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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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The Slit Lamp SL-D701 is an AC-powered slittlamp biomicroscope intended for use in eye examination of the anterior eye segment, from the cornea epithelium to the posterior capsule. It is used to aid in the diagnosis of diseases or trauma which affect the structural properties of the anterior eye segment.

The Slit Lamp SL-D701 is an AC-powered device that is a microscope intended for use in eye examination that projects into a patient's eye through a control diaphragm a thin, intense beam of light. The Slit Lamp SL-D701 is composed of the following components: microscope unit, illumination unit, base unit, chinrest, table and power unit. The slitlamp biomicroscope is used for the observation of the eye. It has an illumination unit to illuminate the eye, and a binocular stereoscopic microscope to zoom and observe patient's eyes, and also can observe the three-dimensional image.

This document is a 510(k) Summary for the Topcon Slit Lamp SL-D701, a medical device. It provides information for substantial equivalence to previously cleared predicate devices. However, it does not include information about acceptance criteria and a study proving that the device meets those criteria, as typically seen in submissions for AI/ML-enabled devices.

The document states that the Topcon Slit Lamp SL-D701 is substantially equivalent to the predicate devices:

• Haag-Streit AG Slit Lamp BM 900, BQ 900, BP 900 (K100202)
• TOPCON CORPORATION Slit Lamp SL-2G (K110489)

The key takeaway is that this is a traditional medical device (Slit Lamp Biomicroscope), and the submission focuses on demonstrating substantial equivalence to existing devices based on similar intended use, technological characteristics, principles of operation, and compliance with recognized consensus standards. There is no mention of AI/ML, algorithms, or any associated acceptance criteria, test sets, or ground truth establishment studies typically required for such technologies.

Therefore, most of the requested information regarding acceptance criteria and a study proving an AI/ML device meets them is not applicable to this document.

Here's an attempt to answer the questions based on the provided document, highlighting where the information is not present or not applicable:

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

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

This information is not applicable to this 510(k) submission, as it describes a traditional hardware device (slit lamp) and not an AI/ML diagnostic algorithm that would require a test set of data samples. The performance data presented refers to bench testing against international standards for ophthalmic instruments.

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)

This information is not applicable. Ground truth establishment by experts is relevant for AI/ML diagnostic devices, not for the physical performance testing of a slit lamp as described here. The "performance data" refers to compliance with engineering and safety standards.

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

This information is not applicable. Adjudication methods are used in studies involving human interpretation or AI/ML evaluations to resolve disagreements in ground truth or diagnostic outputs. This submission focuses on bench testing.

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

There is no indication that a multi-reader multi-case (MRMC) comparative effectiveness study was done. This type of study is typically conducted for AI/ML-assisted diagnostic devices to measure the impact of the AI on human reader performance, which is not relevant for this traditional slit lamp submission.

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

This information is not applicable. The device is a physical slit lamp biomicroscope; there is no standalone algorithm to evaluate.

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

This information is not applicable. The "ground truth" for this device's performance is its adherence to specified engineering and safety standards (e.g., light hazard protection, general requirements for ophthalmic instruments), as demonstrated through bench testing. There is no diagnostic "ground truth" in the context of disease detection or image interpretation for a software algorithm.

8. The sample size for the training set

This information is not applicable. There is no mention of a training set, as the device is a physical instrument, not an AI/ML algorithm that learns from data.

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

This information is not applicable, as there is no training set mentioned or implied for this traditional medical device.

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The TRC-NW8 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.

This product is a retinal camera designed to observe, photograph or record the fundus oculi of a patient without coming into contact with the patient's eye and provide as an electronic image the obtained fundus oculi information for subsequent diagnosis. The TRC-NW8 can take both color photography and red-free photography. The TRC-NW8 is equipped with an observation monitor used for observation purpose and display of a photographed image. This product uses attached commercial digital single-lens reflex camera to photograph or record the fundus oculi of a patient. A photographed image may be recorded on a commercial memory card built into a commercial digital single-lens reflex camera or a personal computer (hereinafter referred to as a PC) or commercial memory devices (flash memories, hard disc, etc.). A commercial digital printer is connected and can print the observed images and the photographed images of the fundus.

