iQ-solutions

K231929

Sydney Neuroimaging Analysis Centre Pty Ltd · cleared 2023-12-18 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
“iQ-solutions™ is a software medical device intended for automatic annotation, visualization, and quantification of segmentable brain structures from a set of brain MRI scans.”
Algorithmpre-trained convolutional neural networks (CNN); Segmentation by machine learning and deep learning algorithms (supervised segmentation with Convolutional Neural Networks)
source quote (p.6)
“iQ-solutions™ analysis module consists of pre-trained convolutional neural networks (CNN) that have been verified and validated to segment the specific brain structures and create binary masks accordingly using the incoming head MRI scans. Each convolutional neural network is coupled with a pre-processing component that transforms the MRI scans to the standard position and contrast; and a post-processing component that prepares for the output annotations, statistical calculation, and the input of the next analysis component in either analysis pipeline.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (1)

Bench

n=81 cases

endpoints: Accuracy; DICE score; R^2; STD; PSNR

standards: ISO 13485:2016, ISO 14971:2019, IEC 62304:2006 + A1:2015, IEC 62366-1:2015, ISO 12052:2006, CFR 21 Part 820 Quality System Regulation for Medical Devices

Reported performance (5 observations)

accuracyas written: “Accuracy”1
source quote (p.15)
“Accuracy = 100%”
diceas written: “DICE”0.982
source quote (p.15)
“DICE = 0.982”
diceas written: “DICE”0.789
source quote (p.15)
“DICE = 0.789”
diceas written: “DICE”0.79
source quote (p.15)
“DICE = 0.790”
diceas written: “DICE”0.972
source quote (p.15)
“DICE = 0.972”

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); a recall is shown as device-attributed only when the recall record itself lists this clearance number. 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).

Applicable FDA guidance — what the submission is measured against

FDA guidance documents and guiding principles applicable to 510(k) AI/ML devices in the Radiology panel. A curated reference index, not legal or regulatory advice — each item states its own status, and a draft is never binding.

Applicability is derived from the device's FDA advisory panel and pathway — cross-cutting guidances apply to every AI/ML device; panel-specific ones are flagged. Titles, dates, and links verified against fda.gov as of July 2026.

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K231929