NS-HGlio

K221738

Neosoma Inc. · cleared 2022-09-27 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd

source quote (p.4)

“NS-HGlio is a non-invasive software as a medical device (SaMD) tool intended for labeling, visualization, and volumetric quantification of high-grade brain gliomas for a population that has been pathologically diagnosed to have brain tumors.”

Algorithmdeep learning methodology

source quote (p.5)

“NS-HGlio device takes as an input imported Digital Imaging and Communications in Medicine (DICOM) images of high-grade brain glioma acquired with standard brain tumor MRI protocols and uses a deep learning methodology to semi-automatically label the different subcomponents of the high-grade glioma.”

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)

Retrospective clinical

n=33 patients

endpoints: Dice Similarity Coefficient (DSC); Intraclass correlation coefficient (ICC)

standards: IEC 62304:2006/AC:2015 - Medical device software Software life cycle processes, FDA Guidance document, “Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices.”

Reported performance (3 observations)

diceas written: “Dice Similarity Coefficient (DSC) on preoperative imaging”0.88CI 0.86-0.90

source quote (p.7)

“The device achieved a mean DSC of 0.88 with 95% CI of 0.86-0.90 on preoperative imaging and 0.80 with 95% CI of 0.77-0.83 on postoperative imaging respectively.”

diceas written: “Dice Similarity Coefficient (DSC) on postoperative imaging”0.8CI 0.77-0.83

source quote (p.7)

“The device achieved a mean DSC of 0.88 with 95% CI of 0.86-0.90 on preoperative imaging and 0.80 with 95% CI of 0.77-0.83 on postoperative imaging respectively.”

agreement_kappaas written: “Intraclass correlation coefficient (ICC)”0.98CI 0.97-0.99

source quote (p.7)

“The mean ICC was 0.98 with 95% CI of 0.97-0.99.”

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).