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Vitrea™2 is a medical diagnostic workstation that allows the processing, review, analysis, communication and media interchange of multi-dimensional digital images acquired from a variety of imaging devices. In addition, Vitrea™2 has the following specific indications.

VScore™ (K990442) is an option within the Vitrea™2 application and is intended for cardiac scoring from whole body CT derived measurements, including non-invasive detection and quantification of atherosclerotic plaque. Two image processing options, EKG Gate (K001682) and Auto Gate (K003230), allow the operator to select images with reduced motion artifacts when processing data for Coronary Artery Calcification Scoring.

Automated Vascular Measurement (K002519) is an option within the Vitrea™2 application and is intended for study/analysis of selected vessels for stenosis analysis, pre/post stent planning and directional vessel tortuosity evaluation.

Tumor Volume Measurement (K002519) is an option within the Vitrea™2 application and is intended for the analysis/quantification of tumor volumes obtained from MR brain series scans.

CT Brain Perfusion (K003639) is an option within the Vitrea™2 application and is intended for post processing based on dynamic CT images continuously acquired during the injection of contrast for the visualization of apparent blood flow in brain tissue and pictorial illustration of perfusion related parameters to aid in the type and extent of cerebral perfusion disturbances.

ImageCheckerCT is an option within the Vitrea™2 application and is intended for the display of a composite view of 2D crosssections, and 3D volumes of Chest CT images, including findings of regions of interest ("ROI") identified by the radiologist, or Computer Assisted Detection ("CAD") findings.

Vitrea™2 is a medical diagnostic workstation that allows the processing, review, analysis, communication and media interchange of multi-dimensional digital images acquired from a variety of imaging devices. Vitrea™2, version 3.4 is an upgrade to Vitrea™2, version 2.1 initially released for commercial distribution by FDA on K002519.

Vitrea 2 provides multi-dimensional visualization of digital images to aid clinicians in their analysis of anatomy and pathology. The Vitrea2 user interface follows typical clinical workflow patterns to process, review, and analyze digital images, including:

• Retrieve image data over the network via DICOM .
• Display images that are automatically adapted to exam type via dedicated protocols .
• Select images for closer examination from a gallery of up to six 2D or 3D views .
• . Interactively manipulate an image in real-time to visualize anatomy and pathology
• Annotate, tag, measure, and record selected views
• Output selected views to standard film or paper printers, or post a report to an Intranet Web server or . export views to another DICOM device
• Retrieve reports that are archived on a Web server .

Here's a breakdown of the requested information based on the provided text:

Acceptance Criteria and Device Performance Study

The provided document is a 510(k) Summary for Vitrea2, Version 3.4. It declares substantial equivalence of the device to predicate devices rather than providing detailed acceptance criteria and a performance study with quantitative metrics.

The document states: "The Vitrea2, Version 3.4 Workstation will successfully complete Integration testing/verification prior to Beta validation. The software Beta testing validating the workstation will be successfully completed prior to release." This indicates that internal testing and validation were conducted, but specific metrics, acceptance criteria, or the results of those tests are not provided in this summary.

Therefore, many of the requested details about acceptance criteria, specific performance metrics, sample sizes, and ground truth establishment for a standalone or comparative effectiveness study are not available in this document. The summary focuses on comparing the new device's intended use and technological characteristics to previously cleared predicate devices to establish substantial equivalence.

Based on the information available, here's what can be extracted:

1. Table of Acceptance Criteria and Reported Device Performance

Not explicitly provided in the 510(k) Summary. The document asserts the device's functionality and safety through comparison to predicate devices and general software development processes, but does not list specific quantitative acceptance criteria or corresponding performance scores for any of its features (VScore, Automated Vascular Measurement, Tumor Volume Measurement, CT Brain Perfusion, or ImageCheckerCT).

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

Not provided in the 510(k) Summary. There is no mention of a specific test set, its size, or the provenance of the data used for any validation studies.

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

Not provided in the 510(k) Summary. The document does not detail how ground truth was established for any testing, nor does it specify the number or qualifications of experts involved.

4. Adjudication Method for the Test Set

Not provided in the 510(k) Summary. There is no mention of an adjudication method for any test set.

