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LnK Cervical Interbody Fusion Cage System is indicated for use in skeletally mature patients with degenerative disc disease (DDD) of the cervical spine with accompanying radicular symptoms at one disc level. DDD is defined as discogenic pain with degeneration of the disc confirmed by patient history and radiographic studies. LnK Cervical Interbody Fusion Cage System is used to facilitate intervertebral body fusion in the cervical spine at the C3 to C7 disc levels using autograft bone. LnK. Cervical Interbody Fusion Cage System is to be used with supplemental fixation. Patients should have at least six (6) weeks of non-operative treatment with an intervertebral cage.

LnK Cervical Interbody Fusion Cage System intended for use as an interbody fusion cage device and must be used with supplemental fixation. The devices are available in a variety of different sizes and configurations to accommodate anatomical variation in different vertebral levels and/or patient anatomy. The devices are made of PEEK-OPTIMA® LTI with marker pins made of Unalloyed Tantalum.

This document is a 510(k) premarket notification for a medical device, the "LnK Cervical Interbody Fusion Cage System." It is a submission to the FDA seeking clearance to market the device, arguing for substantial equivalence to a previously cleared predicate device. Therefore, the document describes a study that proves the device meets the acceptance criteria, but it does not present a typical "study" in the sense of a clinical trial with human subjects and statistical performance metrics like sensitivity, specificity, or AUC for a diagnostic AI device.

Instead, the "study" referred to here is a set of mechanical performance tests conducted to demonstrate the physical and structural integrity of the interbody fusion cage and its equivalence to a predicate device.

Here's an breakdown based on your request, with the caveat that the "device performance" in this context refers to mechanical properties, not diagnostic accuracy:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size: The document does not specify a numerical "sample size" in terms of individual devices tested for each mechanical test. However, it indicates that the "additional components" (the 7° angled cages) were compared to the already existing "LnK Cervical Interbody Fusion Cage System (K143360)".
• Data Provenance: The mechanical test data (for K143360) would be from laboratory testing. The Finite Element (FE) analysis is a computational method. The country of origin for the data generation is not explicitly stated for the testing, but the manufacturer is L&K BIOMED Co., Ltd. in the Republic of Korea. The data is "retrospective" in the sense that existing test data from K143360 is being leveraged for the new submission.

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

• This question is not applicable in the context of this device and submission. This is a mechanical device, not a diagnostic one requiring expert interpretation of images or patient data to establish ground truth. The "ground truth" here is adherence to mechanical standards specified by ASTM.

4. Adjudication Method for the Test Set

• This question is not applicable. Mechanical tests for medical devices are typically pass/fail based on predetermined thresholds within the ASTM standards, not on human adjudication of ambiguous cases.

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 question is not applicable as this is a mechanical interbody fusion cage, not an AI-powered diagnostic or assistive tool.

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

• This question is not applicable as this is a mechanical interbody fusion cage, not an algorithm.

7. The Type of Ground Truth Used

• The "ground truth" for this submission are the performance requirements and test methods outlined in the ASTM standards (ASTM F 2077 and ASTM F 2267). The device's mechanical performance is compared against these engineering standards. For the new components, their performance against these standards is established by showing they are not a "worse case" than the predicate device, which itself met these standards.

8. The Sample Size for the Training Set

• This question is not applicable as this is a submission for a mechanical device, not a machine learning model that requires a training set. The "analogy" for a training set here would be the design and manufacturing processes that result in the device, and the testing of previous iterations or predicate devices.

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

• This question is not applicable for the reasons stated above.

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LnK Cervical Interbody Fusion Cage System is indicated for use in skeletally mature patients with degenerative disc disease (DDD) of the cervical spine with accompanying radicular symptoms at one disc level. DDD is defined as discogenic pain with degeneration of the disc confirmed by patient history and radiographic studies. LnK Cervical Interbody Fusion Cage System is used to facilitate intervertebral body fusion in the cervical spine at the C3 to C7 disc levels using autograft bone. LnK Cervical Interbody Fusion Cage System is to be used with supplemental fixation. Patients should have at least six (6) weeks of non-operative treatment prior to treatment with an intervertebral cage.

LnK Cervical Interbody Fusion Cage System intended for use as an interbody fusion cage device and must be used with supplemental fixation. The devices are available in a variety of different sizes and configurations to accommodate anatomical variation in different vertebral levels and/or patient anatomy. The devices are made of PEEK-OPTIMA® LTI with marker pins made of Unalloyed Tantalum.

The provided text describes the LnK Cervical Interbody Fusion Cage System and its 510(k) submission (K143360) to the FDA. This document is a premarket notification for a medical device, specifically an intervertebral body fusion device, which falls under Class II.

It's important to understand that a 510(k) submission, especially for a Class II device like this, typically focuses on demonstrating substantial equivalence to a previously legally marketed predicate device rather than conducting extensive clinical trials or complex AI performance studies. Therefore, the information you're requesting regarding AI performance analysis, sample sizes for test/training sets, expert ground truth establishment, MRMC studies, or standalone algorithm performance will not be found in this type of document. These are common components of submissions for devices with novel algorithms, AI/ML components, or higher risk classifications, which this device does not appear to have.

The "study that proves the device meets the acceptance criteria" in this context refers to non-clinical performance testing to demonstrate the device's mechanical integrity and safety, comparing it to an existing predicate device.

Here's the breakdown of the available information based on your request:

Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly defined by the safety and performance standards of the predicate device and the relevant ASTM standards for interbody fusion devices. The reported device performance is a declaration of equivalence and testing according to these standards.

Non-AI / Non-Algorithm-Based Information from the Document:

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

   • This document describes performance based on mechanical testing of the physical device components according to ASTM standards, not clinical patient data or data sets for an algorithm. Therefore, "sample size for the test set" would refer to the number of physical devices or components tested, which is not specified but would be dictated by the ASTM standards.
   • Data provenance: Not applicable in the sense of patient data. The mechanical tests are laboratory-based.
   • Retrospective or prospective: Not applicable.

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

   • Not applicable. Ground truth for an AI/algorithm is not being established here. The "truth" is whether the physical device meets mechanical performance specifications, which is determined by objective physical measurements according to validated test methods (ASTM standards), not expert interpretation of outputs.

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

   • Not applicable. This is relevant for clinical outcome adjudication or image interpretation, not mechanical testing of physical implants.

4. 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 device is a physical implant, not an AI-assisted diagnostic or therapeutic tool for human readers.

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

   • No, a standalone algorithm performance study was not done. This device does not contain an algorithm.

6. The type of ground truth used (expert concensus, pathology, outcomes data, etc):

   • For the mechanical performance, the "ground truth" is defined by the validated and standardized mechanical testing protocols (ASTM F 2077 and ASTM F 2267) which establish the pass/fail criteria for various mechanical stresses (axial compression, shear, torsion, expulsion, subsidence).

7. The sample size for the training set:

   • Not applicable. This device does not involve a training set for an algorithm.

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

   • Not applicable.

In summary: The provided document is for a traditional medical implant, and the approval is based on demonstrating substantial equivalence to a predicate device through non-clinical performance (mechanical testing) and material and design comparisons, not AI/ML performance studies.

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