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The SpineView X-Pac Expandable Lumbar Cage System is indicated for use as an intervertebral body fusion device in skeletally mature patients. The system is designed for use with autogenous bone graft material to facilitate spinal fusion. The system is intended for use in patients with degenerative disc disease (defined as discogenic back pain with degeneration of the disc confirmed by patient history and radiographic studies) at one or two contiguous levels of the lumbar spine (L2-S1). Patients should have at least 6 months of non-operative treatment prior to surgery. In addition, these patients may have up to Grade 1 spondylolisthesis or retrolisthesis at the involved level(s). These implants are used to facilitate fusion in the lumbar spine and are placed via transforaminal approach using autogenous bone graft material. The system is intended for use with supplemental fixation systems cleared for use by the FDA for use in the thoracolumbar spine.

The Spine View X-Pac Expandable Lumbar Cage System is a lumbar interbody fusion system comprised of a cage implant and instruments. The implants are used to provide structural stability in skeletally mature individuals following discectomy and are placed via the transforaminal approach. The device is available in various sizes to accommodate varying anatomy. The primary difference between the previously cleared and the modified cage models is that the expansion of the upper plate is parallel to the bottom housing, whereas the previously cleared device expands at an angle. The implants are designed for use with autogenous bone graft material. Protrusions on the superior and inferior surfaces of each implant grip the endplates of the adjacent vertebrae to resist expulsion. The implants are manufactured from medical grade titanium alloy per ASTM F136 and ASTM F1295. The Spine View X-Pac Expandable Lumbar Cage System implants are single-use, provided non-sterile, and are intended to be cleaned and steam sterilized before use. The instruments are re-usable, provided nonsterile, and are intended to be cleaned and steam sterilized before use.

The provided text is a 510(k) premarket notification for the SpineView X-Pac Expandable Lumbar Cage System. It details the device's description, indications for use, and a comparison to a predicate device, focusing on mechanical testing performance data to demonstrate substantial equivalence.

However, the document does not contain any information about a study proving the device meets acceptance criteria related to an AI/machine learning model's performance, human reader studies (MRMC), or a standalone algorithm performance. The acceptance criteria discussed in the document are limited to the mechanical performance of the physical device (e.g., static and dynamic compression, subsidence, expulsion) in accordance with FDA guidance and ASTM standards for intervertebral fusion devices.

Therefore, I cannot provide the requested information regarding AI model performance, expert ground truth, adjudication methods, or MRMC studies because this document pertains to a physical medical device and not a software as a medical device (SaMD) or an AI-enabled diagnostic tool.

The information I can extract, pertaining to the physical device's acceptance criteria and performance, is as follows:

1. Table of Acceptance Criteria (Mechanical Performance) and Reported Device Performance:

Note: The document states that these tests were conducted "to demonstrate substantial equivalence to the predicate," implying that the performance met the thresholds necessary for this claim. Specific numerical performance values are not provided in this summary.

Regarding the other requested information (2-9), it is not applicable to this document as it does not describe an AI/ML-based device or a clinical study for software performance:

• 2. Sample size used for the test set and the data provenance: Not applicable to this type of device (physical implant). Mechanical testing utilizes test samples of the device itself, not patient data.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for mechanical testing is based on engineered specifications and standardized test methods.
• 4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
• 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 for a physical implant, not an AI diagnostic tool.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
• 7. The type of ground truth used (expert concensus, pathology, outcomes data, etc): For mechanical testing, the "ground truth" is defined by the performance requirements of the ASTM standards and FDA guidance for intervertebral fusion devices (e.g., specific load capacities, displacement limits).
• 8. The sample size for the training set: Not applicable. There is no AI model or training set described.
• 9. How the ground truth for the training set was established: Not applicable.

In summary, this 510(k) submission focuses on demonstrating the substantial equivalence of a physical medical device (SpineView X-Pac Expandable Lumbar Cage System) through mechanical performance testing, rather than the performance of an AI/machine learning algorithm.

