MRCAT Head & Neck

K214081

Philips Oy · cleared 2022-04-05 · product code MUJ · Radiology

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.5)
“MRCAT Head & Neck is a software application to Ingenia, Ingenia Ambition, and Ingenia Elition MR systems. MRCAT Head and Neck functionality is implemented as a software plug-in for the MR main software, and it contains the following main features: 1) Automatic post-processing tool delivering MRCAT images 2) Examcard with mDixon imaging protocol 3) DICOM export of MRCAT image.”
Algorithmmachine learning based segmentation and convolutional neural network (CNN)
source quote (p.5)
“MRCAT algorithm enables automatic tissue characterization: Bones are segmented from mDixon in-phase and water images using machine learning based segmentation. The intensity normalized images are then used as input in a convolutional neural network (CNN).”
Adaptive (vs locked)No
source quote (p.6)
“The training of the CNN is locked and is not adapted during use. Both algorithms are locked; they do not change after installation based on new data during the use.”
PCCPNo
source quote (p.6)
“The training of the CNN is locked and is not adapted during use. Both algorithms are locked; they do not change after installation based on new data during the use.”
Cybersecurity addressedFDA source did not state this

Validation studies (2)

Bench

sample size not stated

endpoints: ± 1 mm accuracy: 200 mm diameter sphere; ± 2 mm accuracy: 400 mm diameter sphere (limited in the bore direction by +/- 160 mm from the z=0 mm plane); ± 5 mm accuracy: 500 mm diameter sphere (limited in the bore direction by +/- 160 mm from the z=0 mm plane)

standards: ANSI/AAMI ES60601-1: 2012, IEC 60601-1-6:2010, IEC 60601-2-33:2015, IEC 62304:2016, IEC 62366-1:2020, ISO 14971:2019

Retrospective clinical

sample size not stated

endpoints: dose accuracy; gamma analysis criterion 2%/2mm; average simulated dose based on MRCAT Head & Neck shall not deviate more than 5% or 1 Gy

Reported performance (3 observations)

accuracyas written: “Geometric accuracy for 200 mm diameter sphere”1
source quote (p.12)
“± 1 mm accuracy: 200 mm diameter sphere”
accuracyas written: “Geometric accuracy for 400 mm diameter sphere”2
source quote (p.12)
“± 2 mm accuracy: 400 mm diameter sphere (limited in the bore direction by +/- 160 mm from the z=0 mm plane)”
accuracyas written: “Geometric accuracy for 500 mm diameter sphere”5
source quote (p.12)
“± 5 mm accuracy: 500 mm diameter sphere (limited in the bore direction by +/- 160 mm from the z=0 mm plane)”

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

35
recalls in product code, 24mo
17
MAUDE reports in code, 12mo
-50%
vs code's own 3-yr baseline
2
drift signals on this device
  • recall_reason_pattern

    Software/algorithm-related recall in product code MUJ (Philips Medical Systems (Cleveland) Inc, initiated 2025-08-05): "Due to a software issue, there is a potential image error of the Region of Interest for expansion/contraction for HFP (Head First Prone), FFS (Feet First Supine) and FFP (Feet Firs" Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:97049

  • recall_reason_pattern

    Software/algorithm-related recall in product code MUJ (Philips Medical Systems (Cleveland) Inc, initiated 2025-07-17): "Due to software issue, Radiation Therapy Planning system may provide incorrect dataset calculations when performing the "Stopping Power Ratio" (SPR) ," Recalling firm is another firm in the same product code.

    first seen 2026-07-08 · recall res_event_number:97309

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/K214081