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The ENDOSKELETON® TO Interbody Fusion Device is indicated for use in skeletally mature patients with Degenerative Disc Disease (DDD) at one or two contiguous levels from L2- S1. DDD is defined as discogenic back pain with degeneration of the disc confirmed by patient history and radiographic studies. Patients should have received 6 months of non- operative treatment prior to treatment with the device must be used with supplemental fixation. These DDD patients may also have up to Grade I spondylolisthesis or retrolisthesis at the involved level(s). It is indicated to be used with autograft bone.

This traditional 510(k) is intended to add additional products to the Endoskeleton® TO System that have been additively manufactured from titanium alloy.

The Endoskeleton® TO Interbody Fusion Device implants are available in a variety of sizes for treatment in Posterior Lumbar Interbody Fusion (PLIF) to accommodate patient anatomy and are designed with a large hollow region in the center to house autograft bone material. The Endoskeleton® TO Interbody Fusion Device is offered with or without nanoLOCK® Surface Technology. The nanoLOCK® Surface Technology is identical to the previously cleared product (K141953), which is a microscopic roughened surface with nano-scale features. The version without nanoLOCK® Surface Technology has a macro surface roughness.

The implant system must be used with supplemental fixation for stabilizing the implants when placed in the interbody space.

The implants are composed of medical grade titanium alloy (Ti 6Al-4V ELI) per ASTM F136 and ASTM F3001.

The components included in this submission for additive manufacturing are sterile only.

The provided text describes a 510(k) premarket notification for a medical device, the Endoskeleton® TO Interbody Fusion Device (IBD). This document focuses on demonstrating substantial equivalence to previously cleared devices rather than establishing novel safety and effectiveness through clinical trials with defined acceptance criteria and human performance metrics.

Therefore, many of the requested elements for describing acceptance criteria and a study proving device performance are not applicable to this type of submission. The information provided primarily details mechanical testing to ensure the new manufacturing process (additive manufacturing) does not compromise the device's structural integrity compared to its predicate devices.

However, I can extract information related to the performance testing and its conclusions:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify exact sample sizes for each mechanical test. However, it indicates these were bench tests (mechanical, biocompatibility, cleaning, endotoxin) performed on physical device samples. Therefore, the "data provenance" is derived from these laboratory tests rather than patient data (e.g., country of origin of data, retrospective/prospective).

3. Number of Experts Used to Establish Ground Truth and Qualifications

This is not applicable as the submission relies on objective mechanical and material science testing against established standards, not interpretation by clinical experts to establish a "ground truth."

4. Adjudication Method

This is not applicable for the same reasons as #3.

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

No MRMC study was performed or mentioned. This type of study is typically relevant for diagnostic imaging devices where human interpretation is a key component. This device is an implantable surgical device.

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

This is not applicable. The device is an implantable medical product, not an algorithm, and does not involve human-in-the-loop performance in the context of its function.

7. Type of Ground Truth Used

The "ground truth" used for this submission is based on:

• Established ASTM (American Society for Testing and Materials) standards for mechanical testing.
• ISO (International Organization for Standardization) standards (ISO 10993) for biocompatibility and cleaning validation.
• AAMI (Association for the Advancement of Medical Instrumentation) standard (AAMI ST72) for bacterial endotoxin testing.

The "ground truth" is that the new, additively manufactured device performs mechanically and biologically equivalently to the predicate devices as demonstrated by adherence to these industry and regulatory standards.

8. Sample Size for the Training Set

This is not applicable. There is no "training set" in the context of an implantable medical device submission of this nature. Machine learning or AI models, which would require training sets, are not involved.

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

This is not applicable for the same reasons as #8.

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The Endoskeleton TO® Interbody Fusion Device is indicated for use in skeletally mature patients with Degenerative Disc Disease (DDD) at one or two contiguous levels from L2-S1. DDD is defined as discogenic back pain with degeneration of the disc confirmed by patient history and radiographic studies. Patients should have received 6 months of non-operative treatment prior to treatment with the devices. The device must be used with supplemental fixation. These DDD patients may also have up to Grade I spondylolisthesis at the involved level(s). It is indicated to be used with autograft bone.

The Endoskeleton TO is comprised of a variety of implant sizes to accommodate various patient's anatomy and pathology, and associated instrumentation. All implantable components are manufactured from medical grade titanium alloy (Ti6Al4V-ELI).

Here's a breakdown of the acceptance criteria and the study details for the Endoskeleton TO Interbody Fusion Device, based on the provided 510(k) summary:

This device is not an AI/ML powered device but rather a physical interbody fusion device. Therefore, many of the typical questions for AI/ML devices regarding human-in-the-loop, effect size, training data, and ground truth establishment are not applicable.

Acceptance Criteria and Reported Device Performance

Study Details

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

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

   • Sample Size: Not explicitly stated as a number of devices. The document mentions "variety of implant sizes" being tested. However, the testing was conducted on the "Endoskeleton TO Interbody Fusion Device," implying representative samples of the device were used.
   • Data Provenance: This was pre-clinical bench testing performed in a laboratory setting, not clinical data from patients.

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

   • This is not applicable as the "ground truth" for this type of medical device refers to the physical and mechanical properties of the device as measured against established engineering standards (ASTM standards). There are no human experts "establishing ground truth" in the way it applies to diagnostic or prognostic AI/ML devices. The "experts" would be the engineers and technicians conducting the ASTM standard tests.

4. Adjudication method for the test set:

   • Not applicable in the context of mechanical bench testing. The "adjudication" is the direct measurement and comparison of the device's performance against the established ASTM standards and the performance of predicate devices.

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 an interbody fusion implant, not an AI/ML diagnostic or assistive tool. Therefore, MRMC studies involving human readers and AI assistance are not relevant.

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

   • Not applicable. This is a physical medical device, not an algorithm. Bench testing is analogous to "standalone" performance for a physical device, in that its mechanical properties are evaluated independently of patient interaction at this stage.

7. The type of ground truth used:

   • For this device, the "ground truth" is defined by established engineering standards (ASTM F2077-03, ASTM F2267-04) and the performance characteristics of legally marketed predicate devices. The device's performance is compared against these benchmarks to demonstrate substantial equivalence.

8. The sample size for the training set:

   • Not applicable. This device does not use a "training set" in the machine learning sense. The device is designed and manufactured, and then its physical properties are tested.

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

   • Not applicable, as there is no "training set." The design and manufacturing processes are guided by engineering principles, material science, and regulatory requirements, not by machine learning training data.

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