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3nethra neo HD FA:

3nethra neo HD FA is used as a wide-field retinal imaging digital camera for photo documentation of ocular diseases that manifest in infants. The device acquires only images and does not provide any pathological analysis or diagnosis for treatment.

3nethra neo HD:

3nethra neo HD is used as a wide-field retinal imaging digital camera for photo documentation of ocular diseases that manifest in infants. The device acquires only images and does not provide any pathological analysis or diagnosis for treatment.

The 3nethra neo-HD FA is a handheld wide-angle fundus imaging system for neonatal screening. It is designed to acquire, display, store and transmit images of the posterior and anterior surfaces of human eye. The images assist clinicians in the evaluation and documentation of visual health in retinopathy of prematurity (ROP) and other problems. It operates in contact with the cornea of the eye under test. 3nethra neo HD FA uses continuous white light for operation and hence need pupil dilation. It also equipped with blue light source and green filters for fundus fluorescein angiography (FFA).

The 3nethra neo-HD is a handheld wide-angle fundus imaging system for neonatal screening. It is designed to acquire, display, store and transmit images of the posterior and anterior surfaces of human eye. The images assist clinicians in the evaluation and documentation of visual health in retinopathy of prematurity (ROP) and other problems. It operates in contact with the cornea of the eye under test. 3nethra neo HD uses continuous white light for operation and hence need pupil dilation. The 3nethra neo HD is a lower end variant of the 3nethra neo HD FA without the Fluorescein Angiography feature.

The provided 510(k) clearance letter and summary describe the acceptance criteria and a study to prove the device's performance. Here's a breakdown of the information requested:

The device in question, 3nethra neo HD FA and 3nethra neo HD, are ophthalmic cameras intended for wide-field retinal imaging and photo documentation of ocular diseases in infants. They acquire images only and do not provide pathological analysis or diagnosis.

Acceptance Criteria and Reported Device Performance

The core acceptance criterion for this device, based on the provided document, is substantial equivalence to existing predicate devices, particularly in terms of image quality for the FA functionality. The study focuses on demonstrating that the fluorescent angiography (FA) images produced by the subject device are comparable in quality to those produced by a predicate device.

Study Details

The study described is a clinical observational study focused on image quality comparison.

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

   • The document states "of all study images," implying that all images collected within the clinical observational study were used for the comparison. However, the exact numerical sample size (number of images or patients) for the test set is not explicitly stated in the provided text.
   • Data Provenance: The document does not explicitly state the country of origin of the data or whether the study was retrospective or prospective. It is described as a "clinical observational study," which typically implies prospective data collection, but this is not confirmed.

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

   • The document does not explicitly state the number of experts used or their specific qualifications (e.g., number of years of experience, specific certifications). It simply refers to the primary objective being to demonstrate comparability to a cleared reference device. The process of expert evaluation for "comparable quality" is not detailed.

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

   • The document does not describe any specific adjudication method for evaluating image quality. It states that "all study images were found to be of comparable quality," but the process by which this finding was made (e.g., consensus, majority vote) is not provided.

4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and if so, what was the effect size of how much human readers improve with AI vs. without AI assistance:

   • No, a multi-reader multi-case (MRMC) comparative effectiveness study was not performed or described in the provided text.
   • The device is described as an "Ophthalmic Camera" that "acquires only images and does not provide any pathological analysis or diagnosis for treatment." Therefore, there is no AI assistance component for human readers to be compared against. The study focused on assessing the image quality of the camera itself, not the impact of AI on human interpretation.

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

   • This question is not applicable as the device is an imaging camera that acquires images for human interpretation, not an algorithm providing a standalone diagnostic or analytical output. The study assessed the quality of the images produced by the device.

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

   • The ground truth for the "comparable image quality" assessment appears to be based on a clinical observational study comparing the subject device's images to those from a predicate device (RetCam 3). The implicit ground truth is the accepted, established quality of images from the predicate device.
   • The document does not mention pathology or outcomes data as a direct ground truth for image quality assessment in this context. The study aimed to show that the images themselves were of sufficient quality for their intended purpose (photo documentation) by comparing them to a cleared device.

7. The sample size for the training set:

   • The document does not mention a training set. This is because the device is an imaging camera, not a machine learning or AI algorithm that requires a training set.

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

   • This question is not applicable as there is no mention of a training set for this device.

