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The Endoscopic Injection Needle is an accessory for currently marketed endoscopes to allow delivery of injectable materials into tissue during an endoscopic procedure.

The Endoscopic Injection Needle consists of a luer lock hub, flexible cannula and retractable stainless steel needle at the distal tip. The hub is designed to accommodate a standard syringe. The device is supplied sterile and is for single patient use.

This document is a 510(k) premarket notification for an Endoscopic Injection Needle. The device is an accessory for endoscopes used to deliver injectable materials into tissue during endoscopic procedures. The notification concludes that the device is substantially equivalent to a predicate device (Carbon Medical Technologies Endoscopic Injection Needle K042615).

Based on the provided information, there is no study proving the device meets specific acceptance criteria in the sense of an effectiveness or performance study with a numerical outcome on efficacy, sensitivity, specificity, etc. The document focuses on demonstrating substantial equivalence to a predicate device through technological characteristics, risk assessment (FMEA), and various validation and testing activities related to manufacturing and safety.

Therefore, many of the requested items (e.g., acceptance criteria for clinical performance, sample size for test set, number of experts, adjudication methods, MRMC studies, standalone performance, training set details) are not applicable or not present in this type of submission for this particular device. This 510(k) is for a Class II endoscope accessory, and the focus is on demonstrating that the new device is as safe and effective as a legally marketed predicate device, rather than proving novel clinical efficacy.

However, based on the technological characteristics and performance section, we can infer the "acceptance criteria" and "study" are related to manufacturing, safety, and equivalence to the predicate.

Here's an attempt to answer the questions based on the available information:

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

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

• Sample Size for Test Set: Not explicitly stated. The document refers to "validation" and "testing" (e.g., sterilization validation, functional testing), which would involve samples, but the specific number of units tested is not provided in this summary.
• Data Provenance: Not specified, but likely from in-house lab testing and potentially third-party testing facilities engaged by Carbon Medical Technologies, Inc. It's a technical submission, not a clinical study involving patients, so "country of origin for clinical data" is not relevant here. The studies mentioned (e.g., sterilization, shelf life) are prospective laboratory/engineering studies.

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 Applicable. This submission does not involve clinical "ground truth" derived from expert interpretation of medical data (like images or pathology). The "ground truth" for these tests are objective measurements and established standards for engineering, manufacturing, and safety (e.g., sterility, material properties, functional integrity).

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

• Not Applicable. This is not a clinical study involving subjective interpretation that would require adjudication. The "tests" are objective and based on established protocols and standards.

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

• No. An MRMC study is completely irrelevant for this device. This is a physical medical device (an injection needle), not an AI-powered diagnostic or assistive tool.

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

• No. This is not an algorithm or AI device.

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

• For the validation and testing mentioned, the "ground truth" is based on:
  • Established scientific and engineering principles: (e.g., for functional testing, material properties).
  • Regulatory standards and guidelines: (e.g., for sterilization, biocompatibility, EO residuals, packaging).
  • Predicate device characteristics: For demonstrating technological equivalence.

8. The sample size for the training set

• Not Applicable. This is not a machine learning or AI device that requires a training set.

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

• Not Applicable. This is not a machine learning or AI device.

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