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

No MRMC comparative effectiveness study is reported in this 510(k) Summary. The document focuses on demonstrating substantial equivalence to predicate devices, not on quantifying the improvement of human readers with AI assistance.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

No standalone performance study with specific metrics is reported in this 510(k) Summary. The document describes a medical diagnostic workstation with various processing options to aid clinicians, implying human interaction. It does not provide data on the pure automated performance of its features.

7. Type of Ground Truth Used

Not explicitly stated in the 510(k) Summary. Given the nature of the device (medical image processing software for diagnosis), if ground truth were used, it would typically be based on expertconsensus, pathological findings, or clinical outcomes, but the document does not specify this.

8. Sample Size for the Training Set

Not provided in the 510(k) Summary. There is no mention of a training set or its size. This document is from 2003, predating the widespread use and specific regulatory requirements for detailing AI/ML model training data that are common today.

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

Not provided in the 510(k) Summary. As no training set is mentioned, the method for establishing its ground truth is also not provided.

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The Viatronix V3D Explorer is intended to be used for the display and 2D/3D visualization of medical image data derived from CT, MRI, PET, SPECT scans and X-Ray of the human body including any organ. The volume, linear and angular measurement functions are intended for the evaluation and quantification of turnor or selected organ volume/linear measurements, angular location/ displacement, study/ analysis and evaluation of both hard and soft tissues as well as other internal organ structures for polyp, lesion, mass, implants, fracture, aneurysms, stenoses etc or evaluation of any abnormality / malformation in specified organs obtained from scanning and/or X-Ray. It also supports the interactive segmentation of any organ by removing certain structure(s) from display for critical evaluation of selected part(s) of organ. It is intended for use by radiologists, clinicians and referring physicians to acquire, process, render, evaluate, archive, print and distribute DICOM compliant specified organ image studies, utilizing PC hardware.

The V-3D Explorer is a software device for evaluating CT/MRI scanned and X-Ray images of selected human organ. It is an additional image processing option added to our V-3D visualization system for which pre-market clearance was granted by the FDA vide K#002780, dated November 17, 2000. It is a general software module, designed for use as a part of our V-3D visualization system core technology. The system consists of a V-3D processor and a V-3D viewer in two computer configuration or V-3D processor and V3D viewer in a stand alone one computer configuration. Upon receipt of a multi-slice CT / MR scan image or X-Ray image for any selected organ in a DICOM format, the V-3D processor converts the DICOM image data into an internally recognized volume data format using our core software technology. The V-3D viewer provides interactive orthogonal and multiplanar reformatted 2D and 3D images from the V-3D processor and user can evaluate these images for any abnormality or malformation in specified organs obtained from scanned images or X-Ray images. The volume, linear and angular measurement features provided in the software for the evaluation and quantification of organ volume, linear measurements, angular location/displacement for hard and soft tissues as well as internal organ structures for polyp, lesion, mass, tumor, implants, fracture, aneurysms, stenoses etc. The software also supports interactive segmentation of any organ from removing certain structure from display for critical evaluation of selected part of organ. The intended user can use the software device to acquire, process, render, evaluate, archive, print and distribute DICOM 3.0 compliant images of any organ, utilizing PC hardware.

Here's a breakdown of the acceptance criteria and the study details for the Viatronix V3D Explorer, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document focuses on substantial equivalence rather than explicit quantitative acceptance criteria for device performance. The primary "criterion" is that the V3D Explorer performs similarly to the predicate devices.

• Display and 2D/3D visualization of medical image data (CT, MRI, PET, SPECT, X-Ray)
• Evaluation and quantification of tumor/organ volume, linear measurements, angular location/displacement
• Study/analysis of hard/soft tissues, internal organ structures (polyp, lesion, mass, implants, fracture, aneurysms, stenoses)
• Evaluation of abnormalities/malformations
• Interactive segmentation of organs
• Acquisition, processing, rendering, evaluation, archiving, printing, distribution of DICOM compliant images | - V3D Explorer provided interactive orthogonal and multiplanar reformatted 2D and 3D images from datasets to detect and evaluate known abnormalities or status of organs.
• Volume, linear and angular measurement features were used to evaluate and quantify abnormalities or status of internal organ structures.
• Evaluation results of both predicate device and V3D Explorer device were same, and no significant differences were detected in the results of evaluation.
• DICOM compliant X-Ray images were correctly processed and converted, allowing for accurate display and evaluation.
• Phantom data showed measurements are accurate.
• Concluded the V3D Explorer is substantially equivalent to predicate devices in its ability to review, analyze, and evaluate images. |
  | Accuracy of Measurements:
• Volume, linear, and angular measurements | - Phantom data showed that the measurements are accurate and the V3D Explorer is evaluated to be safe and effective. |
  | Reliability and Ease of Use:
• Consistent operation and user-friendliness | - The product has shown itself to be reliable, easy to use and capable of evaluating DICOM 3.0 compliant scanned images or X-Ray images of any human organs. |
  | Software Development Standards:
• Developed in accordance with accepted standards | - The V3D Explorer Module has been developed in a manner consistent with accepted standards for software development, including both unit and system integration testing protocols. |