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The Resolve Fundus Camera is an automatic eye-fundus camera intended for taking digital images of a human retina with or without the use of a mydriatic agent. It is intended for use as an aid to clinicians in the evaluation and diagnosis of ocular health.

The Resolve Fundus Camera is a fundus camera designed to perform fundus observation, automatic pupil tracking and focusing, automatic image capture, and image preservation. The Resolve Fundus Camera is used for non-mydriatic observation and capturing of retinal images. The fundus camera employes three internal imaging systems to operate: illumination system, imaging system and observation system. Auto-alignment and auto-focus algorithms are used to automatically find and capture desired images of the fundus.

The fundus camera features an internal, movable three-dimensional platform that allows for switching and precise positioning of the left and right eyes. The imaging process is done one eye at a time (left eye and then the right eye). The internal, moveable three-dimensional platform contains two types of cameras: a set of infrared cameras (one on each side) as well as one main camera.

The observation system is used to detect and track the patient's pupil. Next, the illumination system determines the precise location of the ocular fundus after the pupil is located by the observation system. The system precisely finds the relationship between the position of the ocular fundus at different diopters, and the lens of the main camera.

Once the location of the fundus is found, a charge-coupled device (CCD) automatically captures a still image of the fundus through the main camera. The autofocus system utilizes a beam splitter to split a beam of light into two fine beams, which then image the ocular fundus onto the CCD. When the focus is at its sharpest position, the split beams align horizontally. At this point, the LED white light illumination system, installed in the imaging module on the three-dimensional movable platform, emits uniform white light of appropriate intensity to illuminate the ocular fundus. The imaging system captures the fundus information onto the CCD, and the received signals are displayed in real-time on a liquid crystal display (LCD) through the control system. Doctors can visually assess the patient's ocular fundus on the LCD screen.

The provided FDA 510(k) clearance letter for the Optain Health Resolve Fundus Camera focuses primarily on establishing substantial equivalence to a predicate device (Next Sight Srl Nexy). For this type of device (an ophthalmic camera), the clearance process in this document does not necessitate a detailed clinical study for performance evaluation that would typically involve acceptance criteria for diagnostic accuracy (e.g., sensitivity, specificity) of an AI algorithm. Instead, the performance data presented is focused on demonstrating that the device meets safety and basic functional standards, similar to the predicate device.

Therefore, many of the requested points regarding AI algorithm performance (like specific acceptance criteria for diagnostic accuracy, sample sizes for test sets, expert adjudication methods, MRMC studies, standalone performance, and ground truth establishment for training/test sets) are not explicitly described or required for this particular regulatory submission type, given the device's classification and stated indications for use. The device's indication is for "taking digital images" and "aid to clinicians in the evaluation and diagnosis of ocular health," implying that the device primarily performs an imaging function, and any "diagnosis" is still ultimately made by the human clinician using the image.

Below is an attempt to answer the questions based only on the provided text. Where information is not available, it will be stated as such.

Device: Optain Health Resolve Fundus Camera

Indications for Use: The Resolve Fundus Camera is an automatic eye-fundus camera intended for taking digital images of a human retina with or without the use of a mydriatic agent. It is intended for use as an aid to clinicians in the evaluation and diagnosis of ocular health.

Acceptance Criteria and Reported Device Performance

The document describes the device's performance in terms of compliance with recognized consensus standards rather than diagnostic performance metrics (e.g., sensitivity, specificity, accuracy) for an AI algorithm. The acceptance criteria are implicit in meeting the requirements of these standards.

1. Table of Acceptance Criteria and Reported Device Performance:

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

• The document states "Non-clinical testing was performed," and "Performance testing" but does not specify a "test set" in the context of a dataset for evaluating an AI algorithm's diagnostic performance.
• The tests are primarily related to general device safety, function, and image quality standards compliance, not the diagnostic accuracy of an AI.
• Data Provenance: Not specified, but likely laboratory or engineering test data, not patient data from a specific country or retrospective/prospective study.

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

• Not applicable/Not specified in the provided document, as no specific diagnostic ground truth for an AI algorithm's performance is described. The device's function is to aid clinicians, not to output a diagnosis via AI.

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

• Not applicable/Not specified, for the same reasons as above.

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 described in this 510(k) summary. The device's clearance is based on substantial equivalence to a predicate ophthalmic camera, not on a claim of AI-assisted diagnostic improvement.

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

• No standalone AI performance study is described. The device is an "automatic eye-fundus camera" which "aids clinicians." There is no mention of an AI algorithm producing a diagnostic output independently of a human.

