SIS System

K241083

Surgical Information Sciences, Inc. · cleared 2024-06-14 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd

source quote (p.5)

“The SIS System is a software only device based on machine learning and image processing.”

Algorithmmachine learning and image processing, pre-trained deep learning neural network models

source quote (p.5)

“The SIS System is a software only device based on machine learning and image processing. The SIS System provides a patient-specific, 3D anatomical model of specific brain structures based on the patient's own clinical MR image using pre-trained deep learning neural network models.”

Adaptive (vs locked)No

source quote (p.6)

“These pre-trained deep learning neural network models are then applied to a patient's clinical image to predict the shape and position of the patient's specific brain structures of interest. The software development was frozen and labeled before testing on this validation set.”

PCCPNo

Cybersecurity addressedNo

Validation studies (2)

Bench

sample size not stated

Retrospective clinical

sample size not stated

endpoints: Center of mass distance; Mean surface distance; Dice coefficient values

Reported performance (1 observation)

diceas written: “mean Dice coefficient”0.7

source quote (p.6)

“In addition, the mean Dice coefficient in this dataset was 0.7.”

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).