusing on proving its substantial equivalence to a predicate device (K211791) rather than detailing specific acceptance criteria and a comprehensive study proving the device meets them.

The filing states: "The 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, it does not provide the specific acceptance criteria, the detailed results of these tests, or the methodology of the study.

Therefore, many of the requested details cannot be extracted from the given text.

Based on the information provided, here's what can be extracted and what is missing:

Acceptance Criteria and Device Performance

The document does not explicitly state specific acceptance criteria in a quantitative manner or provide a table of reported device performance against such criteria. It generally states that the device "passed all of the tests based on pre-determined Pass/Fail criteria," but these criteria are not detailed.

Study Details

Given the context of a 510(k) for a software update (Ez3D-i v5.4 to Ez3D-i v5.3), the studies conducted appear to be software verification and validation (V&V) and measurement accuracy tests. These are typically internal tests to ensure the new version functions as intended and maintains the performance of the previous version, rather than large-scale clinical trials.

1. Sample sized used for the test set and the data provenance:

• Not explicitly stated for the "measurement accuracy test" or "SW verification/validation." The document mentions the device processes DICOM images from CT, panorama, cephalometric, and intraoral imaging equipment. The data provenance (country of origin, retrospective/prospective) is also not stated.

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

• Not stated. For a software update focusing on functionality and measurement accuracy of an image viewer, ground truth might be established through technical specifications or comparison to known accurate measurements rather than expert consensus on diagnostic interpretations. The document mentions the software is "meant to be used by trained medical professionals such as radiologist and dentist," but it doesn't specify if these professionals were involved in establishing ground truth for testing.

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

• Not stated. This method is typically relevant for human-in-the-loop studies where multiple readers interpret images to establish consensus. For software V&V and measurement accuracy, it's unlikely to be applicable in the traditional sense.

4. 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, an MRMC study was not done or reported. The device is described as "dental imaging software that is intended to provide diagnostic tools" and is used by professionals as "an adjunctive to standard radiology practices for diagnosis." It is not presented as an AI-assisted diagnostic tool that directly improves human reader performance in the way an AI algorithm for disease detection might be. The focus of the submission is on software functionality and substantial equivalence.

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

• Not explicitly detailed as a "standalone performance study" in terms of diagnostic accuracy. The "measurement accuracy test" could be considered a form of standalone testing for specific functions, but no specific metrics (e.g., sensitivity, specificity for diagnostic tasks) are provided. The device is not an AI algorithm making diagnostic predictions in the absence of a human.

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

• Not explicitly stated. For "measurement accuracy," ground truth would likely be established by known physical dimensions or validated measurements. For general software verification/validation, ground truth often relates to the expected output from a given input based on design specifications.

7. The sample size for the training set:

• Not applicable/Not stated. This device is described as a medical image management and processing system, not an AI/ML device that requires a training set. While it performs "3D visualization, 2D analysis, in various MPR (Multi-Planar Reconstruction) functions," these are standard image processing techniques, not algorithms that learn from data.

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

• Not applicable/Not stated. As it's not described as an AI/ML device, there's no "training set."

Summary of what is known from the document:

• Device Name: Ez3D-i /E3 (K222069)
• Intended Use: Dental imaging software for maxillofacial radiographic imaging, providing diagnostic tools to view and interpret DICOM images from various dental imaging equipment, offering 3D visualization, 2D analysis, and MPR functions. Used by trained medical professionals (radiologists and dentists).
• Predicate Device: Ez3D-i /E3 v.5.3 (K211791)
• Studies Conducted: Software verification/validation and measurement accuracy tests.
• Conclusion: The device passed all tests based on pre-determined Pass/Fail criteria, leading to a conclusion of substantial equivalence to the predicate device.

What is demonstrably missing from the provided text:

• Specific, quantitative acceptance criteria.
• Detailed reported performance data against those criteria.
• Specific sample sizes for the test set.
• Data provenance (country of origin, retrospective/prospective).
• Details on experts and ground truth establishment methodologies for the test set.
• Adjudication methods for the test set.
• Any MRMC study details or effect sizes related to AI assistance.
• Detailed standalone performance metrics (e.g., diagnostic accuracy metrics).
• Ground truth type beyond general "measurement accuracy."
• Training set information (as it's not an AI/ML device).

Ask a specific question about this device

The EzDent-i /E2 /ProraView/ Smart M Viewer is dental imaging software that is intended to provide diagnostic tools for maxillofacial radiographic imaging. 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.

The EzDent-i F2 /ProraView/ Smart M Viewer is intended for use as software to acquire, view, save 2D image files, and load DICOM project files from panorama, cephalometric, and intra-oral imaging equipment.

The EzDent-i / E2 / Prora View / Smart M Viewer v.3.3 is a device that provides various features to acquire, transfer, edit, display, store, and perform digital processing of medical images. The subject device is a patient & image management software specifically for digital dental radiography. It also provides server/client model so that the users upload and download clinical diagnostic images and patient information from any workstations in the network environment.