The provided text does not contain information about acceptance criteria, device performance metrics (like sensitivity, specificity, or accuracy), or a study that evaluates the device's clinical performance against such criteria.

The document is a 510(k) summary for the Topcon TRC-NW8 Non-Mydriatic Retinal Camera. It primarily focuses on demonstrating substantial equivalence to a predicate device (TRC-NW8F) and compliance with general safety and performance standards.

Here's a breakdown of what can be extracted and what is missing based on your request:

1. Table of Acceptance Criteria and Reported Device Performance:

• Acceptance Criteria: Not explicitly stated in terms of clinical performance (e.g., image quality metrics or diagnostic accuracy). The acceptance criteria mentioned are related to compliance with recognized consensus standards (IEC 60601-1, IEC 60601-1-2, ISO 15004-1, ISO 15004-2) and the results of a risk analysis assessment.
• Reported Device Performance: The document states that "Design verification tests were performed as a result of the risk analysis assessment. These test results demonstrated that the TRC-NW8 met predetermined acceptance criteria." However, no specific performance metrics or data (e.g., image resolution, diagnostic accuracy) are reported.

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

• Not provided. The document does not describe any clinical test set or data used to evaluate the device's performance in a diagnostic context. The testing mentioned appears to be engineering design verification for safety and fundamental requirements.

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

• Not applicable/Not provided. Since no clinical test set is described, there's no mention of experts or ground truth establishment for diagnostic performance.

4. Adjudication Method:

• Not applicable/Not provided. No clinical performance study requiring adjudication is described.

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

• No. The document does not mention any MRMC study or a comparison of human reader performance with or without AI assistance. The device is a retinal camera, not an AI-powered diagnostic tool in this context.

6. Standalone (Algorithm Only) Performance Study:

• No. The device is a retinal camera for capturing images, not an algorithm for standalone diagnostic performance.

7. Type of Ground Truth Used:

• Not applicable/Not provided. No clinical study for diagnostic accuracy is described that would require a ground truth.

8. Sample Size for the Training Set:

• Not applicable/Not provided. The device is not an AI algorithm that requires a training set.

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

• Not applicable/Not provided. As above, no AI training set is mentioned.

Summary of available "Performance Data" from the document:

The "Performance Data" section solely refers to the device's compliance with electrical safety, EMC, and ophthalmic instrument-specific fundamental requirements and light hazard protection standards. It also states that design verification tests were performed as a result of risk analysis and that the results met predetermined acceptance criteria, but it does not detail those criteria or results in a clinical or diagnostic performance context.

This 510(k) summary focuses on the safety and fundamental performance characteristics of the hardware device (retinal camera) and its substantial equivalence to an existing device, rather than on the diagnostic or clinical accuracy of images or any integrated AI component.

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The NON-MYDRIATIC RETINAL CAMERA TRC-NW8F 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 use of a mydriatic.

This product is a retinal camera designed to observe, photograph or record the fundus oculi of a patient without coming into contact with the patient's eye and provide as an electronic image the obtained fundus oculi information for subsequent diagnosis. This product can take both color photography and fluorescein angiography. This product is equipped with an observation monitor used for observation purpose and display of a photographed image. This product uses attached commercial digital single-lens reflex camera to photograph or record the fundus oculi of a patient. A photographed image may be recorded on a commercial memory card built into an commercial digital single-lens reflex camera or a personal computer (hereinafter referred to as a PC) or commercial memory devices (flash memories, hard disc, etc.). A commercial digital printer is connected and can print the observed images and the photographed images of the fundus.

Here's an analysis of the provided text regarding the acceptance criteria and study proving the device meets them:

Acceptance Criteria and Device Performance Study for NON-MYDRIATIC RETINAL CAMERA TRC-NW8F

Based on the provided 510(k) summary (K100207), the device is a retinal camera intended for capturing images of the retina and the anterior segment of the eye. The acceptance criteria and the studies that demonstrate the device meets these criteria are focused on safety and functional performance, primarily by adherence to established international standards and demonstrating substantial equivalence to predicate devices.

