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NFC-600 is a non-contact, high resolution digital imaging device which is suitable for photographing, displaying and storing images of the retina and external areas of the eye to be evaluated under non-mydriatic conditions.

NFC-600 is indicated for in-vivo viewing of the posterior and external area of the eye and the images are intended for use as an aid to clinicians in the evaluation, diagnosis and documentation of ocular health.

NFC-600 is a non-contact fundus camera for capturing, storing and displaying the color fundus images with 12 million pixels. It was designed a non-contact, images provide high resolution digital imaging device, auto 3D tracking, auto exposure, and auto capture functions, a portable device with auto-focusing technique and easy operation.

Different from the all-in-one design (built-in PC module) of previous cleared product. NFC-600 removed the embedded computer module and designed to use the USB 2.0 port which is located behind the base to connect to the user's PC or laptop, making the device smaller and lighter to achieve a portable design. The dimensions of NFC-600 is about 330mm (L)x 260mm (W)x 330mm (H) and the whole weight not more than 12 kg.

Same as the predicate device, NFC-600 uses NIR LED as illumination during alignment to the retina of patients' eyes. All operations are performed through the proprietary software, which will be installed in the user's PC or laptop to capture, store, view, retrieve, and export ophthalmic images.

The provided text describes a 510(k) premarket notification for the Crystalvue Medical Corporation's NFC-600 Automated Portable Retinal Camera. This submission aims to demonstrate substantial equivalence to a legally marketed predicate device, the NFC-700 Non-Mydriatic Auto Fundus Camera (K182199).

Crucially, the provided text does not contain any performance data from a clinical study or a standalone algorithm performance evaluation to demonstrate that the device meets specific acceptance criteria based on accuracy metrics. Instead, it focuses on demonstrating substantial equivalence by proving that the modifications made to the NFC-600 (primarily changing from an embedded computer to an external PC connection) do not negatively impact its safety or effectiveness compared to the predicate device.

Therefore, I cannot populate a table of acceptance criteria and reported device performance from this document, nor can I provide details on sample size, data provenance, expert ground truth establishment, or clinical study design elements (MRMC, standalone performance, training set details) as these are not present in the provided 510(k) summary.

The document indicates that the acceptance criteria are met by demonstrating equivalence in several key areas:

• Intended Use / Indications for Use: The NFC-600 has the exact same intended use and indications for use as the predicate device.
• Operating Principle: The optical design and operating principle are identical to the predicate device.
• Technological Characteristics and Performance: Key characteristics like image resolution (12 MP), eye fixation (internal 10 points), light source (NIR LED/White LED), alignment (fully automatic 3D tracking), field of view (45°), minimum pupil size (4.0 mm), working distance (25 mm), and focus adjustment range are all identical to the predicate.
• Materials: Contact materials with patients (chinrest, forehead rest) are the same.
• Safety and Effectiveness: Non-clinical tests (electrical safety, electromagnetic compatibility) were conducted to ensure the changed control circuit and PCB control board do not affect safety and effectiveness. These tests complied with relevant consensus standards (IEC 60601-1:2005, IEC 60601-1-2:2014). The optical design complies with ISO 15004-1:2006, ANSI Z80.36:2016, and ISO 10940:2009. Biocompatibility was evaluated according to ISO10993 series, and the software was validated according to IEC 62304:2015.

Summary of Device Performance Demonstration as per the provided text:

The study proving the device meets the acceptance criteria is not a clinical performance study measuring diagnostic accuracy. Rather, it is a technical and design equivalence study designed to demonstrate that the modified device (NFC-600) is as safe and effective as its predicate (NFC-700) despite a design change (moving the embedded computer to an external PC).

1. Table of Acceptance Criteria and Reported Device Performance: This information is not provided in the typical format of a clinical performance study. Instead, the acceptance criteria are implicitly met by demonstrating sameness or compliance with regulatory standards for the modified components.

