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The Streamline TL Spinal Fixation System components are non-cervical spinal fixation devices intended as an adjunct to fusion for use as a pedicle screw (T1-S2), posterior hook (T1-L5) or sacral/iliac screw fixation is limited to skeletally mature patients. These devices are indicated for all of the following indications: degenerative disc disease (defined as discogenic back pain with degeneration of the disc confirmed by history and radiographic studies), spondylolisthesis, trauma, (i.e., fracture or dislocation), deformities or curvatures (i.e., scoliosis, and/or lordosis, Scheuermann's Disease), tumor, stenosis, pseudarthrosis, and failed previous fusion.

The Streamline TL Spinal System consists of a variety of rods, screws (poly-axial, fixed, and reduction), rod connectors, crosslinks, set screws, hooks and other connecting components used to build a spinal construct. The implant components can be rigidly locked into a variety of configurations, with each construct being tailor-made for the individual case. The Streamline TL Spinal System includes Class I manual instrumentation to facilitate implantation of the device components.

The provided document is a 510(k) premarket notification letter from the FDA regarding a spinal fixation system. It details the device's indications for use, its description, and a summary of performance testing.

However, the document does not contain any information about acceptance criteria or a study proving the device meets acceptance criteria in the context of an Artificial Intelligence (AI) or machine learning (ML) enabled medical device. The device in question is a physical spinal fixation system, not a software or AI/ML product.

Therefore, I cannot provide the requested information for the acceptance criteria and the study that proves the device meets them, as the provided text pertains to a mechanical medical device and not an AI/ML system.

To answer your request, I would need a document describing the validation activities for an AI/ML-enabled medical device.

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The Streamline 71. Spinal System components are non-cervical spinal fixation devices intended as an adjunct to fusion for use as a pedicle screw (TI-S2). sacral/iliac screw fixation or as an anterolateral fixation system (T8 - L5). Pedicle screw fixation is limited to skeletally mature patients. These devices are indicated for all of the following indications: degenerative disc discase (defined as discogenic back pain with degeneration of the disc confirmed by history and radiographic studies), spondylolisthesis, trauma, (i.e., fracture or dislocation), deformities or curvatures (i.e. scoliosis, kyphosis, and/or lordosis, Scheuermann's Disease), turnor, stenosis, pseudoarthrosis, and failed previous fusion.

The Streamline TL Spinal System consists of a variety of rods, screws (poly-axial, fixed, and reduction), transverse connectors, set screws and other connecting components used to build a spinal construct. The implant components can be rigidly locked into a variety of configurations, with each construct being tailor-made for the individual case. Sacral/iliac screws are designed for posterior fixation. The Streamline TL Spinal System includes Class I manual instrumentation to facilitate implantation of the device components. The Streamline TL Spinal System may be used with the Streamline TL Crosslink, SpineWorks FixxSure Crosslink or the Quantum® Spinal System X-Link® and rods. This 510(k) is intended to introduce a line extension to the existing Streamline TL Spinal System. The line extension consists of additional diameters for the poly-axial screws.

Here's an analysis of the provided 510(k) summary regarding acceptance criteria and supporting studies:

Based on the provided text, the Streamline TL Spinal System is a Class III medical device requiring premarket notification (510(k)) to demonstrate substantial equivalence to a predicate device. This type of submission generally relies on demonstrating that the new device is as safe and effective as a legally marketed predicate device, rather than proving performance against specific acceptance criteria for a novel technology.

Crucially, the provided text does not describe any specific acceptance criteria or a study designed to prove the device meets such criteria in the way one might expect for a diagnostic AI/ML device.

Instead, the submission focuses on substantial equivalence to existing predicate devices.

Here's a breakdown of the requested information based on the provided document:

Acceptance Criteria and Device Performance (Not applicable in the AI/ML sense)

Since this document is for a spinal fixation system, there are no "acceptance criteria" for an AI/ML algorithm's performance (e.g., sensitivity, specificity, AUC). The "performance" of this device is assessed through its material properties, design, and intended use being substantially equivalent to a predicate.

Study Information (Focused on Substantial Equivalence, not AI/ML performance)

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

   • Not applicable for a clinical study in the AI/ML context. The submission states: "Engineering analysis was completed for the subject components and demonstrated no pre-clinical performance data was required to demonstrate equivalence of the product." This indicates that physical testing (e.g., mechanical, fatigue) of the new components to demonstrate equivalence was likely performed, rather than a clinical trial with a "test set" of patients or data. No details on the sample size for this engineering analysis are provided, nor is data provenance relevant in this context.

2. 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):

   • Not applicable. There was no clinical "test set" requiring expert-established ground truth for performance evaluation in the context of an AI/ML device.

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

   • Not applicable. There was no clinical "test set" requiring adjudication.

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 pedicle screw system, not an AI-assisted diagnostic tool.

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

   • Not applicable. This is not an algorithm or AI device.

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

   • Not applicable. No ground truth in the clinical sense (for AI/ML performance) was needed. The "ground truth" for this device's safety and effectiveness relies on its physical properties and design conforming to established standards and demonstrating equivalence to predicate devices, which have already been deemed safe and effective.

7. The sample size for the training set:

   • Not applicable. This device does not involve a "training set" in the context of AI/ML.

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

   • Not applicable. This device does not involve a "training set."

Summary of the Product's Regulatory Pathway Based on the Provided Text:

The Streamline TL Spinal System (specifically the line extension with additional poly-axial screw diameters) received 510(k) clearance based on demonstrating substantial equivalence to predicate devices (the original Pioneer Streamline TL Spinal System and Blackstone Medical's Firebird Spinal Fixation System).

The primary method for demonstrating this equivalence was through engineering analysis, which concluded that "no pre-clinical performance data was required to demonstrate equivalence of the product." This means that the FDA was satisfied that the new components did not raise new questions of safety or effectiveness, and their performance could be inferred from the predicate devices through design and material similarities, likely backed by mechanical testing (though not explicitly detailed as "data" in this summary).

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