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X-ray imaging of whole body - Computerized Tomography Including: Axial Volumetric (Helical) CT Fluoroscopy

The Asteion (TSX-021A) is a whole body CT Scanner that employs slip ring technology which allows continuous rotation of the x-ray tube and x-ray detector. The x-ray detector collects transmission data, as it and the x-ray tube rotate 360 degrees axially around a human body. Computer controlled data processing reconstructs the transmission data into a two dimensional image representing a "slice" of the body. As is common with today's CT Scanner, the Asteion has the capability to acquire volumetric (helical) data by initiating table movement during data This data can be reconstructed per the operator's preference, to include three acquisition. dimensional rendering of the patient data. Additionally the TSX-021A is capable of CT Fluoroscopy, which is used on other Toshiba CT scanners and has received previous market clearance from the Agency. This device incorporates a standard x-ray tube and a solid state x-ray detector for the acquisition of data. The microprocessor based computer, hard disk storage of software and data, and display electronics are mature technologies that are standard to and well known throughout the medical device industry.

This 510(k) summary describes a CT scanner (Asteion CT Scanner, TSX-021A) which is a "New Product" and appears to leverage substantial equivalence to a predicate device (Toshiba TSX-011A, Xpress [K903701/A]). The context of this document is a regulatory submission for market clearance, rather than a detailed performance study like those for AI/CADe devices. As such, the information you're requesting regarding "acceptance criteria" and a "study that proves the device meets the acceptance criteria" in the context of device performance metrics for AI/CADe devices is not directly applicable or available in this document.

Instead, the "acceptance criteria" for a traditional medical device like a CT scanner in a 510(k) submission primarily revolve around substantial equivalence to a predicate device and conformance to established standards for safety and performance (not algorithmic performance). The "study" proving this typically involves comparisons of technological characteristics and intended uses, along with adherence to manufacturing regulations and recognized standards.

Here's an attempt to answer your questions based on the provided text, reinterpreting "acceptance criteria" and "study" in the context of a traditional device 510(k) submission:

1. A table of acceptance criteria and the reported device performance

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

This information is not provided in the document. A 510(k) for a CT scanner typically doesn't involve clinical "test sets" in the same way an AI/CADe device would. Performance is generally demonstrated through engineering testing, compliance with standards, and comparison to the predicate device's established performance, rather than a clinical trial with a specific patient dataset.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

This information is not provided and is not relevant for this type of device submission. Ground truth establishment by experts is a typical requirement for AI/CADe devices to assess diagnostic accuracy, which is not the focus of this CT scanner's 510(k).

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

This information is not provided and is not relevant for this type of device submission.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

This information is not provided and is not relevant for this type of device submission. MRMC studies are used for evaluating the impact of AI/CADe assistance on human reader performance, which does not apply to a standalone CT imaging system.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

This information is not provided and is not relevant for this type of device submission. The CT scanner itself is the device; it does not contain an "algorithm only" component that would be evaluated for standalone performance in this context. Its performance is its ability to acquire and reconstruct images conforming to specifications.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)

This information is not provided and is not relevant for this type of device submission.

8. The sample size for the training set

This information is not provided and is not relevant for this type of device submission. Training sets are pertinent to machine learning algorithms.

9. How the ground truth for the training set was established

This information is not provided and is not relevant for this type of device submission.

In summary: The provided document is a 510(k) summary for a conventional CT scanner. The "acceptance criteria" and "study" are framed around demonstrating substantial equivalence to a predicate device and adherence to recognized safety and quality standards, rather than clinical performance metrics derived from patient data analysis typically associated with AI/CADe device submissions.

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