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This device is indicated to acquire and display cross-sectional volumes of the whole body, to include the head.

The Aquilion has the capability to provide volume sets. These volume sets can be used to perform specialized studies, using indicated software/hardware, by a trained and qualified physician.

The Aquilion LB Triton, TSX-201A/2, v4.91 is a whole body CT scanner. This device captures cross sectional volume data sets. The device consists of a gantry, patient couch (table) and peripheral cabinets used for data processing and display.

Here's an analysis of the provided text regarding the Toshiba Aquilion LB Triton (K123500) and its acceptance criteria and supporting studies:

This submission is for a modification to a cleared CT scanner, the Aquilion LB CT Scanner TSX-201A. The changes involve increased image reconstruction speed, increased high voltage generator, noise reduction processing software (AIDR 3D) as a standard feature, and an upgraded computer console. The core imaging chain (gantry, detector/DAS, tube, beam limiting device) remains unchanged.

The study presented focuses on demonstrating substantial equivalence to predicate devices rather than proving specific clinical performance against novel acceptance criteria.

1. Table of Acceptance Criteria and Reported Device Performance

Given that this is a modification of an existing device and the primary goal is to demonstrate "substantial equivalence," the "acceptance criteria" are essentially that the modified device performs comparably to the predicate device in terms of image quality metrics and diagnostic quality, without introducing new safety or effectiveness concerns.

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

• Sample Size for Test Set:
  • Phantoms: The document mentions "brain, chest, abdomen and pelvis anthropomorphic phantoms" for image comparison data and "phantoms" for image quality metrics. The exact number of phantoms or scans performed on them is not specified.
  • Clinical Studies (Diagnostic Images): The document states "representative diagnostic images including brain, chest, abdomen and peripheral exams were obtained using the subject device." The exact number of patients/exams for these diagnostic images is not specified.
• Data Provenance: The document does not explicitly state the country of origin. Given the submitter is "Toshiba America Medical Systems, Inc." located in Tustin, CA, it is plausible the testing was conducted in the US or involved data from US-based sites, but this is an inference. The study appears to be prospective for the purpose of this submission, as the data collection was specifically to demonstrate substantial equivalence of the modified device.

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

• Number of Experts: The document does not specify the number of experts used for any evaluation, nor does it explicitly state the process for "ground truth" establishment by experts.
• Qualifications of Experts: The document does not provide qualifications for any potential experts involved.

It's important to note that the study relied heavily on phantom data for quantitative image quality metrics and demonstration of diagnostic quality using representative images, rather than a formal reader study with expert-established ground truth on patient cases.

4. Adjudication Method for the Test Set

The document does not describe any adjudication method (e.g., 2+1, 3+1). The nature of the study, which relies on phantom-based image metric comparisons and qualitative assessment of diagnostic images, typically does not involve adjudication as seen in clinical trials with expert readers.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done or at least not described in this 510(k) summary. The submission focuses on demonstrating substantial equivalence through technical performance metrics and qualitative diagnostic image assessment, not on measuring human reader performance improvement with or without AI assistance.

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

Yes, in essence, the image quality metrics study using phantoms and the image comparison data using anthropomorphic phantoms can be considered a form of standalone performance evaluation. The device (algorithm and hardware) produced images, and those images were then analyzed for various technical attributes (spatial resolution, CT number, CNR, uniformity, noise properties, low contrast resolution) directly, without a human interpretation step as the primary outcome. The "diagnostic quality" assessment also refers to the images themselves.

7. The Type of Ground Truth Used

• Phantom Gold Standard: For the image quality metrics (spatial resolution, CT number, CNR, uniformity, noise properties, low contrast resolution), the "ground truth" is established by the physical properties of the phantoms themselves and quantitative measurements derived from them, compared to the expected performance from the predicate device.
• Implicit Diagnostic Quality: For the "representative diagnostic images," the "ground truth" is implied to be the acceptable diagnostic quality as determined by experienced clinical practitioners (though the document doesn't detail the assessment method or who performed it). There's no mention of pathology, clinical outcomes, or expert consensus on a specific finding for these images.

8. The Sample Size for the Training Set

The document does not provide any information about a training set. This submission is for a CT scanner's hardware and software modification, not a machine learning or AI algorithm that typically requires a specific training set of medical images. While the AIDR 3D noise reduction software is mentioned, the details of its development (including training data) would likely have been part of its original 510(k) clearance (K113466) and are not elaborated upon here.

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

Since no information regarding a training set is provided, the method for establishing its ground truth is also not described.

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