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

• Sample Size: "Scanned image or X-Ray datasets of various patients organs" and "Patients' various organs" were used. The exact number of patients or cases is not specified.
• Data Provenance: The data came from "various patients organs with known abnormalities or status." It is not explicitly stated whether the data was retrospective or prospective, or the country of origin. However, the use of "known abnormalities or status" suggests that these were existing clinical cases, implying a retrospective nature.

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

The document does not explicitly state the number of experts or their qualifications involved in establishing the ground truth for the test set. It mentions "known abnormalities or status," which implies that a previous clinical assessment (likely by medical professionals) already determined these conditions.

4. Adjudication Method for the Test Set

The document does not describe an adjudication method for establishing ground truth from multiple experts. The ground truth appears to be based on pre-existing "known abnormalities or status".

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, a Multi Reader Multi Case (MRMC) comparative effectiveness study was not done. The study directly compared the V3D Explorer's output against predicate devices and pre-calculated phantom values, not against human reader performance with or without the device. The V3D Explorer is presented as an image processing and visualization tool to be used by radiologists, clinicians, and referring physicians, not as an AI-assisted diagnostic aid that directly improves human reader performance in a quantitative sense as might be assessed in an MRMC study.

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

Yes, a standalone evaluation was implicitly done. The software's functionalities, measurements, and processing capabilities were tested independently (or in comparison to predicate devices) to verify its performance. The phrase "Evaluation results of both predicate device and V3D Explorer device were same and no significant differences were detected" suggests a direct comparison of the software outputs.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

• "Known abnormalities or status": For patient data, the ground truth was based on pre-existing clinical knowledge of the patient's condition. The specific method (e.g., pathology reports, follow-up, expert consensus) is not detailed.
• "Pre-calculated values": For phantom datasets, the ground truth was established by known, pre-calculated values for the phantom's characteristics.

8. The Sample Size for the Training Set

The document does not mention a "training set" in the context of machine learning or AI. This device is described as a software tool for image processing and visualization, not an AI/ML diagnostic algorithm that typically requires a dedicated training set. The software development included "unit and system integration testing protocols," which would involve software validation on various datasets, but these are not referred to as a "training set" in the modern AI sense.

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

As no training set (in the AI/ML sense) is mentioned, there is no information on how its ground truth was established. The testing described is more akin to software validation against known outcomes or established standards.

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CADstream is a Computer Aided Detection (CAD) system intended for use in analyzing magnetic resonance imaging (MRI) studies. CADstream automatically registers serial patient image acquisitions to minimize the impact of patient motion, segments and labels tissue types based on enhancement characteristics (parametric image maps), and performs other user-defined post-processing functions (image subtractions, multiplanar reformats, maximum intensity projections).

When interpreted by a skilled physician, this device provides information that may be useful in screening and diagnosis. CADstream can also be used to provide accurate and reproducible measurements of the longest diameters and volume of segmented tissues. Patient management decisions should not be made based solely on the results of CADstream analysis.

The CADstream device relies on the assumption that pixels having similar MR signal intensities represent similar tissues. The CADstream software simultaneously analyzes the pixel signal intensities from multiple MR sequences and applies multivariate pattern recognition methods to perform tissue segmentation and classification.

The CADstream system consists of proprietary software developed by Confirma installed on an off-the-shelf personal computer and a monitor configured as an CADstream display station.

The provided document is a 510(k) summary for the CADstream Version 2.0 MRI Image Processing Software. It does not contain detailed information about specific acceptance criteria or an explicit study proving performance against such criteria. The document focuses on the device's intended use, description, software development processes, and regulatory substantiation.

