Search Results

The Spectral OCT/SLO is a non-contact, high-resolution non-invasive tomographic and confocal imaging device. It is indicated for in vivo viewing, axial cross-sectional, and three-dimensional imaging and measurcment of posterior ocular structures including: retina, macula, retinanserve fibre layer and optic disk. It is used as a diagnostic device to aid in the detection and management of ocular diseases affecting the posterior segment of the eye. In addition, corners and conjunctiva can be imaged with the system by changing the focal position.

The OPKO/OTI Spectral OCT/SLO is a computerized instrument that employs non-invasive, low-coherence interferometry to acquire simultaneous highresolution cross-sectional OCT (Optical Coherence Tomography) and confocal images of ocular structure, including retina, retinal nerve fiber layer, macula and optic disc of the eye.

The provided 510(k) summary for the OPKO/OTI Spectral OCT/SLO outlines certain performance data, but it does not specify formal acceptance criteria or a detailed study proving the device unequivocally meets such criteria in terms of diagnostic accuracy or clinical utility. Instead, the submission focuses on demonstrating substantial equivalence to predicate devices, particularly regarding measurement precision and agreement.

Here's an analysis based on the provided text, addressing your specific points:

1. Table of Acceptance Criteria and Reported Device Performance

Formal acceptance criteria (e.g., minimum sensitivity, specificity, or specific limits of agreement for clinical tasks) are not explicitly stated in the provided document. The performance evaluation primarily focuses on direct comparison with predicate devices for specific measurements.

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

• Sample Size: Thirty-six (36) subjects.
• Data Provenance:
  • Country of Origin: Not specified in the provided text.
  • Retrospective or Prospective: Prospective comparative study.

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

The document does not specify the use of "experts" to establish a ground truth for diagnostic accuracy, sensitivity, or specificity. The study described is a comparative one focusing on the precision and agreement of measurements of retinal, RNFL thickness, and optic nerve disc ratio between the new device and a predicate device. Ground truth for these measurements would typically be derived directly from the device's output, not independent expert interpretation in the way you might assess a diagnostic algorithm.

4. Adjudication Method for the Test Set

This information is not provided as the study design focuses on direct comparison of measurements rather than adjudicating diagnostic interpretations.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done

No, an MRMC comparative effectiveness study, as typically understood for evaluating reader performance with and without AI assistance for diagnostic tasks, was not conducted according to this document. The study described is a direct comparison of the device's measurements to a predicate device, not an evaluation of human readers' diagnostic performance.

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

The device itself is a measurement and imaging tool, not an AI algorithm that produces a diagnostic output in isolation. The "algorithm" here refers to the device's internal processing for image acquisition and measurement. The non-clinical tests included "software validation tests," but this is not equivalent to a standalone performance study for a diagnostic AI algorithm. The clinical test evaluated the device's performance in generating specific measurements.

7. The Type of Ground Truth Used

For the measurements evaluated (retinal, RNFL thickness, and optic nerve disc ratio), the "ground truth" was effectively established by the predicate device (Zeiss Stratus OCT), meaning the study sought to show that the new device's measurements correlated well with and were as precise as the existing, legally marketed device. The study's conclusion explicitly states, "The regression analysis between the measurements are substantially equivalent between the test and the legally marketed predicate devices." This implies that the predicate device served as the reference point for measurement comparison.

8. The Sample Size for the Training Set

The document does not mention a "training set" in the context of an AI/machine learning algorithm. The device, an OCT/SLO system, uses established physical principles (interferometry) and image processing, not a machine learning model that requires a discrete training phase with labeled data.

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

As no training set (for a machine learning algorithm) is mentioned, this information is not applicable. The device's functionality relies on its optical and software design, validated through tests like accuracy, optical emissions, image comparison, and specifically, software validation.

Ask a specific question about this device