PRAEVAorta®2
K243859Nurea · cleared 2025-08-29 · product code QIH · Radiology
Premarket evidence — what FDA accepted
source quote (p.4)
“PRAEVAorta®2 is a software intended to be run on its own or as part of another medical device to automatically calculate maximum diameters of anatomical zones from a DICOM CT image containing blood vessels.”
source quote (p.4)
“PRAEVAorta®2 is designed to measure the maximal transverse diameter of vessels and determine the maximal general diameter using a non-adaptative machine learning algorithm.”
source quote (p.4)
“PRAEVAorta®2 is designed to measure the maximal transverse diameter of vessels and determine the maximal general diameter using a non-adaptative machine learning algorithm.”
source quote (p.12)
“Data security”
Validation studies (1)
Reader study (MRMC)
n=159 cases · 3 site(s)
endpoints: mean absolute error for the total maximum orthogonal aorta diameter; correlation coefficient for the total maximum orthogonal aorta diameter
standards: 21 CFR Part 860 – Medical Device Classification Regulation, 21 CFR Part 820 – Quality System Regulation (QSR), FDA SaMD Guidance - Software as a Medical Device: FDA Guidance, FDA Validation Guidance - General Principles of Software Validation, IEC 62304: 2015 – Medical Device Software - Software Life Cycle Processes, IEC 82304 : 2016 – Health Software - General Requirements for Product Safety, ISO 13485: 2016 – Medial Devices - Quality Management Systems Requirements, ISO 14971: 2019 – Medical Devices – Application of Risk Management to Medical Devices, IEC 62366: 2015 – Medical Devices – Application of Usability Engineering to Medical Devices, ISO 20417 : 2021 – Medical Devices – Information to be supplied by the manufacturer, ISO 15223-1:2021 – Medical Devices – Symbols to Be Used with Medical Device Label, Labeling and information to be supplied
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
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).