K Number
K173432
Date Cleared
2018-04-18

(167 days)

Product Code
Regulation Number
888.3080
Panel
OR
Reference & Predicate Devices
AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
Intended Use

The Camber Spine Technologies ENZA™-A Titanium ALIF 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 pairent history and radiographic studies. Patients should have received 6 months of non-operative treatment prior to treatment with the devices. These DDD patients may also have up to Grade I spondylolisthesis or retrolisthesis at the involved level(s). The Camber Spine Technologies ENZA™-A Titanium ALIF is intended to be used with additional FDA-cleared supplementary fixation systems. The Camber Spine Technologies ENZA™-A Titanium ALIF system must be used with autogenous graft material.

Device Description

The Camber Spine Technologies ENZA™-A Titanium ALIF is an Interbody Fusion Device that has a hollow chamber to permit packing with autogenous graft material to facilitate fusion. The superior and inferior surfaces of the device have a rough surface to help prevent movement of the device while fusion takes place. Additionally, the device has integrated fixation through superior and inferior anchoring plates. These implants may be implanted via a laparoscopic or an open anterior approach. Patients with previous non-fusion spinal surgery at the treated level may be treated.

AI/ML Overview

The provided text describes a 510(k) premarket notification for a medical device called the ENZA™-A Titanium ALIF, an intervertebral body fusion device. The focus of this document is to demonstrate "substantial equivalence" to predicate devices, rather than providing a performance study to prove the device meets specific acceptance criteria in the context of an AI/ML algorithm or diagnostic accuracy.

Therefore, the information requested in your prompt regarding acceptance criteria and a study proving a device meets those criteria (especially points 2-9 which are highly relevant to AI/ML device testing) cannot be fully answered as presented in this document. This document details the mechanical testing performed, but not clinical performance or diagnostic accuracy.

However, I can extract information related to the mechanical performance testing that was done to support substantial equivalence.

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

The document states: "Testing performed indicate that the ENZA™-A Titanium ALIF is as mechanically sound as predicate devices. Testing included static compression, static compression-shear, dynamic compression, dynamic compression-shear, expulsion, and subsidence per ASTM F2077-14 and F2267-04. The results demonstrate that the acceptance criteria defined by predicate device performance were met."

While the specific numerical acceptance criteria and reported device performance (e.g., actual force values or displacement) are not provided in this summary, the key statement is that the acceptance criteria defined by predicate device performance were met. This implies that the new device's performance in mechanical testing was comparable to or better than the predicate devices against the standards ASTM F2077-14 and F2267-04.

Acceptance Criterion (Type of Testing)Reported Device Performance
Static Compression (per ASTM F2077-14)Met predicate device performance standards
Static Compression-Shear (per ASTM F2077-14)Met predicate device performance standards
Dynamic Compression (per ASTM F2077-14)Met predicate device performance standards
Dynamic Compression-Shear (per ASTM F2077-14)Met predicate device performance standards
Expulsion (per ASTM F2267-04)Met predicate device performance standards
Subsidence (per ASTM F2267-04)Met predicate device performance standards

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

This document details mechanical testing of a medical implant, not a test set for an AI/ML algorithm. Therefore, information regarding "sample size for the test set" in the context of patients or data provenance is not applicable here. The "sample size" would refer to the number of physical devices tested. This information is not provided in the document.

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 is not applicable as the study involves mechanical testing of a physical device, not an AI/ML algorithm requiring expert ground truth for diagnostic accuracy.

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

This is not applicable as the study involves mechanical testing of a physical device.

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 is not applicable as the study involves mechanical testing of a physical device.

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

This is not applicable as the study involves mechanical testing of a physical device.

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

For the mechanical testing, the "ground truth" would be established by the standardized methods outlined in ASTM F2077-14 and F2267-04. These standards define the test setup, loading conditions, and measurement techniques to objectively assess the mechanical performance characteristics (e.g., compression strength, shear stiffness, resistance to expulsion, and subsidence). The acceptance criteria are derived from the performance of the predicate devices against these objective measurements.

8. The sample size for the training set

This is not applicable as the study involves mechanical testing of a physical device, not an AI/ML algorithm that requires a training set.

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

This is not applicable as the study involves mechanical testing of a physical device.

§ 888.3080 Intervertebral body fusion device.

(a)
Identification. An intervertebral body fusion device is an implanted single or multiple component spinal device made from a variety of materials, including titanium and polymers. The device is inserted into the intervertebral body space of the cervical or lumbosacral spine, and is intended for intervertebral body fusion.(b)
Classification. (1) Class II (special controls) for intervertebral body fusion devices that contain bone grafting material. The special control is the FDA guidance document entitled “Class II Special Controls Guidance Document: Intervertebral Body Fusion Device.” See § 888.1(e) for the availability of this guidance document.(2) Class III (premarket approval) for intervertebral body fusion devices that include any therapeutic biologic (e.g., bone morphogenic protein). Intervertebral body fusion devices that contain any therapeutic biologic require premarket approval.
(c)
Date premarket approval application (PMA) or notice of product development protocol (PDP) is required. Devices described in paragraph (b)(2) of this section shall have an approved PMA or a declared completed PDP in effect before being placed in commercial distribution.