AI-Rad Companion Brain MR

K232305

Siemens Medical Solutions U.S.A. · cleared 2023-10-23 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
AI-Rad Companion Brain MR is a post-processing image analysis software that assists clinicians in viewing, analyzing, and evaluating MR brain images.
Algorithmautomatic quantification and visual assessment of the volumetric properties of various brain structures based on T1 MPRAGE datasets
source quote (p.7)
Companion Brain MR addresses the automatic quantification and visual assessment of the volumetric properties of various brain structures based on T1 MPRAGE datasets.
Adaptive (vs locked)No
source quote (p.15)
Brain morphometry follow-up consists of atrophy rate calculation Morphometry follow-up does not include any machine learning or deep learning component therefore it is verified by V&V testing, and no additional evaluation is provided in this document.
PCCPFDA source did not state this
Cybersecurity addressedYes
source quote (p.14)
Siemens Healthineers adheres to the cybersecurity requirements as defined the FDA Guidance “Content of Premarket Submissions for Management for Cybersecurity in Medical Devices,” issued October 2, 2014 by implementing a process of preventing unauthorized access, modifications, misuse or denial of use, or the unauthorized use of information that is stored, accessed, or transferred from a medical device to an external recipient.

Validation studies (2)

Bench

sample size not stated

standards: IEC 62366-1 Edition 1.1 2020-06 CONSOLIDATED VERSION, ISO 14971 Third Edition 2019-12, IEC 62304 Edition 1.1 2015-06, PS 3.1-3.20 2021e, 15223-1 Fourth edition 2021-07, 82304-1 Edition 1.0 2016-10

Retrospective clinical

n=75 patients · 4 site(s)

endpoints: Volumetric Segmentation Accuracy; Voxel-wise Segmentation Accuracy; WMH Change Region-wise Segmentation Accuracy

Reported performance (2 observations)

diceas written: “Dice0.5CI [0.42,0.57]
source quote (p.16)
Dice AVG 0.50 95% CI [0.42,0.57]
f1as written: “F1-score0.69CI [0.633,0.733]
source quote (p.16)
F1-score AVG 0.69 95% CI [0.633,0.733]

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
0
drift signals on this device

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/K232305