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510(k) Data Aggregation
(91 days)
"POINT" Kinguide Agile Hybrid Navigation System is intended as an aid for precisely locating anatomical structures in either open or percutaneous neurosurgical and orthopedic procedures.
The device is indicated for pedicle screw entry point alignment and angular orientation when using a posterior approach into T12 to S1 vertebrae, and where reference to the rigid anatomical structure can be identified by intraoperative 3D reconstruction images.
"POINT" Kinguide Agile Hybrid Navigation System (Kinguide Agile) is an imageguided system (IGS) that consists of an infrared navigation camera, a system workstation (computer), navigation software, and surgical instruments. This medical device system can also be referred to as an orthopedic stereotaxic instrument (OLO) according to the U.S. FDA Device Classification.
Kinguide Agile uses optical positioning technologies to track the position of surgical instruments in relation to patient anatomy by means of Dynamic Reference Frames (DRFs) and identify the patient anatomical structure on intraoperative images (obtained using the 3D C-arm or CT*). The user loads the software to plan the surgical procedure and then registers the patient anatomy during surgery to allow the software to track the patient's anatomy and the navigable surgical instruments in real-time.
The software application primarily provides the stereotactic navigation function to match the coordinates of the patient anatomical structure and establishes a surgical navigation map. The user can perform the operation according to the surgical navigation map through the use of navigable surgical instruments. During surgery, the positions of navigable surgical instruments are continuously updated on the imaging system via optical tracking.
*CT image DICOM file reconstructed from the 3D C-arm or the same function equipment.
The provided document is a 510(k) Premarket Notification from the FDA, asserting substantial equivalence of the "POINT" Kinguide Agile Hybrid Navigation System to previously cleared devices. It outlines the device's indications for use, a comparison to predicate devices, and lists various performance tests and compliance with standards.
However, the document does not contain the specific acceptance criteria for system performance beyond general accuracy expectations, nor does it detail the methodology or results of a study that directly proves the device meets these criteria. It refers to verification and validation results and reports overall accuracy figures, but the granular details expected for a comprehensive study description are absent.
Therefore, much of the requested information cannot be directly extracted from the provided text.
Here is an attempt to address your request based on the available information from the document, with clear indications where the information is not present.
1. Table of Acceptance Criteria and Reported Device Performance
The document states a system accuracy requirement and reports the performance. While it doesn't explicitly frame these as "acceptance criteria" for a specific study, these are the performance targets the device demonstrated.
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Mean positional error $\leq$ 2.0 mm | Mean positional error of $\leq$ 2.0 mm (Stated as demonstrated performance) |
| Mean trajectory error $\leq$ 2 degrees | Mean trajectory error of $\leq$ 2 degrees (Stated as demonstrated performance) |
| (For pedicle screw entry point alignment and angular orientation in T12 to S1 vertebrae) | Mean accuracy of $\leq$ 2.0 mm for location error and $\leq$ 2.0° for trajectory angle error. |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size for Test Set: Not specified. The document mentions "verification and validation results" and "Non-clinical Performance (Accuracy)" and "Cadaveric Validation Report," but it does not provide the sample size (e.g., number of cases, number of anatomical structures, number of screws tested) for these studies.
- Data Provenance (e.g., country of origin, retrospective or prospective): Not specified. The document does not provide details on the origin of the data or the study design (retrospective or prospective). The company's address is in New Taipei City, Taiwan, suggesting the studies might have been conducted there, but this is not explicitly stated.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications of Experts
- Number of Experts: Not specified.
- Qualifications of Experts: Not specified. The document does not mention the use of experts for establishing ground truth in the context of these performance tests. The performance assessments appear to be based on physical measurements and system capabilities rather than human expert assessment of images.
4. Adjudication Method for the Test Set (e.g., 2+1, 3+1, none)
- Adjudication Method: Not applicable/Not specified. The tests described (positional and trajectory accuracy) are objective engineering and performance measurements, not typically requiring human adjudication in the way medical image interpretation might. The document does not mention any form of adjudication.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, and Effect Size of Human Reader Improvement with AI vs. Without AI Assistance
- MRMC Study: No, a MRMC comparative effectiveness study was not done or described. This device is a surgical navigation system, not an AI-assisted diagnostic imaging tool that would typically involve human readers interpreting images. Its "performance" relates to its ability to accurately track and guide surgical instruments.
- Effect Size of Human Reader Improvement: Not applicable. As no MRMC study was done, this information is not provided.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was Done
- Standalone Performance: Yes, implicitly. The reported "System Accuracy Requirement" and "Non-clinical Performance (Accuracy)" (mean accuracy of $\leq$ 2.0 mm for location error and $\leq$ 2.0° for trajectory angle error) appear to be measurements of the device's inherent accuracy, likely in a controlled, non-human-in-the-loop setting (e.g., phantom studies, cadaveric studies without surgical intervention by humans as the primary variable). The "Cadaveric Validation Report" and "Compatibility and Measuring Accuracy Verification Report" suggest standalone performance testing.