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

• Not applicable/Not specified, as the performance evaluation is focused on device functionality and safety standards, not diagnostic accuracy against a clinical ground truth.

8. The sample size for the training set:

• Not applicable/Not specified. The document does not describe a training set for an AI algorithm. If there are "auto-alignment and auto-focus algorithms," these might involve machine learning, but the document does not detail their training data or performance evaluation beyond general "software verification and validation."

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

• Not applicable/Not specified, for the same reasons as above.

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Sentinel Camera is a non-mydriatic medical digital camera that is intended to capture digital images of the human eye.

The Sentinel Camera is accompanied by the following accessories: a charging base, eye cup, and power cable. The Sentinel Camera is designed for use in a medical environment. Captured images are used for documentation and consultation. Sentinel Camera has internal memory where captured images are stored. The Sentinel Camera is designed for non-mydriatic retinal imaging. In non-mydriatic imaging no mydriasis is needed because infrared light is used for targeting the retina and white light is flashed when an image is taken. The pupil does not respond to the infrared light, so examination is convenient for the patient. With small pupils, it is recommended to use mydriatic drops. The Sentinel Camera has three internal fixation targets for the patient to fixate on during imaging. The middle fixation target provides a macula-centered image. The left and right fixation targets provide disc-centered images. The transfer of images to the AI Optics Server is carried out via Wi-Fi communication. The Sentinel Camera has a rechargeable Li-ion battery that is charged when the camera is placed on charging base, which is connected to the mains by the power cable.

The provided text describes a 510(k) summary for the "Sentinel Camera," an ophthalmic camera. However, it does not contain information about acceptance criteria or a study that proves the device meets those criteria, particularly in the context of an AI-powered diagnostic or assistive tool. The document focuses on comparing the Sentinel Camera to a predicate device (Optomed Aurora Camera) based on their technical characteristics and safety/performance standards.

The 510(k) summary explicitly states: "Performance data for the Sentinel Camera, including extensive testing against recognized standards, supports the substantial equivalence of the Sentinel Camera to the predicate device. Both devices underwent similar testing to external standards." It concludes that the device "meets the necessary safety and performance criteria, with no new questions of safety or effectiveness."

Crucially, there is no mention of any AI component within the Sentinel Camera's functionality in this document, nor any studies that would involve AI performance metrics (like sensitivity, specificity, or human-AI collaboration studies). The device is described as "a non-mydriatic medical digital camera that is intended to capture digital images of the human eye."

Therefore, based on the provided text, I cannot answer the questions regarding acceptance criteria and studies proving the device meets them in the context of AI performance. The document does not provide such information.

If this device were to incorporate AI functionality, the information requested (acceptance criteria, study design, sample sizes, ground truth establishment, expert qualifications, etc.) would be crucial for its regulatory submission. However, this particular document does not detail any such AI-related performance studies.

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Verily Numetric Retinal Camera is a non-contact, high resolution digital imaging device which is suitable for photographing, displaying and storing images of the retina segment of the eye to be evaluated under non-mydriatic conditions.

Verily Numetric Retinal Camera is indicated for in-vivo viewing of the posterior segment of the eye. The images are intended for use as an aid to clinicians in the evaluation, diagnosis, and documentation of ocular health.

The Verily Numetric Retinal Camera (VNRC), the subject device, is a tabletop fundus camera that provides non-mydriatic, color, posterior segment images of the eye as an aid to clinicians in the evaluation and diagnosis of eye disease. It is a non-contact, high-resolution digital imaging device that is suitable for photographing, displaying, and storing images of the retina to be evaluated under non-mydriatic conditions.

The Verily Numetric Retinal Camera takes images of the fundus in the following manner:

Focusing: The patient interactively focuses an image shown on a microdisplay to the best qualitative focus by turning a knob on an external peripheral device which modulates the camera optics.

Alignment: The patient is shown a fixation target on the microdisplay and through an interactive session with position feedback, the patient aligns their pupil to the camera. The pupil location is determined using eye-tracking.

Image Capture: White light from LEDs illuminates the fundus. The light reflection from the fundus is captured by a color CMOS sensor.

The Verily Numetric Retinal Camera has the following acceptance criteria and reported device performance:

1. Table of Acceptance Criteria and Reported Device Performance

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Optina-4C™ is intended to capture images of the retina at multiple wavelengths (colors) under mydriatic conditions.