It also supports general image formats such as JPG and BMP for 2D image viewing as well as DICOM format. For 3D image management, it provides uploading and downloading support for dental CT Images in DICOM format. It interfaces with a 3D imaging software made by our company, the Ez3D-i (K131616, K150761, K161246, K163539, K173863, K190791, K200178, K211791) but does not view, transfer or process 3D radiographs.

The subject device supports the acquisition of dental images by interfacing with OpenCV library to import the intra-oral camera images. It also supports the acquisition of CT/Panoramic/Cephalo/Intra-Oral Sensor /Intra-Oral Scanner images by interfacing with Xray capture software.

This document describes a 510(k) premarket notification for the EzDent-i / E2 / ProraView/ Smart M Viewer, a dental imaging software. The submission aims to demonstrate substantial equivalence to a previously cleared version of the same software (EzDent-i / E2 / Prora View / Smart M Viewer v.3.2, K211795).

Based on the provided information, the following can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria or detailed device performance metrics in a pass/fail format. Instead, it relies on a statement that "The device passed all of the tests based on pre-determined Pass/Fail criteria." The study's focus was on demonstrating that modifications made to the software "do not raise the questions of safety or effectiveness" and that the newer version is substantially equivalent to the predicate device.

The reported device performance, in terms of meeting criteria, is implicitly described as:

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

The document states that "SW verification/validation and the measurement accuracy test were conducted." However, it does not provide any details regarding:

• The specific sample size (e.g., number of images, number of cases) used for the test set.
• The data provenance (e.g., country of origin, retrospective or prospective nature of the data).

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

This information is not provided in the document. The document mentions that the software's diagnostic tools are "meant to be used by trained medical professionals such as radiologist and dentist" and that "Results produced by the software's diagnostic, treatment planning and simulation tools are dependent on the interpretation of trained and licensed radiologists, clinicians and referring physicians as an adjunctive to standard radiology practices for diagnosis." However, it does not specify how ground truth was established for the performance testing.

4. Adjudication Method for the Test Set

The document does not specify any adjudication method (e.g., 2+1, 3+1, none) used for establishing ground truth for the test set.

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

An MRMC comparative effectiveness study was not performed or reported in this submission. The study focuses on demonstrating substantial equivalence of the modified software version to its predicate through software verification/validation and measurement accuracy testing, rather than evaluating human reader performance with or without AI assistance.

6. Standalone (Algorithm Only) Performance Study

A standalone performance study focused on the algorithm's performance without human-in-the-loop interaction was performed implicitly through the "SW verification/validation and the measurement accuracy test." These tests are typically designed to assess the software's intrinsic functionalities and accuracy parameters independently. The submission indicates that these tests were conducted and passed. However, specific metrics (e.g., sensitivity, specificity, AUC) for diagnostic capabilities are not provided, as the device is characterized as a "medical image management and processing system" with "diagnostic tools," meaning it is an adjunctive tool for image interpretation by clinicians.

7. Type of Ground Truth Used

The type of ground truth used for the "SW verification/validation and the measurement accuracy test" is not explicitly stated. Given the nature of a "medical image management and processing system" and its function of enabling trained professionals to "view and interpret" images and provide "diagnostic tools," the ground truth for measurement accuracy tests would likely involve precisely measured objects or features within reference images. For software functionality, it would involve confirming that features operate as intended based on predefined specifications. Pathology or outcomes data are not mentioned as being used for ground truth.

8. Sample Size for the Training Set

The document does not provide any information about a training set or its sample size. This submission describes an updated version of existing software, and the evaluation focuses on comparing it to a predicate device rather than on the development and training of a new AI algorithm.

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

As no training set is mentioned, information on how its ground truth was established is not applicable/not provided in this document.

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EzOrtho is a software indicated for use by dentists who provide orthodontic treatment for image analysis, simulation, profilogram, VTO/STO and patient consultation. Results produced by the software's diagnostic, treatment planning and simulation tools are dependent on the interpretation of trained and licensed practitioners or dentists.

EzOrtho is a 2D orthodontic analysis and simulation program developed by Ewoosoft. It is of Moderate level of concern. EzOrtho manages patient information and images for orthodontic analysis. This software also assists in orthodontic treatment by providing accurate image analysis, profilograms, superimpositions, and VTO (visualised treatment objective) and STO (surgical treatment objective) simulations. The analyzed results are saved in chart format so that the user can easily store and track the treatment and records of each patient.

The provided text, K220003, is a 510(k) summary for a software device called "EzOrtho v1.3." This document focuses on demonstrating substantial equivalence to a previously cleared predicate device (EzOrtho v1.2) rather than presenting a performance study with acceptance criteria and a detailed study design.

Therefore, the requested information, specifically regarding acceptance criteria, a detailed study proving device performance against these criteria, sample sizes, expert ground truth establishment, MRMC studies, standalone performance, and ground truth types, is not explicitly available in the provided document.