   Acceptance Criterion implicitly met by Equivalence to Predicate	Reported Device Performance (NFC-600)
   Intended Use / Indication for Use	Identical to predicate: Non-contact, high resolution digital imaging device suitable for photographing, displaying, and storing images of the retina and external areas of the eye under non-mydriatic conditions. Indicated for in-vivo viewing of the posterior and external area of the eye; images aid clinicians in evaluation, diagnosis, and documentation of ocular health.
   Operating Principle	Identical to predicate: Based on monocular indirect ophthalmoscopy; uses NIR LED for observation, white LED for flash; automatic 3D tracking, autofocus, and capture functions.
   Technological Characteristics	Identical to predicate:

• Image Resolution: 12 MP
• Eye Fixation: Internal 10 points
• Light Source: Observation (NIR LED), Flash (White LED)
• Alignment: Fully automatic 3D tracking
• Field of View: 45°
• Minimum Pupil Size: 4.0 mm
• Working Distance: 25 mm
• Focus Adjustment Range: -15D to +10D (without compensation lens), -30D to -10D or +5D to +30D (with compensation lens) |
  | Materials (Patient Contact) | Identical to predicate: Chinrest (ABS), Forehead rest (TPE). Biocompatibility evaluated according to ISO10993 series. |
  | Electrical Safety & EMC | Complies with IEC 60601-1:2005 (MOD) and IEC 60601-1-2:2014. (Test conducted due to control circuit/PCB modification). |
  | Optical Safety Standards | Complies with ISO 15004-1:2006, ANSI Z80.36:2016, and ISO 10940:2009. (Optical design is identical to predicate, these were likely part of initial predicate clearance). |
  | Software Validation | Identical software to predicate, validated according to IEC 62304:2015. |
  | Physical Dimensions/Weight | Changed from predicate, but this is the nature of the modification, making it smaller and lighter (W260 x D330 x H330 mm, 12 Kg) due to external PC. This is presented as an intended modification, not a performance criterion to be met but a design change assessed for its impact on safety/effectiveness (which was deemed negligible). |

2. Sample sizes used for the test set and the data provenance: Not applicable. The "test set" here refers to non-clinical tests (electrical, EMC, optical performance assessments on the device itself) rather than a clinical dataset of patient images. Data provenance is not mentioned as clinical data was not used for this specific submission's demonstration of equivalence.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No clinical ground truth was established for this 510(k) submission, as it focused on demonstrating substantial equivalence through technical testing and design comparison.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable. No clinical test set requiring adjudication was used.

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 applicable. This submission is for an ophthalmic camera, not an AI-powered diagnostic device, and no MRMC study was conducted.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an AI algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable to a clinical ground truth. The "truth" demonstrated here is that the modified device's performance characteristics and safety profile are equivalent to its predicate, established through engineering tests and direct comparison of specifications.

8. The sample size for the training set: Not applicable. This is a hardware device submission, not an AI algorithm requiring a training set.

9. How the ground truth for the training set was established: Not applicable.

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NFC-700 is a non-contact, high resolution digital imaging device which is suitable for photographing, displaying and storing images of the retina and external areas of the eye to be evaluated under non-mydriatic conditions. NFC-700 is indicated for in-vivo viewing of the posterior and external area of the eye and the images are intended for use as an aid to clinicians in the evaluation, diagnosis and documentation of ocular health.

The NFC-700 is a non-contact fundus camera for capturing, storing and displaying the color fundus images with 12MP. It was designed a non-contact, high resolution digital imaging device, auto 3D tracking, fast and easy to use retinal imaging system and provide images of the eye as an aid to clinicians in the diagnosis of diabetic retinopathy, AMD, glaucoma and other retinal diseases. NFC-700 was designed as an All-in-one system with full auto-focusing technique and easy operation. The large 10.1" touch screen makes it easy to control all of the operating procedures and makes the measurement and image check easily. NFC-700 uses NIR LED as illumination during alignment to the retina of patients' eyes, users can just touch the center of the pupil on the screen to capture the image. There also some interface located at the bottom of the device such as USB, HDMI, Ethernet make user to store, retrieve, archive and share the digital images by USB or LAN.

Here's a breakdown of the acceptance criteria and the study details for the NFC-700 non-mydriatic auto fundus camera, based on the provided text:

Acceptance Criteria and Device Performance

Study Details

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

   • Test Set Sample Size: 119 patients (eyes).
   • Data Provenance: The text does not explicitly state the country of origin. It describes a "single-site study" and mentions "Consented subjects will undergo ophthalmic examination." This suggests it was a prospective study.

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

   • Number of Experts: One ophthalmologist.
   • Qualifications: "The ophthalmologist reviews all fundus images..." (No further specific qualifications or years of experience are provided beyond "ophthalmologist").

