EFAI Intelligent Cardiothoracic Ratio (iCTR) Assessment System
K212624Ever Fortune. AI Co., Ltd. · cleared 2022-04-04 · product code QIH · Radiology
Premarket evidence — what FDA accepted
Device typesamd
source quote (p.5)
“The iCTR is a non-invasive software medical device designed to be installed on the computer with specific system requirements.”
Algorithmartificial intelligence algorithm
source quote (p.3)
“The iCTR is designed to measure the maximal transverse diameter of heart and maximal inner transverse diameter of thoracic cavity and calculate the CTR of a chest X-ray image in posterior-anterior (PA) chest view using an artificial intelligence algorithm.”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this
Validation studies (2)
Retrospective clinical
n=840 images · 3 site(s)
endpoints: Accuracy
standards: IMDRF/SaMD WG/N41FINAL:2017
Bench
sample size not stated
standards: IEC 62304, IEC 62366-1, IEC 62366-2
Reported performance (5 observations)
sensitivity0.99
source quote (p.10)
“The quality control models are capable of filtering out non-chest X-ray images (Sensitivity 0.99, Accuracy 0.99), filtering out the non-PA view chest X-ray images(Sensitivity 0.99, Accuracy 0.97)”
accuracyas written: “Accuracy (filtering non-chest X-ray images)”0.99
source quote (p.10)
“The quality control models are capable of filtering out non-chest X-ray images (Sensitivity 0.99, Accuracy 0.99)”
sensitivityas written: “Sensitivity (filtering non-PA view chest X-ray images)”0.99
source quote (p.10)
“filtering out the non-PA view chest X-ray images(Sensitivity 0.99, Accuracy 0.97)”
accuracyas written: “Accuracy (filtering non-PA view chest X-ray images)”0.97
source quote (p.10)
“filtering out the non-PA view chest X-ray images(Sensitivity 0.99, Accuracy 0.97)”
accuracyas written: “Accuracy (EFAI iCTR system)”0.95
source quote (p.10)
“The accuracy of EFAI iCTR system is 0.95.”
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).