Here's an analysis based on the information provided, highlighting what is present and what is missing:

Description of Acceptance Criteria and Study to Prove Device Meets Them

1. Table of Acceptance Criteria and Reported Device Performance:

The document mentions that "Performance testing of the features described in the user manual has been successfully completed utilizing clinical datasets" and "Software beta testing also has been completed, validating that the requirements for these features have been met." However, it does not explicitly list the acceptance criteria in terms of specific performance metrics (e.g., sensitivity, specificity, accuracy, precision of measurements) or the quantitative results of these tests.

The document describes the device's functions:

• Automatically registers serial patient image acquisitions to minimize motion impact.
• Segments and labels tissue types based on enhancement characteristics (parametric image maps).
• Performs user-defined post-processing functions (image subtractions, multiplanar reformats, maximum intensity projections).
• Provides accurate and reproducible measurements of the longest diameters and volume of segmented tissues.

Without explicit acceptance criteria and corresponding performance metrics, a table cannot be constructed.

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

The document states "Performance testing... has been successfully completed utilizing clinical datasets." However, it does not specify the sample size (number of cases or patients) used for this testing. It also does not provide information on the data provenance (e.g., country of origin, retrospective or prospective nature).

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

The document does not provide details about the number of experts, their qualifications, or how ground truth was established for the clinical datasets used in performance testing.

4. Adjudication Method for the Test Set:

The document does not describe any adjudication method (e.g., 2+1, 3+1 consensus) used for the test set.

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

The document does not mention a multi-reader multi-case (MRMC) comparative effectiveness study comparing human readers with and without AI assistance, nor does it specify any effect size or improvement. The "Intended Use Statement" notes that "When interpreted by a skilled physician, this device provides information that may be useful in screening and diagnosis" and "Patient management decisions should not be made based solely on the results of CADstream analysis," implying human oversight but not a formal comparative study of reader performance.

6. Standalone (Algorithm Only) Performance Study:

The document describes the device's features and states "CADstream automatically registers... segments and labels... and performs other user-defined post-processing functions... CADstream can also be used to provide accurate and reproducible measurements..." This implies standalone algorithmic capabilities. However, it does not present a dedicated standalone performance study with quantitative metrics (e.g., sensitivity, specificity, F1-score) in isolation from human interpretation. The primary use case described involves interpretation by a skilled physician.

7. Type of Ground Truth Used:

The document refers to "clinical datasets" but does not specify the type of ground truth used (e.g., expert consensus, pathology reports, follow-up outcomes data) for evaluating the device's performance.

8. Sample Size for the Training Set:

The document does not specify the sample size of the training set used for developing the multivariate pattern recognition methods.

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

The document states that "CADstream software simultaneously analyzes the pixel signal intensities from multiple MR sequences and applies multivariate pattern recognition methods to perform tissue segmentation and classification." However, it does not describe how the ground truth for training these methods was established.

In summary, the provided document is a high-level regulatory submission that attests to developmental processes and general performance testing but lacks the specific quantitative details typically found in a clinical study report regarding acceptance criteria, sample sizes, expert involvement, and explicit performance metrics.

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Volume Interactions Pte Ltd's Image Processing System is a medical device for the display and visualization of 3D medical image data derived from CT and MRI scans. It is intended to be used by qualified and trained medial professionals, after proper installation.

Volume Interactions Pte Ltd's Image Processing System is not intended to be used in direct contact with the patient nor is it intended to be connected to equipment that is used in direct contact with the patient.

Volume Interactions Image Processing System reads DICOM 3.0 format medical image data sets (and other formats) and displays 3D image reconstructions of these data sets through various user selectable industry standard rendering methods and algorithms. The clinical users can spatially manipulate, process to highlight structures and volumes of interest, and measure distances and volumes in the 3D image reconstructions. The processed data can be stored either as 3D image data in a proprietary format. or as 2D picture projections of the 3D image data in TIFF image format. The system runs on commercially available IBM PC compatible computers and hardware components with the Microsoft Windows NT and 2000 operating systems.

The system consists of three product modules namely, VizDexter™ 2.0, Dextroscope™ and DextroBeam™. The modules are described as follows:

VizDexter™ 2.0 is software that processes tomographic (e.g.: Computer Tomography, Magnetic Resonance Imaging) data and produces stereoscopic 3D renderings for surgery planning and visualization purposes. The software user selectable industry standard rendering methods and algorithms.

