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The Digital Imaging Systems (BSR), are intended for use in acquiring diagnosic quality images during cardiac, angiographic, vascular and neurovascular applications.

Digital Imaging System (BSR)

The provided text describes a 510(k) premarket notification for a medical device called the "Digital Imaging System (BSR)". This type of submission is for demonstrating substantial equivalence to a legally marketed predicate device, rather than performing a de novo study with acceptance criteria and a detailed study proving performance against those criteria.

Therefore, many of the requested sections regarding acceptance criteria, specific study designs, sample sizes, expert involvement, and ground truth establishment are not applicable or explicitly mentioned in this document. The document focuses on demonstrating that the new device has the same intended use and similar technological characteristics as existing, legally marketed devices.

Here's an attempt to answer the questions based only on the provided text, noting where information is not available:

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

This document does not specify quantitative acceptance criteria or a dedicated performance study with reported metrics against those criteria. The core assertion is substantial equivalence to predicate devices. The "performance" is implicitly deemed acceptable if it matches that of the predicate.

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

Not applicable. The document describes a 510(k) submission for substantial equivalence, not a performance study with a test set of data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

Not applicable. No explicit ground truth establishment process for a test set is described.

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

Not applicable. No test set adjudication is described.

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

Not applicable. This device is an "Angiographic x-ray system" / "digital imaging system," not an AI-powered diagnostic tool. There is no mention of AI or human reader improvement.

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

Not applicable. This is a hardware imaging system, not an algorithm, and the concept of "standalone performance" in this context is not relevant as described in the document.

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

Not applicable. The document assesses substantial equivalence to predicate devices, not performance against an independent ground truth for diagnostic accuracy.

8. The sample size for the training set

Not applicable. This is a hardware system, not a machine learning model requiring a training set.

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

Not applicable. This is a hardware system, not a machine learning model.

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Digital Imaging System, Model DigiTREX-X000 is a digital video processing system and is intended to be produced by the radiographic, fluoroscopic, or special procedure systems, excluding mamography.

Digital Imaging System, Model DigiTrex-1000 and DigiTrex-2000 is a digital video processing system.

I am sorry, but the provided text does not contain the detailed information necessary to answer your request about acceptance criteria and a study proving device performance. The document is an FDA clearance letter for the DigiTrex-1000 and DigiTrex-2000 digital imaging systems, indicating substantial equivalence to a predicate device.

It mentions that the device is cleared based on the information provided in the 510(k) submission and that it passed general controls provisions and compliance with good manufacturing practices. However, it does not include:

• A table of acceptance criteria and reported device performance.
• Details about sample size, data provenance, number or qualifications of experts, or adjudication methods for any test set.
• Information on MRMC comparative effectiveness studies or standalone algorithm performance.
• The type of ground truth used.
• Sample size or ground truth establishment methods for a training set.

To answer your questions, I would need access to the actual 510(k) submission document or a summary thereof, which would contain the study details and acceptance criteria.

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• Image Acquisition .
• . Display Control/Image Processing
• Input /Output Control .
• . Patient Data Management

Digital image recording and display system fo use in a cardiac catheterization laboratory or radiography/fluoroscopy suite.

The provided text is a 510(k) summary for the Camtronics Digital Imaging System, submitted in 1995. This document focuses on demonstrating substantial equivalence to predicate devices, rather than establishing acceptance criteria or reporting on a clinical study for device performance against specific metrics. Therefore, much of the requested information cannot be extracted directly from this document.

Here's a breakdown of what can and cannot be answered based on the provided text:

1. Table of acceptance criteria and the reported device performance:

This information is not provided in the document. The 510(k) summary is comparing the features and specifications of the new device to predicate devices to argue for substantial equivalence, not against pre-defined acceptance criteria for 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. The document explicitly states: "Performance data: Not required for determination of substantial equivalence for this class of device." This indicates that a formal study with a test set and associated data provenance was not conducted or submitted for this specific regulatory pathway.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

This information is not provided. Since performance data and a test set are stated as "not required," there would be no ground truth establishment by experts for such a study.

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

This information is not provided. As no test set performance data was required or provided, there would be no adjudication method.

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. The device described is a "Digital Imaging System," a Picture Archiving and Communications Device, intended for image acquisition, display control/image processing, input/output control, and patient data management. It predates the widespread concept of AI assistance in medical imaging and its primary function is not to interpret images or assist human readers in that capacity. Therefore, an MRMC study on reader improvement with AI assistance would not be applicable to this device or its regulatory submission context in 1995.

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

This information is not provided. Given the device's function as an imaging system, not an interpretive algorithm, a standalone performance study in the modern sense of AI algorithms would not have been relevant or conducted for this submission.

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

This information is not provided. As no performance study with a test set was required or presented, there is no mention of ground truth types.

8. The sample size for the training set:

This information is not provided. As this is a digital imaging system and not a machine learning algorithm in the modern sense, the concept of a "training set" as it relates to AI/ML would not apply. The device's functionality is based on established engineering principles for image acquisition, processing, and display.

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

This information is not provided. Similar to point 8, the concept of a training set and its associated ground truth establishment is not applicable to this type of device and its regulatory submission in 1995.

In summary: The provided 510(k) summary focuses on demonstrating substantial equivalence of the Camtronics Digital Imaging System to existing predicate devices based on feature comparison. It explicitly states that "Performance data: Not required for determination of substantial equivalence for this class of device." Therefore, the document does not contain information about acceptance criteria, performance studies, test/training sets, or ground truth establishment that would typically be found in submissions for devices requiring such data (e.g., AI/ML-driven diagnostic devices).

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