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The Z-Ray digital radiography system was designed for the sole purpose of capturing radiographic images of teeth and the surrounding structures limited to the oral cavity. This device should be used under the direction of a licensed Dentist when it is deemed necessary to perform a radiographic series of a patient for diagnostic purposes.

The Zuma Dental Z-ray x-ray image sensor is a fully integrated CMOS photodiode array specifically designed for dental radiography. The sensor is available in two image sizes that correspond to a #2 size and a #1 size dental film. Each consists of a matrix of silicon photodiodes on 22.5 um centers. An integrated scintillator screen converts x-ray photons to visible light sensed by the silicon photodiodes. A rugged thermoplastic enclosure, with rounded corners for patient comfort, protects the sensor from everyday handling and cleaning. The CMOS sensor connects directly to a USB/PC connection without the need for an intermediate electrical interface. Zuma Z-Ray works with standard dental extra-oral x-ray sources without connection to the x-ray source. Zuma Z-Ray captures an image automatically upon sensing the external x-ray source and after completion of the x-ray procedure, transfers the image to an imaging software program on the PC for diagnostic evaluation.

The provided text describes a 510(k) premarket notification for the Zuma Dental Z-Ray Intra-Oral Digital Radiography System. The document focuses on demonstrating substantial equivalence to predicate devices rather than proving the device meets specific performance acceptance criteria through a clinical study with detailed metrics like sensitivity, specificity, or reader performance.

The submission claims that the Z-Ray system is "as safe and effective as the referenced predicate devices" (Schick Computed Oral Radiography System K072134 and Dexis Sensor K090458) due to "minimal technological differences."

Here's an analysis of the provided information relative to your request:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative acceptance criteria for image quality or diagnostic performance (e.g., minimum sensitivity, specificity, or reader agreement percentages). Instead, it relies on a qualitative assessment of "diagnostic quality images" and equivalence to predicate devices.

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

The document refers to "in-vitro bench testing" and a "test protocol for comparison evaluation" but does not specify the sample size for the test set (number of images or cases). The data provenance is also not specified, although "in-vitro bench testing" implies a controlled laboratory setting rather than patient data from a specific country or a retrospective/prospective study.

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

The document mentions "qualified examiners" who "concluded and certified that the diagnostic images produced by the Z-Ray System are equivalent to those produced by the predicate device." However, it does not specify the number of experts or their qualifications (e.g., "radiologist with 10 years of experience").

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1) for establishing ground truth or confirming the equivalence of diagnostic images. The examiners "concluded and certified," suggesting a consensus or independent assessment, but the process is not detailed.

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 document describes bench testing primarily aimed at demonstrating substantial equivalence in performance, not a clinical trial evaluating human reader improvement with or without AI assistance.

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

The Z-Ray system is an intra-oral digital radiography system, which is a hardware device for capturing images. It is not an AI algorithm. Therefore, the concept of a "standalone (i.e., algorithm only without human-in-the-loop performance)" study does not apply to this device in the traditional sense of AI performance evaluation. The "performance" being evaluated is of the image capture hardware itself.

7. The Type of Ground Truth Used

The ground truth or comparison standard used was the diagnostic image quality produced by a predicate device (Schick CDR K072134) and the assessment of "diagnostic quality images" by "qualified examiners." This is an expert consensus/comparison-based ground truth related to image fidelity and diagnostic utility, rather than pathology, outcomes data, or a pre-defined objective reference standard.

8. The Sample Size for the Training Set

The Z-Ray system is an image capture device, not an AI model that requires a "training set" in the context of machine learning. Therefore, this question is not applicable. The document describes a "Summary of Bench Test" which would be more akin to a validation or test set for the hardware's performance.

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

As stated above, this question is not applicable as the device is not an AI model requiring a training set.

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The Computed Oral Radiology System is indicated for patients undergoing an intra-oral dental x-ray examination. It produces instant, digital, intra-oral images of a patient's mouth while reducing the necessary x-ray dosage.

