VisAble.IO

K240773

Techsomed · cleared 2024-04-15 · product code QTZ · Radiology

Premarket evidence — what FDA accepted

Device typesamd

source quote (p.4)

“VisAble.IO is a stand-alone software application with tools and features designed to assist users in planning ablation procedures as well as tools for treatment confirmation.”

AlgorithmAI algorithms for liver segmentation and liver vessel segmentation; includes Segmentation, Image Registration, Measurement and Quantification

source quote (p.9)

“The liver segmentation and liver vessel segmentation algorithms for CT processing are Al algorithms. The training and model validation dataset characteristics are as follows: VisAble.IO uses several algorithms to perform operations to present information to the user in order for them to evaluate the planned and post ablation zones. These include: Segmentation, Image Registration, Measurement and Quantification”

Adaptive (vs locked)FDA source did not state this

PCCPFDA source did not state this

Cybersecurity addressedNo

Validation studies (11)

Retrospective clinical

n=1,091 images · 38 site(s)

Retrospective clinical

n=393 images · 36 site(s)

Retrospective clinical

n=418 images · 3 site(s)

Standalone

n=50 cases

endpoints: Mean DICE

standards: 21 CFR Part 820.30, FDA "Guidance on Software Contained in Medical Devices", DICOM standard

Standalone

n=59 cases

endpoints: Mean DICE

standards: 21 CFR Part 820.30, FDA "Guidance on Software Contained in Medical Devices", DICOM standard

Standalone

n=59 cases

endpoints: Mean DICE

standards: 21 CFR Part 820.30, FDA "Guidance on Software Contained in Medical Devices", DICOM standard

Standalone

n=100 cases

endpoints: Mean DICE

standards: 21 CFR Part 820.30, FDA "Guidance on Software Contained in Medical Devices", DICOM standard

Standalone

n=25 cases

endpoints: Mean DICE

standards: 21 CFR Part 820.30, FDA "Guidance on Software Contained in Medical Devices", DICOM standard

Standalone

n=50 cases

endpoints: Mean DICE

standards: 21 CFR Part 820.30, FDA "Guidance on Software Contained in Medical Devices", DICOM standard

Standalone

n=46 cases

endpoints: MCD

standards: 21 CFR Part 820.30, FDA "Guidance on Software Contained in Medical Devices", DICOM standard

Standalone

n=25 cases

endpoints: MCD

standards: 21 CFR Part 820.30, FDA "Guidance on Software Contained in Medical Devices", DICOM standard

Reported performance (6 observations)

diceas written: “Mean DICE (Liver Segmentation CT)”0.98

source quote (p.10)

“Mean DICE =0.98”

diceas written: “Mean DICE (Ablation Target Segmentation CT)”0.82

source quote (p.10)

“Mean DICE = 0.82”

diceas written: “Mean DICE (Ablation Zone Segmentation CT)”0.88

source quote (p.10)

“Mean DICE = 0.88”

diceas written: “Mean DICE (Liver Vessels Segmentation CT)”0.72

source quote (p.10)

“Mean DICE = 0.72”

diceas written: “Mean DICE (Liver Segmentation MR)”0.93

source quote (p.10)

“Mean DICE = 0.93”

diceas written: “Mean DICE (Ablation Target Segmentation MR)”0.76

source quote (p.10)

“Mean DICE = 0.76”

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). 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).