OrthoNext Platform System

K242270

Orthofix Srl · cleared 2024-12-19 · product code QIH · Radiology

FDA 510(k) summary for OrthoNext Platform System (K242270)

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
2
Cited predicates
2
Performance observations
8
Product code
QIH
Official FDA 510(k) database record ↗FDA 510(k) source PDF ↗

Premarket evidence — what FDA accepted

Device typesamd
source quote (p.6)
“The subject OrthoNext™ Platform System is a web-based modular software system, indicated for assisting healthcare professionals in planning of orthopedic surgery and treatment both preoperatively and postoperatively, including deformity analysis and correction with several Orthofix products.”
AlgorithmAI/ML algorithm for automatic marker detection
source quote (p.10)
“In addition, considerations on accuracy, specificity and sensitivity of the AI/ML algorithm for the automatic marker detection have been included in the submission:”
Adaptive (vs locked)FDA source did not state this
PCCPFDA source did not state this
Cybersecurity addressedFDA source did not state this

Validation studies (2)

Bench

n=1,000 images

endpoints: zero false positives; precision; accuracy; TPR/recall; FPR; F1 Score

Bench

sample size not stated

endpoints: mean error for linear measurements; mean error for angular measurements; mean percentage error for linear measurements; mean percentage error for angular measurements

Reported performance (8 observations)

sensitivity0.75
source quote (p.10)
“AI/ML Algorithm Sensitivity (TPR): 0.75”
accuracyas written: “AI/ML Algorithm Accuracy”0.8
source quote (p.10)
“AI/ML Algorithm Accuracy: 0.8”
specificityas written: “AI/ML Algorithm Specificity (Precision)”1
source quote (p.10)
“AI/ML Algorithm Specificity (Precision): 1”
ppvas written: “Precision”1
source quote (p.11)
“Precision 1”
accuracyas written: “Accuracy”0.8
source quote (p.11)
“Accuracy 0.8”
sensitivityas written: “TPR/Recall”0.75
source quote (p.11)
“TPR/Recall 0.75”
f1as written: “F1 Score”0.86
source quote (p.11)
“F1 Score 0.86”
iouas written: “Intersection over Union (%)”79
source quote (p.12)
“Intersection over Union (%) 79”

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

1
recalls in product code, 24mo
4
MAUDE reports in code, 12mo
—
vs code's own 3-yr baseline
1
drift signals on this device
  • recall_reason_pattern

    Software/algorithm-related recall in product code QIH (PIE Medical Imaging B.V., initiated 2026-05-07): "User measurement value reported by diagnostic bioimaging software intended to measure/visualize cardiovascular structures may be larger (0.8% to 34.4%) than the actual anatomical d" Recalling firm is another firm in the same product code.

    first seen 2026-08-26 · recall res_event_number:98930

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 2026-08-26.

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 QIH

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

ADAS 3D

K253969

Adas3D Medical S.L.

cleared 2026-06-29

Auto-Seg (SO-0012), Spine Auto-Seg (SO-0012)

K253628

Agada Medical, Ltd.

cleared 2026-06-29

syngo.CT Coronary Cockpit

K253786

Siemens Medical Solutions USA, Inc.

cleared 2026-06-25

CMN Capillary Function with Oncology Virtual Expert

K260316

Cercare Medical A/S

cleared 2026-06-22

Synapse PACS (7.6.0)

K261713

FUJIFILM Healthcare Americas Corporation

cleared 2026-06-18

MediAI-OA

K253172

Crescom Co., Ltd.

cleared 2026-06-15

AiORTA - Plan v2.0

K254207

ViTAA Medical Solutions, Inc.

cleared 2026-03-30

SwiftMR

K253775

Airs Medical, Inc.

cleared 2026-03-26

Constat Precedent · public FDA/CMS data · descriptive decision-support, not regulatory or reimbursement advice. Share this page: constat.dev/precedent/device/K242270