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The OEC 9800 Plus is designed to provide fluoroscopic and spot-film imaging of the patient during diagnostic, surgical and interventional procedures. Clinical application may include cholangiography, endoscopic, urologic, orthopedic, neurologic, vascular, cardiac, critical care and emergency room procedures.

The OEC® 9800 Plus is a system used to assist trained Surgeons. The system is used to provide X-Ray images while the Surgeon performs a medical procedure. Images from the system help the Surgeon to visualize the patients' anatomy. This visualization helps to localize surgical regions of interest and pathology. The images provide real-time visualization and records of pre-surgical anatomy, in vivo-surgical activity and post surgical outcomes.

The proposed device will add an alternative supplier for the X-Ray Tube. The current tube and the proposed tube have the same specifications and will be interchangeable. Verification activities confirmed that the proposed tube meets the same specification as the current supplier's tube.

The proposed device will add an alternative supplier for the Radiological Imaging Unit (RIU) or Image Intensifier. The current RIU and the proposed RIU have the same specifications and will be interchangeable. Verification activities confirmed that the alternate RIU meets the same specification as the current supplier's RIU.

The proposed device will provide an optional wireless foot switch and hand switch. The new option is equivalent to the predicate in that functionality is identical. The wireless option provides placement flexibility and reduced cable clutter.

Two printed circuit board assemblies have been combined into a single board in the proposed device due to parts obsolescence. Both the proposed and predicate assemblies share common specifications as confirmed through verification testing.

The proposed device will include a LCD monitor which replaces the obsolete CRT monitor. Both the proposed and predicate assemblies share common specifications as confirmed through verification testing.

The proposed device includes an alternative solid state drive. This drive provides a faster write speed. Both drives meet their specifications.

The proposed device will include a different model of an OEM injector system. Both the proposed and predicate OEM injector systems share common specifications as confirmed through verification testing.

Here's an analysis of the provided text regarding the acceptance criteria and study for the OEC® 9800 Plus, structured according to your request:

Acceptance Criteria and Device Performance

This 510(k) summary primarily describes modifications to an existing fluoroscopic imaging system (OEC® 9800 Plus) rather than a novel device. The core acceptance criteria revolve around demonstrating that the modified components (X-Ray tube, RIU/Image Intensifier, wireless switches, PCBs, LCD monitor, solid state drive, OEM injector system) perform equivalently to the original components and that the overall system maintains its safety, effectiveness, and intended use as the predicate device.

Table of Acceptance Criteria and Reported Device Performance:

Study Details:

1. Sample sizes used for the test set and the data provenance:

   • The document does not specify numerical sample sizes for test sets (e.g., number of images, number of patients, number of devices tested).
   • The testing described is primarily retrospective in the sense that the device is a modification to an already cleared product. The testing involved verification and validation of component changes and system performance against established specifications.
   • Data provenance: Not explicitly stated as "country of origin for data" in the context of clinical data, as no clinical studies on human patients were performed. The testing seems to be internal to GE Healthcare Surgery, likely performed at their facilities or those of their component suppliers.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • The document states "testing performed by users with relevant clinical experience" for the "Product Simulated Use Testing."
   • It does not specify the number of experts, nor their specific qualifications (e.g., "Radiologist with 10 years of experience"). It's a general statement about "users with relevant clinical experience."

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

   • No formal adjudication method (like 2+1 or 3+1 consensus for image interpretation) is mentioned. This is typical for a 510(k) submission for modifications where the focus is on engineering verification and validation rather than new clinical claims requiring extensive reader studies.

4. 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 study was done. This submission is for modifications to an existing fluoroscopic imaging system, not an AI-powered diagnostic tool. The purpose was to demonstrate equivalence of new components and maintain overall system performance, not to evaluate human reader performance with or without AI.

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

   • This question is not applicable. The device is an image-intensified fluoroscopic X-ray system, a hardware and software system for image acquisition and display, not a standalone AI algorithm. The performance evaluated was the system's ability to produce images and function correctly.

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

   • For component-level changes, the "ground truth" was the specifications of the predicate device's components. The new components had to match or exceed these specifications.
   • For system-level functionality and performance (like image quality, electrical/mechanical tests), the "ground truth" was established engineering design input requirements and established standards (e.g., IEC 60601 series, 21 CFR 1020.30-32).
   • For "Product Simulated Use Testing," the "ground truth" for meeting user needs was likely based on the assessment/feedback of "users with relevant clinical experience" against the intended use and established functional requirements.