1. Table of Acceptance Criteria and Reported Device Performance

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

The provided document does not specify a sample size or data provenance (e.g., country of origin, retrospective or prospective) for a clinical test set in the traditional sense of evaluating diagnostic accuracy.

The performance evaluation is based on engineering and performance testing against international standards (ISO, IEC) and internal TOPCON standards, which typically involve testing units of the device in a controlled environment, not on human subjects or clinical data in the context of diagnostic accuracy.

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

This information is not applicable in the context of the provided performance data. The device's performance is not being evaluated for diagnostic accuracy against a ground truth established by medical experts. Instead, it is being evaluated for compliance with technical standards related to safety and imaging capabilities by engineers and testing facilities.

4. Adjudication Method for the Test Set

The concept of an adjudication method (e.g., 2+1, 3+1) is not applicable here. Adjudication is used to resolve disagreements among experts when establishing ground truth for diagnostic accuracy studies. The studies described are technical compliance tests, not diagnostic performance evaluations.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The submission focuses on device safety and technical performance through compliance with standards, and substantial equivalence to predicate devices, not on human reader performance with or without AI assistance. This device is a camera, not an AI diagnostic tool.

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

No, a standalone (algorithm only) performance study was not done. This device is a retinal camera, a hardware device for image capture, not an algorithm. Therefore, an algorithm-only performance study is not relevant.

7. The Type of Ground Truth Used

The "ground truth" for the device's performance, in this context, is defined by:

• International Standards: e.g., ISO 15004-2:2007 (light hazard), ISO 10940:1998 (resolving power, field of view), IEC 60601-1 (electrical safety), IEC 60601-1-2 (EMC).
• TOPCON Self Standards: For resolving power and photographic angular field of view, these internal standards serve as the performance benchmarks.

There is no "expert consensus," "pathology," or "outcomes data" ground truth utilized for the acceptance criteria described.

8. The Sample Size for the Training Set

Not applicable. This submission describes a medical imaging device (a camera), not an AI algorithm that requires a training set.

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

Not applicable. As this is not an AI algorithm, there is no training set or ground truth establishment related to AI.

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The 3D OPTICAL COHERENCE TOMOGRAPHY 3D OCT-2000 is a non-contact, high resolution tomographic and biomicroscopic imaging device. It is indicated for in vivo viewing, axial, cross-sectional and three-dimensional imaging and measurement of posterior ocular structures including retina, retinal nerve fiber layer, macula, and optic disk. It is intended for use as a diagnostic device to aid in the detection and management of ocular diseases affecting the posterior segment of the eye.

The 3D OCT-2000 is a non-contact ophthalmic imaging system for the viewing and axial cross sectional imaging of posterior ocular structures. It is used for in vivo imaging of the retina, retinal nerve fiber layer and optic disc. It is intended for use as a diagnostic device to aid in the detection and management of ocular diseases, including but not limited to macular edema and central serous retinopathy. During OCT imaging, the scan beam for the 3D OCT-2000 is delivered as pulsed lighting. The PC software of the 3D OCT-2000 has same functions of the PC software of the 3D OCT-1000 and 3D OCT-10000 MARK II and also the PC software of the 3D OCT-2000 has same functions for the measurement of retinal thickness of the 3D OCT-1000 for Measurement of Retinal Thickness.

The provided text describes the Topcon 3D OCT-2000 and its substantial equivalence to previous models. However, it does not contain specific acceptance criteria, detailed study results, or information about sample sizes for test or training sets, ground truth establishment methods, expert involvement, or MRMC studies for this device.

The document focuses on the device's intended use, technological characteristics, and conformity to general medical device standards. The "Performance Data" section states that "Software validation testing (with PC software) and image capture testing were performed on the 3D OCT-2000. And also, the test results for the 3D OCT-2000 demonstrated sufficient equivalence with measuring the retinal thickness from the 3D OCT-1000 for Measurement of Retinal Thickness." However, it does not elaborate on these test results or specify any quantitative acceptance criteria.

Therefore, many of the requested details cannot be extracted from the given text.