Optina-4C™ (model: MHRC-C1N) is a mydriatic fundus camera (also called retinal camera) that presents eye care practitioners (optometrists and ophthalmologists) with a series 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 Optina-4C™ 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 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 Optina-4C™ acquisition software. The retinal images captured by Optina-4C™ 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.

The provided text is a 510(k) summary for the Optina-4C (MHRC-C1N) device, which is a mydriatic fundus camera. The document primarily focuses on demonstrating substantial equivalence to a predicate device (MHRC-C1) and outlines various performance tests conducted to support this claim.

However, the document does not contain specific acceptance criteria for the device's performance regarding its intended use of capturing retinal images, nor does it present a detailed study that proves the device meets such criteria in terms of clinical accuracy or utility.

Instead, the document focuses on:

• Technological equivalence: Stating that the main elements of the hardware, illumination, and monochromatic images are the same as the predicate.
• Verification of safety and regulatory compliance: Covering software evaluation, electrical safety, electromagnetic compatibility, biocompatibility, and compliance with recognized consensus standards for ophthalmic cameras (ISO 15004-1:2020, ISO 10940:2009, ANSI Z80.36:2021).
• Spectral accuracy and reliability of retinal images: This was evaluated in an "eye model using a reference material with tabulated spectral bands," but no specific acceptance criteria or performance metrics (e.g., sensitivity, specificity, accuracy for a particular clinical task) are provided from this evaluation.

Therefore, I cannot populate the requested table and information as the necessary details regarding acceptance criteria, reported device performance related to a specific clinical task, test set characteristics, expert involvement, adjudication, or a multi-reader multi-case study are not present in the provided text. The document describes tests to ensure the device functions safely and in a manner similar to its predicate, but not how well it performs a particular diagnostic task against established clinical benchmarks or ground truth.

Missing Information:

• No specific acceptance criteria for diagnostic performance (e.g., image quality metrics, sensitivity/specificity for detecting a condition).
• No reported clinical performance metrics directly related to the device's ability to 'capture images' that translates to a clinical outcome.
• No details on a clinical study where the device's images were evaluated for a specific purpose against a ground truth.

The document seems to describe the device as an image capture device, and the "performance testing" focuses on its technical specifications and safety rather than its diagnostic accuracy for a particular condition.

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Zilia Ocular is a non-contact imaging device for capturing, displaying and storing images of the retina under mydriatic conditions.

Zilia Ocular is intended for use as an aid to clinicians in the evaluation and documentation of ocular health.

The Zilia Ocular Fundus Camera (Zilia Ocular FC) is a non-contact, stand-alone device designed to image the eye fundus.

The device includes a base, a head support, an onboard computer with a 15.6'' touch-screen display and an optical head. A joystick, situated at the base of the device, controls the movements of the optical head to enable adequate positioning. The touch-screen display also includes a user interface allowing the user to control the device and acquire and display patient data and images.

The Zilia Ocular FC uses near-infrared (NIR) light-emitting diodes (LEDs) as illumination during alignment to the patient's pupil, and a white LED during focusing and imaging of the eye fundus. The region of the eye fundus being imaged can be modified by changing or moving the fixation target. The images are saved and stored on the onboard computer.

The dimensions of the Zilia Ocular FC are 620 mm (L) by 360 mm (W) by 500 mm (H) and it weighs about 32 kg.

The provided document is a 510(k) Summary for the Zilia Ocular Fundus Camera (Zilia Ocular FC). It describes the device, its intended use, and performance testing conducted to demonstrate substantial equivalence to predicate and reference devices.

However, the document does not contain specific acceptance criteria, reported device performance data against those criteria, or the details of a clinical study (such as sample size, data provenance, expert ground truth establishment, adjudication methods, MRMC studies, or standalone algorithm performance).

The document explicitly states: "Clinical Performance Data: This section is not applicable because clinical data was not provided for this 510(k) submission."

Therefore, I cannot provide the information requested in points 1, 2, 3, 4, 5, 6, 7, 8, and 9 based on the provided text. The submission relied on non-clinical performance testing (electrical safety, EMC, recognized standards, risk management, biocompatibility, processing of healthcare products, software evaluation, and usability) to demonstrate substantial equivalence, rather than clinical performance data.

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General ophthalmic imaging including retinal, corneal, and external structures of the eye.

