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The COR Analyzer II is intended to assist a trained physician to analyze Computed Tomography (CT) Angiographic images. The device is not intended for use with mammography. The COR Analyzer II is specifically indicated to provide visualization of the major coronary vessels and lesions, thus assisting the physician in visualizing the coronary anatomy and pathology. COR Analyzer II has abilities for coronary vessels segmentations, abnormalities display and processing.

COR Analyzer I is a post processing software application which runs on a stand-alone Windows based work-station. The device input is Computed Tomography Angiography (CTA) set of images. The received data is displayed on the workstation screen, reviewed and selected by the operator for processing. Software provides the location and segmentation of the coronary artery tree. The software also labels the coronary arteries and displays them uniquely colored in a 3D view. The artery changes of volumes are processed and deviations from expected values are detected. When a deviation exceeds threshold value it is displayed on the 3D view.

The provided text does not contain detailed information about the acceptance criteria or a specific study proving the device meets those criteria. The 510(k) summary (K072242) for COR Analyzer II states that "Bench and clinical data demonstrate that the COR Analyzer II meets the required specifications." However, it does not provide the specific acceptance criteria, performance metrics, study design, or results of those bench and clinical studies.

Therefore, I cannot populate the table or answer most of the questions based on the provided document.

Here's a breakdown of what can be extracted and what is missing:

Conclusion:

The provided 510(k) summary for K072242, COR Analyzer II, briefly mentions that bench and clinical data "demonstrate that the COR Analyzer II meets the required specifications" and that "No adverse effects have been detected." However, it does not elaborate on the specific acceptance criteria, the details of these studies, the methodologies used (like sample sizes, ground truth establishment, expert involvement, or adjudication methods), or the actual performance results. This level of detail is typically found in the full 510(k) submission not publicly available here, or in supporting documentation that would accompany such a summary for a reviewer.

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VITALConnect, Version 4.1 is a medical diagnostic software system intended to process. analyze, review, and distribute multi-dimensional digital Images acquired from a variety of imaging devices including: CT, MR, CR/DR/DX, SC, US, NM, PET, XA, and RF, etc. VTALConnect is not meant for primary image interpretation in mammography. In addition. the VITALConnect system has the following specific intended use:

Vessel Probe is intended for viewing the anatomy and pathology of a patient's coronary arteries. Clinicians select any artery to view the following anatomical references: the highted vessel in 3D, two rotate-able curved MPR vessel views displayed at angles orthogonal to each other, and cross sections of the vessel. Cross sectional measurements can be obtained using standard Vital Images software measuring tools. Clinicians can manually measure the lumen width to obtain percentage stenosis calculations, based on the ratio of the smallest to the largest diameter. In addition, clinicians can manually measure vessel length along the centerline in standard curved MPR views and examine Hounsfield Units statistics.

CT Coronary Artery Analysis is intended for viewing the anatomy and pathology of a patient's coronary arteries. Clinicians can select any coronary artery to view the following anatomical references: the highlighted vessel in 3D, two rotatable curved MPR vessel views displayed at 90 degree angles to each other, and cross sections of the clinician can semiautomatically determine contrasted lumen boundaries, stenosis measurements, and maximum and minimum lumen diameters. In addition, clinicians can edit lumen boundaries and examine Houndsfield unit statistics.

The ViTALConnect 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 ViTALConnect system provides multi-dimensional visualization of digital images to aid clinicians in their analysis of anatomy and pathology. The ViTALConnect system 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 .

The provided text does NOT describe specific acceptance criteria with numerical targets (e.g., sensitivity, specificity, accuracy thresholds) or a detailed study proving the device meets said criteria.

Instead, it offers a general overview of the device, its intended use, a comparison to predicate devices, and a high-level summary of the validation process.

Here's a breakdown of the requested information based on the provided text, highlighting what is missing:

• "The ViTALConnect 4.1 system will successfully complete integration testing/verification testing prior to Beta validation."
• "Software Beta testing/validation will be successfully completed prior to release."
  This indicates a general requirement for successful completion of tests, but no quantifiable performance metrics are reported. |
  | 2. Sample size used for the test set and the data provenance | Not specified. The document mentions "Software Beta testing/validation" but does not provide details on the sample size of cases/images used in this testing, nor the country of origin of the data or whether it was retrospective or prospective. |
  | 3. Number of experts used to establish the ground truth for the test set and their qualifications | Not specified. The document does not mention the use of experts to establish a ground truth for any test set or their qualifications. |
  | 4. Adjudication method for the test set | Not specified. There is no mention of any adjudication method (e.g., 2+1, 3+1, none) for a test set. |
  | 5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and its effect size. | No. The document does not mention an MRMC comparative effectiveness study or any effect size related to human readers improving with AI assistance. The device is a "Medical Image Processing Software" intended for clinicians to "process, analyze, review," and in the case of "CT Coronary Artery Analysis," it can "semiautomatically determine contrasted lumen boundaries, stenosis measurements," but there is no study described that compares human performance with and without this assistance. |
  | 6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done | Not explicitly stated as a standalone performance evaluation with metrics. The description of "CT Coronary Artery Analysis" suggests semi-automatic functions (e.g., "semiautomatically determine contrasted lumen boundaries"), implying an algorithm-only component. However, the document does not report specific standalone performance metrics (like sensitivity, specificity, or accuracy) for these semi-automatic functions. The overall system is described as assisting clinicians in their analysis and measurements, not as a fully autonomous diagnostic tool. |
  | 7. The type of ground truth used | Not specified. Since no specific performance studies or test sets with ground truth are detailed, the type of ground truth (e.g., expert consensus, pathology, outcomes data) is not mentioned. |
  | 8. The sample size for the training set | Not specified. The document refers to the general software development process ("designed, developed, tested, and validated according to written procedures") but does not provide any details about a training set or its size, which would typically be associated with machine learning development. Given the 2007 submission date, the device likely predates widespread deep learning applications with distinct "training sets" as understood today. |
  | 9. How the ground truth for the training set was established | Not applicable/Not specified. As no training set is mentioned, naturally, how its ground truth was established is not discussed. |

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Myrian is a multi modality medical diagnostic device. It is aimed at reviewing and analysing anatomy and pathology. It also includes DICOM communication capabilities and media interchange features (printing, CD burning, storing). It runs on any standard PC including laptops that might be purchased independently by the end user. It provides user a set of tools meant to create and modify volumes of interest. This device is not indicated for mammography use. Lossy compressed mammography images and digitized film screen images must not be used for primary image interpretations. Mammographic images may only be interpreted using an FDA approved monitor that offers at least 5 mega pixel resolution and meets other technical specifications approved by the FDA.

Myrian® system is a software suite providing the following services : Import of DICOM images from any DICOM modality, workstation or PACS Visualization of DICOM images in thin MPR, thick MPR and full 3D volume rendering Creation of VOI (Volume Of Interest) with dedicated tools Calculation of volumes, surface and of average, minimum and maximum densities of VOI Follow-up of patient examination Generation of medical reports Export of DICOM images to any format, DICOM entity or media

Here's an analysis of the provided text regarding the Intrasense MYRIAN device:

Analysis of Intrasense MYRIAN Device Performance and Study

1. Table of Acceptance Criteria and Reported Device Performance

Based on the provided text, specific numerical acceptance criteria and corresponding reported device performance metrics are not explicitly stated. The submission focuses on demonstrating substantial equivalence to predicate devices and adherence to general software safety guidelines.

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

The document mentions "User Site Testing, Benchmarking and clinical data analysis" for performance verification. However, no specific sample sizes for the test set or details about data provenance (e.g., country of origin, retrospective/prospective nature) are provided.

3. Number of Experts Used to Establish Ground Truth and Qualifications

The document does not specify the number of experts used to establish ground truth or their qualifications. It states that "Typical users of Myrian® with its Modules are trained medical professionals, including but not limited to radiologists, technologists and clinicians," and that images, "When interpreted by a trained physician, filmed or displayed images on the Myrian® and its Modules may be used as a basis for diagnosis." This implies that medical professionals would be involved in evaluating the device, but no details on ground truth establishment are given.

4. Adjudication Method

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

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

The document does not indicate that a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was performed. There is no mention of comparing human readers with and without AI assistance or any effect size of improvement. The device description and performance data focus on its standalone functionality and equivalence to predicate devices.

6. Standalone (Algorithm Only) Performance Study

The document implies that the device's performance was evaluated in various settings, stating "User Site Testing, Benchmarking and clinical data analysis demonstrate that MYRIAN meet the required specifications." This suggests that the algorithm and its features were tested for their intended functionality, which aligns with standalone performance evaluation. However, specific metrics of "algorithm-only" performance (like sensitivity, specificity, accuracy for a particular task) are not provided. The focus is on the software suite's general functionality for image processing, visualization, and measurement.

7. Type of Ground Truth Used

The document does not explicitly state the type of ground truth used (e.g., expert consensus, pathology, outcomes data). While it mentions that images interpreted by a trained physician may be used for diagnosis, it doesn't describe how ground truth was established for the purpose of validating the device's performance.

8. Sample Size for the Training Set

The document does not specify the sample size used for any training set. Given the submission date (2007) and the description of the device (a software suite for general image processing and visualization), it's highly likely that this device does not utilize deep learning or other machine learning algorithms that require explicit "training sets" in the modern sense. It appears to be a rule-based or conventional image processing software.

9. How Ground Truth for the Training Set Was Established

As there's no mention of a training set, the document does not describe how ground truth for a training set was established.

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