(246 days)
Spine & Trauma 3D is intended as an intraoperative image-guided localization system to enable minimally invasive surgery. It links a freehand probe, tracked by a passive marker sensor system to virtual computer image space on a patient's preoperative or Intraoperative 2D or 3D image data.
Spine & Trauma 3D enables computer-assisted navigation of medical image data, which can either be acquired preoperatively or intraoperatively by an appropriate image acquisition system.
The software offers screw implant size planning and navigation on rigid bone structures with precalibrated and additional individually-calibrated surgical tools. The system is indicated for any medical condition in which the use of stereotactic surgery may be appropriate and where a reference to a rigid anatomical structure, such as the skull, the pelvis, a long bone or vertebra can be identified relative to the acquired image (CT, MR, 2D fluoroscopic image reconstruction) and/or an image data based model of the anatomy.
This navigation system consists of software and hardware components and is an image guided surgery system for navigated treatments in the fields of spine and trauma surgery, whereas the user may use 3D data based on CT, MR or XT. The Software may be installed on a fixed (e.g. Buzz Navigation (CM)) or mobile (e.g. Kick, Curve) navigation platform and supports the surgeon in clinical procedures by displaying tracked instruments in patient's image data. Such instruments can be held by a surgeon or by a mechatronic arm, which passively keeps the instrument in the position. (Mechatronic Vario Guide, "Cirq").
Based on the provided text, the documentation does not describe a study involving an AI/Machine Learning device that requires a test set with ground truth established by experts, an adjudication method, or a multi-reader, multi-case comparative effectiveness study. The device, "Spine & Trauma Navigation," is a stereotaxic instrument for image-guided localization in surgery, linking a freehand probe to virtual computer image space on patient data. It is not an AI/ML diagnostic or predictive device.
Therefore, many of the requested details about acceptance criteria and study proving the device meets them, especially those related to AI/ML performance metrics, are not applicable or extractable from this document. The document focuses on the verification of the navigational system's functionalities, accuracy, safety, and compliance with standards rather than AI/ML performance.
Here's an attempt to answer the questions based on the available information, noting where information is not present or not applicable to an AI/ML context:
1. Table of acceptance criteria and the reported device performance
The document broadly states that "The essential performance characteristic for this product is the overall registration and navigation accuracy of the system to ensure the safe and effective use according to the intended use." Specific quantitative acceptance criteria for navigation accuracy (e.g., in mm) or the reported numerical performance are not explicitly provided in the summary.
Instead, the document details various verification tests and their conclusions:
| Acceptance Criteria Category (Derived from "Verification Summary") | Reported Device Performance / Conclusion |
|---|---|
| Verification of general functions (accurate positioning, robust alignment of surgical instrument with Mechatronic Vario Guide) | "Verification of general functions successful. All requirements met." |
| General design requirements (overall design, layout, general behavior) | "Verification of general design requirements successful." |
| Safety tests regarding risk analysis (effectiveness of risk control measures) | "Risk control measures are effective and mitigate the associated risks." |
| Human factors / Usability Testing (clinical workflow with Mechatronic Vario Guide) | "System is safe and effective to use." |
| Product safety tests (compliance with AAMI/ANSI ES60601-1:2005/(R)2012 for medical electrical equipment) | "Compliance with standards requirements demonstrated, no deviations." |
| Biocompatibility / Reprocessing (material properties, response to cleaning/disinfection/sterilization) | "Biocompatibility assessment and reprocessing tests successful." |
| Environmental tests (adherence to RoHS, REACH, WEEE directives) | "Environmental tests successful." |
| Integration tests with spine navigation applications and Brainlab navigation platforms | "Integration and compatibility tests successful." |
| Mechanical tests (stability, interface tests, holding force) | "Mechanical tests successful." |
| Integration tests of Surgical Base System (braking concept, visual indicators, holding forces) | "Surgical Base System integration tests successful." |
| Surgical Base System firmware software verification (compliance with IEC 62304 and FDA Guidance) | "Surgical Base System software verification successful." |
| Integration tests of sterile drape (form, fit, function, sterile barrier, navigation compatibility) | "Drape integration tests successful." |
2. Sample size used for the test set and the data provenance
- Test Sample Size: Not specified quantitatively. For "Verification of general functions," tests were conducted "on an MIS Spine Training Model." For "Human factors / Usability Testing," tests involved "surgeons and OR nurses." The number of models, cases, or participants is not given.
- Data Provenance: Not explicitly stated. The tests were performed in a "simulated clinical environment." There is no mention of country of origin for any data or whether it was retrospective or prospective patient data, as the tests involved models and simulated environments, not real patient data in a traditional clinical study sense.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Number of Experts: Not specified. For "Verification of general functions," tests were "performed by spinal surgeons." For "Human factors / Usability Testing," tests were performed "with surgeons and OR nurses." The exact number or qualifications (e.g., years of experience) beyond their titles are not provided.
- Ground Truth Establishment: For a navigation system, "ground truth" would typically refer to the true anatomical position or trajectory. The document does not describe a method for establishing such ground truth by experts in a review process, as might be done for diagnostic image interpretation. Instead, the "accuracy" is verified as part of the system's function (e.g., "accurate positioning").
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not applicable / No information provided. The nature of the device (a surgical navigation system, not a diagnostic AI/ML algorithm) and the described verification tests do not suggest a need for, or implementation of, an adjudication method for establishing ground truth from multiple human readers.
5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance
- No, not specified. This device is a surgical navigation system, not an AI-assisted image interpretation tool for human readers. Therefore, an MRMC comparative effectiveness study regarding human reader improvement with AI assistance is not applicable and was not reported. The focus is on the system's ability to guide surgical instruments, not to enhance human interpretation of images.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Not applicable. The device is inherently a "human-in-the-loop" system, designed to assist surgeons during procedures by displaying tracked instruments in patient image data. Its performance is evaluated in the context of its intended use in guiding a human operator. There is no "algorithm-only" performance that would be separate from its interactive nature. The "software verification" and "mechanical tests" ensure the underlying components function correctly, but the overall "performance" is tied to its use by an operator.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- The document implies ground truth is established by the system's design specifications and verified through functional testing against these specifications. For parameters like "accurate positioning," it would presumably be measured directly against known coordinates or physical measurements on a phantom model. Ground truth is therefore based on engineering specifications and measurements on physical models/phantoms rather than medical expert consensus, pathology, or outcomes data, as this is a navigation device and not a diagnostic tool.
8. The sample size for the training set
- Not applicable / Not provided. This is a traditional image-guided surgical navigation system, not an AI/ML system that undergoes a training phase with a "training set" in the context of deep learning models. The software components are developed and verified through standard software engineering practices.
9. How the ground truth for the training set was established
- Not applicable. As this is not an AI/ML system that utilizes a training set in the conventional sense, the concept of establishing ground truth for a training set does not apply.
§ 882.4560 Stereotaxic instrument.
(a)
Identification. A stereotaxic instrument is a device consisting of a rigid frame with a calibrated guide mechanism for precisely positioning probes or other devices within a patient's brain, spinal cord, or other part of the nervous system.(b)
Classification. Class II (performance standards).