Search Results

The Distal Femoral Growing Prosthesis is indicated for pediatric patients who have not achieved full skeletal maturity (open epiphysis), where radical resection and replacement of the distal femur and or/proximal tibia is required with the following conditions:

. Oncology indications
Severe trauma .
. Noninflammatory degenerative joint disease including osteoarthritis
. Correction of functional deformity
. Rheumatoid arthritis
. Revision procedures where other treatments or devices have failed

The devices are single use implants intended only for implantation with bone cement.

Compatible components of the GMRS, MRH, MRS, and KRH when used with the Distal Femoral Growing Prosthesis are intended for use in pediatric patients for the abovementioned indications.

Device Description

The Distal Femoral Growing Prosthesis System provides a means to reconstruct large bone defects resulting from bone resection in skeletally immature patients. The device can be expanded as a patient grows so that leg-length equality can be achieved. The device utilizes a rotating hinge design. The expansion process is mechanical and is conducted with subsequent minimally invasive procedures following the initial implantation surgery.

AI/ML Overview

Acceptance Criteria and Device Performance Study for the Distal Femoral Growing Prosthesis System

The provided document describes the "Distal Femoral Growing Prosthesis System" and its substantial equivalence to predicate devices, without detailed acceptance criteria typically found for diagnostic or AI-driven devices. This submission for K122015 is for a medical implant (prosthesis), and its "acceptance criteria" are primarily related to its mechanical performance and compliance with established standards for such devices, rather than a diagnostic accuracy or efficacy typical for AI-enabled devices.

Here's an interpretation of "acceptance criteria" and "device performance" based on the provided text, focusing on the non-clinical testing performed.

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criterion (Implicit)	Reported Device Performance
Mechanical Stability during Expansion Feature Operation: The expansion feature of the device must not cause collapse/retraction before, during, or after physiological loading. (Implied for safe and effective longitudinal growth adjustment)	"Single-axis and multi-axis life cycle testing of the Distal Femoral Growing Prosthesis was conducted to verify that the expansion feature of the device will not cause the subject component to collapse/retract before, after and during physiological loading. All specimens tested ran out without evidence of collapse of the device."
Fatigue Resistance of Crossover Bearing Component: The crossover bearing component must withstand physiological loading. (Implied for long-term durability and function)	"Fatigue testing was also conducted on the Distal Femoral Growing Prosthesis crossover bearing component. All test specimens withstood physiological loading as compared to the predicate device."
Substantial Equivalence to Predicate Devices: Technological characteristics (material, design, sizes, operational principles) should be similar or identical to predicate devices. (A regulatory acceptance criterion for 510(k) clearance)	"The technological characteristics (material, design, sizes, and operational principles) of the Distal Femoral Growing Prosthesis System are similar or identical to its predicate devices." and "The Distal Femoral Growing Prosthesis System devices are substantially equivalent to the predicate devices identified in this premarket notification."

2. Sample Size Used for the Test Set and Data Provenance

Sample Size: The document does not specify the exact number of "specimens" tested for single-axis, multi-axis life cycle testing, or fatigue testing. It refers to "All specimens tested" and "All test specimens," implying a sufficient number were used to demonstrate the stated performance.
Data Provenance: The testing was "Non-clinical laboratory testing." This indicates the data was generated in a controlled laboratory environment, not from patient data, and is thus prospective in nature for the purpose of design verification. The country of origin for the lab is not specified.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This is not applicable for this type of device and testing. The "ground truth" for mechanical testing is established by engineering specifications, material science principles, and established testing standards (e.g., ISO, ASTM for similar medical devices). There are no human "experts" establishing a diagnostic ground truth in this context.

4. Adjudication Method for the Test Set

This is not applicable for non-clinical mechanical testing. Adjudication methods like 2+1 or 3+1 are used to establish ground truth for clinical cases, often in diagnostic studies where expert consensus is needed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not done. Such studies are typically conducted for devices that assist human interpretation (e.g., AI for radiology). This submission is for a prosthetic implant whose performance is assessed through mechanical and material testing, not human interpretation. The document explicitly states: "Clinical testing was not required for this submission."

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

This question is not applicable. The device is a physical prosthesis, not an algorithm or AI system. Its "performance" is inherently standalone in the sense that its mechanical properties are evaluated intrinsically, without human interaction during the test itself (though humans design the test).

7. The Type of Ground Truth Used

The ground truth for this device's acceptance criteria primarily involved engineering specifications, established biomechanical performance standards for orthopedic implants, and comparison to predicate device performance. This is validated through laboratory testing designed to simulate physiological loads and growth expansion cycles.

8. The Sample Size for the Training Set

This concept is not applicable. "Training set" refers to data used to train machine learning models. This device is a mechanical prosthesis and does not involve any machine learning components.

9. How the Ground Truth for the Training Set Was Established

This question is not applicable, as there is no training set for a mechanical prosthetic device.

Ask a Question

Ask a specific question about this device

Page 1 of 1