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OIS Symphony is a comprehensive software platform for the import, integration and review of patient data and clinical information in an eye care environment. OIS Symphony allows for the collection, management, enhancement and review of the patient demographics, image data, diagnostic data and clinical reports from a variety of medical devices through either a direct connection with the instruments or through computerized networks.

The OIS Symphony System is a software solution for the display, management, archive, interface and integration of ophthalmic device reports, images and data. OIS Symphony consists of image display via Symphony Web, Image Import via Symphony Import and integration of imaging performed in OIS WinStation.

OIS Symphony is a software solution consistent with the predicate devices listed herein, using databases for patient demographics, server and other systems of intercommunication with hospital systems via HL7 and DICOM to provide to clinicians a single image viewing and management solution of images imported from various contributing devices throughout the clinical environment.

Symphony provides the ability to review data from any network-connected computer, and is protected by appropriate security login which permits only authorized user access. Symphony uses 256 bit or greater encryption via secure socket layer (SSL) to assure a network environment which is secure.

This document describes the OIS Symphony Image Management System, a software solution for managing ophthalmic patient data and images. However, the provided text does not contain acceptance criteria for device performance or a study demonstrating that the device meets such criteria.

The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to predicate devices, rather than establishing specific performance metrics against pre-defined acceptance criteria through a formal study.

Here's what can be extracted from the provided text, and what is missing:

Missing Information:
The primary request for acceptance criteria and a study proving their fulfillment cannot be answered from this document. The document states "Final testing of OIS Symphony included various performance tests and software validation tests, designed to ensure that the device met all its functional specifications," but does not provide details on these tests, their specific acceptance criteria, or the results.

Information that can be extracted (or confirmed as absent):

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

   • Acceptance Criteria: Not provided. The document mentions "functional specifications" but does not detail them or any associated quantitative or qualitative acceptance criteria.
   • Reported Device Performance: Not provided against any specific criteria.

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

   • Sample Size (Test Set): Not mentioned.
   • Data Provenance: Not mentioned.

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):

   • Not applicable as no specific performance study with ground truth establishment is described.

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

   • Not applicable as no specific performance study with ground truth establishment 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:

   • No MRMC study is mentioned. This device is an image management system, not an AI diagnostic tool, so such a study would likely not be relevant.

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

   • Not applicable. The OIS Symphony is a software platform for data management and display, not an AI algorithm performing standalone diagnostic tasks.

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

   • Not applicable as no specific performance study with ground truth establishment is described.

8. The sample size for the training set:

   • Not applicable as this is not an AI/machine learning device that would typically have a "training set." It's a software system for data management.

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

   • Not applicable.

Summary based on the provided text:

The OIS Symphony Image Management System is a software solution for displaying, managing, archiving, and integrating ophthalmic device reports, images, and data. It functions by using databases for patient demographics, servers, and intercommunication systems via HL7 and DICOM. The manufacturer claims that the device has undergone "extensive performance testing and validation" to ensure it met "all its functional specifications." However, the document does not elaborate on these specifications, the testing methodology, the sample sizes used, or the results of these tests.

The primary method for demonstrating safety and effectiveness in this 510(k) summary is by showing substantial equivalence to existing predicate devices (Zeiss Forum, Nidek NAVIS, and Topcon Synergy), highlighting that it employs similar technological characteristics and has a comparable intended use. The FDA's letter confirms the determination of substantial equivalence.

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The OIS EyeScan Portable Modular Imaging System is a portable monocular camera intended for imaging of both the posterior segment (including structures of the retina, vitreous and choroid) and anterior segment (including structures of the orbit, lids, cornea, iris and lens) of the eye. The device is suitable for documentation of findings in a clinical setting.

OIS EyeScan is a portable, modular imaging device, which is designed to perform retinal imaging (including color, FA, FAF, Red-free) and corneal imaging (including tear film analysis, corneal fluorescences, slit). OIS EyeScan Portable Modular Imaging System, consistent with the predicate imaging devices previously listed, uses light photography to obtain clinical information. OIS EyeScan captures images using light sources (LEDs of different colors), functionally optimized lenses and filters, and digital camera sensors. OIS EyeScan uses OIS WinStation software for image capture, review and analysis. The device comprises a base unit, and interchangeable imaging modules and optional chin rest. Images may be stored on industry standard storage media.

The provided text describes the OIS EyeScan Portable Modular Imaging System, a portable monocular camera intended for imaging both the posterior and anterior segments of the eye. It is suitable for documenting findings in a clinical setting.

However, the document is a 510(k) summary, which focuses on demonstrating substantial equivalence to pre-existing predicate devices rather than proving a new device's efficacy through specific clinical performance studies with acceptance criteria, sample sizes, and ground truth methodologies.

Therefore, the requested information cannot be fully extracted as such studies are not present in this 510(k) submission.