Dextroscope™ is an interactive console and display system that allows the user to interact with two hands with the 3D images generated by the VizDexter™ software. The Dextroscope™ user works seated, with both forearms positioned on armrests. Wearing stereoscopic glasses, the user looks into a mirror and perceives the virtual image within comfortable reach of both hands for precise hand-eye coordinated manipulation. The hardware uses various industry standard components.

DextroBeam™ is an interactive console intended for group collaborative discussions with 3D images using a stereoscopic projection system. The DextroBeam™ system uses the base of the Dextroscope™ as the 3D interaction interface with the virtual objects. The monitor of the Dextroscope™ is replaced by a screen projection system, so instead of looking into the mirror of the Dextroscope™, the user looks at large stereoscopic screen projections while working with the virtual data in reach of his hands. This enables the discussion of 3D data sets with other specialists in stereoscopic 3D. The hardware uses various industry standard components.

The provided text is a 510(k) summary for the Volume Interactions Image Processing System (VizDexter™ 2.0, Dextroscope™, and DextroBeam™). This document focuses on demonstrating substantial equivalence to predicate devices rather than proving performance against specific acceptance criteria through a study.

Therefore, the document does not contain the acceptance criteria or a study that proves the device meets specific performance criteria in the way a clinical validation or standalone performance study would. It primarily compares the technological characteristics and intended use of the new device with existing, legally marketed devices.

However, based on the information provided, here's what can be inferred or explicitly stated regarding the device's nature and the lack of specific performance study details:

1. Table of Acceptance Criteria and Reported Device Performance:

The 510(k) summary does not present specific quantitative acceptance criteria or a direct study measuring device performance against such criteria. The "performance" demonstrated is substantial equivalence to predicate devices in functionality and safety. The tables compare features, not quantitative performance metrics.

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

No information is provided regarding a "test set" in the context of a performance study. The submission relies on a comparison of technological characteristics with predicate devices.

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

Not applicable, as no performance study with a test set requiring ground truth establishment is described.

4. Adjudication Method for the Test Set:

Not applicable, as no performance study with a test set requiring adjudication is described.

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

No MRMC study is mentioned in the document. The comparison is between the technological features of the device and its predicates, not a comparative effectiveness study involving human readers with and without AI assistance.

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

No standalone performance study for the algorithm itself (VizDexter™ 2.0) is described in terms of specific performance metrics. The document focuses on the system as a whole, including the human interaction components (Dextroscope™, DextroBeam™). The functions described are image processing and visualization, which inherently involve human interpretation.

7. The Type of Ground Truth Used:

Not applicable, as no performance study is detailed that would require a ground truth for evaluation.

8. The Sample Size for the Training Set:

No information is provided regarding a "training set." The device is an "Image Processing System" that utilizes "industry standard rendering methods and algorithms," implying it's not a machine learning model that would require a dedicated training set in the modern sense.

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

Not applicable, as no training set is mentioned.

In summary:

This 510(k) submission is a "substantial equivalence" filing for an image processing and visualization system from 2002. It focuses on demonstrating that the device has similar technological characteristics and intended use as already marketed devices. It does not present clinical performance data, acceptance criteria, or studies of the kind typically expected for AI/ML-driven diagnostic devices today. The "proof" of meeting acceptance criteria is implicitly through the FDA's determination of substantial equivalence based on the comparison of features and the device's classification as a Picture Archiving and Communications System, where the clinician retains responsibility for interpretation.

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The Viatronix V3D Explorer is intended to be used for the display and 2D/3D visualization of medical image data derived from CT, MRI, PET and SPECT scans of the human body including any organ. The volume , linear and angular measurement functions are intended for the evaluation and quantification of turnor or selected organ volume/linear measurements, angular location/ displacement, study/ analysis and evaluation of both hard and soft tissues as well as other internal organ structures for polyp, lesion, mass, implants, fracture, aneurysms, stenoses etc or evaluation of any abnormality / malformation in specified organs obtained from scanning. It also supports the interactive segmentation of any organ by removing certain structure(s) from display for critical evaluation of selected part(s) of organ. It is intended for use by radiologists, clinicians and referring physicians to acquire, process, render, evaluate, archive, print and distribute DICOM 3.0 compliant specified organ image studies, utilizing PC hardware.

