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The KOWA DR-1a is an ocular surface interferometer, which is an ophthalmic imaging device that is intended for use by physician in adult patients to observe and record a video image of specular (interferometric) observations of the tear film, which can be visually monitored and photographically documented.

The KOWA DR-1a is ocular surface interferometer, which is an ophthalmic imaging device that is intended for use by a physician in adult patients to observe and record a video image of specular (interferometric) observations of the tear film, which can be visually monitored and photographically documented. This instrument is intended to observe and record a video of the interference image with illuminating white light on the tear film layer. Users can replay the recorded image on the instrument's monitor to observe the condition of the tear film layer. In addition, using the image currently being replayed, users can measure the duration time by specifying 2 different point of time. This instrument has a function that allows users to output a video or a still image clipped from the video to an external personal computer.

Here's an analysis of the acceptance criteria and study proving the device meets them, based on the provided text, categorized by your requests.

Important Note: The provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device for regulatory clearance. It is not a detailed clinical study report designed to prove clinical accuracy or effectiveness of an AI algorithm in the specific ways you requested (e.g., MRMC study, standalone performance, expert consensus as ground truth for AI model). The KOWA DR-1a is an ophthalmic camera, and the performance data presented primarily focuses on its physical and optical characteristics compared to the predicate, and safety/electrical/biocompatibility testing. There is no mention of an AI component in this device or its performance evaluation. Therefore, many of your questions related to AI performance, such as sensitivity, specificity, MRMC studies, or training/test set ground truth for AI, cannot be answered from this document.

Acceptance Criteria and Device Performance (Based on Device Characteristics and Comparative Testing, Not AI Performance)

1. Table of acceptance criteria and the reported device performance

Since this is a substantial equivalence submission for an ophthalmic camera and not an AI algorithm, the "acceptance criteria" are generally that the new device is as safe and effective as the predicate, with no new safety or effectiveness concerns. The performance data presented focuses on physical and optical characteristics.

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

• Sample Size for Comparative Testing: Not explicitly stated with patient numbers. The performance comparison refers to "Test was performed to evaluate performance of the KOWA DR-1a compared to the LipiView regarding Illumination area, Image resolution and Interference image." It doesn't specify if this involved human subjects or just device measurements.
• Sample Size for Repeatability: "The repeatability was investigated by comparing the hue values measured with three units of DR-1α and by three examiners. Each measurement was repeated 5 times." This refers to device measurements, not a patient test set.
• Data Provenance: The document is a 510(k) submission from Kowa Company, Ltd. in Japan. The testing described would typically be conducted by the manufacturer in a controlled environment. The document does not specify country of origin for any "test set" and given it's a device performance study for substantial equivalence, it's unlikely to involve large-scale retrospective or prospective patient data in the way an AI algorithm study would.

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

• This device is an ophthalmic camera. The performance tests described relate to its physical and optical characteristics (e.g., image resolution, illumination, repeatability of hue values) and safety. There is no mention of "ground truth" in the context of clinical interpretation by experts because the device itself does not provide a diagnosis or interpretation that would require clinical ground truth for validation in this submission.
• For the repeatability test, "three examiners" were used. Their qualifications are not specified, but they would likely be trained operators or engineers.

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

• Adjudication methods like 2+1 or 3+1 are typically used in clinical studies where multiple human readers interpret medical images and their consensus or a tie-breaker establishes a "ground truth" for disease presence/absence or findings.
• Not applicable for the device performance tests described in this 510(k) summary, as it does not involve clinical interpretation or a "test set" requiring adjudication of clinical findings.

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

• An MRMC study is designed to evaluate the impact of a new technology (like AI) on physician performance.
• No MRMC study was performed or needed for this 510(k) submission, as the KOWA DR-1a is an ophthalmic camera and the document does not indicate it incorporates an AI component influencing clinical decision-making or diagnosis. The focus is on the device's ability to capture images.

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

• This question pertains to the performance of an AI algorithm independent of human interaction (e.g., its sensitivity, specificity, AUC for a diagnostic task).
• Not applicable. The KOWA DR-1a is an ophthalmic camera. The document does not describe any standalone AI algorithm for interpretation or diagnosis.

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

• As explained above, the "ground truth" concept (e.g., for disease diagnosis) is not relevant to the performance tests reported here.
• The reported performance tests rely on technical measurements and compliance with established standards:
  • Illumination area and image resolution are measured specifications.
  • Repeatability is assessed against an "acceptance range" for hue values (an objective measurement).
  • Safety checks (optical radiation, EMC, electrical, biocompatibility) are assessed against specific industry and regulatory standards.

8. The sample size for the training set

• This question applies to AI/machine learning models.
• Not applicable. This document is for the clearance of an ophthalmic camera and does not describe the development or validation of an AI algorithm, thus there is no "training set."

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

• This question applies to AI/machine learning models.
• Not applicable. As there's no mention of an AI model or training set, this information is not provided.

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The CenterVue EIDON FA is a confocal scanning ophthalmoscope indicated for color, infrared and autofluorescence imaging and fluorescein angiography of a human retina with or without the use of a mydriatic agent.

The CenterVue EIDON FA has been derived from the CenterVue EIDON, a retinal imaging device cleared under K142047. EIDON FA is a scanning ophthalmoscope which uses LED light to capture confocal images of the retina. In particular, EIDON FA uses infrared light to obtain infraredreflectance images, white light to obtain color images and blue light to obtain auto-fluorescence and fluorescence images. EIDON FA can be used with or without pharmacological dilation.