The Phoenix ICON system is an updated cart based retinal imaging system covering the design changes to date on the predicate device, Phoenix ICON. The Phoenix ICON GO retinal imaging system is a portable version of the predicate device, Phoenix ICON (K170527) including the design changes in the Phoenix ICON system.

Both the Phoenix ICON and Phoenix ICON GO are wide-field, handheld, high resolution, real-time retinal imaging devices. They are intended to be used for general ophthalmic imaging including retinal, corneal, and external structures of the eye. The intended users of the Phoenix ICON and Phoenix ICON GO are clinical imaging technicians, ophthalmic technicians, nurses, and physicians. The devices may be used in hospitals, medical clinics, and physician's offices.

The Phoenix ICON platform consists of either a cart based (Phoenix ICON) or portable (Phoenix ICON GO) control box used in conjunction with a hand-held camera (Handpiece) using interchangeable LED based light sources (White and Blue light). The Phoenix ICON cart contains an AC mains power attachment, a battery module, a keyboard interface, a monitor, and a computer with Phoenix ICON software. The Phoenix ICON GO contains a portable control box with battery function and has an interface for attachment to a specified laptop computer which runs the Phoenix ICON software. Both systems may be used with a Foot Pedal, White Light Module (standard), Blue Light Module (FA) and/or Diffuser accessory.

The Phoenix ICON Handpiece contains a wide-field, high resolution camera is used in three (3) modes, External Imaging (White Light), Retinal Imaging (White Light), and Fluorescein Angiography (Blue Light). For external imaging, the Diffuser accessory is placed over the lens tip to diffuse the light and provide for images of the outer surfaces of the eye. Both Retinal Imaging and Fluorescein Angiography are performed with the glass lens of the Handpiece coupled to the cornea via an imaging gel. In these imaging methods, LED light is emitted into the eye to illuminate the retina for image capture.

Both the Phoenix ICON and Phoenix ICON GO are software-controlled systems which can capture either video or still images and store them on the control box (Cart computer or GO laptop) for later review. The Phoenix ICON system may be connected to IT networks under IT supervision.

The provided document does not contain details about specific acceptance criteria for a device's performance in a clinical study or a study proving that the device meets those criteria. Instead, it is a 510(k) summary for the NeoLight Phoenix ICON and Phoenix ICON GO ophthalmic cameras, aimed at demonstrating substantial equivalence to a predicate device (K170527, Phoenix ICON by Phoenix Technology Group, LLC).

The document focuses on comparing technological characteristics and safety testing, not on clinical performance acceptance criteria or a study to demonstrate such.

However, based on the Performance Testing section (Table 5.3) related to Simulated Use, it states:
Characteristic: Image Clarity - Comparison between subject and predicate images to ensure equivalent visual quality of the captured images.
Results: Pass.

While this indicates some form of performance assessment related to image quality, it does not provide the specific acceptance criteria (e.g., quantitative metrics, thresholds) or the detailed methodology of the study. It also doesn't present the "reported device performance" in a manner typical for clinical trials (e.g., sensitivity, specificity, or reader agreement scores).

Therefore, a table of acceptance criteria and reported device performance, as well as several other requested details, cannot be fully extracted from the provided text.

Here's an attempt to answer the questions based only on the available information, noting where information is missing:

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

Note: The document only provides a high-level "Pass" result for "Image Clarity - Comparison between subject and predicate images to ensure equivalent visual quality of the captured images." It does not specify quantitative acceptance criteria or detailed performance metrics.

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

The document mentions "Simulated Use" testing for "Image Clarity - Comparison between subject and predicate images." However, it does not specify the sample size used for this comparison, nor does it provide any information on data provenance (e.g., country of origin, retrospective/prospective nature).

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)

The document does not provide any information about the number or qualifications of experts used for establishing ground truth or evaluating image clarity.

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

The document does not specify any adjudication method used for the image clarity comparison.

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

The document describes the device as an "Ophthalmic Camera" for "General ophthalmic imaging." It is a imaging acquisition device and does not include AI functionality. Therefore, an MRMC comparative effectiveness study involving AI assistance for human readers is not relevant to this submission, and no such study is mentioned.

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

This device is an ophthalmic camera. Its function is to capture images. It does not appear to incorporate an algorithm that independently processes or interprets images to provide a diagnosis or finding, nor does it claim AI capabilities. Therefore, a standalone algorithm performance study is not applicable and not mentioned. The "Simulated Use" test assesses the visual quality of the captured images, not the performance of an interpretive algorithm.

