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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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The Jumong Series Stationary Radiographic System is intended for use by a qualified/trained doctor or technician on both adult and pediatric subjects for taking diagnostic radiographic exposures of the skull, spinal column, chest. abdomen, extremities, and other body parts. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. Not for mammography.

This device represents a new combination of an already cleared solid state digital x-ray acquisition panel with software and diagnostic x-ray compnents required to make a complete system. Film cassettes may be employed in place of the digital panel. The purchaser can select from one of four configurations. The x-ray generator is a CPI CMP 200DR. The x-ray tubes are supplied by Varian (RAD-14), and the collimator is the Ralco R225 ACS DHHS. The system complies with the CDRH Radiological Health performance standard in the Code of Federal Regulations, as well as the voluntary IEC standards IEC 60601-1 and IEC 60601-1-2. All major components are either UL or CSA listed.

The provided text is a 510(k) summary for the "Jumong Series Stationary Radiographic System." It primarily focuses on demonstrating substantial equivalence to a predicate device rather than providing specific acceptance criteria and performance data from a standalone study. Therefore, much of the requested information cannot be extracted directly from this document.

Here's what can be gathered:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state quantitative acceptance criteria for image quality or clinical performance that the device was tested against. Instead, it relies on demonstrating that the device meets general safety and performance standards, and that its components (like digital panels) are previously cleared. The "performance" assessment is framed as "bench, safety test, and software validation documentation indicates that the new device is as safe and effective as the predicate device" and that the device "conforms to US Performance Standards" and various IEC/NEMA voluntary standards.

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

The document mentions that "Clinical images were provided," but does not specify the sample size, data provenance (e.g., country of origin), or whether they were retrospective or prospective. It explicitly states these images "were not necessary to establish substantial equivalence."

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 in the document. The phrase "clinical images were provided" suggests some form of evaluation but no details on expert involvement or ground truth establishment for a test set.

4. Adjudication Method:

This information is not provided in the document.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

No MRMC comparative effectiveness study is mentioned in the document. The submission focuses on substantial equivalence based on technical characteristics and safety/performance standards, rather than a clinical trial comparing human reader performance.

6. Standalone Performance Study:

The document implies that images were used to show the "complete system works as intended," suggesting some form of standalone evaluation. However, it does not describe a formal standalone performance study with specific metrics, acceptance criteria, or a detailed methodology. The "non-clinical testing" section primarily covers integration, bench, safety, and software validation.

7. Type of Ground Truth Used:

The document does not explicitly state the type of ground truth used for any clinical image evaluation, given that the clinical images were "not necessary to establish substantial equivalence."

8. Sample Size for the Training Set:

This information is not applicable as the document describes a device (X-ray system), not an AI algorithm that would typically require a training set.

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

This information is not applicable as the document describes a device (X-ray system), not an AI algorithm.

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Sedecal "NOVA FA DR System" is intended for use by a qualified/trained doctor or technician on both adult and pediatric subjects for taking diagnostic radiographic exposures of the skull, spinal column, chest, abdomen, extremities, and other body parts. Applications can be performed with the patient sitting, standing, or lying in the prone or supine position. Not for mammography.

"NOVA FA DR System" refers to a full Digital Radiography system consisting of: NOVA: Automatic Ceiling Suspension NBS: Tilting Vertical Wall Stand system with CXDI Canon Detectors 401C / 401C Compact / 55C / 501C (Option 1) NET: Elevating Table with CXDI Canon Detector (same detectors as Wall Stand) (Option 2) Flexi DT: Mobile Elevating Table SEDECAL SHF Generator Series, output powers: 50 kW / 65 kW / 80 kW Toshiba Tube: maximum heat dissipation: 300 kHU / 400 kHU Ralco Collimator: Manual / Motorized

Here's a breakdown of the acceptance criteria and study information for the Sedecal "NOVA FA DR System" based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document describes a modification to an existing X-ray system (K090279). The acceptance criterion for this modification is implicitly to demonstrate that the modified device is as safe and effective as the predicate device, with images of at least comparable quality.

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

• Sample Size for Test Set: Not explicitly stated. The document mentions "various human body structures (chest, skull, abdomen, extremities)" were acquired, but no number of cases or patients is provided.
• Data Provenance: Not explicitly stated (e.g., country of origin). The study used "clinical images," implying prospective acquisition for the purpose of the study, but this is not explicitly confirmed. Given Sedecal is based in Spain, it's plausible the images were acquired there, but this is speculation.

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

• Number of Experts: One.
• Qualifications of Experts: "Board Certified Radiologist." No specific years of experience are mentioned.

4. Adjudication Method for the Test Set:

• Adjudication Method: None explicitly mentioned. With only one radiologist, there was no need for adjudication for consensus.

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 MRMC or AI comparative effectiveness study was performed or mentioned. This submission is for a modification to a digital X-ray system, not an AI-powered diagnostic tool. The focus is on the imaging system itself, not on reader performance improvement with or without AI.

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

• This is not applicable as the device is a digital X-ray system, not an algorithm, and its performance inherently involves human operation and interpretation.

7. The Type of Ground Truth Used:

• Ground Truth Type: Expert opinion/evaluation by a Board Certified Radiologist. The "good quality, high resolution, and clinically acceptable" assessment served as the ground truth for image quality.

8. The Sample Size for the Training Set:

• Not applicable/Not mentioned. This document describes a 510(k) for a hardware modification and new detectors, not an AI/machine learning algorithm that requires a training set. The "testing" refers to verification and validation of the hardware performance, software integration, and image quality.

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

• Not applicable/Not mentioned. As above, there is no training set for an AI algorithm.

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