Search Results

The SpineAssist System is indicated for precise positioning of surgical instruments during spinal stabilization surgery. The device enables pre-operative planning of the surgical procedure and subsequent spatial positioning and orientation of the surgical tool during intra-operative procedures.

The Hover-T Bridge accessory used in conjunction with the SpineAssist device for minimally invasive surgical procedures, is intended for use for lumbar spinal fusion stabilization surgery.

The SpineAssist device developed by Mazor Surgical Technologies is an accurate imageguided positioning system that extends surgical capability in terms of precision, miniaturization and accessibility. The SpineAssist surgical positioning system assists the surgeon in the operating room to accurately position hand held surgical tools according to a computerized image-based pre-operative plan and to accurately guide surgical tools along given trajectories. The system's software processes fluoroscopic and CT images via proprietary algorithms and automatically exports the desired coordinates to the SpineAssist Device, which positions its articulating arm and tool guide. Using the Hover-T kit, a special bone attachment component, the SpineAssist device attaches to the bone on which the procedure is being performed and assists surgeons in precisely guiding handheld surgical tools in line with the computerized, image-based, pre-operative plan.

The provided text describes the SpineAssist System and its clearance as a medical device, but it does not contain the detailed information necessary to fully answer all aspects of your request regarding acceptance criteria and a study proving device performance.

Specifically, the document is a 510(k) premarket notification approval. While it confirms the device's intended use and substantial equivalence to a predicate device, it does not include a dedicated section detailing specific acceptance criteria for performance, nor does it outline the methodology, results, and detailed characteristics of a study designed to prove the device meets such criteria.

Therefore, I can only provide information based on what is available in the document.

Here's an attempt to answer your questions to the best of my ability with the provided text, while also explicitly stating what information is not available:

1. A table of acceptance criteria and the reported device performance

This information is not provided in the given document. The 510(k) summary focuses on substantial equivalence to a predicate device rather than presenting a performance study against specific acceptance criteria.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

This information is not provided in the given document. The document refers to the device's "precision" and "accuracy" as part of its technological characteristics, but it does not detail any specific test set, its sample size, or its provenance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

This information is not provided in the given document. As no specific performance study with a test set is detailed, information about ground truth establishment or experts is absent.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

This information is not provided in the given document.

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

This information is not provided in the given document. The device assists surgeons in positioning tools; it's not described as an AI diagnostic or interpretive tool where "human readers" would be a relevant metric for improvement with AI assistance.

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

This information is not explicitly detailed in the given document. The description states the device "assists the surgeon" and "guides surgical tools," implying a human-in-the-loop system. While it has proprietary algorithms for image processing and coordinate export, a standalone performance evaluation of the algorithms completely independent of human interaction is not described.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

This information is not provided in the given document.

8. The sample size for the training set

This information is not provided in the given document. The document mentions "proprietary algorithms" and processing of images but does not delve into the development or training of these algorithms.

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

This information is not provided in the given document.

Ask a specific question about this device

The SpineAssist is indicated for precise positioning of surgical instruments during spinal fusion stabilization surgery. The device enables pre-operative planning of the surgical procedure and subsequent spatial positioning and orientation of the surgical tool during intra-operative procedures.

The SpineAssist device is a computer controlled miniature medical image-guided surgery (IGS) system which serves as a technological platform for solutions that provide unprecedented levels of accuracy, precision and accessibility in performing orthopedic procedures. The SpineAssist is designed to assist surgeons in precisely guiding handheld surgical tools in line with a computerized, image-based preoperative plan along given trajectories. The system's software processes fluoroscopic and CT images via proprietary algorithms and automatically exports the desired coordinates to the MSG, which positions its articulating arm and tool guide. Through the bone-attaching procedure, the SpineAssist device attaches to the bone on which the procedure is being performed and assists surgeons in precisely guiding handheld surgical tools in line with the computerized, image-based, pre-operative plan.

The main components of the SpineAssist device include:

• A. Planning System;
• B. Workstation; and
• C. Miniature Surgical Guidance System MSG

The provided text describes the SpineAssist Device, a surgical navigation system, and its 510(k) clearance. However, it does not contain specific acceptance criteria, detailed study designs with sample sizes for test sets, expert qualifications, adjudication methods, or quantitative performance metrics regarding accuracy or clinical outcomes directly. The content focuses on regulatory compliance, intended use, and comparison to predicate devices, rather than a detailed performance study report.

Therefore, many of the requested details cannot be extracted directly from the provided text. I will provide what can be inferred or explicitly stated.

Description of the Acceptance Criteria and Device Performance

The document indicates that testing was performed to assure compliance with various standards and to validate the accuracy and repeatability of the device. However, specific numerical acceptance criteria for accuracy and repeatability are not provided in the text, nor are the detailed reported device performance values against such criteria.

The acceptance criteria implied are primarily related to:

• Electrical Safety: Compliance with EN 60601-1.
• Electromagnetic Compatibility: Compliance with EN 60601-1-2.
• Software Validation: Compliance with IEC 60601-1-4 and FDA Guidance for Software in Medical Devices.
• Accuracy and Repeatability: These were "performed to validate," but no specific quantitative thresholds or results are given.

Since no specific performance data or acceptance criteria are listed, the table below will reflect the general statements made in the document.

1. Table of Acceptance Criteria and Reported Device Performance

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

The document states that "Additional device performance tests were performed to validate the accuracy and repeatability of the device." However, the sample size used for these tests (e.g., number of procedures, patients, or data points) and the data provenance (e.g., country of origin, retrospective/prospective) are not mentioned in the provided text.

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

This information is not provided in the text. The document describes a technical device for surgical guidance but does not detail studies involving human-expert-established ground truth for a test set.

4. Adjudication Method for the Test Set

This information is not provided in the text.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No MRMC comparative effectiveness study is mentioned in the provided text. The document does not describe human readers using or not using the AI to assess an outcome, nor does it discuss an effect size for human improvement. The device is purely a surgical guidance system, not an AI for image interpretation that would typically require MRMC studies.

6. Standalone Performance Study (Algorithm Only Without Human-in-the-Loop Performance)

The document mentions that "Tests were also carried out to satisfy the requirements... Additional device performance tests were performed to validate the accuracy and repeatability of the device." This implies standalone technical performance testing of the device's accuracy and repeatability, separate from human performance. However, specific metrics and results of this standalone performance are not quantitatively detailed.

7. Type of Ground Truth Used

Given that the performance tests mentioned are for "accuracy and repeatability," the ground truth for these tests would likely involve physical measurements and engineering tolerances rather than expert consensus, pathology, or outcomes data in a clinical sense. For example, accuracy could be measured against a known physical target, and repeatability by measuring multiple attempts to reach the same target. However, the exact nature of the ground truth is not explicitly stated.

8. Sample Size for the Training Set

This information is not provided in the text. The document does not describe a machine learning model requiring a training set in the conventional sense. The "proprietary algorithms" process fluoroscopic and CT images, but the specifics of their development and training data are not disclosed.

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

Since there is no information on a specific training set or a machine learning model detailed for, this information is not provided in the text.

Ask a specific question about this device