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

For the "Image Clarity" assessment, the implicit "ground truth" was a visual comparison to the predicate device's images to ensure equivalent visual quality. The document does not specify a separate, independent ground truth method like expert consensus on pathology, or outcomes data.

8. The sample size for the training set

The document concerns an ophthalmic camera, not an AI/ML algorithm requiring a training set. Therefore, this question is not applicable.

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

As the device is an ophthalmic camera and not an AI/ML algorithm, there is no training set and therefore no ground truth for a training set.

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The iExaminer system with PanOptic Plus, consisting of PanOptic Plus, SmartClip, iExaminer application, and one of the following: iPhone 11 Pro, iPhone 11 Pro Max, iPhone 12 Pro, is intended to be used to capture images as an aid to clinicians in the evaluation, and documentation of ocular health. The images from the iExaminer System with PanOptic Plus are not intended to be used as a sole means of diagnosis.

The iExaminer System with PanOptic Plus is a medical device that allows the user to capture images through the use of a PanOptic Plus ophthalmoscope and a smart device. The iExaminer System with PanOptic Plus consists of (also see Figure 1):

1. PanOptic Plus Ophthalmoscope:
   a. Ophthalmoscope Head
   b. Compatible energy sources (i.e. battery handles or wall units)
   c. Optional Patient Eyecup
2. Smart device attachment instrument (made of SmartBracket and SmartClip);
3. Compatible smart device (iPhone X, iPhone 11 Pro, iPhone 11 Pro Max, iPhone 12 Pro).
4. iExaminer Pro Software Application.
   The iExaminer system with PanOptic Plus is intended to take photographs of the eye and surrounding area.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided FDA 510(k) summary:

Acceptance Criteria and Device Performance

The document states that a non-clinical and clinical (image comparison) study was performed to demonstrate that the iExaminer System with PanOptic Plus images are substantially equivalent to the predicate device images in their usefulness for documentation and clinical referrals. The acceptance criteria themselves are not explicitly detailed in a table with specific numerical thresholds for metrics like sensitivity, specificity, or accuracy. Instead, the general acceptance criterion for the clinical study was that the new device's images are "substantially equivalent" in usefulness for documentation and clinical referrals compared to the predicate device.

Given that no specific performance metrics like sensitivity or specificity were reported for the device itself against a ground truth, it's not possible to create a table of acceptance criteria and reported device performance in those terms. The study focuses on comparative usefulness.

However, based on the conclusion, the device did meet the established acceptance criteria:
"The results of the image comparison study demonstrate that the iExaminer System with PanOptic Plus has passed all established acceptance criteria and is as safe and effective as the predicate device for its intended use."

Study Details:

1. A table of acceptance criteria and the reported device performance
   As noted above, explicit numerical acceptance criteria for performance metrics (sensitivity, specificity) are not provided. The acceptance criterion was "substantially equivalent" usefulness of images for documentation and clinical referrals compared to the predicate device. The study concluded this criterion was met.

2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)
   The document does not specify the sample size for the test set (number of images or patients). It also does not mention the country of origin of the data or whether it was retrospective or prospective.

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)
   The document does not describe the establishment of a "ground truth" by experts for specific pathologies. Instead, the study was an "image comparison study" where the new device's images were compared to the predicate device's images for "usefulness for documentation and clinical referrals." The number and qualifications of experts (if any specific graders were involved in comparing image usefulness) are not detailed.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set
   The document does not provide details on any adjudication method used for comparing images or establishing usefulness.

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, a multi-reader multi-case (MRMC) comparative effectiveness study focusing on human reader improvement with or without AI assistance was not conducted or reported. The study was an "image comparison study" between two devices to show substantial equivalence. The device itself is an image capture system, not an AI-powered diagnostic tool.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
   No, a standalone algorithm performance study was not done. The device is a system for capturing images for human clinicians to evaluate, not an automated diagnostic algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
   The study did not use a traditional "ground truth" in the sense of confirmed diseases (e.g., pathology, outcomes data, or expert consensus on diagnosis). Instead, it focused on the "usefulness for documentation and clinical referrals" of images captured by the proposed device compared to images from the predicate device. The predicate device's images are assumed to be a sufficient and already accepted reference point for "usefulness."

8. The sample size for the training set
   This information is not applicable. The device is an image capture system, not an AI model that requires a training set.

9. How the ground truth for the training set was established
   This information is not applicable, as there is no training set for an AI model.

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