Cleared Traditional

K223106 - Brainlab Elements Image Fusion, Contouring (4.5) (FDA 510(k) Clearance)

Also includes:
Image Fusion (4.5) Fibertracking (2.0) BOLD MRI Mapping (1.0) Image Fusion Angio (1.0)

Class II Radiology device cleared through predicate-based substantial equivalence - typically does not require clinical trials.

K223106 · Brainlab AG · Radiology device
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Jul 2023
Decision
287d
Days
Class 2
Risk

K223106 is an FDA 510(k) clearance for the Brainlab Elements Image Fusion, Contouring (4.5). Classified as Automated Radiological Image Processing Software within the QIH classification (a category dominated by AI-based automated radiology processing systems), Class II - Special Controls.

Submitted by Brainlab AG (Munich, DE). The FDA issued a Cleared decision on July 14, 2023 after a review of 287 days - an extended review cycle.

This device falls under the Radiology FDA review panel, regulated under 21 CFR 892.2050 - the FDA radiology and imaging software oversight framework. The Traditional 510(k) pathway establishes clearance through substantial equivalence to a legally marketed predicate device, without requiring clinical trial data.

Device pattern: Incremental AI imaging tool. Moderate-to-high equivalence dependency. Overall, this clearance reflects a predicate-aligned approval typical of modern AI radiology extensions - not a novel clinical breakthrough, but a validated iteration within an established regulatory category.

View all Brainlab AG devices

Submission Details

510(k) Number K223106 FDA.gov
FDA Decision Cleared Substantially Equivalent - Traditional 510(k) (SESE)
Date Received September 30, 2022
Decision Date July 14, 2023
Days to Decision 287 days
Submission Type Traditional
Review Panel Radiology (RA)
Summary Summary PDF
Third-party Review No - reviewed directly by FDA
Combination Product No
PCCP Authorized No
Regulatory Context
Review time vs. panel average
180d slower than avg
Panel avg: 107d · This submission: 287d
Pathway characteristics
Predicate-based equivalence. No clinical trials required.

Device Classification

Product Code QIH Automated Radiological Image Processing Software
Device Class Class 2 - Special Controls
CFR Regulation 21 CFR 892.2050
Definition To Provide Automated Radiological Image Processing And Analysis Tools. Software Implementing Artificial Intelligence Including Nonadaptive Machine Learning Algorithms Trained With Clinical And/or Artificial Data. In These Devices, The Algorithm Training Data Typically Impacts Device Performance. Adaptive Ai Algorithms Are Not Within Scope Of This Product Code.
What this classification means

Class II devices require demonstration of substantial equivalence to a legally marketed predicate device. This pathway does not require clinical trials - it relies on engineering equivalence and performance data. Most Radiology devices follow this clearance model.

Regulatory Peers - QIH Automated Radiological Image Processing Software

All 285
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