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This device is indicated to acquire and display cross sectional volumes of the whole the head, with the capability to image whole organs in a single rotation. Whole organs include but are not limited to brain, heart, pancreas, etc.

The Aquilion ONE has the capability to provide volume sets of the entire organ. These volume sets can be used to perform specialized studies, using indicated software, of the whole organ by a trained and qualified physician.

The Aquilion ONE Vision, TSX-301C/1, /2, /3, /4, /5, /6, /7, /8, v7.0 are whole body CT scanners that capture cross sectional volume data sets used to perform specialized studies, using indicated software/hardware, by a trained and qualified physician. These systems are based upon the technology and materials of previously marketed Toshiba CT systems.

The provided document is a 510(k) summary for the Toshiba Aquilion ONE Vision CT system. While it details several modifications and general safety and testing procedures, it does not provide specific acceptance criteria or a comprehensive study report with quantitative performance metrics that would directly answer your request in the format you've outlined for acceptance criteria, sample sizes, and detailed ground truth establishment.

The document states that the submitter conducted "Risk analysis and verification/validation testing through bench testing" and "clinical evaluations" to demonstrate that the modifications meet requirements and perform as intended. However, the specific metrics, thresholds for acceptance, and detailed results are not provided in this summary.

Here's a breakdown of what can be inferred or is explicitly stated, and what is missing based on your request:

1. Table of Acceptance Criteria and Reported Device Performance:

This information is not provided in the document. The document mentions "image quality metric of AIDR 3D Enhanced versus current AIDR 3D is substantially equivalent to or better than the predicate device with regard to spatial resolution, CT number and contrast-to-noise ratio, noise properties and standard deviation of noise." It also states that SurekV selects appropriate kV and SEMAR functions similarly. However, no specific numerical acceptance criteria (e.g., "spatial resolution must be > X lp/cm") or reported performance values are given.

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

• Test Set Sample Size: Not explicitly stated. The document mentions evaluation "utilizing phantoms" for image quality metrics and "clinical evaluations" for new applications. However, the number of phantoms or clinical cases is not specified.
• Data Provenance (country of origin, retrospective/prospective): Not explicitly stated. Given the nature of a 510(k) submission and the description of "clinical evaluations," it's likely conducted with clinical data, but whether it's retrospective or prospective, or the origin, is not mentioned.

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

Not explicitly stated. For the "clinical evaluations" of the new applications (4D Orthopedic Analysis and 4D Cerebral Artery Morphological Analysis), the document states that results "were comparable to manual measurements and/or segmentations." This implies expert involvement for these manual processes, but the number and qualifications of these experts are not detailed.

4. Adjudication Method for the Test Set:

Not explicitly stated. Since the number of experts and how "ground truth" was established for clinical evaluations is vague, the adjudication method is also not mentioned.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the effect size of human readers with vs. without AI assistance:

No, an MRMC comparative effectiveness study is not mentioned. The document describes a comparison of the modified device's performance against the predicate device and against "manual measurements and/or segmentations" for clinical applications. There's no indication of a study involving human readers' performance with and without AI assistance (as this is a CT scanner, not a diagnostic AI software).

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

Yes, a form of standalone performance evaluation was done. The testing for image quality metrics (spatial resolution, CT number, CNR, noise) using phantoms, and the confirmation that SurekV selects appropriate kV and SEMAR functions similarly, are examples of standalone algorithm/system performance evaluation.

7. The Type of Ground Truth Used:

• For image quality metrics (spatial resolution, CT number, CNR, noise): Phantom-based measurements. Phantoms represent a known, objective standard.
• For clinical evaluations of new applications (4D Orthopedic Analysis and 4D Cerebral Artery Morphological Analysis): Comparison to "manual measurements and/or segmentations." This suggests expert-derived ground truth, though the specifics are lacking.

8. The Sample Size for the Training Set:

Not applicable/Not provided. This document is for a CT scanner, which is hardware, with software modifications including image reconstruction (AIDR 3D Enhanced) and new clinical applications. While these might have internal "training" or calibration components, the concept of a "training set" in the context of a learning algorithm for diagnostic decision support is not highlighted or described. The focus is on verifying the performance of the modified system.

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

Not applicable/Not provided. (See point 8).

In summary, the provided 510(k) document is a regulatory summary focusing on demonstrating substantial equivalence to predicate devices and adherence to safety standards. It does not contain the detailed study protocols, acceptance criteria, and quantitative performance results typically found in full clinical or technical study reports.

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