CT CoPilot

K161322

ZEPMED, LLC. · cleared 2016-12-07 · product code LLZ · Radiology

FDA 510(k) summary for CT CoPilot (K161322)

Constat organizes this clearance into predicate context, validation evidence, reported performance, postmarket signals, and reimbursement links. Each extracted claim stays tied to the public FDA source; missing fields remain explicitly unstated.

Validation studies
3
Cited predicates
1
Performance observations
0
Product code
LLZ
Official FDA 510(k) database record ↗FDA 510(k) source PDF ↗

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.3)
“CT CoPilotTM is intended for automatic labeling, visualization and volumetric quantification of segmentable structures from sets of CT images of the brain. This software is intended to automate the current manual process of identifying, labeling and quantifying structures identified on CT images of the brain and to provide automated registration and reformatting of data. CT CoPilotTM consists of proprietary software developed by ZepMed, Inc. installed on an off-the-shelf personal computer.”
AlgorithmAtlas-based registration, alignment, and segmentation for volumetric quantification. It uses a "measurement index" based on deviation from a normalized anatomic atlas for error detection.
source quote (p.5)
“CT CoPilotTM incorporates registration, alignment, and segmentation methods similar to a previous 510(k) cleared device, known as NeuroQuant (K061855), to automatically label and quantify the volume of segmentable structures in MRI images of the head. Alignment of subject to Atlas space is an important software step in the overall process of registration and segmentation. CT CoPilotTM uses the mechanism for determination of alignment accuracy instantiated in the predicate device (NeuroQuant) for establishing the relationship between image quality and overall alignment accuracy. Specifically, a “measurement index” is determined for each study based on the deviation of each image from the normalized anatomic index embedded in the program. The measurement index is determined by the deviation of the image volumes from normal atlas space.”
Adaptive (vs locked)No
PCCPNo
Cybersecurity addressedNo

Validation studies (3)

Bench

n=100 images

endpoints: The inter-subject variability of the angle formed by the inter-hemispheric plane and the vertical line, as measured on axial views (yaw), is less than 15 degrees.; The inter-subject variability of the positioning of the inter-hemispheric plane and the vertical line, as measured on coronal views (roll), is less than 15 degrees.; The inter-subject variability of the positioning of the AC/PC plane and the horizontal line, as measured on sagittal views, is less than 15 degrees.

Bench

n=34 patients

endpoints: correlation coefficients between the automatic software segmentation accuracy of relevant anatomical structures; segmentation reliability demonstrates equivalent test-retest performance as expert manually segmented subjects

Bench

sample size not stated

standards: ISO 14971 Second Edition 2007, Medical Devices - Application Of Risk Management To Medical Devices., ISO 62304: The Harmonized Standard for Medical Device Software Development, NEMA PS 3.1 - 3.20 (2011), Digital Imaging And Communications In Medicine (Dicom) Set.

Reported performance (0 observations)

FDA source did not state a quantitative performance metric — non-reporting is itself the signal.

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

25
recalls in product code, 24mo
397
MAUDE reports in code, 12mo
+963%
vs code's own 3-yr baseline
31
drift signals on this device
  • predicate_cohort_contagion

    K161322 shares predicate K061855 with K213645 (ClearPoint Maestro Brain Model), whose product code QIH recorded 1 recall event(s) in the trailing 24 months.

    first seen 2026-09-02 · predicate:K061855 sibling:K213645

  • recall_reason_pattern

    Software/algorithm-related recall in product code LLZ (Merge Healthcare, Inc., initiated 2026-07-22): "Software issue may cause measurements to be displayed inaccurately." Recalling firm is another firm in the same product code.

    first seen 2026-09-02 · recall res_event_number:99520

  • recall_reason_pattern

    Software/algorithm-related recall in product code LLZ (FUJIFILM Healthcare Americas Corporation, initiated 2026-07-22): "Software issue may cause the ruler measurement to be inaccurate." Recalling firm is another firm in the same product code.

    first seen 2026-09-02 · recall res_event_number:99529

  • recall_reason_pattern

    Software/algorithm-related recall in product code LLZ (Merge Healthcare, Inc., initiated 2026-06-30): "Merge Healthcare has identified a potential issue that may cause thumbnails from a previously opened patient study to be displayed in the Thumbnail Bar while a different patient st" Recalling firm is another firm in the same product code.

    first seen 2026-09-02 · recall res_event_number:99391

  • recall_reason_pattern

    Software/algorithm-related recall in product code LLZ (Boston Scientific Corporation, initiated 2026-06-19): "Software anomaly occurs when a user adds one or more vials to the cart and subsequently returns to the Activity Calculator to modify one or more input. When a user modifies an inpu" Recalling firm is another firm in the same product code.

    first seen 2026-09-02 · recall res_event_number:99236

  • adverse_event_inflection

    MAUDE adverse-event reports for product code LLZ: 295 in the 12 months ending 2026-06, vs a 37.7/12mo average over the prior 3 windows (+683%). Code-level count — reports are not attributed to this specific device.

    first seen 2026-07-08 · openFDA /device/event.json count=date_received product_code=LLZ

  • …and 25 more.

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 2026-09-02.

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.

Related FDA clearances

More AI/ML devices under product code LLZ

These are recent clearances in the same FDA product-code category. Shared classification does not by itself make a device an appropriate predicate.

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Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K161322