7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)
- Type of Ground Truth: The ground truth for positional and trajectory accuracy would primarily be established through physical measurements against known standards or reference points (e.g., using a precisely calibrated phantom or a CMM - coordinate measuring machine). The "Cadaveric Validation Report" implies real anatomical structures were used, where the "ground truth" for screw placement or trajectory would be derived from post-procedure imaging (e.g., CT scans) analyzed against planned trajectories and positions. It does not mention expert consensus readings or pathology.
8. The Sample Size for the Training Set
- Sample Size for Training Set: Not applicable/Not specified. The document describes a navigation system, not a machine learning or AI model that requires a "training set" in the conventional sense of image data for model learning. The navigation algorithm uses transformation matrices, which are mathematical calculations based on tracking data, not a learned model from a large dataset.
9. How the Ground Truth for the Training Set Was Established
- How Ground Truth for Training Set Was Established: Not applicable. As explained above, there is no "training set" for a machine learning model, and thus no ground truth establishment for such a set. The accuracy of the system's underlying mathematical algorithms and optical tracking mechanism is verified through engineering tests.
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(186 days)
"POINT" Kinguide Agile Hybrid Navigation System is intended as an aid for precisely locating anatomical structures in either open or percutaneous neurosurgical and orthopedic procedures.
The device is indicated for pedicle screw entry point alignment and angular orientation when using a posterior approach into T12 and L1 vertebrae, and where reference to the rigid anatomical structure can be identified by intraoperative 3D reconstruction images.
"POINT" Kinguide Agile Hybrid Navigation System (Kinguide Agile) is an imageguided system (IGS) that consists of an infrared navigation camera, a system workstation (computer), navigation software, and surgical instruments. This medical device system can also be referred to as an orthopedic stereotaxic instrument (OLO) according to the U.S. FDA Device Classification.
Kinguide Agile uses optical positioning technologies to track the position of surgical instruments in relation to patient anatomy by means of Dynamic Reference Frames (DRFs) and identify the patient anatomical structure on intraoperative images (obtained using the 3D C-arm or CT*). The user loads the software to plan the surgical procedure and then registers the patient anatomy during surgery to allow the software to track the patient's anatomy and the navigable surgical instruments in real-time.
The software application primarily provides the stereotactic navigation function to match the coordinates of the patient anatomical structure and establishes a surgical navigation map. The user can perform the operation according to the surgical navigation map through the use of navigable surgical instruments. During surgery, the positions of navigable surgical instruments are continuously updated on the imaging system via optical tracking.
*CT image DICOM file reconstructed from the 3D C-arm or the same function equipment.
The "POINT" Kinguide Agile Hybrid Navigation System is intended as an aid for precisely locating anatomical structures in either open or percutaneous neurosurgical and orthopedic procedures. Specifically, it is indicated for pedicle screw entry point alignment and angular orientation when using a posterior approach into T12 and L1 vertebrae, and where reference to the rigid anatomical structure can be identified by intraoperative 3D reconstruction images.
1. Table of Acceptance Criteria and Reported Device Performance:
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Mean Positional Error ≤ 2.0 mm | Mean Positional Error ≤ 2.0 mm |
| Mean Trajectory Error ≤ 2.0° | Mean Trajectory Error ≤ 2.0° |
2. Sample Size Used for the Test Set and Data Provenance:
The document does not explicitly state the specific sample size used for the test set for the accuracy verification. It mentions a "Cadaveric Validation Report," suggesting that testing was performed on cadaveric specimens, which would be retrospective data. The provenance (country of origin) of this data is not specified.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications:
The document does not specify the number of experts or their qualifications used to establish ground truth for the test set.
4. Adjudication Method for the Test Set:
The document does not mention any adjudication method used for the test set.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done:
No, an MRMC comparative effectiveness study involving human readers with and without AI assistance was not mentioned. The device is a "Kinguide Agile Hybrid Navigation System," which is an image-guided system for surgical navigation, not an AI-assisted diagnostic tool that would typically involve human reader studies for comparative effectiveness.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:
Yes, a standalone performance evaluation of the device's accuracy was conducted. The "Non-clinical Performance (Accuracy)" section specifically states: "The system has a mean accuracy of ≤ 2.0 mm for location error and ≤ 2.0° for trajectory angle error." This refers to the intrinsic accuracy of the navigation system itself, independent of human interaction during the measurement process, aside from the initial setup and data acquisition.
