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I-View Gold sensors are digital dental intraoral sensors intended to collect dental x-ray photons and convert them into electronic impulses that may be stored, viewed, and manipulated for diagnostic use by dentists.

The subject I-View Gold and Imagen Gold sensors are intraoral digital x-ray systems comprised of two components: (1) an intraoral detector which connects to a PC via a USB port: and (2) an Image Management Software package.

The subject comes in two sizes: Size 1 is 600mm² and Size 2 is 884mm² and two brand names.

Direct digital systems acquire images with a sensor that is connected to a computer to produce an image almost instantaneously following exposure.

This document describes the marketing clearance for the I-View Gold and Imagen Gold Dental Sensors (K200625). The submission focuses on demonstrating substantial equivalence to a legally marketed predicate device (EzSensor Classic, K153060), rather than providing detailed acceptance criteria and a standalone study proving the device meets those specific acceptance criteria for performance metrics like diagnostic accuracy.

The FDA's 510(k) clearance process primarily evaluates whether a new device is "substantially equivalent" to a legally marketed predicate device in terms of intended use, technological characteristics, and safety and effectiveness. It does not typically require the applicant to establish novel performance acceptance criteria or conduct a de novo clinical study to prove those criteria are met, especially for devices with well-understood technology and established clinical pathways like dental X-ray sensors.

Therefore, the requested information regarding "acceptance criteria" and "the study that proves the device meets the acceptance criteria" in the context of diagnostic performance (e.g., sensitivity, specificity, accuracy for a specific clinical task) is not found in this 510(k) summary. The document focuses on demonstrating that the new device functions similarly and is as safe and effective as the predicate based on bench testing (SSIX Report, electrical safety, EMC, software documentation) and comparison of technical specifications.

Here's a breakdown of what can be extracted about "acceptance" and "testing" from the provided document, framed within the substantial equivalence argument, and what information is not available:

Information Available/Inferred from the Document:

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

   • Acceptance Criteria (Implied for Substantial Equivalence): The implicit "acceptance criterion" is that the technological characteristics and performance are comparable to the predicate device (EzSensor Classic, K153060) to ensure equivalent safety and effectiveness.
   • Reported Device Performance (Comparative Metrics): The table Compares technological characteristics. The "performance" here refers to measured physical and technical parameters, not diagnostic accuracy. The reported values for the subject device are expected to be sufficiently similar to the predicate to establish equivalence.

   Characteristic	Acceptance Criteria (Implicit: Comparable to Predicate)	Reported Device Performance (Subject Device)	Predicate Device Performance
   Common Name	Intraoral Digital X-Ray Sensor	Intraoral Digital X-Ray Sensor	Intraoral Digital X-Ray Sensor
   Indications for Use	Same as predicate	Same as predicate	Same as subject
   Intended Use	Same as predicate	Same as predicate	Same as subject
   Principles of operation	Same as predicate ('X-ray radiation => scintillator => fiber optic => CMOS => electronics => PC')	Same as predicate	Same as subject
   Sensor Thickness (mm)	4.8 mm	4.8	4.8
   USB Module	Integrated USB 2.0 module	Integrated USB 2.0 module	Integrated USB 2.0 module
   Pixel Pitch (Full/Binning mode)	14.8 / 29.6	14.8 / 29.6	14.8 / 29.6
   DQE (6lp/mm, Full/Binning mode)	0.38 / 0.34	0.38 / 0.34	0.38 / 0.34
   MTF (3lp/mm, Full/Binning mode)	0.642 / 0.630	0.642 / 0.630	0.642 / 0.630
   Typical dose range (Incisor & Canine)	300 ~ 500	300 ~ 500	300 ~ 500
   Typical dose range (Molar)	400 ~ 600	400 ~ 600	400 ~ 600
   Standards of Conformity	Compliance with relevant IEC/ISO standards	Listed standards achieved	Listed standards achieved
   Biocompatibility	Not warranted (no patient contact)	Not warranted (no patient contact), single-use protective barrier used	Not warranted (no patient contact), single-use protective barrier used
   Electrical Safety & EMC	Compliance with IEC 60601-1, IEC 60601-1-2	Conforms to standards	Conforms to standards

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

   • Test Set Sample Size: Not applicable/Not specified for a clinical performance test. The "test set" here refers to the physical units subjected to bench testing (e.g., for electrical safety, EMC, SSIX report). The sample size for these engineering tests is not provided in this summary.
   • Data Provenance: The tests are "Non-Clinical Performance Data." There is no mention of patient data (images) or their provenance (country of origin, retrospective/prospective) because a clinical study was not presented for this 510(k) submission.

