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510(k) Data Aggregation
(106 days)
VISULAS green is intended for use in photocoagulating ocular tissues of the treatment of diseases of the eve, including
- · Photocoagulation of the retina
- Trabeculoplasty
- · Iridotomy
VISULAS green is an ophthalmic laser used for standard photocoagulation treatments of ocular tissue with 532 nm wavelength. VISULAS green is operated in single-spot mode or in multi-spot mode.
VISULAS green consists of a laser console, touch control panel, optional laser light applicators such as laser slit lamp or laser indirect ophthalmoscope, foot switch and instrument table. The device can also be used with various accessories, such as SL Imaging Solution, contact lenses or Applanation Tonometer.
The provided FDA 510(k) summary for the VISULAS green device (K232051) focuses on establishing substantial equivalence to a predicate device (VISULAS green, K181682) rather than presenting a study demonstrating the device meets a specific set of clinical performance acceptance criteria. Therefore, much of the requested information regarding a comparative effectiveness study, standalone performance, ground truth, and expert involvement is not present in this document.
However, I can extract information about the types of testing performed and the general conclusion of substantial equivalence.
1. Table of Acceptance Criteria and Reported Device Performance
The document does not specify quantitative acceptance criteria for clinical performance that the device was tested against. Instead, it states that the device underwent various forms of testing to demonstrate equivalence and compliance with standards.
| Type of Testing/Evaluation | Acceptance Criteria (Implicit) | Reported Device Performance |
|---|---|---|
| Biocompatibility | Align with current recognized standards; meet or exceed testing performed on the predicate device. | Biocompatibility testing demonstrated equivalency between the subject device and the predicate device. |
| Laser Safety | Compliance with ANSI/AAMI ES60601-1, ANSI Z80.36, IEC 60825-1, IEC 60601-2-22. | VISULAS green was found to comply with ANSI/AAMI ES60601-1:2005/(R) 2012, ANSI Z80.36-2016, IEC 60825-1:2007, IEC 60601-2-22:2012. |
| Electrical Safety | Compliance with ANSI/AAMI ES60601-1. | VISULAS green was found to comply with ANSI/AAMI ES60601-1:2005/(R) 2012. |
| Electromagnetic Compatibility (EMC) | Compliance with IEC 60601-1-2. | VISULAS green was found to comply with IEC 60601-1-2:2014. |
| Battery Safety | Compliance with IEC 62133. | VISULAS green was found to comply with IEC 62133: 2012 (likely related to any rechargeable components). |
| Software Verification & Validation | Adherence to FDA's "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices"; works as designed. | Software verification and validation testing was conducted, and documentation was provided. Verification and validation of VISULAS green demonstrated that the product works as designed. |
| Bench Testing (Functional & System-level) | Meet defined system specifications. | Non-clinical system testing provided an evaluation of the system relevant to each of the system specifications. The functional and system level testing showed that the system met the defined specifications. ZEISS demonstrated non-clinical equivalency between the subject device and the predicate device. |
| Overall (Substantial Equivalence) | Similar in technological characteristics, performance, principles of operation, and identical indications for use as the predicate device; no new issues of safety or effectiveness. | The VISULAS green is substantially equivalent to the predicate device, VISULAS green (K181682). Differences do not raise any new issues of safety or effectiveness. |
2. Sample size used for the test set and the data provenance
Not applicable. The document describes engineering and software verification and validation, as well as biocompatibility testing, but does not detail a clinical test set for evaluating device performance against diseases of the eye. The focus is on demonstrating equivalence to a predicate device through technical specifications and non-clinical testing.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not applicable. As no clinical test set is described, there's no mention of experts establishing a ground truth for such a set.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable. No clinical test set is described.
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
Not applicable. The device (VISULAS green) is an ophthalmic laser for photocoagulation, not an AI-powered diagnostic or assistive tool for human readers. Therefore, an MRMC study comparing human reader performance with and without AI assistance is not relevant to this device's submission.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. The VISULAS green is a medical device (laser system), not a standalone algorithm. Its performance is inherent to its physical operation and interaction with ocular tissues, guided by a human operator.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
For the technical testing detailed (biocompatibility, safety, software, bench testing), the "ground truth" would be the established engineering specifications, recognized industry standards, and the performance characteristics of the predicate device. No clinical "ground truth" (e.g., pathology, outcomes) is described as being directly used to measure the subject device's efficacy in treating specific diseases in a clinical study.
8. The sample size for the training set
Not applicable. This device is a laser system, not an AI/ML algorithm that requires a training set of data.
9. How the ground truth for the training set was established
Not applicable. This device is a laser system, not an AI/ML algorithm.
