Myomics

K241922

Phantomics Inc. · cleared 2025-02-28 · product code QIH · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
Myomics is a software application for analysis cardiovascular MR images in DICOM Standard format. The software can be used as a stand-alone product that can be integrated into a hospital or private practice environment.
AlgorithmAI-powered algorithms; machine learning algorithms; semi-automatic segmentation
source quote (p.4)
The software comprises various analysis modules, including Al-powered algorithms, for a comprehensive evaluation of MR images. The machine learning algorithms of Myomics were trained and tested using images from various major MR imaging device vendors. Yes (Semi-automatic segmentation)
Adaptive (vs locked)No
source quote (p.9)
The data used for Al performance testing was not utilized during the algorithm training process.
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (2)

Bench

sample size not stated

endpoints: substantial equivalence in performance; compare the semi-automatic segmentation function (endocardium and epicardium contour)

standards: ISO 13485:2016, IEC 62304:2015, ISO 14971:2019

Retrospective clinical

n=728 cases

endpoints: evaluate the ML model's effectiveness in segmenting the Myocardium; average DICE Score of over 0.7

standards: ISO 13485:2016, IEC 62304:2015, ISO 14971:2019

Reported performance (1 observation)

diceas written: “DICE Score0.7
source quote (p.9)
Upon evaluating the performance of each AI module used in Myomics, all modules attained an average DICE Score of over 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

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).

RIGOR™ Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: radar.healthai.com/precedent/device/K241922