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

   • Not applicable. No clinical test set with ground truth established by experts is described, as this is a substantial equivalence submission relying on bench testing and comparison to a predicate, not a de novo clinical performance study for diagnostic accuracy.

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

   • Not applicable. No clinical test set requiring 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. This device is a digital X-ray sensor, not an AI-powered diagnostic aid. Therefore, no MRMC study or assessment of AI assistance to human readers was performed or presented.

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

   • Not applicable. This device is a hardware sensor with image acquisition and management software, not an algorithm for autonomous diagnostic performance.

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

   • Not applicable for clinical ground truth. The "ground truth" for the non-clinical tests would be defined by engineering specifications and reference standards (e.g., a calibrated measurement for DQE, MTF).

8. The sample size for the training set:

   • Not applicable. This is a hardware device with associated image processing firmware/software, not a machine learning model that requires a training set in the AI sense.

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

   • Not applicable. See point 8.

Summary of what's provided related to "proving" performance:

The document states "Bench tests were performed and the SSIX Report is shown in this submission. Additional certificates for the device are also within this submission." These tests (e.g., DQE, MTF, electrical safety, EMC) provide objective measurements of the device's physical and technical performance parameters, which are then compared to the predicate device to argue for substantial equivalence. The "proof" here is that these technical specifications are essentially identical to those of the cleared predicate device, and the device conforms to relevant safety and performance standards (IEC, ISO).

In a 510(k), especially for a device like this, the "acceptance criteria" for clearance are primarily:

• Same intended use as the predicate.
• Same technological characteristics as the predicate OR different technological characteristics that do not raise new questions of safety and effectiveness.
• Performance data (bench testing) demonstrating that the device is as safe and effective as the predicate.

This submission explicitly concludes: "The subject and the predicate device have the same intended use and the same technological features. I View Gold and Imagen Gold Sensors and share the same principles of operation, sensor technology, use the same USB connection to PC and use similar imaging firmware. The conclusion is that the subject device is as safe and effective as the predicate." The "study" proving this is the collection of non-clinical bench tests and the detailed comparative analysis of technical specifications presented in the submission.

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I-View dental sensor is used for a radiographic examination by a dental professional to assist in the diagnosing of diseases of the teeth, jaw and oral structures.

The subject device I View is an intraoral digital x-ray systems comprised of two components: (1) an intraoral detector which connects to a PC via a USB port; and (2) an Image Mangement Software package.

The subject devices comes in two sizes: Size 1 is 600mm² and Size 2 is 884mm².

The Size 1 sensor is also known as factory code S11684-12; Size 2 sensor is known as factory code S116845-12. I View and Imagen Sensor will both have Size 1 and Size 2. Two different trade names are for marketing purposes.

The provided text is a 510(k) summary for the "I View and Imagen Sensor" dental x-ray system, which is a Class II medical device. The document states that the subject device is substantially equivalent to a predicate device, the "QuickRay HD." The primary method used to demonstrate this equivalence is by asserting that the subject device is identical in hardware and firmware to the predicate device, with only the software package being different (though its functionality is claimed to be the same).

Here's an analysis of the acceptance criteria and the study as described in the document:

1. Table of Acceptance Criteria and Reported Device Performance

Because the device is claimed to be identical to a predicate that was already cleared, the acceptance criteria are largely linked to demonstrating this identity and conformity to relevant standards rather than establishing new performance metrics.

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

The document does not describe a new, specific "test set" in terms of patient images or cases for the subject device. Instead, it relies on:

• Clinical images from the predicate device: The text states, "Clinical images were examined by Dr. Parham... and found to be diagnostically relevant and reliable. These tests were provided for the predicate device submission..."
• The provenance of these predicate clinical images is vague, only mentioning "Dr. Parham, a qualified practitioner in Ormond Beach, FL." It does not specify the country of origin of the data nor whether it was retrospective or prospective.