The device and its predicates are small digital imaging receptors that may be used in place of dental x-ray film. The images are displayed on a computer workstation. The modified device uses wireless IEEE 802.11 b/g protocol for image data transfer and control signal transfer to and from the Power and Transceiver (PAT) and the host computer. A rechargeable battery power source is also included in the PAT. A Counter Top Dock (CTD) has been added to this system. The CTD is a support device that provides charging power to the PAT and is used to provide a temporary wired connection, via USB, from the host computer to the PAT to allow initial configuration to the host wireless network.

This 510(k) summary does not contain the detailed information necessary to fully answer all aspects of your request regarding acceptance criteria and the comprehensive study that proves the device meets those criteria. The provided document is primarily a summary for a 510(k) clearance, which focuses on demonstrating substantial equivalence to a predicate device rather than detailing extensive performance studies with specific acceptance criteria.

However, based on the information provided, here's what can be extracted and inferred:

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

The document does not explicitly state quantitative acceptance criteria or detailed performance metrics. The submission focuses on the modification of an already cleared device (K072134) to incorporate wireless functionality. Therefore, the "acceptance criteria" are mostly implicit in demonstrating that the wireless modification does not degrade the performance or safety of the existing device and maintains substantial equivalence to the predicate.

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 provided in the 510(k) summary. The document mentions "Testing and design validation," but does not specify sample sizes, data provenance (e.g., country of origin), or whether these tests were 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)

This information is not provided in the 510(k) summary. It's unlikely that such a detailed ground truth establishment would be required or documented in a 510(k) for a modification focused on wireless connectivity, unless there were specific concerns about diagnostic image quality degradation, which are not raised.

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

This information is not provided in the 510(k) summary.

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 is not applicable to this submission. The device is a digital imaging receptor (X-ray sensor) and associated software for displaying images. It is not an AI-assisted diagnostic tool designed to improve human reader performance.

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

This is not applicable in the context of an AI algorithm. The device, the Computed Oral Radiology System, is an imaging acquisition and display system. Its primary role is to provide images, not to perform independent diagnoses via an algorithm.

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

This information is not provided and likely not relevant for a 510(k) focusing on a wireless connectivity modification for an imaging device. The "ground truth" for the performance of such a device generally relates to objective image quality metrics (resolution, signal-to-noise ratio, contrast) and functional performance, rather than diagnostic accuracy against a clinical ground truth.

8. The sample size for the training set

This is not applicable in the context of a traditional "training set" for machine learning. The device is not described as involving machine learning or AI that would require a distinct training set. The "training" for this type of device would refer to internal development and testing, not an AI training data set.

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

This is not applicable as there is no mention of a training set for an AI algorithm.

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The EzSensor is used to collect dental x-rays photons and convert them into electronic impulses that may be stored, viewed and manipulated for diagnostic use by dentists.

The EzSensor is a solid state x-ray imager designed for dental radiographic applications. The EzSensor provides digital image capture for conventional film/screen radiographic dental examinations. The device is used to replace radiographic film/screen systems in general dental diagnostic procedures. The captured digital image is transferred to Personal Computer via USB interface port.

The provided 510(k) summary (K090526) describes a new dental X-ray imager, EzSensor, seeking substantial equivalence to a predicate device, Schick's CDR (K072134). However, the document primarily focuses on demonstrating device characteristics and safety/performance testing in comparison to the predicate, rather than providing details of a clinical study with specific acceptance criteria and outcome data for the EzSensor's diagnostic performance for the purposes of this request.

Therefore, many of the requested sections below cannot be fully populated as the document does not contain the detailed clinical study information.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The 510(k) summary does not explicitly state acceptance criteria in terms of diagnostic performance (e.g., sensitivity, specificity, accuracy) for the EzSensor. It focuses on demonstrating substantial equivalence to the predicate device through technical specifications and safety/performance testing.

The document mentions "Electrical, mechanical, environmental safety and performance testing according to standard EN/IEC 60601-1 was performed, and EMC testing was conducted in accordance with standard EN/IEC 60601-1-2(2001). All test results were satisfactory." and "Software testing and validation were done according to written test protocols established before testing was conducted. Test results were reviewed by designated technical professionals before software proceeded to release. Test results support the conclusion that actual device performance satisfies the design intent." However, these refer to technical and safety performance, not diagnostic efficacy.

