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This is a stationary digital x-ray system for general radiography and RSA (Roentgen Stereophotogrammetric Analysis procedures). Not for mammography.

The Halifax SR Suite consists of two X-Ray imaging systems; the two systems are integrated through a synchronization switch. The switch allows the two X-Ray imaging systems to fire simultaneously, providing a pair of X-Ray images from different perspectives to be taken at the exact same time. This process allows for Roentgen Stereophotogrammetric Analysis (RSA). RSA is a stereo x-ray technique that enables measurements more precise than single plane radiography based on phantom precision studies. The resulting level of precision provides measurements of joint replacement stability.

The Halifax Imaging Kit is part of the SR Suite product line and provides an alternative path to creating an SR Suite. The Halifax Imaging Kit consists of FDA cleared and/or certified X-Ray components integrated into an existing digital radiography room already containing an FDA cleared x-ray imaging system to form an SR Suite. The exposures of the Halifax Imaging Kit and the existing Digital Radiography (DR) system are synchronized by replacing the trigger switches of the two systems with either the Universal Synchronization Switch or the Imaging Kit Control Module (IKCM).

The Universal Synchronization Switch or IKCM ensures the two X-Ray imaging systems fire simultaneously, therefore providing a pair of X-Ray images from two different perspectives taken at the exact same time. There are two versions of the Halifax Imaging Kits:

a) UNIVERSAL SYNCHRONIZATION (NON-GE BASED CONFIGURATION) The Universal Synchronization Switch synchronizes two independent X-ray systems as accurately as possible by using the manual pushbutton interface of each X-ray system. This replaces the synchronization switch that was described in our predicate K121345.

b) IMAGING KIT CONTROL MODULE (GE BASED CONFIGURATION) The general purpose of the IKCM is to coordinate and control the activities of the detector and workstation with the activities of the generator, as well as coordinate the exposures between the client's clinical system and the Halifax Imaging Kit for RSA exposures. The current version of the IKCM is designed specifically for interfacing with the following components:

•GEHC WDR1 Upgrade Kit which consists of a 'Flashpad' detector, a workstation named 'MagicPC', and a 'Cabinet' for power distribution and communication control. Integrating with a pre-existing system (GEHC Discovery XR656 Plus).

· EMD Technologies Epsilon Series generator. (Or generators already on site)

The provided text describes a 510(k) premarket notification for the "Halifax Imaging Kit," a stationary digital x-ray system. The submission focuses on demonstrating substantial equivalence to a predicate device (Halifax SR Suite 1.0, K121345).

Based on the information provided in the document, here's a breakdown of the acceptance criteria and the study that proves the device meets them:

No specific acceptance criteria table or quantitative performance metrics are explicitly stated in this 510(k) summary. The submission focuses on demonstrating "substantial equivalence" rather than proving specific performance metrics of the device itself. The primary "study" to meet acceptance criteria relies on demonstrating that the new device configuration (Halifax Imaging Kit) is as safe and effective as its predicate device and that its components (like digital panels) already have their own 510(k) clearances.

Therefore, the "acceptance criteria" here is primarily about fulfilling the FDA's requirements for substantial equivalence, rather than meeting specific quantifiable performance targets for a diagnostic or AI-driven system.

However, I can extract information related to the closest aspects of your request:

1. Table of Acceptance Criteria and Reported Device Performance

As noted, there is no explicit table of acceptance criteria with quantitative performance metrics for this device as it's not a diagnostic AI system. The acceptance criteria for a 510(k) submission of this nature are generally qualitative and relate to safety, effectiveness, and substantial equivalence to a predicate device.

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

• Test Set Description: The "test set" primarily refers to components, bench tests, and a phantom study.
• Sample Size: Not applicable in the traditional sense of a clinical or image-based test set for an AI/diagnostic algorithm.
  • For the bench testing, no "sample size" of patients or images is mentioned. It refers to testing of the Universal Synchronization Switch (board level functionality, firmware, enclosure wiring) and the Imaging Kit Control Module.
  • For the phantom study (for precision validation per installation), the sample size would be the "small carbon fibre box" used for in vitro precision and accuracy calculation. No specific number of phantom images or measurements is given, but it implies a single phantom setup used for validation.
• Data Provenance: Not explicitly stated for specific data points other than the general context of the company being Halifax Biomedical Inc. (Canada) and the submission to FDA (USA). The phantom study refers to validation at a "[Hospital]" in "[City]" ([Room details]), "[State/Province]", "[Country]" – implying it could be anywhere, but the company is Canadian. The data is prospective in the sense that the bench testing and phantom validation are performed as part of the device development and installation process.

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

• Not applicable. This submission does not involve human expert adjudication of medical images to establish ground truth for a diagnostic algorithm. The "ground truth" for the device's functionality relates to its mechanical/electrical performance, precise synchronization, and ability to perform RSA measurements.
• The "experts" would be the engineers and QA personnel performing the bench tests and the precision validation (phantom study). Their qualifications are typically implied by their roles in medical device development and testing.

4. Adjudication Method for the Test Set

• Not applicable. No human image-reading adjudication method is mentioned as this is not a diagnostic imaging AI system. The "adjudication" of performance is done through objective bench test results and phantom study measurements against expected performance, rather than through consensus of human readers interpreting clinical images.

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

• No. An MRMC study was not done. This device is an X-ray system, not an AI or CAD system intended to assist human readers. The document explicitly states "Clinical testing was not required to establish equivalence because all of the new digital receptor panels already have their own 510(k) clearances."

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

• Not applicable. This is an X-ray imaging system, not a standalone algorithm. While it produces images for Roentgen Stereophotogrammetric Analysis (RSA), the "algorithm" for RSA (RSA-CMS software) is stated to be "Unchanged" from the predicate device and was cleared under K042383. The submission is about the kit that acquires the images, not a new RSA analysis algorithm.

7. The Type of Ground Truth Used

• Engineering specifications and physical measurements (for bench testing and phantom studies).
  • For the Universal Synchronization Switch and Imaging Kit Control Module: Proper Board level functionality, firmware performance, proper enclosure internal wiring assemblies and connections.
  • For the RSA System precision: In vitro precision and accuracy calculated using a phantom study (small carbon fibre box) consistent with common RSA validation techniques. This relies on the known physical properties and movements of the phantom as the "ground truth."
  • For the digital receptor panels: Their own prior 510(k) clearances serve as evidence of their established performance and safety, essentially acting as their "ground truth" for those components.

8. The Sample Size for the Training Set

• Not applicable. This device is an X-ray imaging system, not an AI or machine learning algorithm that requires a training set. The software for RSA analysis (RSA-CMS) is unchanged from the predicate and would have had its own development and validation process earlier, but details are not in this document.

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

• Not applicable. See point 8.

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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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