Search Results

The Intai Anatomy Locking Plate and Screw System is provided non-sterile. The system is intended for use in fixation of fractures to the various bones, including; clavicle, radius, ulna, humerus, femur, tibia, fibula, and acetabulum for adults. This system is not indicated for use in the spine.

The Intai Anatomical Locking Plate and Screw System offers anatomically contoured plates for use with non-locking and locking screws. The plates are provided with locking holes as well as holes for cortex screws to enhance compression pressure. With the combination of locking and compression technology, the system further ensures the stability of the implant devices.

The provided text is a 510(k) Premarket Notification for the "Intai Anatomical Locking Plate and Screw System." This document is a regulatory submission for a medical device and does not describe:

• Acceptance criteria for an AI/ML powered medical device. The device is a physical bone fixation system.
• A study involving a test set, ground truth, experts, or AI/ML performance. The performance data discussed relates to biomechanical testing of the physical plates and screws (e.g., bend, fatigue, torque, pullout testing) against ASTM standards, not a clinical or AI-driven performance study.
• Training sets or adjudication methods for AI/ML models.

Therefore, I cannot extract the requested information regarding AI/ML device performance, ground truth, expert adjudication, or MRMC studies from the provided text. The document focuses on demonstrating substantial equivalence of a bone fixation system to existing predicate devices based on its intended use, materials, design features, and biomechanical non-clinical tests.

Ask a specific question about this device

The INTAI Surgery Navigation System is indicated for precise positioning of surgical instruments or spinal implants during general spinal surgery when reference to a rigid anatomical structure, such as the vertebra, can be identified relative to a patient's fluoroscopic or CT imagery. It is intended as a planning and intraoperative guidance system to enable open or percutaneous image guided surgery by means of registering intraoperative 2D fluoroscopic projections to pre-operative 3D CT imagery.

Example procedures include but are not limited to:

Posterior-approach spinal implant procedures, such as pedicle screw placement, within the lumbar region.

The INTAI Surgery Navigation System, also known as an image guided system, is comprised of navigation cart, software and its accessories. The system uses wireless optical tracking technology to identify the position of instruments relative to the patient's anatomy and displays such position on preoperative or intraoperative images of the patient. The images can help guide the surgeons during spinal surgical procedures, such as spinal fusion. The software links all system components and provides several application modules for trajectory planning, image registration, instrument auto-identification and real-time navigation.

The provided text describes the regulatory filing for the "INTAI Surgery Navigation System." While it outlines various non-clinical tests performed, it explicitly states that no clinical testing has been conducted (Section 5.7). Therefore, the device performance is evaluated based on system performance validations that use cadavers, not human clinical data.

Here's a breakdown based on the information provided:

1. Table of acceptance criteria and the reported device performance:

2. Sample size used for the test set and the data provenance:

• Sample Size: Not explicitly stated for the "System Performance Validation." It only mentions "cadaver" (singular or plural not specified, implying a limited number, potentially one or a few for testing. Given the lack of clinical data, this would be a lab-based, not patient-based, test set.).
• Data Provenance: The testing was "in cadaver." No country of origin is specified for the cadavers, but the applicant's address is Taiwan. This is a non-clinical, simulated use scenario, not real patient data. It is inherently prospective in the sense that the tests were designed and executed to validate the device.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not Applicable. The ground truth for the "System Performance Validation" in cadavers would likely be established through precise physical measurements (e.g., using a coordinate measuring machine or highly accurate calibration tools) relative to the known anatomical structures or fiducials on the cadaver, not through human expert interpretation of images for diagnostic purposes. The document does not mention experts establishing ground truth for this non-clinical test.

4. Adjudication method for the test set:

• Not Applicable. As the ground truth is established through physical measurements in a laboratory setting on cadavers, there is no expert adjudication process over human interpretations.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:

• No. The document explicitly states "No clinical testing has been conducted." An MRMC study involves multiple human readers evaluating medical images, often with and without AI assistance, to assess diagnostic performance. This was not performed.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

• Yes, implicitly. The "System Performance Validation" and "Accuracy" sections describe tests of the device's inherent positional and trajectory accuracy. These tests evaluate the system's ability to precisely track and guide instruments, which is a standalone function of the algorithm and hardware, independent of a human operator's diagnostic decision-making. The acceptance criteria for mean positional error and mean trajectory angle error are quantitative measures of the system's output.

7. The type of ground truth used:

• For the "System Performance Validation," the ground truth would be physical measurements/gold standard metrology in a cadaveric setting, rather than expert consensus on medical images, pathology, or clinical outcomes data. This is a measure of mechanical and algorithmic precision.

8. The sample size for the training set:

• Not specified. The document does not provide details about model training, as it focuses on the regulatory submission and validation of a navigation system, not an AI diagnostic algorithm. While navigation systems use algorithms, the training dataset size for any internal models used (if applicable, e.g., for image registration algorithms) is not disclosed.

9. How the ground truth for the training set was established:

• Not specified. Given the information provided, this question is not directly applicable as the document does not detail the training of an AI model in the conventional sense for diagnostic purposes. The ground truth for system accuracy validation is based on physical measurement, not data-driven machine learning ground truth labeling.

Ask a specific question about this device