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(253 days)
VISULAS green is intended for use in photocoagulation of tissues in the posterior and anterior segments of the eye including trabeculoplasty and iridotomy.
VISULAS green is an ophthalmic laser with a 532 nm wavelength used for standard photocoagulation treatments of ocular tissue. VISULAS green is operated in single-spot mode or in multi-spot mode.
VISULAS green consists of a laser console, touch control panel, optional laser light applicators such as laser slit lamp or laser indirect ophthalmoscope, foot switch and instrument table. The device can also be used with various accessories, such as laser endoprobes, or the SL cam 5.0.
The provided document is a 510(k) premarket notification for the VISULAS green ophthalmic laser system. It describes the device, its intended use, and a comparison to a predicate device (VISULAS 532s Laser System).
It is crucial to understand that this document does not describe a study involving an AI/machine learning device or a comparative effectiveness study with human readers assisting AI. This 510(k) submission is for a conventional medical device (a laser system) and focuses on demonstrating substantial equivalence to a legally marketed predicate device based on technological characteristics, safety standards, and intended use.
Therefore, many of the requested points regarding acceptance criteria and studies for AI/ML performance, such as sample sizes for test sets, data provenance, expert ground truth establishment, adjudication methods, multi-reader multi-case studies, standalone algorithm performance, and training set details, are not applicable to this document as it does not concern an AI/ML device.
However, I can extract information related to the acceptance criteria and performance data for this specific medical device as presented in the document:
1. A table of acceptance criteria and the reported device performance
Based on the document, the "acceptance criteria" are not framed as quantitative performance metrics for a diagnostic or AI device. Instead, they are compliance with established safety and performance standards for a laser system and demonstration of substantial equivalence to a predicate device.
| Acceptance Criterion (Compliance with Standards/Equivalence to Predicate) | Reported Device Performance/Compliance |
|---|---|
| Biocompatibility | Materials and manufacturing are identical to the predicate device and currently marketed devices. No new biocompatibility testing needed. |
| Laser Safety | Complies with: - IEC 60825-1:2007 - IEC 60601-2-22:2012 |
| Electrical Safety | Complies with: - ANSI/AAMI ES60601-1:2005/(R)2012 - IEC 60601-1-2:2014 - IEC 62133: 2012 |
| Electromagnetic Compatibility (EMC) | Complies with: - IEC 60601-1-2:2014 |
| Software Verification & Validation | Software is considered "Major" level of concern. Verification and validation testing conducted as per FDA guidance. Documentation provided. Device works as designed. |
| Technological Equivalence to Predicate (VISULAS 532s) | Same laser type (solid state, frequency-doubled), wavelength (532 nm), power range (50-1500 mW), pulse length (10-2500 ms and cw), repeat mode, laser spot size settings (50-1000 µm), aiming beam (620-650 nm), types of laser applicators, and multi-spot treatment mode. |
| Indications for Use Equivalence to Predicate | VISULAS green is intended for use in photocoagulation of tissues in the posterior and anterior segments of the eye, including trabeculoplasty and iridotomy. This is within the same intended use as the predicate and does not raise different questions of safety and effectiveness. |
| Principle of Operation Equivalence to Predicate | Both devices operate on the principle of photocoagulation (continuous wave operation where thermal energy from laser absorption causes coagulation). |
2. Sample size used for the test set and the data provenance
- Not applicable. This submission is for a conventional laser device, not an AI/ML diagnostic. Performance was demonstrated through compliance with recognized standards and comparison to a predicate, not through a clinical test set of patient data.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- Not applicable. No test set requiring expert ground truth for an AI/ML diagnostic was performed or described.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not applicable. No test set requiring adjudication was performed or described.
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. An MRMC study was not done because this is not an AI-assisted device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- No. This is not an algorithm-only device. It is a physical laser system.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Not applicable. As a conventional laser device, the "ground truth" related to its performance is established by its compliance with industry safety standards (e.g., laser power output accuracy, electrical safety, EMC) and demonstration that its operating principles and technological characteristics are equivalent to a well-established predicate device. There is no diagnostic "ground truth" for patient data in this context.
8. The sample size for the training set
- Not applicable. This device does not involve a training set as it is not an AI/ML device.
9. How the ground truth for the training set was established
- Not applicable. This device does not involve a training set.
In summary, the provided document is a 510(k) premarket notification for a Class II ophthalmic laser device. The "acceptance criteria" and "study" described pertain to demonstrating safety, functional performance, and substantial equivalence to a predicate device, primarily through compliance with established industry standards (e.g., IEC, ANSI) and direct comparison of technical specifications. It does not involve AI/ML technology, and therefore, many of the questions related to AI device performance evaluation are not relevant to this submission.
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