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Torpedo Gelatin Foam is indicated for use in embolization of:
· Hypervascular tumors
· Blood vessels to occlude blood flow to control bleeding / hemorrhaging in the peripheral vasculature

Torpedo Gelatin Foam is a hydrophilic medical device which consists of resorbable dry gelatin foam that is compressed into a cylindrical shape and preloaded into a cartridge with a standard female and male luer fittings. The device is available in two sizes (0.9 mm and 1.7 mm) and two lengths configurations (10 mm and 20 mm).
Once rehydrated, the deformable torpedoes can be injected into the target vessel with an intravascular catheter or a micro-catheter (depending on the size range) to provide a mechanical barrier to blood flow. Contrast enhancement may be used to monitor the embolization procedure using fluoroscopy. The device is intended for single use and is provided sterile.

This document is a 510(k) summary for the Torpedo Gelatin Foam device. It describes the device, its intended use, and its substantial equivalence to a predicate device. However, it does not contain the information requested in your prompt regarding acceptance criteria and the detailed study results that prove the device meets these criteria in the context of an AI-driven medical device.

The provided text does not describe an AI medical device or its performance criteria. It is a traditional medical device 510(k) submission for an embolization device (gelatin foam).

Therefore, I cannot provide the requested information about acceptance criteria and study details for an AI medical device based on the given text. The document refers to:

• Bench testing: Leveraged from a previously cleared device (K183578) with no changes in material, design, or processing.
• Animal testing: Leveraged from the predicate device (K183120) to support new indications for use. An animal study (7 test, 8 control sheep) evaluated vascular occlusion, local tissue effects, and in-vivo degradation over 4 weeks using angiography and histopathology. The outcome was successful embolization and no significant difference in artery patency between devices.

None of this relates to AI performance metrics, sample sizes for AI model testing, expert labeling, MRMC studies, or training set details that would be pertinent to an AI medical device.

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