OptimMRI

K230150

RebrAIn, SAS · cleared 2023-07-21 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.3)
OptimMRI is a software application intended to aid qualified medical professionals in processing, visualizing, and interpreting anatomical structures from medical images.
Algorithmmachine learning models
source quote (p.6)
Permit specialized annotation of anatomic structures using machine learning models
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedYes
source quote (p.5)
ANSI UL 2900-1 Ed.1 2017 Standard for Software Cybersecurity Network-Connectable Products, Part I: General Requirements. AAMI TIR57:2016 Principles for medical device security Risk management.

Validation studies (1)

Retrospective clinical

n=44 images

endpoints: at least 90% of surface distances of STN or VIM were not greater than 2.0mm

standards: ISO, 14971 Third Edition 2019-12, Medical devices Application of Risk Management to medical devices, IEC, 62304 Edition 1.1 2015-06 CONSOLIDATED VERSION, Medical device software – Software life cycle processes, IEC, 82304-1 Edition 1.0 2016-10, Health software – Part 1 : General requirements for product safety, ISO 15223-1:2021, Medical devices Symbols to be used with information to be supplied by the manufacturer Part 1, IEC, /TR 80002-1 Edition 1.0 2009-09, Medical device software – Part 1 : Guidance of the application of ISO 14971 to medical device, ISO 20417 First edition 2021-04 Corrected version 2021-12 Medical devices Information to be supplied by the manufacturer, IEC 62366-1:2015+AMD1:2020 Medical devices Part 1: Application of usability engineering to medical devices + Amend. 1, ANSI UL 2900-1 Ed.1 2017 Standard for Software Cybersecurity Network-Connectable Products, Part I: General Requirements., IEC 80001-1 Edition 1.0 2010-10 Application of risk management for IT-networks incorporating medical devices Part 1: Roles, responsibilities and activities., AAMI TIR57:2016 Principles for medical device security Risk management.

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

0
recalls in product code, 24mo
3
MAUDE reports in code, 12mo
vs code's own 3-yr baseline
1
drift signals on this device
  • re_clearance

    The FDA AI/ML device list shows a newer 510(k) K242054 (decision 2024-08-12) from Rebrain, SAS for a matching device line ("OptimMRI (v2)") — a new clearance for the same line is a change event.

    first seen 2026-07-08 · k_number:K242054

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).

RIGOR™ Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: radar.healthai.com/precedent/device/K230150