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The enSpire™ Discectomy System is intended for use in cutting, grinding and aspirating intervertebral disc material during discectomy procedures in the cervical, thoracic and lumbar spine.

The enSpire™ Discectomy System is a single-use discectomy device that is designed to cut and grind intervertebral disc material. An auger mechanism retrieves the excised debris and ejects it into a collection chamber. The enSpire™ Discectomy System is supplied as a sterile, single patient use, disposable device.

The provided text describes a traditional 510(k) submission for the enSpire™ Discectomy System. This submission focuses on demonstrating substantial equivalence to a predicate device and does not involve AI/ML technology or studies typically associated with diagnostic algorithms. Therefore, much of the requested information regarding acceptance criteria for AI performance, sample sizes for test/training sets, expert ground truth establishment, adjudication methods, and MRMC studies is not applicable or cannot be extracted from this document.

However, I can extract information related to the device's functional performance and non-clinical testing.

Here's a breakdown of the relevant information:

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not explicitly list quantitative "acceptance criteria" in a table format for specific performance metrics in the way one might expect for a diagnostic AI. Instead, the document states that the "enSpire™ Discectorny System meets the established specifications necessary for consistent performance during its intended use." The "reported device performance" is summarized by the successful completion of the non-clinical tests.

Study Proving Device Meets Acceptance Criteria:

The study proving the device meets the acceptance criteria is a series of in-vitro bench studies and non-clinical tests as summarized under "I. Summary of Non-Clinical Data" and detailed in the bulleted list.

2. Sample Size Used for the Test Set and the Data Provenance

• Sample Size:
  • For the non-clinical bench studies, the specific sample sizes for each test (e.g., number of devices tested for tissue removal, durability cycles) are not provided in this 510(k) summary.
• Data Provenance: The studies were in-vitro bench studies, meaning they were conducted in a laboratory setting using simulated conditions or non-human tissue models, not from patient data. Therefore, "country of origin of the data" and "retrospective or prospective" do not apply in the context of patient data.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of those Experts

• This information is not applicable as the studies were non-clinical bench tests evaluating device mechanics and functional performance, not diagnostic interpretations requiring expert ground truth in the medical sense.

4. Adjudication Method for the Test Set

• This information is not applicable for non-clinical bench testing. Performance was assessed against predetermined engineering specifications and functional requirements.

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 comparative effectiveness study was not done. This submission is for a medical device (surgical tool), not an AI/ML diagnostic or assistive technology.

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

• Not applicable. This device is a mechanical surgical tool, not an algorithm.

7. The Type of Ground Truth Used

• For the non-clinical studies, the "ground truth" was established by engineering specifications, functional requirements, and established industry standards (e.g., for biocompatibility, sterility, electrical safety). For example, "No Breach of Annulus or Endplates" is a direct performance criterion with no "expert consensus" needed beyond confirming the physical result.

8. The Sample Size for the Training Set

• Not applicable. There is no "training set" as this is a physical medical device, not an AI/ML algorithm that requires training data.

9. How the Ground Truth for the Training Set Was Established

• Not applicable. (See point 8).

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The SpineView ENSPIRE™ Debrider is intended for use in cutting, grinding and aspirating intervertebral disc material during discectomy procedures in the cervical, thoracic and lumbar spine.

The SpineView ENSPIRE™ Debrider is a single-use discectomy device that is designed to cut and grind intervertebral disc material. Its auger mechaeo mechaeo um retrieves the excised debris and ejects it into a collection chamber.

The provided documentation for K090278, the ENSPIRE™ Debrider System, describes the device's intended use and comparison to predicate devices, along with a summary of supporting data. However, it does not include specific acceptance criteria, a detailed study design with sample sizes for test or training sets, information about ground truth establishment (other than general biocompatibility and bench testing), or specifics about expert involvement or adjudication methods typically found in AI/ML device studies.

This is because the ENSPIRE™ Debrider System is a physical medical device (a surgical tool for discectomy), not an AI/ML software device. Therefore, the types of studies and acceptance criteria applicable to AI/ML would not be relevant in this context. The evaluation focuses on physical characteristics, mechanical performance, biocompatibility, and intended use as a surgical instrument.

Here's a breakdown of what can be extracted from the document, tailored as much as possible to the requested format, while acknowledging the inherent differences for a non-AI/ML device:

1. Table of Acceptance Criteria and Reported Device Performance

As this is not an AI/ML device, there are no "acceptance criteria" in the traditional sense of performance metrics like sensitivity, specificity, or AUC for an algorithm. Rather, performance is assessed through compliance with standards and demonstrating functionality.

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

• Test Set Sample Size: Not explicitly stated.
  • Biocompatibility: ISO 10993 testing involves specific material samples and biological models, but exact numbers or types of tests are not given.
  • Bench Testing: Would involve multiple units of the device tested against various parameters, but specific sample sizes are not provided.
  • Cadaver Testing: The number of cadavers or spinal levels used is not specified.
• Data Provenance:
  • The testing was conducted by SpineView, Inc., likely at their facilities or through contracted laboratories.
  • The data would originate from laboratory and cadaver studies, not from patient data in the typical sense of AI/ML studies (retrospective or prospective patient cohorts).

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

• Number of Experts & Qualifications: Not specified in the provided text.
  • For biocompatibility, experts would be toxicologists and material scientists.
  • For bench testing, engineers and quality assurance personnel would evaluate performance against specifications.
  • For cadaver testing, it would likely involve surgeons or medical professionals familiar with discectomy procedures, but the number and qualifications are not detailed.

4. Adjudication method for the test set

• Adjudication Method: Not applicable or not specified. Decisions in non-AI/ML device testing are typically based on objective measurements against pre-defined specifications and regulatory standards, rather than expert consensus on subjective interpretations. For cadaveric studies, observations by attending surgeons would guide the assessment.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs without AI assistance

• This question is Not Applicable as the ENSPIRE™ Debrider System is a physical surgical device, not an AI/ML diagnostic or assistive software. There are no "human readers" or "AI assistance" in this context.

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

• This question is Not Applicable as the ENSPIRE™ Debrider System is a physical surgical device and does not involve an algorithm.

7. The type of ground truth used

• Type of Ground Truth:
  • Biocompatibility: Established through standardized tests against biological endpoints as defined by ISO 10993. The "ground truth" is that the material either passes or fails these established biological safety criteria.
  • Bench Testing: Engineering specifications and relevant industry standards serve as the "ground truth" for mechanical and functional performance (e.g., a certain cutting force must be achieved, or aspiration rate met).
  • Cadaver Testing: The ability of the device to effectively cut, grind, and aspirate disc material in an anatomical setting, without causing unforeseen damage or encountering significant operational difficulties. The "ground truth" is whether the device performed its intended function successfully and safely in the simulated surgical environment.
  • Substantial Equivalence: The performance and characteristics of the predicate devices serve as the "ground truth" for comparison.

8. The sample size for the training set

• This question is Not Applicable as the ENSPIRE™ Debrider System is a physical device and does not involve AI/ML requiring a training set.

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

• This question is Not Applicable for the same reason mentioned above.

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