(13 days)
This device is designed to produce cross-sectional images of a human body by reconstruction of x-ray transmission data from the same axial plane taken at different angles. These images have been proven to be clinically useful in the diagnosis of spine and head injuries, intracranial tumors, blood clots in the brain, eye trauma, soft tissue lesions in the extremities, gastrointestinal lesions, abdominal and pelvic malignancies, and hepatic metastases. CT is also used to evaluate intestinal obstructions, assess intra-abdominal abnormalities and to examine musculoskeletal degeneration. This device employs no intended uses that are not in cleared devices already found in the marketplace.
X-ray imaging of whole body - Computerized Tomography Including: Axial Volumetric (Helical) CT Fluoroscopy
The Aquilion Super 4 CT Scanner is similar to the Aquilion Multislice CT scanner. The major difference between the two devices is a change of hardware in the computational subsystem and an improved patient couch. This device uses the same software and scanning hardware as the predicate device.
The provided text is a 510(k) Summary for the Aquilion Super 4 CT System. This type of submission is for demonstrating substantial equivalence to a predicate device, not for proving a new device meets specific performance acceptance criteria through clinical studies in the way modern AI/ML device submissions typically do.
Therefore, many of the requested sections about acceptance criteria, study details, sample sizes, and ground truth establishment cannot be found in this document because they are not typically required or included in a 510(k) for a modified conventional medical device like a CT scanner from 2003.
Here's an attempt to answer based only on the provided text, indicating where information is not available:
Acceptance Criteria and Study for Aquilion Super 4 CT System (TSX-101A/7)
This document is a 510(k) submission for the Aquilion Super 4 CT System, which seeks to demonstrate substantial equivalence to a predicate device (TSX-101A Aquilion CT w/ CGS-22A). As such, it focuses on comparing the new device's technological characteristics and intended uses to the predicate, rather than establishing new performance acceptance criteria through a clinical study. Performance is implicitly accepted if it is "substantially equivalent" to the already-cleared predicate device.
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (Explicitly Stated in Document) | Reported Device Performance (as implied by Substantial Equivalence) |
|---|---|
| Same intended uses as predicate device. | "This device employs no intended uses that are not in cleared devices already found in the marketplace." |
| Same technological characteristics as predicate device. | "This device employs the same technological characteristics as the predicate device, differing only in the specifics of subassembly composition." |
| Design and manufacture under Quality System Regulations (21 CFR § 820). | "This device is designed and manufactured under the Quality System Regulations..." |
| Conformance with Federal Diagnostic Equipment Standard (21 CFR § 1020.30 and 1020.33). | "...All requirements of the Federal Diagnostic Equipment Standard... will be met..." |
| Conformance with applicable parts of IEC-60601 - Medical Device Safety standards. | "...this system is in conformance with the applicable parts of the IEC-60601 - Medical Device Safety standards." |
| No explicit quantitative performance acceptance criteria (e.g., sensitivity, specificity, accuracy) are stated as the device is not an AI/ML diagnostic tool. | No explicit quantitative performance metrics are provided, as the submission relies on substantial equivalence to a predicate CT scanner. |
2. Sample size used for the test set and data provenance
- Not Applicable / Not Provided. This submission is for a conventional CT scanner, not an AI/ML diagnostic device requiring a specific test set of images with established ground truth for performance evaluation. The substantial equivalence argument relies on comparing hardware and intended use.
3. Number of experts used to establish the ground truth for the test set and qualification of those experts
- Not Applicable / Not Provided. Ground truth establishment by experts for a test set is not relevant for this type of conventional CT scanner submission.
4. Adjudication method for the test set
- Not Applicable / Not Provided. Adjudication methods are not relevant for this type of conventional CT scanner submission.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and its effect size.
- No, an MRMC comparative effectiveness study was not done. This type of study is typically performed for AI/ML diagnostic devices to assess their impact on human reader performance, which is not applicable to a conventional CT scanner.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done.
- Not Applicable / Not Done. This device is a CT scanner, not an AI algorithm evaluated for standalone performance. Its function is to produce images for human interpretation.
7. The type of ground truth used
- Not Applicable / Not Provided. Ground truth (e.g., pathology, outcomes data) is not established for the performance evaluation of this conventional CT scanner in the context of this 510(k) submission. The device's "ground truth" implicitly relies on the proven clinical utility of CT imaging for diagnosis, which has been established through decades of medical practice and research preceding this submission.
8. The sample size for the training set
- Not Applicable / Not Provided. This device is a CT scanner, not an AI/ML algorithm that requires a training set of data.
9. How the ground truth for the training set was established
- Not Applicable / Not Provided. As noted above, this is not an AI/ML device, so there is no training set or ground truth for it.
§ 892.1750 Computed tomography x-ray system.
(a)
Identification. A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.