Search Results

The UroView 2800 is designed to provide fluoroscopic and spot-film imaging of the patient during diagnostic, surgical, and interventional procedures. Clinical applications may include but are not limited to urologic and endoscopic procedures. The system may be used for other imaging applications at the physician's discretion.

The UroView 2800 is a fluoroscopic x-ray system including a tilting patient-support table with overhead x-ray tube assembly, high-voltage x-ray generator, image intensifier, and video image display. A separate mobile workstation provides digital image processing, image storage capability, and additional video display.

The provided document K993687, concerning the UroView 2800, is a 510(k) summary and not a comprehensive study report. Therefore, it primarily focuses on establishing substantial equivalence to predicate devices and adherence to relevant standards rather than presenting detailed experimental data on acceptance criteria and device performance as one might find in a clinical trial or performance study.

Based on the provided text, a detailed table of acceptance criteria and reported device performance, information on sample sizes, expert qualifications, and adjudication methods for a test set, and specific details about MRMC studies, standalone algorithm performance, or training set ground truth cannot be fully extracted.

The document mainly highlights the device's adherence to various safety and performance standards without explicitly stating "acceptance criteria" through a defined study with quantifiable outcomes against a benchmark. The "performance" described is in the context of meeting general functional requirements and safety standards.

Here's a breakdown of what can be inferred or is missing based on your request:

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

The document does not present a table of specific, quantifiable acceptance criteria alongside reported device performance derived from a dedicated study. Instead, the device's "performance" is implicitly deemed acceptable by its compliance with various recognized industry standards.

• 21 CFR 1020.30-32 (Federal Performance Standard for Diagnostic X-ray Systems)
• ANSI/NFPA 70 & 99 (National Electrical Code and Standard for Health Care Facilities)
• UL 2601 (Medical Electrical Equipment)
• CSA-C22.2 No. 601.1-M90 (Medical Electrical Equipment)
• IEC 60601-1 (Medical Electrical Equipment, General Requirements for Safety)
• IEC 60601-1-2 (Medical Electrical Equipment, Electromagnetic Compatibility)
• IEC 60601-1-3 (Medical Electrical Equipment, Radiation Protection in Diagnostic X-ray)
• IEC 60601-1-4 (Medical Electrical Equipment, Programmable Electrical Medical Systems)
• IEC 60601-2-7 (Medical Electrical Equipment, Safety of HV/X-ray Generators)
• IEC 60601-2-28 (Medical Electrical Equipment, X-ray Tubes and X-ray Source Assemblies)
• IEC 60601-2-32 (Medical Electrical Equipment, Safety of Associated X-ray Equipment)
• IEC 60601-2-46 (Medical Electrical Equipment, Safety of Operating Tables)
• 93/42/EEC - Annex 1 (Essential Requirements of the Medical Devices Directive) |
  | Environmental Parameters (EMC): | Complies with IEC 60601-1-2 (Electromagnetic Compatibility). |
  | Radiation Protection: | Complies with IEC 60601-1-3 (Radiation Protection in Diagnostic X-ray). |
  | Electrical Safety: | Complies with UL 2601, CSA-C22.2 No. 601.1-M90, IEC 60601-1, and relevant parts of IEC 60601-2 series for X-ray generators, tubes, and associated equipment. |
  | Software/Programmability: | Complies with IEC 60601-1-4 (Programmable Electrical Medical Systems). |
  | Patient Support Table Safety: | Complies with IEC 60601-2-46 (Safety of Operating Tables). |

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

• Missing. The document does not describe a "test set" in the context of an AI/algorithm evaluation. This is a medical device (fluoroscopic x-ray system), not an AI algorithm. Its performance is assessed through compliance with engineering and safety standards, not typically by analyzing a dataset of medical images.
• Data Provenance: Not applicable as it's not an AI/data-driven device.

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)

• Missing/Not Applicable. The concept of "ground truth" established by experts for a test set is not relevant for this type of device submission. Its safety and effectiveness are established through adherence to engineering and performance standards, and comparisons to predicate devices, rather than through diagnosis or interpretation of clinical images by experts.

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

• Missing/Not Applicable. Adjudication methods are typically used in clinical studies involving interpretation tasks and expert consensus, which is not the nature of this 510(k) submission.

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 Applicable. The UroView 2800 is a physical medical imaging system, not an AI or computer-aided detection/diagnosis (CAD) system. Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance would not have been performed or reported in this context.

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

• Not Applicable. This is not an AI algorithm.

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

• Not Applicable in the traditional sense. The "ground truth" for this device's acceptance is its compliance with established regulatory and industry standards for X-ray systems (e.g., radiation output limits, electrical safety, image quality specifications as defined by the standards).

8. The sample size for the training set

• Not Applicable. The UroView 2800 is a conventional medical device; there is no "training set" as it does not employ machine learning or AI algorithms that require data for training.

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

• Not Applicable. See point 8.

Ask a specific question about this device