Search Results

The TSX-101A CT Scanners are indicated for head and whole body computed tomography applications.
X-ray imaging of whole body - Computerized Tomography Including: Axial Volumetric (Helical) CT Fluoroscopy

The Aquilion TSX101A/A and TSX-101A/C CT Scanner Systems are composed of a gantry, patient table, image acquisition hardware and software, an operator console and associated accessories. Materials and construction are similar to the Aquilion CT Scanner Multi-slice 16 (CGS-31A) [K022050] and the TSX-101A/7 Aquilion Super 4 CT Scanner [K031469], and are compliant with IEC60601-1 and associated collateral and particular standards, and applicable sections of 21 CFR Subchapter J.

The provided text is a 510(k) summary for the Toshiba Aquilion Multislice CT Scanners (TSX-101A/A and TSX-101A/C). This document describes the device, its intended use, and argues for its substantial equivalence to previously marketed predicate devices.

Crucially, this document does not contain information about specific acceptance criteria or a study designed to prove the device meets those criteria in the way a clinical performance study would for an AI/CAD device. This is a Computed Tomography (CT) scanner, which is a medical imaging device, not an AI or CAD software that produces diagnostic interpretations or measurements.

The "Summary of Studies" section in the K033418 510(k) document states:
"These devices have been evaluated for electrical, mechanical, and radiation safety. Furthermore they conform to applicable medical device safety and performance standards."

This indicates that the studies conducted were primarily focused on safety and engineering standards compliance rather than clinical performance metrics like sensitivity, specificity, or reader improvement with AI.

Therefore, for many of your requested points, the answer based on this document will be that the information is not applicable or not provided.

Here's a breakdown based on the information available:

1. Table of Acceptance Criteria and Reported Device Performance

Not Applicable/Not Provided. This document does not describe specific clinical acceptance criteria (e.g., sensitivity, specificity, accuracy) for a diagnostic task or algorithm performance. The device is a CT scanner, and the evaluation focuses on its safety and conformance to general engineering and radiation safety standards.

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

Not Applicable/Not Provided. The document does not describe a "test set" in the context of clinical performance evaluation for a diagnostic algorithm. The evaluations were for electrical, mechanical, and radiation safety of the hardware.

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

Not Applicable/Not Provided. There is no mention of experts establishing ground truth for a clinical test set, as this was not a clinical performance study of a diagnostic algorithm.

4. Adjudication Method for the Test Set

Not Applicable/Not Provided. Since there was no clinical test set for diagnostic performance, no adjudication method is described.

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

No. The document does not mention an MRMC comparative effectiveness study. This type of study is typically done for AI/CAD devices to evaluate reader performance with and without AI assistance, which is outside the scope of a CT scanner's hardware safety and performance evaluation.

6. Standalone (i.e., algorithm only without human-in-the-loop performance) Study

No. The document does not describe a standalone performance study. This is a hardware device (CT scanner) and does not have a standalone algorithm for diagnostic interpretation in the sense of AI/CAD software.

7. Type of Ground Truth Used

Not Applicable/Not Provided. There is no mention of ground truth in the context of diagnostic accuracy, as the studies focused on safety and functional compliance of the CT scanner hardware.

8. Sample Size for the Training Set

Not Applicable/Not Provided. This device is a CT scanner, not a machine learning algorithm. Therefore, there is no "training set" in the context of AI development.

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

Not Applicable/Not Provided. As there is no training set mentioned, this point is not applicable.

Ask a specific question about this device