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These are stationary x-ray systems intended for obtaining radiographic images of various portions of the human body in a clinical environment. The devices are not intended for mammography

This is a complete stationary diagnostic x-ray system employing digital x-ray panels coupled with image acquisition software. The key features are: Ceiling Tube Suspension, Motorized Movements, Auto-Positioning, Tube Mounted 10" Touch Screen, Elevating 6 Way Table Patient Load: 5501bs, Single User Interface, High Frequency Generator. This ergonomic design incorporates automatic motorized positioning, creating an efficient workflow increasing the patient throughput. Precision offers automatic stitching enhancing the workflow further. Tube, vertical wall stand and table have extended range of motion for easy patient positioning. The acquisition software is installed on a Windows compatible workstation. The high frequency generator is available in different power ratings. All components are either 510(k) exempt or previously cleared. Generators are available in 50, 65, 80 kW (High Frequency) models.

Here's an analysis of the provided text regarding the acceptance criteria and study for the Arcoma AB 0180 Intuition & 0072 Precision Stationary Digital X-Ray Systems (K140683):

1. Table of Acceptance Criteria and Reported Device Performance

The provided document does not explicitly list quantitative acceptance criteria for the device's performance. Instead, it focuses on demonstrating substantial equivalence to a predicate device (Arcoma Intuition, K073632) through functional comparisons, non-clinical tests, and a qualitative clinical evaluation.

The "acceptance criteria" can be inferred from the overall claim of substantial equivalence and the scope of the testing performed, primarily that the modified device is "as safe, as effective, and performs as well as or better than the legally marketed device."

• Individual and system performance.
• Electrical safety and electromagnetic compatibility.
• Software integration validation.
• Risk analysis.
• Compliance with IEC safety and EMC standards. | Met. "The modified unit has undergone individual and system performance tests, electrical safety and electromagnetic compatibility testing, as well as software integration validation and risk analysis. The unit meets IEC safety and EMC standards."

Functionally identical capabilities to predicate device despite panel, generator, and tube stand modifications. Specifically, new Canon digital panels (K103591, K102012) each have their own 510(k) clearances, implying their individual performance meets regulatory standards. |
| Clinical Performance:

• Diagnostic quality of images. | Met. "Clinical images were obtained in accordance with the FDA Guidance Document on Solid State Imaging Devices. They were evaluated by professional radiologist and found to be of good diagnostic quality." |
  | Overall Equivalence:
• As safe and effective as predicate.
• Performs as well as or better than predicate. | Met. "The nonclinical and clinical tests that the device is as safe, as effective, and performs as well as or better than the legally marketed device identified in paragraph 3."

Technological characteristics are "essentially the same" as the predicate, with modifications to digital panels, x-ray generator, and tube stands that retain "functionally identical capabilities." New panels offer higher resolution and wired/wireless options, suggesting potential improvements without detrimental impact. |

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

• Test Set Sample Size: The document does not specify a numerical sample size for the clinical images used in the clinical study. It states only that "Clinical images were obtained."
• Data Provenance: The document does not specify the country of origin of the data or whether the study was retrospective or prospective.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

• Number of Experts: The document states that clinical images "were evaluated by professional radiologist" (singular, though likely implying multiple, it does not specify the number).
• Qualifications of Experts: The experts are described only as "professional radiologist." No further details on their experience level (e.g., "10 years of experience") are provided.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1) for the clinical image evaluation. It simply states that the images "were evaluated by professional radiologist and found to be of good diagnostic quality."

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The study described is a qualitative evaluation of image quality by radiologists, comparing the modified device's performance to an implicit standard of "good diagnostic quality" rather than a direct comparison against the predicate by multiple readers on multiple cases. Therefore, no effect size of human readers improving with AI vs. without AI assistance is applicable or reported, as this device is a traditional x-ray system, not an AI-powered diagnostic tool.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

No, a standalone (algorithm only) performance study was not done. This device is a digital X-ray system, and its primary output is human-interpretable images, not an automated diagnostic algorithm.

7. The Type of Ground Truth Used

The ground truth for the clinical images seems to be based on expert consensus (or individual expert opinion) regarding "good diagnostic quality." The text does not mention pathology, outcomes data, or other objective ground truth measures for evaluating the images.

8. The Sample Size for the Training Set

This information is not applicable and not provided in the document. This device is a traditional digital X-ray system, not an AI or machine learning algorithm that requires a training set. The "software integration validation" mentioned refers to the system's operational software, not an AI model.

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

This information is not applicable as there is no training set for an AI/ML algorithm described.

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