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

• The document mentions one expert: "Dr. Parham, a qualified practitioner in Ormond Beach, FL."
• Qualifications: Described as a "qualified practitioner." No further details on specific certifications (e.g., dentist, radiologist), years of experience, or specialty are provided.

4. Adjudication Method for the Test Set

• None specified for the subject device. The reliance is on a single "qualified practitioner" for the predicate device's clinical images. There's no mention of a consensus or multi-reader adjudication process described for either the predicate's original evaluation or for the current submission.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• No, an MRMC comparative effectiveness study was not done. The submission establishes substantial equivalence primarily through technical and functional identity to a predicate device, not through a comparative clinical study. Therefore, no effect size of human readers improving with or without AI assistance is reported.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study Was Done

• No, a standalone study was not done as the device itself is a digital x-ray sensor for capturing images, not an AI algorithm for interpreting them without human involvement. The "Deep-View" software is an "image management software package" that assists dental professionals in diagnosing, implying human-in-the-loop performance. While the software has its own prior clearance (K160386), this document doesn't detail a standalone performance study for the interpretation aspect within this submission.

7. The Type of Ground Truth Used

• For the clinical performance validation (from the predicate device), the ground truth appears to be based on expert assessment/consensus (from Dr. Parham). The statement "found to be diagnostically relevant and reliable" implies an expert opinion as the ground truth. There is no mention of pathology, long-term outcomes data, or other objective measures for ground truth.

8. The Sample Size for the Training Set

• The document does not describe a training set in the context of machine learning or AI algorithms for image interpretation for this device. The software "Deep-View" is an image management software. If the term "training set" refers to data used to develop the core firmware/hardware for image acquisition, that information is not provided or deemed unnecessary given the equivalence claim to the predicate.

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

• As no training set (in the ML/AI sense) is described, this information is not applicable and not provided in the document. The device is an image acquisition hardware, not an image interpretation AI, making the concept of a "training set" for ground truth determination irrelevant to this 510(k) submission.

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QuickRay HD is used for a radiographic examination by a dental professional to assist in the diagnosing of diseases of the teeth, jaw and oral structures.

Radiographic examination to assist with diagnosis of diseases of the teeth, jaw, and oral structure.

The QuickRay HD dental sensor is intended to replace film and to capture an intraoral x-ray image, when exposed to X-rays, for dental diagnostic purposes.

The subject QuickRay HD are intraoral digital x-ray systems comprised of two components: (1) an intraoral detector which connects to a PC via a USB port; and (2) an Image Mangement Software package.

The subject devices comes in two sizes: Size 1 is 600mm² and Size 2 is 884mm².

QuickRay HD, Size 1 is also known as factory code S11684-12; QuickRay HD, Size 2 is also known as factory code S116845-12.

The type of x-ray systems that integrate with the QuickRay HD sensor are wall-mounted xray generators (both AC and DC) with a tube current between 1 and 15 mA inclusive, and with a tube voltage between 50 and 100 kV inclusive, with in-built controls to set exposure parameters. Generators allow variable mA/kV to be selected, all will control the exposure time.

This device and software cannot act as an x-ray generator controller. All control of x-ray generation is done by controls built into the generator itself. There is no connection between the subject device and the x-ray generator. The subject device does not control the generator, it is a receiver.

The Xray Vision software by Apteryx is a Windows based image management database/software primarily used by dentists to acquire, enhance, store, communicate, print, recall and display digital images.

Here's an analysis of the provided text to extract information related to acceptance criteria and the study proving the device meets them. It's important to note that this document is a 510(k) summary for a premarket notification, which typically focuses on demonstrating substantial equivalence to a predicate device rather than presenting a full clinical trial. As such, some of the requested information (like detailed MRMC studies or large-scale multi-expert ground truthing) may not be explicitly present or required for this type of submission.

The device in question is the QuickRay HD Intraoral Sensor.

