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The Mydriatic Hyperspectral Retinal Camera (MHRC-C1) is intended to capture images of the retina at multiple wavelengths (colors) under mydriatic conditions.

The Mydriatic Hyperspectral Retinal Camera (MHRC-C1) is a mydriatic fundus camera (also called retinal camera) that presents eye care practitioners (optometrists and ophthalmologists) with a series of 92 images of the retina obtained sequentially at specific wavelengths (colors) in the spectral range 905 nm to 450 nm in steps of 5 nm.

Pictures of the retina are obtained on a field-of-view of 31.5° without contact with the eye. The patient is positioned in front of the device with the chin on the chinrest and forehead on the forehead rest and a positioning system is used to align the camera relative to the patient's eye. An external fixation target is available to guide the patient's eye. A focus wheel allows for the accommodation for eye refractive error in the range of -15 to +15 diopters. The images are displayed on a monitor and can be saved on the computer for future consultation.

The illumination light of the MHRC-C1 is provided by a Tunable Laser Source (TLS). The TLS selects a narrow band of light from a broadband white illumination source. Only a single monochromatic band can output the TLS at a time. The alignment of the retinal camera relative to the patient's eye phase is performed with the illumination light set at a wavelength of 700 nm. The image acquisition phase consists of the sequential acquisition of a series of 92 monochromatic images at wavelengths from 905 nm to 450 nm in steps of 5 nm. Each frame is captured with an exposure time of 10 ms, resulting in a total acquisition time of 920 ms.

The 92 images can be visualized one by one in the MHRC-C1 acquisition software. The retinal images captured by the MHRC-C1 are monochromatic images having a spectral bandwidth of ~10 nm centered on the wavelength indicated in the upper left corner of the visualization pane, with a spectral accuracy of 7.5 nm.

This document is a 510(k) summary for the Optina Diagnostics Mydriatic Hyperspectral Retinal Camera (MHRC-C1). It describes the device's characteristics and the performance testing conducted to support its substantial equivalence to predicate devices. However, it does not contain the level of detail typically found in a full clinical study report that would include direct acceptance criteria and detailed study results for an AI-powered device.

Based on the provided text, the MHRC-C1 is an ophthalmic camera intended to capture images of the retina at multiple wavelengths (colors) under mydriatic conditions. It is not described as an AI-powered device; rather, it is a hardware device for image capture. Therefore, many of the requested criteria, such as "effect size of how much human readers improve with AI vs without AI assistance" or "standalone (i.e. algorithm only without human-in-the loop performance)", are not applicable to this specific device as presented in the summary.

The acceptance criteria and performance data described in this document relate to the camera's ability to capture images accurately and reliably, rather than the performance of an AI algorithm on those images.

Here's an analysis of the provided information relative to your request, noting where the information is not present or applicable:

Acceptance Criteria and Device Performance

Since this is a fundus camera and not an AI/algorithm-based diagnostic device, the acceptance criteria are related to the physical performance of the camera itself.

Study Information

1. Sample sizes used for the test set and the data provenance:

   • The document describes performance testing on the device itself (e.g., electrical safety, spectral accuracy with a spectrometer and eye model) rather than a clinical study evaluating its diagnostic performance on human subjects or clinical images.
   • Therefore, there is no "test set" of patient data in the sense of a clinical validation dataset for an AI algorithm. The testing involves physical measurements and eye models.
   • Data provenance: Not applicable in the context of clinical image data. The testing was done on the device and its components.

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

   • Not applicable as this is a camera, not an AI diagnostic device requiring expert interpretation of a clinical test set. The ground truth for the device's technical specifications (e.g., spectral accuracy, electrical safety) would be established by engineering and metrology standards, not clinical experts for diagnostic accuracy.

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

   • Not applicable for the reasons stated above.

4. 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. This device is a fundus camera, primarily a hardware image acquisition device, not an AI diagnostic tool designed to assist human readers. The document does not describe any AI component or human reader study.

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

   • No. This is not an algorithm. It's a camera.

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

   • The ground truth for the device's performance relates to engineering specifications and recognized consensus standards (e.g., ISO, ANSI IEC standards for ophthalmic cameras, electrical safety, biocompatibility, and spectral accuracy measurements using laboratory equipment like spectrometers and eye models). It is not clinical ground truth derived from expert consensus, pathology, or outcomes data.

