VEA Align; spineEOS
K240582EOS imaging · cleared 2024-06-25 · product code QIH · Radiology
Premarket evidence — what FDA accepted
source quote (p.6)
“VEA Align is a software indicated for assisting healthcare professionals with global alignment assessment through clinical parameters computation. The product uses biplanar 2D X-ray images... and generates an initial placement of the patient anatomic landmarks on the images using a machine learning-based algorithm. spineEOS is a software indicated for assisting healthcare professionals with preoperative planning of spine surgeries.”
source quote (p.6)
“The product uses biplanar 2D X-ray images... and generates an initial placement of the patient anatomic landmarks on the images using a machine learning-based algorithm. Alignment mode: The 3D model supports the initial placement of the patient anatomic landmarks on the images using a machine learning-based algorithm. 3D mode: The 3D reconstruction model is initialized by an AI algorithm and then deformed manually by the user through control points up to matching”
Validation studies (2)
Retrospective clinical
n=538 patients
endpoints: For spinal landmark accuracy the metric computed was the Euclidean distance and for spinal mesh accuracy the metric computed was point to surface distance. The acceptance criteria for both landmark and mesh accuracy errors was defined as: Median error ≤ 3 mm 3rd Quartile ≤ 5 mm
Bench
n=538 patients
endpoints: Direct comparison between skeletal landmark locations between the subject device and predicate VEA align (K231917) met acceptance criteria for algorithm performance.; Direct comparison between additional spinal landmarks location between the subject device and predicate sterEOS Workstation (K172346) met acceptance criteria for algorithm performance.; Direct comparison between the 3D thoraco-lumbar mesh from subject device and the 3D thoraco-lumbar mesh from the predicate sterEOS Workstation (K172346) met the acceptance criteria demonstrating substantial equivalence of the subject device.
Reported performance (0 observations)
FDA source did not state a quantitative performance metric — non-reporting is itself the signal.
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
- re_clearance
The FDA AI/ML device list shows a newer 510(k) K251747 (decision 2025-08-15) from EOS imaging for a matching device line ("VEA Align; spineEOS") — a new clearance for the same line is a change event.
first seen 2026-07-08 · k_number:K251747
Recall and MAUDE counts are product-code-level (reports aren't reliably attributable to one device). 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).