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The SpineView X-Pac Expandable Lumbar Cage System is indicated for use as an intervertebral body fusion device in skeletally mature patients. The system is designed for use with autogenous bone graft material to facilitate spinal fusion.

The system is intended for use in patients with degenerative disc disease (defined as discogenic back pain with degeneration of the disc confirmed by patient history and radiographic studies) at one or two contiguous levels of the lumbar spine (L2-S1). Patients should have at least 6 months of non-operative treatment prior to surgery. In addition, these patients may have up to Grade 1 spondylolisthesis or retrolisthesis at the involved level(s). These implants are used to facilitate fusion in the lumbar spine and are placed via transforaminal approach using autogenous bone graft material. The system is intended for use with supplemental fixation systems cleared for use by the FDA for use in the thoracolumbar spine.

The SpineView X-Pac Expandable Lumbar Cage System is a lumbar interbody fusion system comprised of a caqe implant and instruments. The implants are used to provide structural stability in skeletally mature individuals following discectomy and are placed via the transforaminal approach. The device is available in various sizes to accommodate varying anatomy and can expand to the desired lordosis. The implants are designed for use with autogenous bone graft material. Protrusions on the superior and inferior surfaces of each implant grip the endplates of the adjacent vertebrae to resist expulsion. The implants are manufactured from medical grade titanium alloy per ASTM F136 and ASTM F1295.

The SpineView X-Pac Expandable Lumbar Cage System implants are singleuse, provided non-sterile, and are intended to be cleaned and steam sterilized before use. The instruments are re-usable, provided non-sterile, and are intended to be cleaned and steam sterilized before use.

This document is a 510(k) premarket notification decision letter from the FDA regarding the SpineView X-Pac Expandable Lumbar Cage System. It does not describe an AI medical device or a study involving acceptance criteria for such a device.

The document discusses:

• The FDA's decision that the SpineView X-Pac Expandable Lumbar Cage System is substantially equivalent to a legally marketed predicate device.
• The regulatory classification and product code for the device.
• Indications for Use of the SpineView X-Pac Expandable Lumbar Cage System.
• A brief device description: an intervertebral body fusion device made of medical-grade titanium alloy, single-use, provided non-sterile, and intended to be cleaned and steam sterilized before use, with reusable instruments.
• A mention of mechanical testing (static and dynamic compression, static and dynamic compression-shear, and subsidence) conducted in accordance with specific guidance documents and ASTM standards to demonstrate substantial equivalence to the predicate.

There is no mention of:

• Acceptance criteria in terms of AI/algorithm performance (e.g., sensitivity, specificity, AUC).
• A study proving a device meets such acceptance criteria.
• Sample sizes for test or training sets for an AI algorithm.
• Data provenance for AI models.
• Experts used to establish ground truth.
• Adjudication methods.
• Multi-reader multi-case (MRMC) studies or human reader improvement with AI.
• Standalone algorithm performance.
• How ground truth was established for training data.

Therefore, I cannot provide the requested information based on the provided text, as it pertains to a traditional medical device (an implantable cage system) and not an AI/software as a medical device (SaMD).

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The FlexLite™ Camera is indicated for use for endoscopic visualization in the surgical area of the cervical, thoracic, or lumbar spine during diagnostic or interventional spinal procedures such as discectomy, nucleotomy and foraminotomy.

The Spine View FlexLite™ Camera is a flexible, reusable arthroscope designed for endoscopic visualization during diagnostic or interventional spinal procedures with access to the target area established through a surgical opening. The device includes fiber-optic illumination bundles with an integrated LED light source in the handle and a distal tip CCD image sensor with associated electronics. The camera is offered to support NTSC and PAL video formats. The FlexLite™ Camera is designed for use with the commercially available Vision-Sciences DPU-5050 Video Processor Unit (K102733, K072073) for image display and transfer. The FlexLite™ Camera contains neither software nor firmware. The FlexLite™ Camera is provided non-sterile to the customer and must be cleaned and sterilized by the user prior to each use.