Here's an breakdown of what can be extracted and what cannot:

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

• Acceptance Criteria: Not explicitly stated in terms of quantitative performance metrics for disease detection or diagnostic accuracy. The acceptance criteria for this 510(k) submission revolve around demonstrating substantial equivalence to predicate devices. This means the device should have similar technological characteristics, intended use, and be as safe and effective as existing legally marketed devices.
• Reported Device Performance: The document only states that the device was subjected to "extensive performance testing and validation" and that "EMC and safety tests currently underway will ensure the device complies with industry and safety standards." No specific performance metrics (e.g., sensitivity, specificity, accuracy) are reported for clinical tasks.

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

• Not applicable. This submission focuses on demonstrating substantial equivalence, not on a clinical performance study with a test set of patient data to assess diagnostic accuracy. Therefore, sample sizes and data provenance for such a test set are not mentioned.

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):

• Not applicable. As there is no clinical performance study with a "test set" of patient data to establish ground truth on, this information is not provided.

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

• Not applicable. No clinical performance study requiring adjudication 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. This document describes a new imaging system, not an AI-powered diagnostic aide designed to assist human readers. Therefore, an MRMC study comparing human readers with and without AI assistance was not performed or reported.

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

• Not applicable. This device is an imaging system, not a standalone diagnostic algorithm.

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

• Not applicable. As a clinical performance study for diagnostic accuracy is not outlined, the concept of "ground truth" for disease states is not relevant in this 510(k) summary. The "ground truth" for this submission would be adherence to functional specifications, safety standards, and equivalence to predicate devices.

8. The sample size for the training set:

• Not applicable. This device is an imaging system, not a machine learning algorithm that requires a training set of data.

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

• Not applicable. As there is no training set mentioned, this information is irrelevant.

Summary of Device Evaluation in the 510(k) Submission:

The OIS EyeScan Portable Modular Imaging System demonstrated substantial equivalence by:

• Comparative Analysis to Predicate Devices: The submission extensively compares the OIS EyeScan to several predicate devices (Topcon TRC-50EX and TRC-50IX, WinStation Digital Imaging System, IRI Integrated Retinal Imager, BX900, Tearscope Plus).
• Similarities Highlighted: The document emphasizes that the OIS EyeScan employs similar principles (light photography), light sources (LEDs instead of halogen/xenon lamps), optical specifications, image processing, and storage capabilities as the predicate devices.
• Performance Testing: While specific results are not provided, the document states the device underwent "extensive performance testing and validation" and "software validation tests" to ensure it met "all its functional specifications." This functional specification fulfillment is the closest equivalent to "acceptance criteria" in this context.
• Safety and EMC Compliance: The submission notes that EMC and safety tests were underway or completed to ensure compliance with industry and safety standards, another critical aspect of demonstrating equivalence.

Conclusion Drawn:

The conclusion drawn from the performance testing (functional and safety) and the comparison to predicate devices is that the OIS EyeScan Portable Modular Imaging System is substantially equivalent in safety and effectiveness to the listed predicate devices. This substantial equivalence is the primary "proof" provided in a 510(k) process for devices of this nature, rather than a clinical trial demonstrating specific diagnostic performance metrics against a defined ground truth.

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The WinStation Retinal Imager™ has the same intended use as other fundus cameras. It is specifically used to produce color or black and white images of the retina (fundus imaging) and anterior segment (slit lamp imaging), and fluorescein and ICG angiographic images in a non-invasive manner.

Not Found

I am sorry, but the provided text does not contain the acceptance criteria and study details you've requested regarding a medical device. The document is a 510(k) clearance letter from the FDA for the "WinStation Retinal Imager," dated October 23, 1998. It states that the device is substantially equivalent to legally marketed predicate devices and outlines the indications for use.

To answer your questions, I would need a different document, such as a summary of safety and effectiveness (SSE), a clinical study report, or similar regulatory submission details that would include:

1. Acceptance criteria and device performance: These are typically defined metrics (e.g., sensitivity, specificity, accuracy) that the device must meet, along with the reported performance values from a study.
2. Sample size and data provenance: Details about the number of cases/patients used in testing and where the data came from (e.g., country, retrospective/prospective).
3. Number and qualifications of experts for ground truth: Information about the specialists who established the correct diagnoses or measurements, including their experience levels.
4. Adjudication method for ground truth: How disagreements among experts were resolved (e.g., majority vote, senior expert decision).
5. MRMC comparative effectiveness study: If human reader performance with and without AI assistance was evaluated, and the effect size measured.
6. Standalone performance: The performance of the algorithm without human intervention.
7. Type of ground truth: How the true status of a condition was determined (e.g., pathology, clinical follow-up, expert consensus).
8. Training set sample size: The number of data points used to train the AI model.
9. Ground truth establishment for training set: How the correct labels were assigned to the training data.

The current document only provides the FDA clearance, trade name, regulatory class, product code, and a general statement of indications for use, without any performance data or study design details.

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