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The Balloon Inflation System is intended to be used for the reduction of fractures and/or creation of a void in cancellous bone in the spine. This includes percutaneous vertebral augmentation. The system is to be used with cleared spinal polymethylmethacrylate (PMMA) bone cements indicated for use during percutaneous vertebral augmentation, such as kyphoplasty.

Balloon Inflation System is mainly used to treat vertebral compression fractures caused by osteoporosis. Puncture needles or dilators are used to establish working channels, then balloon catheters are placed along the working channels and inflation device connect to balloon catheter and control it expansion to lift the upper and lower endplates of the vertebral body, restore the height of the vertebral body, and form bone cement filling cavities.

This is a 510(k) Premarket Notification for a Balloon Inflation System, which is a medical device, and therefore the document does not contain information about acceptance criteria and study designs typically associated with AI/ML-driven software devices. The provided text is a summary of documentation for a physical medical device.

Specifically, the document addresses:

• Device Name: Balloon Inflation System
• Regulation Number/Name: 21 CFR 888.3027, Polymethylmethacrylate (PMMA) Bone Cement
• Regulatory Class: Class II
• Product Code: NDN
• Intended Use: For the reduction of fractures and/or creation of a void in cancellous bone in the spine (percutaneous vertebral augmentation, e.g., kyphoplasty), to be used with cleared spinal PMMA bone cements.

The acceptance criteria and supporting studies for this type of device focus on non-clinical bench testing to demonstrate performance, safety, and substantial equivalence to a predicate device, rather than AI/ML performance metrics.

Here's a breakdown of the information that is present, relevant to a physical medical device, contrasted with the AI/ML-specific questions you asked:

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

The document provides a summary of non-clinical tests that were performed and states that the "test results met the preset criteria." However, it does not provide a detailed table of specific acceptance criteria values (e.g., "burst pressure > X psi") or the exact reported performance values. It only generically states that results met criteria.

Here's what's described:

2. Sample size used for the test set and the data provenance

For the non-clinical tests mentioned, sample sizes are not specified. Data provenance is implied to be laboratory testing conducted by or for Ningbo HicRen Biotechnology Co., Ltd. There is no mention of human subject data (retrospective or prospective) as this is not an AI/ML device.

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

This is not applicable to a physical medical device submission. "Ground truth" in this context refers to engineering specifications and performance standards established through industry standards (like ISO) and regulatory requirements.

4. Adjudication method for the test set

Not applicable. Adjudication methods like 2+1 or 3+1 are used for expert review of human image interpretations, which is not relevant here.

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. This is an AI/ML device-specific question.

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

Not applicable. This is an AI/ML device-specific question.

7. The type of ground truth used

For this physical device, the "ground truth" is based on engineering specifications, established international standards (e.g., ISO 11138-2, ISO 10993 series), and pre-set internal criteria for performance and safety. There is no pathology or outcomes data used for "ground truth" in this context.

8. The sample size for the training set

Not applicable. This is not an AI/ML device, so there is no "training set."

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

Not applicable. There is no training set or corresponding ground truth for an AI/ML model for this physical device.

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