The CenterVue EIDON FA is part of a family of devices, which includes three models: EIDON FA, EIDON AF, and EIDON. EIDON is the base model, which features the following imaging modalities: infrared reflectance, color and red-free. EIDON AF adds autofluorescence imaging to the base model. The EIDON FA is the fully featured device, which adds fluorescein angiography to the capabilities of the EIDON AF and encompasses the features and functionality of the other models.

EIDON FA operates as a standalone unit, running a dedicated software application, is intended for prescription use only, and includes:

1. an optical head, including a removable lens cap;
2. a patient head-rest, including a removable front-rest;
3. a patient chin rest;
4. a base, including a touch-screen device (tablet with magnetic holder and USB cable), USB joystick and an external power supply.

EIDON FA operates based on the following principles:
a) An illumination system consisting of an infrared (IR) LED (825-875 nm and 940 nm), a white LED (440-650 nm), a blue LED (440-475 nm) and a green LED, illuminates the patient eye with the following functions:

• the IR LED with central wavelength at 850 nm allows the capture of IR photos. The patient's retina is uniformly illuminated by a line in a horizontal direction. Along the optical path there is an oscillating mirror which scans the line in order to illuminate the retina with a field of view of 60°.
• Two IR LEDs with central wavelength at 940 nm are seen from the eye in a free viewing system. The two LEDs are equally shifted with respect to the machine's optical axis. The LEDS are switched on during all exams in order to enable pupil tracking.
• The white and blue LEDs allow the capture of color photos. The retina is uniformly illuminated by a line in the horizontal direction. Along the optical path an oscillating mirror scans the line in order to illuminate the retina with a field of view of 60°.
• The blue LED is also used to capture auto-fluorescence and fluorescence retinal images;
• The green LED is used as fixation target.
  b) An imaging system including a barrier filter (high-pass with a cutoff at 500 nm) stops back reflected light from the retina and allows fluorescent light to be detected for imaging. A focusing lens is included in the imaging path to achieve optimal focusing on a CMOS camera.
  c) An anterior segment alignment system is included, using two cameras and the two IR LEDs. The LEDs illuminate the anterior segment by diffusion, whereas allow a stereoscopic reconstruction of the pupil's position to be obtained with respect to the instrument's front lens.

EIDON FA interacts with the patient by directing infrared, white, blue (for imaging) and green (for fixation) illumination into the patient's eye. The chin-rest and head-rest are the only parts of the device that contact the patient. The chin-rest includes a patient proximity sensor and is motorized for height adjustment.

The provided text describes the regulatory information and technical specifications of the CenterVue EIDON FA device, focusing on its substantial equivalence to predicate devices for FDA clearance. However, it does not contain specific acceptance criteria, comprehensive study details, or performance data in the structured format requested. The clinical performance data section is very brief and high-level.

Therefore, I cannot fully complete the requested table and answer all points accurately based solely on the provided text. I will extract and present the available information, and explicitly state where information is missing.

Acceptance Criteria and Device Performance Study for CenterVue EIDON FA

The provided documentation describes the CenterVue EIDON FA as a confocal scanning ophthalmoscope indicated for color, infrared, autofluorescence imaging, and fluorescein angiography of the human retina. The substantial equivalence determination relies on comparisons to predicate devices (CenterVue EIDON, Kowa VX-20, and Heidelberg Spectralis HRA²).

1. Table of Acceptance Criteria and Reported Device Performance

Based on the provided text, the acceptance criteria are not explicitly stated as numerical thresholds or specific performance metrics. Instead, the focus is on demonstrating "substantial equivalence" to predicate devices, particularly regarding imaging capability and safety. The performance is reported qualitatively.

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

• Sample Size: The document states, "Images of eyes with and without diagnosed pathology were included in the comparison." However, it does not specify the number of images or patients used in the clinical comparison.
• Data Provenance: Not explicitly stated (e.g., country of origin). The study implicitly appears to be retrospective, as it involves comparing EIDON FA images with existing images from predicate devices.

3. Number of Experts Used to Establish Ground Truth and Qualifications

• Number of Experts: This information is not provided in the document.
• Qualifications of Experts: This information is not provided in the document. The assessment is described as a "comparison" of images, but who performed this comparison (e.g., a panel of ophthalmologists/radiologists or internal staff) and their qualifications are not detailed.

4. Adjudication Method for the Test Set

• The document does not describe any specific adjudication method (e.g., 2+1, 3+1) for the clinical image comparison. The assessment seems to be a general comparison.

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

• No, a MRMC study comparing human readers with and without AI assistance was not mentioned or performed. This submission is for an imaging device, not an AI-powered diagnostic algorithm designed to assist human readers. The clinical performance data section describes a comparison of image quality between the EIDON FA device and predicate devices.

6. Standalone (Algorithm Only) Performance

• This question is not applicable as the EIDON FA is an imaging device, not an AI algorithm. Its "performance" refers to the quality of the images it produces, which are then interpreted by a human clinician.

7. Type of Ground Truth Used

• The "ground truth" for the clinical comparison was implicitly the diagnosed pathology of the eyes. The study included "images of eyes with and without diagnosed pathology." The comparison was about the similarity of images captured by EIDON FA to those from predicate devices, rather than a direct diagnostic accuracy assessment against a gold standard for a specific condition.

8. Sample Size for the Training Set

• This question is not applicable, as the device is an imaging system and not an AI algorithm that requires a training set in the typical machine learning sense. The "training" of the device is its manufacturing and calibration process, not data-driven machine learning.

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

• This question is not applicable for the same reason as point 8.

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