Here's a breakdown of what can and cannot be answered based on the provided input:

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

• Acceptance Criteria: Not explicitly stated in the document. The document mentions conformity to several IEC and ISO standards (IEC 60601-1, IEC 60601-1-2, IEC 60825-1, ISO 15004-1:2006, ISO 15004-2:2007). These standards define general safety, electromagnetic compatibility, laser safety, and fundamental requirements for ophthalmic instruments. While successfully meeting these standards implies acceptance, the document does not provide specific performance metrics (e.g., accuracy, sensitivity, specificity for disease detection) with corresponding acceptance thresholds.
• Reported Device Performance: The document only generally states, "The results of performance testing and software validation testing did not raise any issues on the safety or effectiveness of the device." It also mentions "sufficient equivalence with measuring the retinal thickness from the 3D OCT-1000 for Measurement of Retinal Thickness," but no numerical data is provided.

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

• Sample Size for Test Set: Not specified.
• Data Provenance: Not specified.

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 specified. The document does not detail any studies involving expert ground truth establishment for performance evaluation.

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

• Not specified.

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 specified. This device (3D OCT-2000) is a diagnostic imaging device, not explicitly an AI-assisted diagnostic tool as described in the context of MRMC for AI improvement. The document presents it as substantially equivalent to prior predicate devices based on technological characteristics and intended use, not necessarily improved human reader performance with AI.

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

• The device is an imaging system. Its 'performance' would be related to image quality, measurement accuracy, and safety, not an algorithm's standalone diagnostic performance in the AI sense. The document states "software validation testing" was done, but gives no specifics on algorithm-only performance metrics.

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

• Not specified.

8. The sample size for the training set

• Not applicable/Not specified. The document describes a "substantially equivalent" declaration, not a de novo clearance for a machine learning algorithm that typically requires a distinct training set.

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

• Not applicable/Not specified.

Summary of available information:

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The TOPCON Retinal Camera TRC-NW7SF MARK II 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 use of a mydriatic.
Retina Camera TRC-NW7SF MARK II system 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 or without the use of mydriatic.

This product is a retinal camera designed to observe, photograph or record the fundus oculi of a patient without coming into contact with the patient's eye and provide as an electronic image the obtained fundus oculi information for subsequent diagnosis. This product comes in two types: a type that capable of both color photography and fluorescein angiography (hereinafter referred to as FA photography); and "Type IA" capable of color photography, FA photography and indocyanine green angiography (hereinafter referred to as IA photography). This product is either equipped with or without an observation monitor used for observation purpose and display of a photographed image. This product comes in three types: a type that houses a digital photography unit for photographing an image; a type to which a commercial TV camera is attached; and a type to which a commercial digital single-lens reflex camera. A digital photography unit, a TV camera and a digital single-lens reflex camera are hereinafter generally referred to as an electronic photography device. A photographed image may be recorded on a commercial memory card built into an electronic photography device, or a connected commercial printer, or a personal computer (hereinafter referred to as a PC).

The provided text describes the 510(k) summary for the TOPCON Retinal Camera TRC-NW7SF MARK II. It does not contain information about acceptance criteria or a study that specifically addresses device performance in terms of clinical accuracy or diagnostic capabilities, especially in a way that would involve sample sizes, expert ground truth, or MRMC studies for AI devices. This submission predates the widespread regulatory evaluation of AI/ML-based medical devices.

Instead, the performance data provided focuses on:

• Conformance to international standards for safety and technical specifications. This is a common approach for traditional medical devices.
• Substantial equivalence to predicate devices. The claim is that the new device performs as safely and effectively as existing, legally marketed devices.

Therefore, many of the requested points cannot be answered based on the provided text.

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

1. Table of Acceptance Criteria and Reported Device Performance

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

• The provided document does not describe a test set or data provenance for a clinical performance study as one would typically expect for an AI/ML device. The "performance data" refers to compliance with safety and technical standards, not diagnostic accuracy based on patient images.

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

• Not applicable; no clinical performance study involving expert ground truth is described.

