Constellation (CON-001)

K241280

Q Bio, Inc. · cleared 2024-09-12 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd

source quote (p.6)

“Constellation is an automated image post-processing software application used in a clinical MRI setting.”

AlgorithmNon-AI based Algorithms (brain, lungs, femur, lower limb muscles, SAT) and Convolutional neural networks (kidneys, spleen, liver, VAT)

source quote (p.9)

“Non-Al based Algorithms (brain, lungs, femur, lower limb muscles, SAT) Convolutional neural networks (kidneys, spleen, liver, VAT)”

Adaptive (vs locked)No

PCCPNo

Cybersecurity addressedNo

Validation studies (7)

Retrospective clinical

sample size not stated

endpoints: Dice Similarity Coefficient (DSC); mean percent absolute difference

Retrospective clinical

sample size not stated

endpoints: mean percent absolute difference; Pearson's correlation coefficient

Reader study (MRMC)

sample size not stated

endpoints: Liver Volume of Interest (VOI) placement

Bench

sample size not stated

endpoints: Dice Similarity Coefficient (DSC); mean percent absolute difference

Bench

sample size not stated

endpoints: mean percent absolute difference; Pearson's correlation coefficient

Bench

sample size not stated

endpoints: passing results on all applicable unit, integration, and requirements testing

standards: General Principles of Software Validation, Guidance for Industry and FDA Staff

Bench

sample size not stated

endpoints: passing results in the applied usability testing

standards: Applying Human Factors and Usability Engineering to Medical Devices

Reported performance (1 observation)

diceas written: “Dice Similarity Coefficient (DSC)”stated without value

source quote (p.12)

“Segmentation accuracy of the lungs, liver, spleen, kidneys, muscle, and fat (visceral and subcutaneous) is evaluated using the Dice Similarity Coefficient (DSC) and mean percent absolute difference as primary and secondary figures of merit (FOM).”

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

recalls in product code, 24mo

MAUDE reports in code, 12mo

—

vs code's own 3-yr baseline

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).