(68 days)
The TL-HEX System is intended for limb lengthening by metaphyseal distractions, fixation of open and closed fractures, treatment of non-union or pseudoarthrosis of long bones and correction of bony or soft tissue defects or deformities.
Indications, both for adults and all pediatric subgroups except newborns, include:
- · Post-traumatic joint contracture which has resulted in loss of range of motion
- · Fractures and disease which generally may result in joint contractures or loss of range of motion and fractures requiring distraction
- · Open and closed fracture fixation
- · Pseudoarthrosis of long bones
- · Limb lengthening by epiphyseal or metaphyseal distraction
- · Correction of bony or soft tissue deformities
- · Correction of bony or soft tissue defects
- · Joint arthrodesis
- · Infected fractures or non unions
The Subject device is a multilateral external fixation system. The System can also be used with a web-based software component that is designed to be used to assist the physician in creating a patient adjustment schedule that assists in adjusting the six struts.
Components of the System include:
Full, 5/8 and 3/8 aluminum Rings Double Row Footplates Adjustable struts Aluminum strut clips (number and direction) Stainless steel instrumentation such as hex drivers, wrenches, and pliers Implantable components such as half pins and wires Web-based software
This document (K170650) describes the Orthofix TrueLok Hexapod System (TL-HEX) V2.0, an external fixation system used for various orthopedic conditions. The provided text is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device rather than detailing specific algorithm performance for an AI/ML medical device. Therefore, much of the requested information regarding AI/ML device performance metrics, such as accuracy, sensitivity, specificity, and aspects of a clinical study for AI systems, is not present in this document.
The document primarily covers the mechanical and software validation of the device, focusing on its physical and computational aspects for planning, rather than AI-driven diagnostic or prognostic capabilities.
Here's a breakdown of the available information based on your request:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not present acceptance criteria or reported performance in the typical format for an AI/ML device (e.g., accuracy, sensitivity, specificity). Instead, it refers to:
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Mechanical performance to withstand expected loads | All testing met or exceeded the requirements established by test protocols and applicable standards. Hardware components capable of withstanding expected loads without failure. |
| Software functionality as intended | Software verification and validation testing completed in conformance with FDA guidance. Results indicate updated software continues to perform as intended. |
| Compliance with ASTM F1541-02 "Standard Specification and Test Methods for External Skeletal Fixation Devices" | Testing was performed against this standard. |
| Software IQ, OQ, PQ (Installation, Operational, Performance Qualification) | These qualifications were completed. |
2. Sample Size Used for the Test Set and Data Provenance
This document describes a medical device for bone fixation and correction, not an AI/ML diagnostic or prognostic system that processes patient data/images for analysis. Therefore, there is no "test set" in the context of patient data for AI model evaluation.
The "testing" mentioned refers to mechanical and software validation of the device's components and planning software. The sample sizes for these engineering tests (e.g., number of devices tested, number of software iterations tested) are not specified in this summary.
Data Provenance: Not applicable in the context of patient data for AI/ML. The device itself is manufactured by Orthofix Srl in Italy.
Retrospective or Prospective: Not applicable as it's not a study on patient data or clinical outcomes in the AI context.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
This information is not applicable as the document describes validation of a mechanical and software system for surgical planning, not an AI/ML system requiring expert-established ground truth from medical images/data. The ground truth for the software's performance is its ability to accurately calculate adjustment schedules based on physician input, and for the mechanical components, it's their ability to withstand loads according to engineering standards.
4. Adjudication Method for the Test Set
Not applicable. As there's no "test set" of patient cases for AI evaluation, there's no need for an adjudication method by medical experts.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No. This document does not mention an MRMC study. The device is a physical fixation system along with planning software; it is not presented as an AI assistance tool for human readers in diagnostic tasks. Therefore, there's no discussion of human readers improving with AI assistance.
6. Standalone (Algorithm Only Without Human-in-the-Loop Performance)
The "software component" mentioned assists the physician in creating an adjustment schedule. This implies a human-in-the-loop system where the physician uses the software as a tool. The document does not provide a standalone performance evaluation of an algorithm without human input, as this is not an AI diagnostic algorithm.
7. The Type of Ground Truth Used
For the mechanical components, the ground truth is established by engineering standards (e.g., ASTM F1541-02) and internal test protocols for resisting specified loads without failure.
For the software, the ground truth relates to its computational accuracy and functional correctness in generating adjustment schedules based on input data, validated through standard software verification and validation (V&V) procedures (IQ, OQ, PQ). It's not based on expert consensus from medical images or pathology.
8. The Sample Size for the Training Set
Not applicable. This document describes the validation of a software application that calculates adjustments, not an AI/ML model that would require a "training set" of data to learn from. The software is likely based on deterministic algorithms and geometric principles.
9. How the Ground Truth for the Training Set Was Established
Not applicable. As there is no AI/ML training set, there is no ground truth established for it.
§ 888.3030 Single/multiple component metallic bone fixation appliances and accessories.
(a)
Identification. Single/multiple component metallic bone fixation appliances and accessories are devices intended to be implanted consisting of one or more metallic components and their metallic fasteners. The devices contain a plate, a nail/plate combination, or a blade/plate combination that are made of alloys, such as cobalt-chromium-molybdenum, stainless steel, and titanium, that are intended to be held in position with fasteners, such as screws and nails, or bolts, nuts, and washers. These devices are used for fixation of fractures of the proximal or distal end of long bones, such as intracapsular, intertrochanteric, intercervical, supracondylar, or condylar fractures of the femur; for fusion of a joint; or for surgical procedures that involve cutting a bone. The devices may be implanted or attached through the skin so that a pulling force (traction) may be applied to the skeletal system.(b)
Classification. Class II.