Search Results
Found 1 results
510(k) Data Aggregation
(28 days)
LDR SPINE CERVICAL INTERBODY FUSION SYSTME-ROI-C LORDOTIC IMPLANTS
The LDR Spine Cervical Interbody Fusion 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 from C2-T1. DDD is defined as discogenic pain with degeneration of the disc confirmed by history and radiographic studies. These patients should have had six weeks of non-operative treatment. The LDR Spine ROI-C Cervical Interbody Fusion System is to be used with autogenous bone graft and implanted via an open, anterior approach. Supplemental internal fixation is required to properly utilize this system.
The ROI-C Lordotic implant is an extension of the currently cleared ROI-C cervical interbody fusion system and is intended for use as an interbody fusion device in the cervical spine. The device is manufactured from medical grade PEEK OPTIMA® LT1 in accordance with ASTM F2026 and has tantalum markers conforming to ASTM F136 embedded in the implant extremities to facilitate visibility in x-ray imaging. The subject device is designed for placement using an open anterior approach.
The provided 510(k) summary describes a spinal interbody fusion device, not an AI/ML medical device. Therefore, many of the requested categories for AI/ML device studies (such as sample sizes for test/training sets, expert ground truth, MRMC studies, standalone performance, etc.) are not applicable and cannot be extracted from this document.
However, I can extract the acceptance criteria and the study that proves the device meets those criteria, based on the non-clinical testing performed for this type of medical device.
Acceptance Criteria and Device Performance for Non-AI/ML Medical Devices (Spinal Interbody Fusion System)
Acceptance Criteria Category | Specific Acceptance Criteria | Reported Device Performance |
---|---|---|
Mechanical Performance | Static Axial Compression (per ASTM F2077) | Performance shown to be substantially equivalent to legally marketed predicate devices. |
Mechanical Performance | Static Axial Torsion (per ASTM F2077) | Performance shown to be substantially equivalent to legally marketed predicate devices. |
Study Description (for a Non-AI/ML device):
- Study Type: Non-clinical bench testing, specifically Finite Element Analysis (FEA) and physical testing simulating relevant loads.
- Proof of Meeting Criteria: The results of the non-clinical testing (Finite Element Analysis) demonstrated that the mechanical performance of the ROI-C Lordotic implant, under static axial compression and static axial torsion, was "substantially equivalent" to its legally marketed predicate devices. "Substantial equivalence" is the regulatory standard for 510(k) clearances, meaning the new device is as safe and effective as a legally marketed device.
Information Not Applicable or Not Available from the Provided Text (as this is not an AI/ML device):
- Sample size used for the test set and the data provenance: Not applicable for non-clinical bench testing of a spinal implant in the context of an AI/ML study. Data provenance (country, retrospective/prospective) also not applicable.
- 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 engineering standards and measurements, not expert human assessment.
- Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.
- 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.
- If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable.
- The type of ground truth used: For this device, the "ground truth" for proving substantial equivalence relates to the mechanical properties and biocompatibility of the materials and design, compared against established standards (e.g., ASTM F2077) and the performance of predicate devices. This is not "expert consensus, pathology, or outcomes data" in the AI/ML context.
- The sample size for the training set: Not applicable.
- How the ground truth for the training set was established: Not applicable.
Ask a specific question about this device
Page 1 of 1