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

• Not applicable; no clinical performance study involving 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

• No MRMC study is mentioned. This device is a retinal camera, not an AI-assisted diagnostic tool as described in the context of MRMC studies with AI.

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

• Not applicable; this is a medical imaging device, not an algorithm being evaluated in a standalone capacity for diagnostic performance.

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

• Not applicable; the "ground truth" here is compliance with technical standards and equivalent performance to predicate devices, not clinical diagnostic accuracy.

8. The sample size for the training set

• Not applicable; this is not an AI/ML device that would require a training set in the sense of machine learning algorithms.

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

• Not applicable; no training set for an AI/ML algorithm is described.

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The IMAGEnet Professional PC Software System is a software program that is intended for use in the collection, storage and management of digital images, patient data, diagnostic data and clinical information from computerized diagnostic imaging devices through direct connection with the instruments or through computerized networks. The software system is indicated for use with retinal camera or digital camera imaging devices, including retinal cameras, non-mydriatic retinal cameras, and slit lamps.

The IMAGEnet Professional PC Software System is a computerized software system that collects, stores, and manages digital images of the retina and anterior segment of the eye. The IMAGEnet Professional PC Software System is compatible with retinal camera or digital camera imaging devices, including retinal cameras, non-mydriatic retinal cameras, and slit lamps. The IMAGEnet Professional PC Software System is installed in a Windows 2000 or Windows XP Compatible PC to automate the functions of image capture, database archival of images, and image processing. The software includes optional functions that allow the user to stitch multiple images together or estimate the desired laser treatment size for photodynamic therapy (PDT). The Topcon IMAGEnet Professional PC Software System is intended as a software program for the use in the management of digital images acquired from diagnostic instruments that capture images of the retina and anterior segment of the eye.

I am sorry, but the provided text does not contain the detailed information necessary to fully answer your request. The document is a 510(k) summary for the IMAGEnet Professional PC Software System, which is a software for managing ophthalmic images.

While it mentions "Software validation testing and image capture testing were performed on the IMAGEnet Professional PC Software System" and states "Test results for the IMAGEnet Professional Software Frorem demonstrated sufficient agreement with captured images," it does not provide the specific acceptance criteria, study details, sample sizes, ground truth establishment, expert qualifications, or adjudication methods that you requested. It primarily focuses on establishing substantial equivalence to predicate devices based on intended use and basic functionality, rather than detailed performance metrics.

Therefore, I cannot extract the following information from the given text:

1. A table of acceptance criteria and the reported device performance: This information is not provided.
2. Sample sized used for the test set and the data provenance: This information is not provided.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: This information is not provided.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: This information is not provided.
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: This device is for image management, not AI-assisted diagnosis, and therefore an MRMC study comparing human readers with and without AI assistance is not relevant or described.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The document describes a software system for image management, not an algorithm with standalone diagnostic performance.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): This information is not provided, as the validation focuses on capturing and managing images accurately, not diagnostic ground truth.
8. The sample size for the training set: This information is not provided.
9. How the ground truth for the training set was established: This information is not provided.

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The Topcon 3D OCT-1000 is a non-contact ophthalmic imaging system for the viewing and axial cross sectional imaging of posterior ocular structures. It is used for in vivo imaging of the retinal nerve fiber layer and optic disc. It is intended for use as a diagnostic device to aid in the detection and management of ocular diseases, including but not limited to macular edema and central serous retinopathy.

The components of the Topcon 3D OCT-1000 include a Main Unit, which houses three optical systems for observing and photographing the retina, a Power Supply Unit, a chin rest, a Spectroscope, and the ability to connect a personal computer for image viewing and analysis.

Here's a breakdown of the acceptance criteria and study details for the Topcon 3D OCT-1000 Optical Coherence Tomography System, based on the provided text:

Acceptance Criteria and Device Performance

Study Details

2. Sample Size and Data Provenance

• Test Set Sample Size: 55 images from 31 eyes. This included at least seven pairs each from subjects with normal eyes, macular holes, cystoid macular edema (CME), epiretinal membrane (ERM), and both dry and wet form age-related macular degeneration.
• Data Provenance: Not explicitly stated in terms of country of origin. The study appears to be a prospective collection of images specifically for this comparison, as it states "Topcon collected 55 images from 31 eyes... obtained using both the 3D OCT-1000 device and a predicate device." This suggests a controlled collection rather than a retrospective analysis of existing data.