This document describes the 510(k) submission for the Spine View FlexLite™ Camera, an arthroscope for endoscopic visualization during spinal procedures. The submission focuses on demonstrating substantial equivalence to predicate devices through non-clinical performance testing.

Here's an analysis of the acceptance criteria and study information provided:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria in a dedicated table with corresponding performance metrics. Instead, it lists various non-clinical tests conducted and makes a general statement about their outcome.

2. Sample Size for Test Set and Data Provenance

• Sample Size: The document does not specify the sample size for individual tests. It only states that "non-clinical testing was conducted."
• Data Provenance: The data is generated from non-clinical testing, meaning it's likely laboratory-based and simulated, rather than human subject data. The country of origin for the data is not explicitly stated but is implied to be within the US, given the submission to the FDA. The data is prospective in the sense that it was specifically generated for this submission to validate the device.

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

• This information is not applicable to this submission. The tests described are primarily engineering and performance-based (e.g., dimensional, electrical safety, sterilization validation). These tests do not typically involve human experts establishing a "ground truth" in the way a diagnostic AI would require for image interpretation. The "ground truth" for these tests would be the established engineering specifications, standards, and validated protocols.

4. Adjudication Method for the Test Set

• This information is not applicable to this submission. Since no human expert interpretation or diagnostic classification is involved in the described non-clinical testing, there is no need for an adjudication method.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No, an MRMC comparative effectiveness study was not done. This type of study (comparing human readers with and without AI assistance) is relevant for diagnostic AI devices, not for a medical device like an arthroscope where the primary function is visualization. The FlexLite™ Camera itself does not contain AI or provide diagnostic interpretations.

6. Standalone Performance Study (Algorithm Only)

• No, a standalone (algorithm only) performance study was not done. This device is a physical camera for endoscopy and does not have an AI algorithm or software that operates independently to perform a diagnostic or therapeutic function. The document explicitly states, "The FlexLite™ Camera contains neither software nor firmware."

7. Type of Ground Truth Used

• The "ground truth" for the non-clinical tests conducted would be the established engineering specifications, recognized industry standards, and validated test protocols. For example, for biocompatibility, the ground truth would be the pass/fail criteria defined by ISO 10993 series standards. For electrical safety, it would be the requirements of relevant IEC standards (e.g., IEC 60601).

8. Sample Size for the Training Set

• This information is not applicable as this device does not involve machine learning or AI algorithms that require a "training set."

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

• This information is not applicable as there is no training set for this device.

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The Spine View Minimally Invasive Surgical (MIS) Decompression System is indicated for use to facilitate access and visualization in the surgical area of the cervical, thoracic, or lumbar spine and is accessorized with surgical tools for interventional spinal procedures such as discectomy, nucleotomy and foraminotomy.

The Minimally Invasive Surgical (MIS) Decompression System is a collection of arthroscopic surgical accessories provided sterile (irradiated) and intended for single-use only. As a group, the accessories are provided to facilitate delivery of an endoscope and other instruments to the targeted treatment site. The addition of a new accessory, the enCise Bone Cutter, as an additional surgical tool to facilitate removal of soft and hard (bone) tissue during interventional spinal procedures. The new component will be offered in two configurations: one compatible with flexible endoscopes, and the second compatible with rigid endoscopes. Two additional enVue Cannula models are also being introduced for compatibility with rigid endoscopes: Long and Standard Jaw. Introduction of the new enCise Bone Cutter and additional configurations of the already cleared enVue Cannula do not affect the intended use or alter the fundamental scientific technology of the system.

The additional accessories being proposed in the modified MIS Decompression System are listed below:

• . enCise Bone Cutter: a tubular sheath with a mechanical "chisel" tip feature designed to cut soft and hard (cartilaginous, bone) tissue during spinal procedures. The enCise Bone Cutter is offered in two configurations (one compatible with flexible endoscopes, and the second compatible with rigid endoscopes).
• enVue Cannula, Standard and Long Jaw: configurations for use with rigid . endoscopes. The working end of the accessories is identical to the previously cleared enVue Cannulas. The only difference is in the handle, which is modified to accommodate rigid endoscopes (up to 5.9 mm OD; 205 mm working length).

