EchoSolv AS

K241245

Echo IQ Ltd · cleared 2024-10-04 · product code POK · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.4)
“EchoSolv AS is a machine learning (ML) and artificial intelligence (AI) based decision support software indicated for use as an adjunct to echocardiography for assessment of severe aortic stenosis (AS).”
Algorithmmachine learning (ML) and artificial intelligence (AI) based algorithm
source quote (p.4)
“EchoSolv AS is a machine learning (ML) and artificial intelligence (AI) based decision support software indicated for use as an adjunct to echocardiography for assessment of severe aortic stenosis (AS).”
Adaptive (vs locked)FDA source did not state this
PCCPNo
Cybersecurity addressedFDA source did not state this

Validation studies (2)

Retrospective clinical

n=6,268 cases

endpoints: Receiver Operating Characteristic (ROC) curve; Area under the receiver operating characteristic (AUROC) curve; Diagnostic likelihood ratios (DLR); Cochrane-Armitage Trend Test

standards: 21 CFR §892.2060 special control 1(iv)

Reader study (MRMC)

n=200 cases · 1 site(s)

endpoints: ROC curves; AUROC; mean AUROC improvement; reader concordance (agreement) using Fleiss' Kappa

standards: 21 CFR §892.2060 special control 1(ii), 21 CFR §892.2060 special control 1(iii)

Reported performance (8 observations)

sensitivity0.801CI 0.786-0.818
source quote (p.8)
“Sensitivity and specificity at the high probability threshold were 0.801(95%CI: 0.786-0.818) and 0.923 (95%CI: 0.915-0.932), respectively”
specificity0.923CI 0.915-0.932
source quote (p.8)
“Sensitivity and specificity at the high probability threshold were 0.801(95%CI: 0.786-0.818) and 0.923 (95%CI: 0.915-0.932), respectively”
aurocas written: “auc”0.948CI 0.943-0.952
source quote (p.8)
“The EchoSolv AS model achieved a native system performance of 0.948 (95% CI: 0.943-0.952) AUROC.”
aurocas written: “AUROC (unassisted reads)”0.865CI 0.837-0.893
source quote (p.9)
“AUROC for unassisted and assisted reads were 0.865 (95%CI: 0.837-0.893) and 0.883 (95%CI: 0.857-0.909), respectively.”
aurocas written: “AUROC (assisted reads)”0.883CI 0.857-0.909
source quote (p.9)
“AUROC for unassisted and assisted reads were 0.865 (95%CI: 0.837-0.893) and 0.883 (95%CI: 0.857-0.909), respectively.”
aurocas written: “mean AUROC improvement”0.018CI 0.037-0.001
source quote (p.9)
“When cardiologist readers were provided with EchoSolv AS to assist with their interpretation of a TTE, there was an improvement in all study endpoints: mean AUROC (0.018±0.010, 95%CI: 0.037-0.001; p=0.064).”
agreement_kappaas written: “Fleiss' Kappa (unassisted reads)”0.641CI 0.597-0.685
source quote (p.9)
“Kappa for unassisted and assisted reads were 0.641 (95%CI: 0.597-0.685) and 0.667 (95%CI: 0.623-0.711), respectively.”
agreement_kappaas written: “Fleiss' Kappa (assisted reads)”0.667CI 0.623-0.711
source quote (p.9)
“Kappa for unassisted and assisted reads were 0.641 (95%CI: 0.597-0.685) and 0.667 (95%CI: 0.623-0.711), respectively.”

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
0
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/K241245