7. The sample size for the training set:

   • Not applicable, as this is a hardware device, not an AI algorithm requiring a training set of data.

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

   • Not applicable for the reasons stated above.

In summary: The provided document is an FDA 510(k) summary for a Mydriatic Hyperspectral Retinal Camera, which is a hardware device for capturing images. It details the device's safety and effectiveness in performing its intended function of image acquisition by demonstrating compliance with various engineering and safety standards. It does not describe an artificial intelligence (AI) component or any clinical studies validating diagnostic performance based on image analysis (whether by AI or human readers). Therefore, many of the specific questions about AI acceptance criteria, training/test sets, expert adjudication, and MRMC studies are not addressed because they are not relevant to the type of device described.

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The Topcon DRI OCT Triton is a non-contact, high resolution tomographic and biomicroscopic imaging device that incorporates a digital camera for photographing, displaying and storing the retina and surrounding parts of the eye to be examined under Mydriatic and non-Mydriatic conditions.

The DRI OCT Triton is indicated for in vivo viewing, axial cross sectional, and three-dimensional imaging and measurement of posterior ocular structures, including retinal nerve fiber layer, macula and optic disc as well as imaging of anterior ocular structures.

It also includes a Reference Database for posterior ocular measurements which provide for the quantitative comparison of retinal nerve fiber layer, optic nerve head, and the human retina to a database of known normal subjects. The DRI OCT Triton is indicated for use as a diagnostic device to aid in the diagnosis, documentation and management of ocular health and diseases in the adult population.

The DRI OCT Triton ("Triton") and the DRI OCT Triton (plus)") are non-contact, highresolution, tomographic and bio-microscopic imaging systems that merge optical coherence tomography (OCT) and fundus camera into a single device. Triton and Triton (plus) employ the swept source OCT (SS-OCT) technology. Both can take anterior OCT images in addition to fundus OCT images. The fundus camera, in both Triton and Triton (plus), includes color imaging, red-free imaging, and infrared light imaging (hereinafter, IR imaging) capabilities for fundus observation. The Triton (plus) has fluorescein angiography (FA), and fundus autofluorescence angiography (FAF) imaging function in addition to all fundus functions for Triton.

The fundus photographs and OCT images are captured by different system components of this device, which enables Triton to capture an OCT image and a fundus image sequentially. It allows in vivo viewing, axial cross sectional, and three dimensional imaging and measurement of posterior ocular structures, including retinal nerve fiber layer, macula and optic disc as well as imaging of anterior ocular structures. It also has a reference database for posterior ocular measurements of normal subjects, which provide for the quantitative comparison of retinal nerve fiber layer, optic nerve head and the macula.

Captured images are transferred from the device to an off-the-shelf personal computer (PC) via LAN cable, where the dedicated software for this device is installed. The transferred data is then automatically processed with analysis functions such as the automatic retinal layers segmentation, the automatic thickness calculation with several grids, the optic disc analysis and comparison with a reference database of eyes free of ocular pathology, and is finally automatically saved to the PC. It allows the user to manually adjust the automated retinal layer segmentation results and optic disc analysis results.

Accessories include the power cord, chin-rest paper sheet, monitor cleaner, LAN cable; chin-rest paper pins, external fixation target, dust cover accessory case, user manual, unpacking and analysis software DVD.

The Topcon DRI OCT Triton is a non-contact, high-resolution tomographic and biomicroscopic imaging device that incorporates a digital camera for photographing, displaying, and storing data of the retina and surrounding parts of the eye. It is indicated for in vivo viewing, axial cross-sectional, and three-dimensional imaging and measurement of posterior ocular structures (retinal nerve fiber layer, macula, and optic disc) and anterior ocular structures. It includes a Reference Database for posterior ocular measurements to quantitatively compare these structures to a database of known normal subjects. The device is intended as a diagnostic aid in the diagnosis, documentation, and management of adult ocular health and diseases.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the Topcon DRI OCT Triton were based on demonstrating substantial equivalence to its predicate devices, the Topcon 3D OCT-1 Maestro and the Topcon TRC-50DX Retinal Camera. This was evaluated through agreement and precision studies, as well as image quality evaluations. The specific acceptance criteria are implicit in the reported performance metrics shown below.