Here's an analysis of the provided text regarding the acceptance criteria and study for the Spine View, Inc. Minimally Invasive Surgical (MIS) Decompression System:

Based on the provided 510(k) Summary (K121548), the device in question is a minimally invasive surgical system, and the filing primarily focuses on demonstrating substantial equivalence to predicate devices for specific new accessories (enCise Bone Cutter, and new enVue Cannula configurations). This type of submission generally relies on non-clinical performance data to show that the new components perform as intended and do not raise new questions of safety or effectiveness compared to legally marketed devices. It is not a study about the performance of an AI/ML algorithm. Therefore, many of the requested categories regarding AI-specific studies, ground truth establishment, expert consensus, and reader studies are not applicable.

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not explicitly state quantitative acceptance criteria in terms of specific thresholds for performance metrics. Instead, it refers to validation against "product specifications and external standard requirements" and aims to demonstrate "substantial equivalence" to predicate devices. The "reported device performance" is summarized as the successful completion of various non-clinical tests.

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

This information is not applicable as the submission describes non-clinical performance testing of mechanical components, not an AI/ML algorithm or a study with a "test set" of patient data. The tests would likely involve prototypes or production units of the device components. There is no mention of country of origin of data or retrospective/prospective in this context.

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

This information is not applicable. The ground truth for this type of medical device submission is typically established through engineering specifications, material science standards, and established biocompatibility principles, performed by qualified engineers and scientists. There are no "patient cases" or an "AI test set" requiring clinical expert consensus for ground truth.

4. Adjudication Method for the Test Set

This information is not applicable. There is no "test set" in the context of clinical data requiring adjudication.

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

This information is not applicable. No AI/ML algorithm is involved in this device submission. This is a special 510(k) for mechanical surgical instruments.

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

This information is not applicable. No AI/ML algorithm is involved in this device submission.

7. The type of ground truth used

For the non-clinical performance data, the "ground truth" is based on:

• Engineering specifications and design requirements: Each test would have a pre-defined performance envelope or target.
• External standards: Relevant ISO standards, ASTM standards, or other industry benchmarks for material properties, sterility, biocompatibility, and mechanical performance.
• Predicate device characteristics: To demonstrate substantial equivalence, the performance of the new device is compared against the known performance and characteristics of the predicate devices.

8. The sample size for the training set

This information is not applicable. There is no AI/ML algorithm and therefore no "training set" of data in this submission.

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

This information is not applicable. There is no AI/ML algorithm and therefore no "training set." The ground truth for the design and testing of the mechanical device is established through engineering principles, material science, and regulatory standards as described in point 7.

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

The modified 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 modified enSpire™ Discectorny System is supplied as a sterile, single patient use, disposable device.

The provided text describes a 510(k) submission for the enSpire™ Discectomy System, a medical device for discectomy procedures. It focuses on demonstrating substantial equivalence to a predicate device and outlines non-clinical testing performed.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based only on the provided text:

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

The document does not explicitly present a table of acceptance criteria with corresponding performance metrics. Instead, it lists the types of non-clinical (bench) tests performed and makes a general statement about their success.

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

The document does not specify the sample size for any of the non-clinical tests conducted. It also does not mention the country of origin of the data or whether the tests were retrospective or prospective, as these are in-vitro bench 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)

This information is not applicable and not provided. The testing described is non-clinical (bench testing) and does not involve human subjects or expert assessment for ground truth determination in the typical sense of a clinical study.

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

This information is not applicable and not provided, as the studies are non-clinical bench tests, not clinical studies requiring adjudication of outcomes or diagnoses.

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 such study was performed or mentioned. The device is a surgical discectomy system, not an AI-assisted diagnostic tool requiring MRMC studies.

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

This information is not applicable. The device is a mechanical surgical tool, not an algorithm.

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

For the non-clinical bench studies, the "ground truth" would be established by the design specifications and engineering requirements of the device. For example, for "Tensile Strength," the ground truth would be a defined tensile strength threshold. For "No Breach of Annulus or Endplates," the ground truth is the absence of such breaches, directly observed during the in-vitro tissue volume removal testing.