Acceptance Criteria and Device Performance Study for QuickRay HD Intraoral Sensor

Context: The QuickRay HD Intraoral Sensor is an intraoral digital X-ray system intended for radiographic examination to assist in diagnosing diseases of the teeth, jaw, and oral structures. The 510(k) submission primarily relies on demonstrating substantial equivalence to a predicate device (Opteo, K133271) and an identical device cleared later (EDLENi Intra-oral Sensor, K150823), rather than extensive new clinical performance studies, which is typical for Class II dental imaging devices.

1. Table of Acceptance Criteria and Reported Device Performance

For this specific 510(k) submission, the "acceptance criteria" are implied by the claim of substantial equivalence to the predicate device, meaning the QuickRay HD must perform comparably or better than the predicate, especially in terms of image quality and safety. The performance is assessed through bench testing and by comparing technological characteristics.

Note: The document explicitly states that the EDLENi Intra-oral Sensor (K150823) is identical to the QuickRay HD, providing further support for substantial equivalence.

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

• Test Set Sample Size: The document does not specify a quantitative "test set sample size" in terms of number of patients or images for a comparative clinical study. The performance assessment is primarily based on:
  • Bench Testing: Conformance to standards (IEC 62220-1 for performance, IEC 60601-1/1-2 for electrical/EMC, IEC 60529 for IP Code). These involve standardized phantom or controlled laboratory tests rather than patient images as a "test set."
  • Clinical Image Examination: "Clinical images were examined" by Dr. Parham. The number of images or cases examined is not specified.
• Data Provenance: The document does not explicitly state the country of origin for the "clinical images" examined by Dr. Parham, but given the location of Dr. Parham (Ormond Beach, FL), it implies the data is from the United States. The study type appears to be retrospective in nature ("clinical images were examined"), rather than a prospectively designed clinical trial.

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

• Number of Experts: Only one expert is explicitly mentioned: "Dr. Parham".
• Qualifications of Experts: Dr. Parham is described as "a qualified practitioner in Ormond Beach, FL." No further specific qualifications (e.g., years of experience, specific board certifications like radiologist) are provided in this summary, other than the implication of being a dental professional.

4. Adjudication Method for the Test Set

• Adjudication Method: None explicitly stated or implied. The assessment was done by a single "qualified practitioner."

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• MRMC Study: No, an MRMC comparative effectiveness study was not conducted or reported in this 510(k) summary. The submission relies on bench testing and a single expert's review of clinical images to demonstrate substantial equivalence, not a direct human reader performance comparison with and without AI assistance. Therefore, no effect size for human readers improving with AI assistance is provided.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

• Standalone Performance: The QuickRay HD is an imaging sensor, not an AI algorithm. Its "performance" is inherently tied to its ability to capture images suitable for human diagnosis. Therefore, the concept of a "standalone (algorithm only)" performance study doesn't directly apply here in the typical AI sense. The bench tests (DQE, MTF, NNPS) represent the inherent technical performance of the device itself (analogous to "standalone" in a hardware context) before image interpretation by a human.

7. The Type of Ground Truth Used

• Type of Ground Truth: For the "clinical images," the ground truth was expert consensus / expert opinion, specifically from "Dr. Parham," who found them "diagnostically relevant and reliable." For the technical performance aspects (resolution, DQE, etc.), the ground truth was based on physical measurements and conformance to established international standards (e.g., IEC 62220-1).

8. The Sample Size for the Training Set

• Training Set Sample Size: The QuickRay HD is a hardware device (intraoral sensor) with associated firmware and image management software. It is not an AI/ML algorithm that is "trained" on a dataset in the typical sense. Therefore, there is no stated training set sample size. The electronics and firmware are reported to be from Hamamatsu and the software from Apteryx, and these components have presumably undergone their own development and testing processes, but no specific training data for the sensor itself for a machine learning purpose is relevant or mentioned.

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

• Ground Truth for Training Set: As the device is not an AI/ML algorithm requiring a training set, the concept of "ground truth for the training set" is not applicable in this context. The "truth" for this device lies in its physical and electrical engineering specifications and its ability to produce images that meet diagnostic quality standards established by experts and industry benchmarks.

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