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

For the Agreement and Precision Study (comparing Triton to Maestro):

• Sample Size: 76 participants, including:
  • 25 Normal eyes
  • 26 Retinal eyes
  • 25 Glaucoma eyes
• Data Provenance: Prospective comparative clinical study conducted at a single U.S. clinical site. (Page 6)

For the Fundus Autofluorescence and Fluorescein Angiography Image Quality Evaluation Study (comparing Triton (plus) to TRC-50DX):

• Specific sample size (number of participants/eyes) is not explicitly stated, but the submission mentions "Majority of the FAF and FA images were graded by both graders" and "response rates (i.e., percentage of subjects whose Triton grades were equal to or better than the corresponding TRC-50DX grades)".
• Data Provenance: Prospective clinical study conducted at one clinical site, located in the United States. (Page 55-56)

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

• Agreement and Precision Study (Fundus Photographs, Anterior B Scan, Posterior B Scan evaluations): The image quality of the fundus photographs, and the image quality of anterior and posterior OCT B scans were graded by two masked independent experts. (Page 7). Their specific qualifications (e.g., years of experience, specialty) were not detailed in the provided text.
• Fundus Autofluorescence and Fluorescein Angiography Image Quality Evaluation Study: The FAF and FA images were graded by two masked independent graders in a blinded and randomized fashion. Their specific qualifications were not detailed. (Page 56).

4. Adjudication Method for the Test Set

• Agreement and Precision Study: The text describes that two masked independent experts graded the images. For fundus photographs, the company performed a further analysis on image quality grades that differed by 1 point, stating this difference is not considered significantly different when both graders' scores are certain values. For posterior B scans, it states that 34% of images differed by one grade, but all these images were considered clinically useful by both graders. This suggests a form of implicit agreement or tolerance for minor discrepancies, rather than a formal adjudication process like 2+1 or 3+1 where a third expert decides.
• Fundus Autofluorescence and Fluorescein Angiography Image Quality Evaluation Study: The text indicates images were graded by "two masked independent graders" who performed the grading in a "blinded and randomized fashion." No explicit adjudication method (e.g., tie-breaking by a third reader) is mentioned for instances of disagreement.

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

• A MRMC comparative effectiveness study was not explicitly described for evaluating human reader improvement with AI assistance. The clinical studies focused on comparing the performance and agreement of the Triton device (algorithm included) with predicate devices directly, and on establishing a reference database. Human readers were involved in grading image quality for agreement studies, but the studies were not designed to measure the effect of AI assistance on human reader performance.

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

• The study primarily focuses on the standalone performance of the DRI OCT Triton device compared to predicate devices for quantitative measurements and image quality. The device itself performs the image acquisition, segmentation, and thickness calculations. The evaluation of image quality by experts is a pragmatic assessment of the output generated by the device, essentially evaluating its standalone output for clinical utility. The quantitative metrics (e.g., retinal thickness measurements, optic disc parameters) are direct outputs of the device's algorithms.

7. The Type of Ground Truth Used

• For the Agreement and Precision Study: The ground truth for quantitative measurements was established by comparison against the measurements obtained from the predicate device (Maestro). For image quality evaluations, the ground truth was established by expert grading/consensus from two masked independent experts.
• For the Fundus Autofluorescence and Fluorescein Angiography Image Quality Evaluation Study: The ground truth for image quality was established by expert grading/consensus from two masked independent graders comparing Triton (plus) images to TRC-50DX images.

8. The Sample Size for the Training Set

The provided text describes clinical studies for performance evaluation and for establishing a reference database. It does not explicitly mention a training set sample size for the device's algorithms. The clinical studies appear to be validation studies rather than studies for training the underlying algorithms. The "Reference Database" was established with 410 evaluable eyes. While this database is used for quantitative comparison within the device, it's not explicitly stated to be the training set for the segmentation or measurement algorithms.

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

Since a "training set" is not explicitly detailed or a method for establishing its ground truth described, this information cannot be provided from the given text. The reference database for quantitative comparisons was established from measurements of 410 normal eyes (age ≥18, no glaucomatous optic nerve damage) collected across six U.S. clinical sites. For these eyes, various scan parameters (full retinal thickness, RNFL thickness, GCL+IPL thickness, GCC thickness, optic disc measurements, TSNIT circle profile measurements) were collected, and percentiles were estimated using quantile regression with age and/or disc area as covariates. This database serves as a "ground truth" for comparison for normal subjects within the device's functionality, but not explicitly as a ground truth for training the segmentation or measurement algorithms themselves.

