SpineAR SNAP (SyncAR Spine)

K252054

Surgical Theater, Inc. · cleared 2025-09-29 · product code SBF · Neurology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“The SpineAR SNAP does not require any custom hardware and is a software-based device that runs on a high-performance desktop PC assembled using “commercial off-the-shelf” components that meet minimum performance requirements.SpineAR Software Version SPR.2.0.0 incorporates AI/ML-enabled vertebra segmentation into the clinical workflow to optimize the preparation of a spine surgical plan for screw placement and decompression.”
Algorithm3D U-Net, a type of neural network architecture that excels at medical image segmentation. The algorithm processes the scan iteratively, patch by patch, from the bottom upwards. A key feature is its use of a "memory" channel. As each vertebra is segmented, it is added to this memory channel. This informs the model of what has already been found, preventing it from re-segmenting the same vertebra and guiding it to the next one in the sequence. This iterative approach allows the model to accurately segment every vertebra separately, using a single, robust process.
source quote (p.10)
“The core of the system is a 3D U-Net, a type of neural network architecture that excels at medical image segmentation. The algorithm processes the scan iteratively, patch by patch, from the bottom upwards. A key feature is its use of a "memory" channel. As each vertebra is segmented, it is added to this memory channel. This informs the model of what has already been found, preventing it from re-segmenting the same vertebra and guiding it to the next one in the sequence. This iterative approach allows the model to accurately segment every vertebra separately, using a single, robust process.”
Adaptive (vs locked)No
PCCPNo
Cybersecurity addressedYes
source quote (p.13)
“Cybersecurity testing was conducted and and documentation was provided as recommended in FDA's guidance document “Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions."”

Validation studies (2)

Retrospective clinical

n=95 scans

endpoints: Mean Dice Coefficient (MDC); CT Labeling Accuracy

Retrospective clinical

n=31 scans

endpoints: Mean Dice Coefficient (MDC)

Reported performance (4 observations)

diceas written: “Mean Dice Coefficient (MDC) for Individual vertebrae”0.912CI 0.907
source quote (p.12)
“Individual vertebrae 1193 0.912 0.907”
diceas written: “Mean Dice Coefficient (MDC) for S”0.879CI 0.835
source quote (p.12)
“S 38 0.879 0.835”
diceas written: “Mean Dice Coefficient (MDC) for Sacrum (excl. S1)”0.901CI 0.861
source quote (p.12)
“Sacrum (excl. S1) 38 0.901 0.861”
diceas written: “Mean Dice Coefficient (MDC) for MRI scans”0.903CI 0.891
source quote (p.12)
“208 0.903 0.891”

Each value carries its own analysis unit and task — never compare or pool across devices. Source: 510(k) summary PDF.

Predicate network

Postmarket — what happened after clearance

1
recalls in product code, 24mo
3
MAUDE reports in code, 12mo
—
vs code's own 3-yr baseline
1
drift signals on this device
  • recall_reason_pattern

    Software/algorithm-related recall in product code SBF (Kico Knee Innovation Company, initiated 2025-09-19): "Complaint identified issue with AI surgical planning software that may result in implant malalignment and/or decrease range of motion." Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:97618

Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device); a recall is shown as device-attributed only when the recall record itself lists this clearance number. Signals are descriptive observables with sources — never a judgment that the device is unsafe or drifting. Snapshot 2026-07-08.

Reimbursement — how devices like this got paid

Not yet tracked — no payment pathway indexed for this clearance (the reimbursement corpus is a growing seed set).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Neurology panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K252054