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The Righton Zoom Slit Lamp NS-2D with photo option is intended for use in eye examination of the anterior eye segment, from the cornea epithelium to the posterior capsule. It is used to aid in the diagnosis of diseases or trauma which affect the structural properties of the anterior eye segment.

The NS-2D zoom slit lamps are designed for ophthalmic observation and microphotography. These slit lamps feature zoom stereoscopic converging microscopes that can be used for ophthalmic observation. Each instrument consists primarily of the main unit and the illumination power supply unit.

The provided 510(k) summary for the Righton Zoom Slit Lamp NS-2D with option does not contain information about acceptance criteria or a study that proves the device meets specific performance criteria.

This submission focuses on establishing substantial equivalence to predicate devices. Substantial equivalence is determined by comparing the new device's intended use, technological characteristics, and safety and effectiveness to legally marketed predicate devices, rather than establishing new performance criteria through a specific study with defined acceptance criteria.

Therefore, many of your requested points cannot be answered from the provided text.

Here's a breakdown of what can and cannot be answered:

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

• Cannot be answered. The submission does not define specific acceptance criteria for performance metrics (e.g., sensitivity, specificity, accuracy) for the device itself or its imaging software. Instead, it compares the device's technical specifications to those of its predicate devices.

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

• Cannot be answered. No test set or associated data is mentioned. The submission is based on non-clinical testing and comparison to predicate devices, not a clinical study with a test set.

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):

• Cannot be answered. No ground truth establishment is described as there is no clinical test set.

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

• Cannot be answered. No adjudication method is mentioned as there is no clinical test set.

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:

• Cannot be answered. This is not an AI-assisted device, and no MRMC study is mentioned. The device is a slit lamp for ophthalmic observation and microphotogrpahy.

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

• Cannot be answered. Not applicable, as this is not an algorithm-only device. The device is a diagnostic instrument.

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

• Cannot be answered. No ground truth is described.

8. The sample size for the training set:

• Cannot be answered. No training set for an algorithm is mentioned.

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

• Cannot be answered. No training set or ground truth establishment is mentioned.

Summary of available information:

The submission focuses entirely on demonstrating substantial equivalence to existing legally marketed predicate devices by comparing their intended use and technological characteristics.

Table of Comparison (substituting "Acceptance Criteria" with "Predicate Device Specifications" as no specific acceptance criteria were provided):

Study to Prove Acceptance Criteria:
The "study" cited is a non-clinical testing results and a comparison to predicate devices, which concluded that the Righton Zoom Slit Lamp NS-2D with option and its data collection/image manipulation software are substantially equivalent to the predicate devices. This means that the device is considered safe and effective because it is similar enough to devices already legally on the market. It does not involve a specific study to meet pre-defined performance acceptance criteria as would be the case for a novel device or an AI algorithm requiring validation of diagnostic performance.

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Synergy is a comprehensive software platform intended for use in acquisition or importing, processing, measurement, analysis and storage of clinical images and videos of the eye as well as in management of patient data, diagnostic data, clinical information, reports from ophthalmic diagnostic instruments through either a direct connection with the instruments or through computerized networks.

Synergy is a software platform that collects, processes, measures, analyzes, stores, and manages patient data and clinical information. Synergy is used together with a number of computerized digital imaging devices. In addition, Synergy software collects and manages patient demographics, image data, and clinical reports from a range of approved medical devices. Synergy enables a real-time review of diagnostic patient information at a PC workstation. In addition to the desktop application, Synergy also includes an internet-browser-based user interface to allow authorized users to access, view, create reports, and analyze patient and examination data saved in a centralized database. The system utilizes dual level authentication and 128-bit encryption to ensure secure networking environment.

This 510(k) summary provides information for the Topcon Medical Systems, Inc. Synergy, an ophthalmic image management system.

Here's a breakdown of the requested information based on the provided text:

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

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

The document explicitly states: "No performance data was required or provided." Therefore, there is no test set sample size and no data provenance mentioned for a clinical performance study. The evaluation focused on software validation and verification.

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

As no performance data was provided, there was no test set and therefore no experts used to establish ground truth for a clinical performance evaluation.

4. Adjudication method for the test set

Not applicable, as no performance study with a test set was conducted.

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 MRMC comparative effectiveness study was done. The device description indicates it is a software platform for image management and analysis, not an AI-assisted diagnostic tool that would typically involve human readers.

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

No standalone performance study was done in the context of clinical accuracy or diagnostic capability, as explicitly stated: "No performance data was required or provided." The "standalone" aspect described is the software itself performing its intended functions (acquisition, processing, measurement, analysis, storage, management) rather than a diagnostic algorithm.

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

Since no performance data or clinical study was conducted, no ground truth was established or used in the context of diagnostic accuracy. The "ground truth" for the device's functionality would have been its own specifications, verified through software validation and verification.

8. The sample size for the training set

Not applicable, as this device is an image management system and not an AI/ML diagnostic algorithm that typically requires a training set for model development.

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

Not applicable, as no training set was used for an AI/ML model.

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The IMAGEnet Professional PC Software System is a software program that is intended for use in the collection, storage and management of digital images, patient data, diagnostic data and clinical information from computerized diagnostic imaging devices through direct connection with the instruments or through computerized networks. The software system is indicated for use with retinal camera or digital camera imaging devices, including retinal cameras, non-mydriatic retinal cameras, and slit lamps.

The IMAGEnet Professional PC Software System is a computerized software system that collects, stores, and manages digital images of the retina and anterior segment of the eye. The IMAGEnet Professional PC Software System is compatible with retinal camera or digital camera imaging devices, including retinal cameras, non-mydriatic retinal cameras, and slit lamps. The IMAGEnet Professional PC Software System is installed in a Windows 2000 or Windows XP Compatible PC to automate the functions of image capture, database archival of images, and image processing. The software includes optional functions that allow the user to stitch multiple images together or estimate the desired laser treatment size for photodynamic therapy (PDT). The Topcon IMAGEnet Professional PC Software System is intended as a software program for the use in the management of digital images acquired from diagnostic instruments that capture images of the retina and anterior segment of the eye.

I am sorry, but the provided text does not contain the detailed information necessary to fully answer your request. The document is a 510(k) summary for the IMAGEnet Professional PC Software System, which is a software for managing ophthalmic images.

While it mentions "Software validation testing and image capture testing were performed on the IMAGEnet Professional PC Software System" and states "Test results for the IMAGEnet Professional Software Frorem demonstrated sufficient agreement with captured images," it does not provide the specific acceptance criteria, study details, sample sizes, ground truth establishment, expert qualifications, or adjudication methods that you requested. It primarily focuses on establishing substantial equivalence to predicate devices based on intended use and basic functionality, rather than detailed performance metrics.

Therefore, I cannot extract the following information from the given text:

1. A table of acceptance criteria and the reported device performance: This information is not provided.
2. Sample sized used for the test set and the data provenance: This information is not provided.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: This information is not provided.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: This information is not provided.
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 device is for image management, not AI-assisted diagnosis, and therefore an MRMC study comparing human readers with and without AI assistance is not relevant or described.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The document describes a software system for image management, not an algorithm with standalone diagnostic performance.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): This information is not provided, as the validation focuses on capturing and managing images accurately, not diagnostic ground truth.
8. The sample size for the training set: This information is not provided.
9. How the ground truth for the training set was established: This information is not provided.

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