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The Non-Mydriatic Retinal Camera TRC-NW8F plus is intended for use in capturing images of the retina and the anterior segment of the eye and presenting the data to the eye care professional, with the use of a mydriatic or without the use of a mydriatic.

The Topcon TRC-NW8F plus is a fundus camera designed to observe, photograph and record the fundus oculi of a patient's eye with or without the use of a mydriatic. The TRC-NW8F plus does not come into contact with the patient's eye and provides the fundus oculi image information as an electronic image for later analysis. The TRC-NW8F plus performs color photography, fluorescein fundus angiography and Autofluorescence (FAF) photography. This product is equipped with an observation monitor used for observation purposes and display of a photographed images. The TRC-NW8F plus uses an attached commercial digital single-lens reflex camera to photograph or record the fundus oculi of a patient. A built in digital camera is used for taking autofluorescence images. The TRC-NW8F plus is only to be used with the Nikon D7000 digital camera.

A photographed image may be recorded on a commercial memory card built into a commercial digital single-lens reflex camera, a personal computer or commercial memory device (flash memories, hard disc, etc.). A commercial digital printer is connected and can print the observed images and the photographed images of the fundus.

This document describes the FDA's 510(k) clearance for the Topcon Non-Mydriatic Retinal Camera TRC-NW8F plus. The clearance is based on demonstrating substantial equivalence to predicate devices (TRC-NW8F and TRC-50DX). The performance data primarily focuses on image quality comparison rather than clinical diagnostic accuracy against a disease state.

Here's an analysis of the provided information concerning acceptance criteria and the supporting study:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are not explicitly stated in a quantitative, pass/fail manner for clinical performance in this document. Instead, the study's acceptance is based on demonstrating that image quality from the TRC-NW8F plus is "either equivalent or similar" to its predicate devices.

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

• Test Set Sample Size: Not explicitly stated. The document refers to "an analysis... of images captured" and "grading of clinical images," but does not provide specific numbers of images or patients.
• Data Provenance: Not explicitly stated. There is no mention of the country of origin or whether the data was retrospective or prospective.

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

• Number of Experts: Not explicitly stated. The document refers to an "analysis" and "grading," implying human review, but does not quantify the number of experts.
• Qualifications of Experts: Not explicitly stated. There is no mention of the background or experience of the individuals who performed the image evaluation/grading.

4. Adjudication Method for the Test Set

• Adjudication Method: Not explicitly stated. The document simply states "formally evaluated" and "grading," without detailing if consensus, majority vote, or other adjudication methods were used.

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

• Was an MRMC study done? No. This type of study would compare human reader performance with and without the AI device's assistance in diagnosing conditions. This submission focuses on the camera's image quality compared to predicate devices, not on diagnostic aid.
• Effect size of improvement: N/A, as an MRMC study was not performed.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

• Was a standalone study done? No. The device itself is an ophthalmic camera. The "performance data" discussed relates to the quality of the images it captures, not an automated diagnostic algorithm. There is no mention of an AI algorithm within this device in the context of standalone diagnostic performance.

7. Type of Ground Truth Used

• "Ground Truth" for Image Quality: The "ground truth" in this context is implicitly the comparator predicate devices' image quality. The study aimed to show the new device's images were "equivalent or similar" to images from established predicate devices in terms of sharpness, focus, and clinical grading. For "model eye images," the ground truth would be the known properties of the model eye and the expected output for a well-functioning camera. For "clinical images," the "ground truth" for the grading is based on expert visual assessment and comparison to predicate device images. This is not a clinical diagnostic ground truth (e.g., pathology confirmed disease, long-term outcomes), but rather an image quality assessment ground truth.

8. Sample Size for the Training Set

• Training Set Sample Size: Not applicable. This device is a retinal camera, not an AI/CADe (Computer-Aided Detection) or CADx (Computer-Aided Diagnosis) system that would typically have a "training set" for an algorithm. The "TRC-NW8F plus" is a hardware device for capturing images.

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

• Ground Truth Establishment for Training Set: Not applicable, as there is no mention of a training set for an AI algorithm.

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