The document states:

• "EzOrtho v1.3 described in this 510(k) has the same intended use and the same technical characteristics as the unmodified device." (Page 6)
• "The subject device and the unmodified device are substantially equivalent, having the same indications for use and functionalities like operation software, computer platform, picture archiving and communication format, image format, image processing features, windowing, image edit, measurements and manipulation." (Page 6)
• "The modifications are changes in PC system requirement information, upgrading the SETTINGS tab (font size change option for analysis chart), upgrading the PATIENT Tab (reset to original DICOM pixel spacing), upgrading the VIEWER Tab (change layouts in presentation mode), upgrading the ANALYSIS Tab (exporting analysis chart), upgrading the PRACTICE Tab (UI upgrade and recurrence option).These differences are not significant since they are additional features for user convenience and do not raise the questions of safety or effectiveness." (Page 6)
• "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." (Page 7)

This indicates that the focus of the submission was on validating the non-significant changes between versions to ensure they did not negatively impact the established safety and effectiveness. The "measurement accuracy test" mentioned is likely a part of the software verification/validation, but its specific methodology, acceptance criteria, and detailed results are not provided in this summary.

In summary, the document does not contain the detailed performance study information requested. It primarily relies on the predicate device's established performance and demonstrates that the modifications in EzOrtho v1.3 do not alter its fundamental functionality or safety/effectiveness profile, hence requiring less extensive clinical performance data than a novel device might.

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EzDent-i is dental imaging software that is intended to provide diagnostic tools for maxillofacial radiographic imaging. 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-i is intended for use as software to acquire, view, save 2D image files, and load DICOM project files from panorama, cephalometric, and intra-oral imaging equipment.

EzDent-i is a device that provides various features to acquire, transfer, edit, display, store, and perform digital processing of medical images. EzDent-i is a patient & image management software specifically for digital dental radiography. It also provides server/client model so that the users upload and download clinical diagnostic images and patient information from any workstations in the network environment.

EzDent-i supports general image formats such as JPG and BMP for 2D image viewing as well as DICOM format. For 3D image management, it provides uploading and downloading support for dental CT Images in DICOM format. It interfaces with a 3D imaging software made by our company, the Ez3D-i (K131616, K150761, K161246, K163539, K173863, K190791, K200178) but the EzDent-i itself does not view, transfer or process 3D radiographs.

EzDent-i supports the acquisition of dental images by interfacing with OpenCV library to import the intra-oral camera images. It also supports the acquisition of CT/Panoramic/Cephalo/Intra-Oral Sensor /Intra-Oral Scanner images by interfacing with Xray capture software.

The provided text describes a 510(k) premarket notification for a dental imaging software named EzDent-i. The primary purpose of this submission is to demonstrate substantial equivalence to a previously cleared predicate device, not to showcase the performance of an AI algorithm based on comparative studies. Therefore, much of the requested information regarding acceptance criteria and performance studies (especially relating to AI, human readers, and ground truth establishment) is not detailed in this document because it is not typically required for a software device demonstrating substantial equivalence by adding convenience features.

However, based on the context of the document, we can infer some details and explicitly state what is not provided.

Here's an attempt to answer your questions based on the provided text, indicating where information is not present:

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

The document does not explicitly state quantitative acceptance criteria or detailed performance metrics. Instead, it relies on demonstrating that the modified device's performance aligns with its intended use and is comparable to the predicate device.

The "Performance Data" section states: "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." This indicates that internal testing was performed, and the device met its internal "Pass/Fail criteria," but these specific criteria and results are not provided in this summary.

Given that this is a 510(k) for a medical image management and processing system (not an AI-driven diagnostic aid that independently identifies pathologies), the "performance" here refers to its ability to correctly acquire, view, save, load, and manipulate dental images, similar to its predicate.

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

The document does not specify any sample size for a test set in terms of patient images. The "performance data" section refers to "SW verification/validation and the measurement accuracy test," implying software-level testing rather than clinical study data on a patient image test set. No information is available regarding data provenance (country of origin, retrospective/prospective).

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 and not provided. The device (EzDent-i) is described as "dental imaging software that is intended to provide diagnostic tools for maxillofacial radiographic imaging. 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." It is a viewer and manager, not an AI diagnostic tool that produces a finding requiring expert ground truth for performance evaluation in the described context. The performance verification likely focuses on technical accuracy of image display, manipulation, and data handling, not diagnostic accuracy against a ground truth.

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

Not applicable and not provided. As per point 3, there's no indication of a diagnostic test set requiring adjudication.

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 such study was mentioned or required for this 510(k) submission. This device is a general image management and processing system, not an AI-assisted diagnostic tool that would typically warrant an MRMC study to show human reader improvement with AI assistance.

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

This device is not an algorithm performing a standalone diagnostic task. It is software that provides "diagnostic tools" for viewing and interpreting images by human professionals. Therefore, a standalone algorithm performance evaluation would not be applicable or described here.

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

Not applicable and not provided. As this is not an AI diagnostic device, the concept of ground truth for diagnostic accuracy (e.g., concerning a disease or finding) is not relevant to the described performance evaluations. The "performance" relates to the software's ability to achieve its technical specifications.

8. The sample size for the training set

Not applicable and not provided. This document describes a traditional software upgrade and substantial equivalence claim, not a machine learning or AI device that would have a training set.

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

Not applicable and not provided. As per point 8, there is no mention of a training set for an AI model in this 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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