7. The sample size for the training set:

   • Not applicable/Not mentioned. This is not an AI/machine learning device that requires a training set.

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

   • Not applicable as there is no training set for an AI algorithm.

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The OEC 9800 Plus Digital Mobile Imaging System is designed to provide fluoroscopic and spot-film imaging of the patient during diagnostic, surgical and interventional procedures. Examples of clinical applications may include cholangiography, endoscopic, urologic, orthopedic, neurologic, vascular, cardiac, critical care and emergency room procedures. The system may be used for other imaging applications at the physician's discretion.

The OEC 9800 Plus is comprised of two mobile units: a C-arm stand and a workstation. The C-arm stand supports the high-voltage generator, x-ray controls, and a "C" shaped apparatus, which supports the x-ray tube on one end and an image intensifier on the other. The C-arm is designed to perform linear and rotational motions that allow the user to position the x-ray imaging components at various angles and distances with respect to the patient. The mobile workstation, supports image display monitors, image processing and recording devices.

This 510(k) summary describes a legacy device that was submitted in 2002. At that time, the FDA's requirements for clinical performance studies and acceptance criteria were different than what they are today. The provided document focuses primarily on demonstrating substantial equivalence to a predicate device, adherence to safety standards, and providing a description of the device and its intended use. It does not contain information related to specific acceptance criteria, a clinical study with detailed performance metrics, sample sizes for test or training sets, expert qualifications, or adjudication methods in the way a modern submission would.

Therefore, I cannot fully answer your request based on the provided text. The document does not include a table of acceptance criteria and reported device performance because such performance studies for demonstrating efficacy in the modern sense were not generally required for this type of device at that time, especially when demonstrating substantial equivalence.

Here's an analysis of what information is available and what is not:

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

• Not Available: The document does not define specific performance acceptance criteria (e.g., in terms of sensitivity, specificity, or image quality metrics) that were then measured and reported. The "performance" described is largely functional equivalence to the predicate and compliance with safety standards rather than clinical efficacy.

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

• Not Available: No test set or clinical performance data is mentioned. The submission is based on substantial equivalence to a predicate device and compliance with safety standards.

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 Available: Since no test set or clinical study is described, there's no mention of experts or ground truth establishment.

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

• Not Available: No test set 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 Available: No MRMC study was done, nor is AI assistance relevant to this device from 2002. This device is an X-ray imaging system, not an AI-powered diagnostic tool.

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

• Not Available: This question is not applicable. The device is a fluoroscopic imaging system, not an algorithm.

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

• Not Available: No clinical ground truth is described.

8. The sample size for the training set

• Not Available: No training set is applicable to this type of device submission.

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

• Not Available: Not applicable.

What the document does provide regarding "acceptance criteria" and "study":

The "study" in this context is the 510(k) Pre-market Notification process, which demonstrates "substantial equivalence" to a legally marketed predicate device. The "acceptance criteria" are implied to be:

• Substantial Equivalence: The OEC 9800 Plus is substantially equivalent to the GE OEC Medical Systems OEC 9800 Digital Mobile Imaging System (the predicate). This is the primary "acceptance criterion" for a 510(k) submission.
• Safety Compliance: The device is designed in accordance with established product safety requirements outlined in various national and international standards (e.g., Federal Performance Standard for Diagnostic X-ray Systems (21 CFR 1020.30-32), ANSI/NFPA 70 & 99, UL 2601, CSA-C22.2 No. 601.1-M90, IEC 60601 series, 93/42/EEC Annex 1). Testing against these standards would have been part of the internal validation process.
• Indications For Use: The device performs its intended fluoroscopic and spot-film imaging functions for diagnostic, surgical, and interventional procedures, matching the predicate.
• Technological Characteristics: The device shares similar technological characteristics (e.g., high-voltage x-ray generator, x-ray tube, image intensifier, digital image processing, image storage, video displays, C-arm design) with the predicate.

In summary, the provided document is a 510(k) summary from 2002 for an X-ray imaging system. It demonstrates substantial equivalence and compliance with safety standards rather than clinical performance based on quantitative metrics from a clinical study with defined acceptance criteria and ground truth, as typically seen for AI/ML-enabled devices today.

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