3. Adjudication method for the test set:

   • The text describes a single ophthalmologist reviewing and grading the images. There is no mention of an adjudication method for discrepancies, implying either none was used or no discrepancies requiring adjudication were present (unlikely in a subjective grading process).

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 comparative effectiveness study was not done. This study compared the image quality of the investigational device (NFC-700) to a reference camera (FundusVue), not the performance of human readers with or without AI assistance. The NFC-700 is a camera, not an AI diagnostic tool.

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

   • Yes, in spirit. The "Performance Data" section primarily details the standalone performance of the NFC-700 camera in terms of image quality and technical specifications. The "Clinical Testing" evaluated the camera's ability to produce diagnostically useful images, which is a standalone assessment of the camera itself. It's important to note this is for the camera's image output, not an AI algorithm's diagnostic output.

6. The type of ground truth used:

   • Expert Consensus (Single Expert): The ground truth for image quality assessment was established by a single ophthalmologist's review using a 5-point grading scale and assessment against clinically significant features.

7. The sample size for the training set:

   • The document does not provide information regarding a training set. This is a fundus camera, not an AI algorithm that typically requires a large training set for model development. The mentions of "Software verification and validation testing" relate to the camera's control software, not an image analysis AI.

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

   • Since no training set information is provided, how its ground truth was established is not applicable here.

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The TonoVue is a non-contact tonometer that is intended to measure the intraocular pressure of the human eye in vivo.

The TonoVue is a non-contact tonometer that intended to measure the intra-ocular pressure of the eye in patients with less than 3 diopters of corneal astigmatism.

TonoVue Tonometer is designed to non-contact tonometer (NCT) that measures the intraocular pressure (IOP) by delivering a soft air puff without contacting eyes directly. It's designed as a full auto-alignment and All-In-One desktop type medical device with built-in thermal line printer. The dimensions of whole device are about 500mm (H) x 260mm (W) x 500mm (L). The AC power input port and a USB port are set at the bottom side of the device, but the USB port only for engineering use. Based on the Imbert-Fick principle, the IOP is calculated by dividing the amount of air pressure into the area of applanated surface. TonoVue utilizes a rapid air puff to apply force for flattening the cornea of human eye, and an advanced electro-optical system to monitor its deformation. The puff force increases until the cornea is applanated over the predetermined area and detected by the pressure sensor inside TonoVue, and the IOP can be calculated.

The provided text describes the acceptance criteria and a clinical study conducted for the TonoVue Non-Contact Tonometer.

Here's an analysis of the information requested:

1. Table of Acceptance Criteria and Reported Device Performance

Additional performance claims:

• Accuracy and Reproducibility: Bench testing proved that the TonoVue non-contact tonometer's IOP measurement result meets product specifications.
• Electrical Safety & EMC: Complies with IEC 60601-1 (safety) and IEC 60601-1-2 (EMC).
• Biocompatibility: Complies with ISO 10993-1 standard.
• Software Validation: Software verification and validation testing were conducted as recommended by FDA Guidance- "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices".

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

• Sample Size: 120 patients.
• Data Provenance: The text does not explicitly state the country of origin or whether the study was retrospective or prospective. Given it's a clinical testing section and refers to "patients," it's implicitly a prospective clinical study.

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

The document does not specify the number of experts or their qualifications for establishing ground truth, nor does it explicitly mention "experts" in the context of ground truth for the clinical study. It refers to a "reference tonometer reading," which would imply an accepted standard for measuring IOP.

4. Adjudication method for the test set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1). The criteria focus on the agreement between the test tonometer and a "reference tonometer."

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, an MRMC comparative effectiveness study involving human readers and AI assistance was not done. The device is a standalone non-contact tonometer, not an AI-assisted diagnostic tool for human readers.

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

Yes, the clinical testing describes the standalone performance of the TonoVue Non-Contact Tonometer, comparing its readings to a "reference tonometer." This is an algorithm-only performance assessment in measuring IOP.

7. The type of ground truth used

The ground truth was established by readings from a "reference tonometer" as per the ISO 8612:2009 standard. This implies a standard, accepted method for measuring intraocular pressure.

8. The sample size for the training set

The document does not mention a "training set" or any machine learning/AI components that would require one. The validation described is for a medical device that mechanically measures IOP.

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

Not applicable, as no training set for a machine learning model is mentioned.

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