8. The sample size for the training set

This information is not applicable and not provided. The device described is a mechanical surgical tool, not an AI/ML algorithm that requires a training set.

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

This information is not applicable and not provided, as there is no training set for this device.

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Surgical accessories are indicated for facilitating endoscopic access and visualization in the surgical area of the cervical, thoracic, or lumbar spine for interventional spinal procedures such as discectomy, nucleotomy and foraminotomy.

The SpineVu Endoscopic Spine System (SESS) is a collection of arthroscopic surgical accessories provided sterile (irradiated) and intended for single-use only. As a group, the accessories are provided to facilitate delivery of an endoscope and other instruments to the targeted treatment site. The SpineVu Endoscopic Spine System (SESS) consists of the following devices: enVue Cannula, enVue Sheath, 16G Introducer Cannula with Stylet, Guidewire, Dilator, Beveled Cannula, Ball-Tipped Probe, Infusion Cannula, Suction Cannula.

The provided document is a 510(k) premarket notification for a medical device called the "SpineVu Endoscopic Spine System (SESS)". It outlines the device's description, intended use, technological comparison to predicate devices, and non-clinical performance data.

However, the document does not contain the specific information requested regarding acceptance criteria and the study that proves the device meets those criteria, such as a table of accuracy metrics, sample sizes for test/training sets, expert qualifications, or details on ground truth establishment.

Instead, the document focuses on demonstrating substantial equivalence to predicate devices through a comparison of technological characteristics and non-clinical performance testing.

Here's what can be extracted from the provided text, and what is missing:

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

• Acceptance Criteria (Implicit): The implicit acceptance criteria are that the modified SpineVu Endoscopic Spine System (SESS) performs according to its stated intended use and functions as intended, meeting design specifications and external standard requirements. This is a general statement rather than specific quantitative metrics.

• Reported Device Performance: The document states: "All data fell well within product specifications and external standard requirements. Results of non-clinical testing demonstrated that the SpineVu Endoscopic Spine System (SESS) is substantially equivalent to the predicate devices for its intended use."

  There is no table explicitly detailing acceptance criteria alongside reported performance for each criterion with quantitative results. The non-clinical tests conducted are listed as:

  • Visual and Dimensional Verification
  • Device to Device Compatibility Testing
  • Tensile Testing
  • Flow Rate Testing
  • Luer Attachment Testing
  • Leakage Testing
  • Jaw & Trigger Force Testing
  • Jaw Cycle Integrity Testing
  • Jaw Activation Testing
  • Biocompatibility Testing
  • Design Validation Testing
  • Packaging Testing
  • Sterility Testing

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

• Not specified. The document only mentions "non-clinical testing" without detailing the methodologies or sample sizes for each test. Data provenance (e.g., country of origin, retrospective/prospective) is also not mentioned.

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

• Not applicable. This is a 510(k) for a surgical accessory based on substantial equivalence and non-clinical (engineering/lab) testing, not a clinical study involving diagnosis or interpretation by experts to establish ground truth for a test set.

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

• Not applicable, for the same reasons as point 3.

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 device is a manual surgical accessory, not an AI-powered diagnostic tool. Therefore, no MRMC comparative effectiveness study was conducted.

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

• Not applicable. This is a physical surgical accessory, not an algorithm.

7. The type of ground truth used:

• For the non-clinical tests listed, the "ground truth" would be established by engineering specifications, validated test methods, and industry standards for mechanical performance, material properties, sterility, and biocompatibility. It is not based on expert consensus, pathology, or outcomes data in the context of diagnostic accuracy.

8. The sample size for the training set:

• Not applicable. This device is a manual surgical accessory. There is no concept of a "training set" in this context.

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

• Not applicable, as there is no training set.