The V-3D Explorer is a software device for evaluating scanned images of selected human organ. It is an additional image processing option added to our V-3D visualization system for which pre-market clearance was granted by the FDA vide K#002780, dated November 17, 2000. It is a general software module, designed for use as a part of our V-3D visualization system core technology. The system consists of a V-3D processor and a V-3D viewer in two computer configuration or V-3D processor and V3D viewer in a stand alone one computer configuration. Upon receipt of a multi-slice CT or MR scan image for any selected organ in a DICOM format, the V-3D processor converts the DICOM image data into an internally recognized volume data format using our core software. technology. The V-3D viewer provides interactive orthogonal and multiplanar reformatted 2D and 3D images from the V-3D processor and user can evaluate these images for any abnormality or malformation in specified organs obtained from scanned images. The volume, linear and angular measurement features provided in the software for the evaluation and quantification of organ volume, linear measurements, angular location/displacement for hard and soft tissues as well as internal organ structures for polyp, lesion, mass, tumor, implants, fracture, aneurysms, stenoses etc. The software also supports interactive segmentation of any organ from removing certain structure from display for critical evaluation of selected part of organ. The intended user can use the software device to acquire, process, render, evaluate, archive, print and distribute DICOM 3.0 compliant images of any organ, utilizing PC hardware.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Viatronix V3D Explorer:

Summary of Acceptance Criteria and Reported Device Performance

Study Information:

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

   • Sample Size: Not explicitly stated as a number of cases or patients. The document vaguely mentions "various patients organs with known abnormalities or status" for non-clinical tests and "Patients' various organs" for clinical tests.
   • Data Provenance: The data used for testing was "Scanned image datasets of various patients organs" and "Patients' scanned organs images." The country of origin is not specified, but it implies retrospective use of existing patient data.

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

   • Not specified. The document indicates that "known abnormalities or status" were used, implying a pre-established understanding of the pathologies in the patient data. It doesn't detail how this "known status" was determined for the purpose of the study, nor does it mention a specific number or qualification of experts establishing this ground truth for the test set itself.

3. Adjudication Method for the Test Set:

   • Not explicitly described. The study compares the V3D Explorer against predicate devices, stating that "evaluation results of both predicate device and V3D Explorer device were same and no significant differences were detected." This implies a direct comparison rather than an adjudication process typically used to reconcile expert discrepancies for ground truth.

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

   • No, a formal MRMC comparative effectiveness study is not described. The study performed was a comparison of the device's functionality and output against predicate devices, not an evaluation of human reader performance with and without AI assistance.
   • Effect Size: Not applicable, as no MRMC study was performed.

5. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

   • Yes, the non-clinical and clinical tests described appear to be primarily standalone evaluations of the software's ability to process images and provide measurements and visualizations comparable to predicate devices. While the software is intended for use by radiologists and clinicians, the evaluation itself focuses on the software's output, not on how human users integrate the software's output into their diagnostic process or how their performance changes. The phrasing "evaluated various organs using the predicate device and recorded the results" and "evaluated all Patients' various organs using V3D Explorer application, and recorded the results" suggests an assessment of the device's output rather than human performance.

6. Type of Ground Truth Used:

   • The ground truth referenced for the test set is "known abnormalities or status" within patient organ images. For phantom datasets, the ground truth was "pre-calculated values." This implies a combination of expert consensus/clinical diagnosis (for patient data) and empirical measurements (for phantom data). Pathology or outcomes data are not explicitly mentioned as ground truth sources.

7. Sample Size for the Training Set:

   • Not specified. The document describes the V3D Explorer as "an additional image processing option added to our V-3D visualization system for which pre-market clearance was granted by the FDA vide K#002780." It mentions "core software technology" developed in a manner consistent with accepted software development standards and unit/system integration testing. It does not provide details on a specific "training set" in the context of machine learning, as this predates widespread deep learning applications for medical image analysis. The "training" likely refers to standard software development and testing practices rather than machine learning model training.

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

   • Given that the document describes software developed under standard engineering practices rather than a machine learning model, the concept of a "training set" with ground truth (as understood for AI/ML) is not directly applicable or discussed in the text. The "ground truth" for the software's development likely refers to functional requirements specifications, expected outputs, and successful execution of unit and integration tests against these specifications. For phantom data, "pre-calculated values" would serve as the ground truth.

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