Cleared Traditional

aprevo® Digital Segmentation (K231955) - FDA 510(k) Clearance

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

K231955 · Carlsmed, Inc. · Radiology device
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Nov 2023
Decision
123d
Days
Class 2
Risk

K231955 is an FDA 510(k) clearance for the aprevo® Digital Segmentation. 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 Carlsmed, Inc. (Carlsbad, US). The FDA issued a Cleared decision on November 3, 2023 after a review of 123 days - within the typical 510(k) review window.

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 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 Carlsmed, Inc. devices

Submission Details

510(k) Number K231955 FDA.gov
FDA Decision Cleared Substantially Equivalent - Traditional 510(k) (SESE)
Date Received July 03, 2023
Decision Date November 03, 2023
Days to Decision 123 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
16d slower than avg
Panel avg: 107d · This submission: 123d
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.

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