7. The Type of Ground Truth Used:
The ground truth for the positional and trajectory accuracy would have been established through precise measurements using a highly accurate reference system (e.g., a calibrated measurement device or a pre-defined anatomical landmark with known coordinates) during the "Performance and Accuracy Verification Report" and "Cadaveric Validation Report." This is typically a technical ground truth rather than expert consensus or pathology.
8. The Sample Size for the Training Set:
The document describes the device as an image-guided navigation system and does not explicitly mention "training set" in the context of machine learning or AI models with distinct training phases. Therefore, no information is provided regarding the sample size for a training set.
9. How the Ground Truth for the Training Set Was Established:
As the document does not discuss a training set in the context of machine learning, it also does not elaborate on how ground truth for such a set would have been established. The core technology lies in optical positioning and image-to-patient registration, not typically in a machine learning model that requires a distinct training phase in the same way a diagnostic AI would.
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(193 days)
"POINT" Kinguide Robotic-Assisted Surgical System is intended as an aid for precisely locating anatomical structures in either open or percutaneous neurosurgical and orthopedic procedures.
The device is indicated for medical condition in which the use of stereotactic spinal surgery may be appropriate, and where reference to a rigid anatomical structure can be identified relative to images of the indications include medical procedures in which pedicle screws are implanted posteriorly into lumbar vertebrae (L1-L5) or sacral vertebrae (S1).
"POINT" Kinguide Robotic-Assisted Surgical System (Kinguide Surgical System) is an orthopedic stereotaxic medical device, which consists of a hand-held robot, a passive arm, a workstation, an infrared navigation camera, navigation software, C-arm ring calibrator and surgical navigation accessories. Among them, the workstation, as the main console for controlling the hand-held robot, is equipped with a computer and control modules, which performs all operations in the surgical procedure through the computer, and transmits its information to the control modules for controlling movements of the hand-held robot. The C-arm ring calibrator and the navigation probe are used to perform registration process. The infrared navigation camera receives the spatial positioning of the patients, the hand-held robot and the surgical accessories through Dynamic Reference Frames (DRFs), and in the meantime the camera sends the data back to the workstation for monitoring stereotactic surgical operation.
The Kinguide Surgical System can assist surgeons to find surgical trajectories quickly and precisely during surgical operations. Software application in the system provides the patient's image to match coordinates of the patient's anatomical structure, and establishes a surgical navigation map. The user can perform the operation according to the surgical navigation map with navigable tools.
Here's a breakdown of the acceptance criteria and study information for the "POINT" Kinguide Robotic-Assisted Surgical System based on the provided document:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Positional Accuracy: Mean Location Error | ≤ 2.0 mm (met criteria) |
| Positional Accuracy: Mean Trajectory Angle Error | ≤ 2° (met criteria) |
2. Sample Size Used for the Test Set and Data Provenance
The document states that "cadaveric validation" was performed. However, it does not specify the sample size for the test set (i.e., the number of cadavers or specific test cases used). The data provenance is cadaveric. The document does not specify the country of origin or if the study was retrospective or prospective, although cadaveric studies are inherently prospective for device testing.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
The document does not provide information on the number of experts used to establish the ground truth for the test set or their qualifications.
4. Adjudication Method for the Test Set
The document does not specify an adjudication method (e.g., 2+1, 3+1, none) for establishing the ground truth of the test set.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
There is no indication that a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done to evaluate how much human readers improve with AI vs. without AI assistance. The device described is a robotic-assisted surgical system, not an AI for image interpretation or diagnosis that would directly involve human readers in that capacity.
6. Standalone Performance (Algorithm Only Without Human-in-the-Loop)
The performance described (positional accuracy for location and trajectory) appears to be a standalone performance of the robotic system itself in achieving targets. The study evaluates the system's ability to guide to a precise location and trajectory, implying an algorithm-only (robotic system only) performance in meeting these physical accuracy metrics. The role of a human surgeon would be to operate the system, but the accuracy itself is attributed to the robotic assistance.
7. Type of Ground Truth Used
The ground truth for the non-clinical performance (accuracy) was established through verification and validation activities, including a "Cadaveric Validation Report," as stated. This suggests that precise physical measurements on cadaveric specimens were used to define the true position and trajectory, against which the robotic system's performance was compared.
8. Sample Size for the Training Set
The document does not provide information about a specific "training set" or its sample size. This type of robotic system involves engineering design and calibration rather than a machine learning model that would typically have a distinct training set for data-driven learning.
9. How the Ground Truth for the Training Set Was Established
As there is no explicit mention of a training set in the context of machine learning, the document does not describe how ground truth for a training set was established. The device's accuracy is likely established through engineering specifications, calibration procedures, and validation against known physical standards.
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