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Vitrea2 is a medical diagnostic system that allows the processing, review, analysis, communication and media interchange of multi-dimensional digital images acquired from a variety of imaging devices. Vitrea2 Version 3.8.1 adds the following previously FDA-cleared software applications to the currently marketed Vitrea2 system: Fusion7D, RTist, ImageChecker CT Lung v2.0 System, AutoPoint Temporal Comparison Tool, and the Pulmonary Artery PE (Patency Exam).

The Vitrea2 system is a medical diagnostic device that allows the processing, review, analysis, communication and media interchange of multi-dimensional digital images acquired from a variety of imaging devices. The Vitrea2 system 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.

The provided text describes the Vitrea2®, Version 3.8.1 Medical Image Processing Software and its substantial equivalence to predicate devices, but it does not contain the specific details about acceptance criteria or a dedicated study proving the device meets those criteria for the Vitrea2 system itself.

Instead, the document primarily focuses on:

• Device Description: What the Vitrea2 system does.
• Intended Use: The purpose of the Vitrea2 system and its added functionalities (Fusion7D, RTist, ImageChecker CT Lung v2.0 System, AutoPoint Temporal Comparison Tool, Pulmonary Artery PE).
• Predicate Device Comparison: How Vitrea2 compares to other legally marketed devices.
• Summary of Studies: A general statement about design, development, testing, and validation according to written procedures, integration testing, Beta testing, and risk management.
• Conclusion: The device is substantially equivalent to predicate devices.
• FDA Clearance Letter: Formal FDA clearance.

The "Summary of Studies" section provides a high-level overview of their development and testing process, but it does not detail performance metrics or studies using specific acceptance criteria, sample sizes, or ground truth methodologies that would typically be presented for a detailed performance study. It mentions internal testing and "Beta validation" but does not provide results from these.

Therefore, for your request, I can only provide what can be inferred or directly stated from the text, and will explicitly state what information is missing.

1. Table of Acceptance Criteria and Reported Device Performance

• "The software utilized was designed, developed, tested, and validated according to written procedures."
• "The Vitrea2, Version 3.8.1 system will successfully complete integration testing prior to Beta validation."
• "Software Beta testing/validation will be successfully completed prior to release."
• "Potential hazards have been studied and controlled by a Risk Management Plan."
• It concludes the device is "substantially equivalent" to predicates. |

Missing Information: Specific quantitative or qualitative acceptance criteria (e.g., accuracy thresholds, precision values, specific clinical endpoints) are not provided. The document does not report performance metrics against any defined acceptance criteria.

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

Missing Information: The document states that "integration testing" and "Beta testing/validation" were successfully completed, but it does not specify the sample size of cases or images used for these tests. It also does not mention 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

Missing Information: The document does not mention the use of external experts for establishing ground truth for any test set, nor does it specify their number or qualifications.

4. Adjudication Method for the Test Set

Missing Information: As no specific test set or expert ground truth establishment is detailed, no adjudication method is mentioned.

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

Missing Information: The document does not describe any MRMC comparative effectiveness study where human readers' performance with and without AI assistance was evaluated, nor does it provide an effect size for such a study.

6. Standalone (Algorithm Only) Performance Study

Missing Information: While the device has functionalities for image processing and analysis, the document does not describe a standalone performance study specifically for an algorithm without human-in-the-loop performance measurement. The descriptions for some of the added functionalities (like ImageChecker CT Lung) sound like CAD systems, which often have standalone performance studies, but no such details are provided for the Vitrea2 system or its components in this document.

7. Type of Ground Truth Used

Missing Information: The document does not specify the type of ground truth used (e.g., expert consensus, pathology, outcomes data) for any of its internal testing or validation.

8. Sample Size for the Training Set

Missing Information: The document does not provide any details about a training set, its size, or its composition. This suggests the Vitrea2 system (or at least the core system described here) may not rely on a machine learning model that requires a dedicated training set in the way a modern AI/CAD system would. It appears to be more of an image processing and visualization platform.

9. How Ground Truth for the Training Set Was Established

Missing Information: As no training set is mentioned, naturally, the method for establishing its ground truth is also not provided.

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RTist is a software application, intended to display and visualize 2D & 3D multimodality (i.e. CT, MRI, and PET) medical image data. The user may process, render, review, store, print and distribute DICOM 3.0 compliant medical image data within the system and/or across computer networks at distributed locations utilizing standard PC hardware.

The volume and linear measurement functions are intended for evaluation and quantification of turnor measurements, location/displacement study, analysis and evaluation of both hard and soft tissues. The software also supports interactive segmentation of the region of interest (ROI), automated contouring of multi-slice ROI and labeling of 'avoidance' structure(s) during critical evaluation.

Typical users of this system are trained professionals, including but not limited to radiologists, clinicians and technicians. When interpreted by a trained physician, reviewed images may be used as an element for diagnosis.

The RTist is a software application acting as a stand alone Picture Archiving and The relise is a betting (PACS). It may be marketed as the software only as well as packaged with a standard 'off the shelf' PC Hardware. It is in effect a 'plug in' publication to the Fusion 7D/ Miraview / Reveal - MVS software platform (reference K020546) but is effectively 'vendor' neutral and as such an enhancement to many other medical image/ data management systems.

The comprehensive array of features provided by the software allows the medical professional to visualize, review, interpret, manipulate, render and distribute medical image data stored in DICOM format. The networking component of the product allows the exchange of medical image data with any other DICOM-compatible or FTPcompatible server over a standard TCP/IP network.

The RTist receives images in DICOM format, which are then converted into volume data format using core software technology. The RTist viewer provides interactive orthogonal and multi-planar reformatting which enables the user to evaluate abnormality or malformation displayed in the image. The volume and linear measurement features provided by the software enable evaluation and quantification of region of interest volume, linear measurements and location/displacement.

The software also supports interactive segmentation of the region of interest (ROI), automated contouring of multi-slice ROI and labeling of structure(s) during critical evaluation.

RTist processes an array of medical images including anatomical images (e.g. CT and conventional MRI), and functional images (e.g. SPECT and PET).

The RTist software incorporates standard visualization features to display the input DICOM data and the results of the registration operations.

The provided text is a 510(k) summary for the RTist software application. It describes the device, its intended use, and lists predicate devices. However, it does not contain any information about acceptance criteria, device performance studies, sample sizes, ground truth establishment, or expert qualifications.

Therefore, I cannot fulfill your request for a table of acceptance criteria and reported device performance or details about a study proving the device meets acceptance criteria based on the provided text. The document is essentially a regulatory submission summary, not a clinical trial report or a performance validation study.

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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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