The comparison table provided in the document focuses on technical specifications between the predicate and proposed device:

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

The document does not describe a clinical test set or data provenance for a diagnostic performance study. The testing mentioned relates to electrical, mechanical, environmental, and software validation.

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

Not applicable, as no diagnostic performance test set is described.

4. Adjudication method for the test set

Not applicable, as no diagnostic performance test set 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. The device is an imaging sensor, not an AI-assisted diagnostic tool as understood in current contexts.

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

The device is a digital X-ray sensor, which requires human interpretation. Standalone "algorithm only" performance would not be relevant in the context of this device as described.

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

Not applicable, as no diagnostic performance study is described. The "ground truth" used for technical testing would be established standards and specifications for electrical, mechanical, and software functionality.

8. The sample size for the training set

Not applicable. The device is a hardware sensor. While it involves software, the document does not describe machine learning or AI models that would typically require a "training set" in the diagnostic performance sense. The software validation mentioned refers to standard software engineering practices.

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

Not applicable, for the reasons stated above.

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The DEXIS sensor is a USB-driven digital sensor which is intended to acquire dental intra-oral radiography images. The DEXIS sensor shall be operated by healthcare professionals, who are educated and competent to perform the acquisition of dental intraoral radiographs. The DEXIS sensor can be used either in combination with special positioning devices to facilitate positioning and alignment with the x-ray beam or it may also be positioned by hand with the assistance of the patient.

The DEXIS sensor is an indirect converting x-ray detector, e.g. incident x-rays are converted by a scintillating material into (visible) light, this light is coupled optically to a light detection imager based on CMOS technology.

The design of the sensor assembly supports the automatic detection of the incident x-rays to generate digital images for dental intra-oral applications.

The DEXIS sensor supports USB 2.0 and USB 1.1 connectivity to personal computers using a dedicated electronic assembly and a sensor software driver.

The provided text is a 510(k) Summary for the DEXIS Sensor, a digital X-ray device. This document focuses on demonstrating substantial equivalence to predicate devices rather than proving the device meets specific acceptance criteria through a clinical study.

Therefore, the document does not contain the information requested regarding acceptance criteria and a study proving the device meets them. It doesn't detail:

1. A table of acceptance criteria and reported device performance.
2. Sample sizes or data provenance for a "test set."
3. Number or qualifications of experts for ground truth establishment.
4. Adjudication method for a test set.
5. Multi-Reader Multi-Case (MRMC) comparative effectiveness study, or effect size of human improvement with AI.
6. Standalone performance of an algorithm without human-in-the-loop.
7. Type of ground truth used (expert consensus, pathology, outcomes data, etc.) for a study.
8. Sample size for a training set.
9. How ground truth for a training set was established.

Instead, the document asserts substantial equivalence by comparing the DEXIS Sensor's characteristics and intended use to two legally marketed predicate devices: Schick Technologies, CDR (K072134) and Suni Medical Imaging, Inc., SuniRay II Digital Radiographic System (K070219).

The key comparison points in the "Substantial Equivalence" table are:

• Indications for Use: All three devices are for acquiring dental intra-oral radiography images, to be operated by healthcare professionals.
• Number of Sensors: DEXIS Sensor has 1, CDR has 3, SuniRay II has 2.
• Sensor Size (mm): DEXIS is 30 x 39; CDR has sizes 31 x 22, 37 x 24, 43 x 30; SuniRay II has sizes 39.5 x 26, 43.5 x 31.5.
• Technology: All three use CMOS.
• Interface to PC: All three use USB.
• Dynamic Range: DEXIS Sensor has 16,384:1; both predicates have 4096:1. (The DEXIS Sensor exceeds the predicate devices in this specification, which is generally considered a positive attribute.)
• Sensor Cable Length (m): DEXIS is 2.8; CDR is 2; SuniRay II is 1.

The conclusion drawn in the document is that the DEXIS Sensor is "substantially equivalent in intended use and technical characteristics" to the predicate devices. This type of submission does not typically include the detailed clinical study information requested.

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