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The Imatron Ultra Access Workstation is intended as an accessory to Imatron's Ultrafast Computed Tomography (CT) Scanner, a cleared device. The Ultra Access Workstation accepts data from Imatron's Ultrafast CT scanner and allows for advanced post processing of such data. Thus, as modified from the ISG Workstation, the Imatron Ultra Access Workstation is intended - as are the predicate devices - for receiving, manipulating, transmitting, storing, viewing, characterizing, comparing and enhancing high quality CT electronic images, as an aid in diagnosis, including for cardiac analysis, by a trained physician.

The Imatron Ultra Access Workstation is intended as an accessory to Imatron's Ultrafast Computed Tomography (CT) Scanner. The Ultra Access Workstation accepts data from Imatron's Ultrafast CT scanner and allows for advanced post processing of such data. The Imatron Ultra Access Workstation is intended for receiving, manipulating, transmitting, storing, viewing, characterizing, comparing and enhancing high quality CT electronic images, as an aid in diagnosis, including for cardiac analysis, by a trained physician.

The provided text describes the "Imatron Ultra Access® Workstation with Cardiac Software Extensions" and its substantial equivalence to predicate devices, rather than a study proving the device meets specific acceptance criteria with detailed performance metrics. The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to legally marketed devices, not on proving new clinical effectiveness or diagnostic accuracy against predefined acceptance criteria.

However, based on the information provided, I can infer the "acceptance criteria" are the features and functionalities present in predicate devices, and the "study" is the substantial equivalence comparison itself.

Here's an analysis based on the document's content:

1. Table of "Acceptance Criteria" (Predicate Device Features) and Reported Device Performance

The acceptance criteria here are derived from the features present in the predicate devices. The "reported device performance" is whether the Ultra Access Device also possesses that feature.

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

The document does not detail a specific "test set" in the context of clinical performance evaluation (e.g., patient cases used to validate diagnostic accuracy). The "testing" mentioned ("The Ultra Access Workstation successfully passed all testing at Imatron") refers to internal verification and validation against design specifications and compliance with standards (e.g., DICOM), confirming functionality and safety aspects. It does not provide information on:

• Sample size: Not specified for any performance testing.
• Data provenance: Not specified.
• Retrospective/Prospective: Not specified.

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

This information is not provided in the 510(k) summary. The document focuses on feature comparison and substantial equivalence, not a clinical trial involving expert-derived ground truth.

4. Adjudication Method for the Test Set

Not applicable as no clinical test set with human ground truth establishment is described.

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

No MRMC study is mentioned or implied. The 510(k) summary is for a device accessory that enables advanced post-processing and display of CT images and does not claim to improve human reader performance through AI assistance as a primary output. The document states the workstation is intended "as an aid in diagnosis, including for cardiac analysis, by a trained physician," implying the physician remains in control.

6. Standalone (Algorithm Only) Performance Study

No standalone performance study is explicitly described as a primary component of this 510(k) submission. The device is an "accessory" to a CT scanner and is an "Image Processing Workstation," meaning its function is to process and display images for a physician. Its performance is implicitly linked to its ability to accurately process and present the data as intended for clinical review, which is covered by compliance with standards and successful internal testing.

7. Type of Ground Truth Used

For the features described, the "ground truth" is largely conceptual compliance with existing standards (DICOM) and mirroring or enhancing functionalities found in predicate devices. For example, the ability to perform "Automatic computation of calcium score" (Item 6) implies an internal algorithm, but its accuracy isn't validated against external ground truth (e.g., pathology or long-term outcomes) in this document. The document notes that "new algorithms may yield more accurate results at higher flow states" for perfusion (Item 17), citing "attached scientific references," suggesting that the underlying algorithms might have been validated elsewhere or are derived from established scientific literature.

8. Sample Size for the Training Set

Not applicable. The document describes an image processing workstation with software features, not a machine learning model that requires a "training set" in the typical AI sense. The software's development likely involved traditional software engineering, testing, and potentially some algorithm development based on existing scientific principles or data characteristics, but not "training data" in the quantity and context usually associated with modern AI/ML.

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

Not applicable, as no training set for an AI/ML model is mentioned.

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