Summary of Missing Information:

The provided 510(k) summary focuses on demonstrating substantial equivalence through comparison to predicate devices and non-clinical (benchtop) testing results. It does not contain the detailed clinical study information (like test/training set sample sizes, expert qualifications, ground truth establishment for diagnostic accuracy, or AI performance metrics) that would typically be found for a device requiring performance evaluation in a clinical or diagnostic context. The acceptance criteria are implicitly defined by compliance with product specifications and external standards, rather than specific quantitative performance metrics from a user study.

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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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The SpineVu Endoscopic Spine System (SESS™) and SpineVu MiniScope are indicated for use for endoscopic access and visualization in the surgical area of the cervical, thoracic, or lumbar spine and are accessorized with surgical and coagulation tools for interventional spinal procedures such as discectomy, nucleotomy and foraminotomy.

The SESS kit is a collection of arthroscopic surgical accessories, including a bipolar RF electrosurgical accessory. The Spine Vu MiniScope is an arthroscope.

The provided text is related to a 510(k) Premarket Notification for the "SpineVu Endoscopic Spine System (SESS)" and "SpineVu MiniScope." This document focuses on demonstrating substantial equivalence to predicate devices rather than proving a device meets specific performance acceptance criteria through a comparative study with a ground truth, as would typically be described for AI/ML device evaluations.

Therefore, many of the requested elements (acceptance criteria table, sample sizes for test sets, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, ground truth types) are not applicable or cannot be extracted from this type of regulatory submission. This document describes a medical device, not a software or AI device that would have performance metrics like sensitivity, specificity, or AUC against a ground truth.

However, I can extract information about the types of testing performed to support the substantial equivalence claim.

Acceptance Criteria and Study to Prove Device Meets Acceptance Criteria

Note: This 510(k) submission focuses on demonstrating substantial equivalence of a physical medical device (endoscopic spine system) to previously cleared predicate devices, rather than establishing performance against specific acceptance criteria for an AI/ML algorithm or software as commonly described in device performance studies for AI. Therefore, the response will focus on the types of evidence provided to support the substantial equivalence claim.

1. Table of Acceptance Criteria and Reported Device Performance

The concept of "acceptance criteria" for performance metrics like sensitivity, specificity, or accuracy, as typically found in AI/ML device studies, is not present in this document. Instead, the submission relies on demonstrating substantial equivalence based on intended use, design, and certain testing types.

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

• Sample Size for Test Set: Not applicable in the context of this 510(k) as it's not an AI/ML performance study with a 'test set' of data.
• Data Provenance:
  • Biocompatibility data and bench testing are laboratory-based.
  • Cadaver testing involves human cadavers. Specific country of origin is not mentioned.
  • The studies described are for regulatory submission to the FDA, implying they were conducted to support this submission. They are not framed as "retrospective" or "prospective" clinical studies.

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

• Not applicable. This submission focuses on the safety and effectiveness of a physical medical device through substantial equivalence, not on the performance of a software or AI algorithm requiring expert-established ground truth. Expert involvement would be in the design, testing, and regulatory review process, but not for "ground truth" calibration for a test set.

4. Adjudication Method

• Not applicable. No adjudication method is described as this is not an AI/ML performance study requiring expert consensus on data labels.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No. An MRMC comparative effectiveness study is not mentioned or implied because this is a physical medical device, not an AI/ML interpretive or diagnostic aid. The "effectiveness" is primarily demonstrated through the intended use and lack of new safety/efficacy concerns compared to predicates.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• Not applicable. The device is a physical endoscopic spine system, not an algorithm.

7. Type of Ground Truth Used

• Not applicable in the AI/ML sense of labeled data. The "truth" for this submission revolves around:
  • Compliance with established standards (ISO 10993 for biocompatibility)
  • Functional performance against engineering specifications and clinical expectations (bench testing)
  • Feasibility of intended use (cadaver testing)
  • Equivalence to predicate devices (demonstrated through comparative analysis of intended use, technology, materials, and safety/performance data).

8. Sample Size for the Training Set

• Not applicable. The device is not an AI/ML algorithm that requires a "training set."

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

• Not applicable. As there is no AI/ML training set, there is no ground truth establishment process for it.

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