3. Number and Qualifications of Experts for Ground Truth

• Number of Experts: Two graders.
• Qualifications: "Predefined diagnostic image criteria" were used, implying the graders were qualified to interpret these images against those criteria, but their specific qualifications (e.g., ophthalmologists, optometrists, years of experience) are not explicitly stated.

4. Adjudication Method for the Test Set

• The text states: "Paired images were independently graded by two graders using predefined diagnostic image criteria. In all of the 55 pairs of images, the graders (with the consensus score) demonstrated..." This indicates an agreement/consensus method, likely a 2-reader consensus where their independent gradings were reconciled to arrive at a "consensus score." The exact method of achieving consensus (e.g., discussion, third reader) is not detailed beyond "consensus score."

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

• No, a MRMC comparative effectiveness study was not explicitly conducted in the typical sense of measuring human reader improvement with and without AI assistance. This study was a direct comparison of image quality between two devices (the new device and a predicate) as graded by human readers, not an assessment of AI's augmentative effect on human performance.
• Effect Size of Human Readers with vs. Without AI: Not applicable, as this was not the design of the study.

6. Standalone Performance (Algorithm Only)

• Yes, a standalone performance study was implicitly done for the device itself. The study's primary goal was to demonstrate that the device (Topcon 3D OCT-1000), in isolation, produced images of comparable or superior diagnostic quality to the predicate device. The grading by human experts was used to evaluate the device's output, not the performance of an AI algorithm within the device. The device's performance was assessed based on the quality of the images it generated.

7. Type of Ground Truth Used

• Expert Consensus / Predefined Diagnostic Image Criteria: The ground truth for evaluating image quality was established by "predefined diagnostic image criteria" applied by two independent graders, whose scores were then subject to a "consensus score." This is a form of expert consensus based on established criteria.

8. Sample Size for the Training Set

• Not applicable/Not provided. The provided text describes a device comparison study for regulatory submission, not the development or validation of an AI algorithm. Therefore, there is no mention of a training set for an AI model.

9. How Ground Truth for the Training Set Was Established

• Not applicable/Not provided (see point 8).

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The Topcon Model TRC-NW200 Non-Mydriatic Camera is intended for use in capturing images of the retina and the anterior segment of the eye and presenting the data to the eyecare professional, without the use of a mydriatic.

The Topcon TRC-NW200 is a non-mydriatic ophthalmic camera that captures and displays images of the eye. The images are captured by using halogen illumination with an infrared filter for observation and a xenon flash bulb for photography. There is no laser illumination. Alignment dots and focusing bars assist the operator in properly positioning the camera. The operator presses a button on the top of the joystick to capture the image. The image is then displayed on the built-in LCD display or, if desired, transferred to a personal computer.

The provided text {0} to {4} describes a 510(k) submission for the Topcon TRC-NW200 Non-Mydriatic Retinal Camera. However, this document does not contain information regarding specific acceptance criteria, a study proving device performance against those criteria, or details about ground truth, sample sizes for testing/training, or expert involvement.

The 510(k) summary focuses on establishing substantial equivalence to predicate devices rather than providing performance metrics against predefined acceptance criteria.

Therefore, I cannot fulfill your request for the tables and detailed information you’ve asked for based on the provided text. The document primarily covers:

• Device Name, Classification, and Submitter Information
• Identification of Predicate Devices
• Description of the Device and its Intended Use
• A statement of Substantial Equivalence outlining that the device has the same intended use, indications, principles of operation, and technical characteristics as the predicates.
• FDA's response letter confirming the substantial equivalence determination and allowing the device to be marketed.
• Indications for Use Statement

There is no mention of specific performance metrics, clinical studies, or data analysis concerning the device's accuracy or effectiveness in capturing images of the retina. The focus is on demonstrating that it functions similarly to previously cleared devices.

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