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The Contour 2000 Mammography system, Model CTR-2000, is used for dedicated mammographic examination.

The Bennett Contour 2000 Mammographic System, Model CTR-1. 2000, is a dedicated mammographic imaging system used as an x-ray source in the performance of mammographic examinations. The CTR-2000 is adaptable to performing screening and/or biopsy procedures with the addition of either a film-based or digital-based image receptor device attached. It consists of the following components; an x-ray generator cabinet, Model M-2000G (single-phase input) or Model M-2000G-3P (three-phase input); a tube stand with a tilting c-arm; mammographic collimator (DM-2000) and tube; an operator control panel, Model M-2000C; and image receptor (film cassette holder or bucky).
The Contour 2000 Mammography System is a microprocessor-controlled x-ray source requiring single-phase 200-240 VAC, 50/60 Hz or three-phase 208-440 VAC, 50/60 Hz for operation. The Contour 2000 system's c-arm is fully counterbalanced and is locked in position using electro-mechanical locks. The c-arm has a fixed source-to-image distance (SID) of 76 cm.

The provided text describes a 510(k) submission for the "Bennett Contour 2000 Mammography System, Model CTR-2000." This document asserts substantial equivalence to predicate devices and focuses on the system's technical specifications and safety rather than a clinical performance study with specific acceptance criteria and reported device performance.

Therefore, the requested information regarding acceptance criteria and a study proving the device meets them cannot be fully extracted as structured in the prompt because the available text does not contain details about a clinical performance study with specific acceptance criteria, test sets, ground truth establishment, or expert evaluations.

The document is a 510(k) summary, which primarily aims to demonstrate substantial equivalence to legally marketed predicate devices based on design, intended use, operation, and safety testing (e.g., conformance to requirements, hazard analysis). It does not present data from a clinical trial or a standalone algorithm performance study.

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

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

• Cannot be provided. The document states that "The safety functions of the Contour 2000 Mammography System have been rigorously tested and analyzed for conformance to requirements. In each case, these functions have performed as required, ensuring that each identified hazardous condition would not occur under simulated conditions. The Contour 2000 Mammography System fulfills its design requirements by providing the operator with the ability to perform safe and effective mammographic examinations." However, it does not specify quantitative acceptance criteria (e.g., sensitivity, specificity, accuracy for a diagnostic task) or reported performance metrics from a clinical study. The focus is on technical and safety conformance, not diagnostic accuracy.

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

• Cannot be provided. No clinical test set or data provenance is mentioned. The testing described is related to the device's technical and safety functions, likely using engineered test cases or simulated conditions, not patient data in a clinical study context.

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)

• Cannot be provided. No clinical test set or ground truth establishment by experts is mentioned.

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

• Cannot be provided. No clinical test set or adjudication method is mentioned.

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

• Cannot be provided. The device described is a mammography imaging system (hardware), not an AI algorithm. Therefore, an MRMC study comparing human readers with and without AI assistance is not applicable and not mentioned.

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

• Cannot be provided. The device is a mammography imaging system (hardware), not a standalone algorithm.

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

• Cannot be provided. No clinical ground truth is mentioned. The "ground truth" for this device's evaluation would relate to its technical specifications and safety performance (e.g., x-ray output accuracy, mechanical stability), not diagnostic outcomes.

8. The sample size for the training set

• Cannot be provided. This is a hardware device, not a machine learning model, so there is no "training set" in the AI sense.

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

• Cannot be provided. Not applicable as this is a hardware device.

Summary of Device and its Evaluation (Based on provided text):

The "Bennett Contour 2000 Mammography System, Model CTR-2000" is a dedicated mammographic imaging system used as an x-ray source for mammographic examinations. Its 510(k) clearance (K984091) was based on demonstrating substantial equivalence to legally marketed predicate devices, including the Bennett Contour M-CTR, LORAD M-IV, Instrumentarium Alpha IQ, GE Senographe 800T, and Planmed Sophie Classic mammographic imaging systems.

The evaluation process described in the 510(k) summary focused on:

• Comparison of basic features, operation, and functionality to predicate devices.
• Rigorous testing and analysis of safety functions to conform to requirements and ensure identified hazardous conditions would not occur under simulated conditions.
• Fulfilling design requirements to provide safe and effective mammographic examinations.

Key takeaway: This document pertains to the clearance of a medical imaging hardware device, not a diagnostic AI algorithm. Therefore, the assessment criteria and study design are fundamentally different from what would be expected for an AI-based diagnostic tool.

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