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The Angiography Injector is intended to aspirate and inject contrast media in the interventional procedure. It can also be used to inject fluids into, or withdraw fluids from the body.

The Angiography Injector is intended to provide the function of aspirating and injecting contrast media in the interventional procedure. It can also be used to inject fluids into, or withdraw fluids from the body. The proposed device is intended for single use and is provided sterile using EO sterilization.

The Angiography Injector consists of six components: 1) Piston, 2) Plunger cap, 3) Push-button 4) Barrel, 5) Plunger and 6) Adapter (rotating or fixed). The proposed device is available in volume of 6mL, 8mL, 10mL and 12mL.

The primary package is blister package and plastic paper package. The blister package and plastic paper package all consist of PE film and Tyvek®2FS paper.

The provided text is a 510(k) summary for a medical device called "Angiography Injector." This document describes the device, its intended use, comparison to a predicate device, and the non-clinical testing performed to demonstrate substantial equivalence.

However, the 510(k) summary does not contain information related to a study proving the device meets specific acceptance criteria in the context of AI/ML performance, human reader studies (MRMC), or a detailed setup for establishing ground truth as typically observed in AI/ML medical device submissions.

The document discusses "acceptance criteria" only in the general sense of meeting design specifications and regulatory standards for a conventional angiography injector (e.g., biocompatibility testing results showing acceptance criteria met, performance tests meeting ISO 7886 requirements). It specifically states: "No clinical study is included in this submission."

Therefore, based on the provided text, I cannot answer the questions about:

• A table of acceptance criteria and reported device performance related to AI/ML or human reader studies.
• Sample sizes for test sets (for AI/ML).
• Data provenance.
• Number of experts and their qualifications for ground truth.
• Adjudication method for test sets.
• MRMC comparative effectiveness study or human reader improvement with AI.
• Standalone (algorithm only) performance.
• Type of ground truth used (expert consensus, pathology, outcomes data, etc.) for AI/ML.
• Sample size for the training set (for AI/ML).
• How ground truth for the training set was established.

This is because the device described is a physical medical instrument (an angiography injector and syringe), not an AI/ML-driven diagnostic or assistive software. The "performance testing" mentioned refers to engineering and safety bench tests (e.g., force to operate piston, freedom from air/liquid leakage, sterility, biocompatibility etc.), not diagnostic performance on medical images.

In summary, the provided document does not support a response to the specific questions regarding AI/ML device performance or clinical study methodologies.

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