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EzSensor T, Intra-oral Imaging System, is 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.

EzSensor T is a solid state x-ray imager designed for dental radiographic applications. EzSensor T 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.

Here's an analysis of the provided text regarding the EzSensor T device, focusing on acceptance criteria and study details:

Interpretation of the Document:

The provided document is a 510(k) summary for the EzSensor T, an intra-oral imaging system. It aims to demonstrate substantial equivalence to a predicate device, not necessarily to independently prove performance against a set of predefined clinical acceptance criteria using a standalone clinical study. The "acceptance criteria" here largely refer to demonstrating the new device's performance is comparable to or better than the predicate device and meets relevant safety and performance standards.

The document emphasizes non-clinical and clinical considerations according to FDA Guidance "Guidance for the Submissions of 510(k)'s for Solid State X-ray Imaging Devices". This implies that the 'study' likely involved technical performance tests and comparative analyses against the predicate, rather than a prospective clinical trial with specific diagnostic accuracy endpoints.

Acceptance Criteria and Reported Device Performance

Note: The document does not explicitly state quantitative "acceptance criteria" in the typical sense of diagnostic metrics (e.g., sensitivity, specificity, AUC) for a clinical study. Instead, it focuses on demonstrating equivalence to a predicate device based on technical specifications and adherence to safety and performance standards. The "reported device performance" is primarily a comparison of technical characteristics to the predicate.

Study Details

Given the nature of a 510(k) summary for substantial equivalence, especially for an imaging device replacing another with similar function, the "study" is primarily a series of non-clinical technical tests and a comparative analysis against the predicate, guided by FDA regulations. It is not presented as a traditional clinical trial.

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

   • Test Set Sample Size: Not explicitly stated as a 'test set' with a specific number of images or patients for diagnostic accuracy assessment. The "all test results were satisfactory" refers to engineering and performance tests.
   • Data Provenance: Not applicable in the context of a retrospective/prospective clinical data set for diagnostic performance. The data provenance is from laboratory and engineering testing.

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

   • Not applicable. The document does not describe a study involving expert readers establishing ground truth for a diagnostic test set. The focus is on technical performance and equivalence.

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

   • Not applicable. There is no mention of a diagnostic test set requiring adjudication in this summary.

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 performed or mentioned. The device is a direct-capture digital X-ray sensor, not an AI-powered diagnostic aide designed to enhance human reader performance.

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

   • Yes, effectively. The "standalone" performance in this context refers to the intrinsic technical performance of the imaging device itself (e.g., resolution, pixel size, EMC compliance) without a human interpreting images. The listed technical specifications (resolution, pixel matrix, etc.) are characteristics of the device operating in a standalone capacity. "All test results were satisfactory" under "Safety, EMC and Performance Data" implies this.

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

   • Not applicable in the typical sense of clinical ground truth. The "ground truth" for the engineering performance tests would be defined by established calibration standards, physical measurements, and regulatory requirements for safe and effective operation of X-ray imaging devices.

7. The sample size for the training set:

   • Not applicable. The EzSensor T is a hardware device (digital X-ray imager for dental applications), not an AI algorithm requiring a training set of data.

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

   • Not applicable, as there is no training set for this hardware device.

Summary of the "Study" from the document:

The "study" referenced in this 510(k) summary primarily consists of:

• Engineering and Performance Testing: Compliance with electrical, mechanical, and environmental safety standards (IEC 60601-1, IEC 60601-1-1, IEC 60601-1-2). This includes verifying technical specifications like resolution, pixel size, etc.
• Comparative Analysis: Side-by-side comparison of technical specifications and Indications for Use with the predicate device (EzSensor K090526) to demonstrate substantial equivalence.
• Compliance with FDA Guidance: Adherence to "Guidance for the Submissions of 510(k)'s for Solid State X-ray Imaging Devices," which likely includes non-clinical and some clinical considerations, but without detailing a full-scale clinical trial with diagnostic endpoints in this summary.

The conclusion is that the EzSensor T is "safe and effective and substantially equivalent to predicate device." This means it meets the regulatory hurdle for market entry based on its similarity to an already approved device and its satisfactory performance in compliance tests.

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The Computed Oral Radiology System is intended for intra-oral x-ray examinations and indicated for dental patients. It produces instant, digital, intraoral x-ray images of a patient's mouth while reducing the necessary x-ray dosage. This device modification in no way alters the indications for use of this machine beyond what was most recently cleared in K072134.

The Computed Oral Radiography System is indicated for patients undergoing an intra-oral dental X-ray examination. It produces instant digital intra-oral X-ray images of a patient's mouth.

The device and its predicates are small digital imaging receptors that may be used in place of dental x-ray film. A new scintillation material differs from the predicate in that in that it affords higher resolution and lower noise. Direct triggering via an x-ray tube continues to be supported as was cleared in K072134 and K041385. The modification offers an improvement in image quality.

The provided text describes a 510(k) premarket notification for a modification to the Schick Computed Oral Radiology System. This document focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study report with specific acceptance criteria and performance metrics.

Therefore, much of the requested information, such as a table of acceptance criteria and reported device performance, sample sizes for test sets, number and qualifications of experts, adjudication methods, details of comparative effectiveness studies, and specific ground truth methodologies for training and test sets, is not available in the provided text.

However, I can extract the available information:

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

• Acceptance Criteria: While no explicit numerical or qualitative acceptance criteria are listed, the document states: "All validation activities have demonstrated that the predetermined acceptance criteria were met." The principal risk identified was "unintended x-ray exposure."
• Reported Device Performance:
  • "A new scintillation material differs from the predicate in that that it affords higher resolution and lower noise."
  • "The modification offers an improvement in image quality."
  • "It produces instant, digital, intraoral x-ray images of a patient's mouth while reducing the necessary x-ray dosage." (This statement is about the overall system's capability, not specific performance metrics of the modification).

Since specific metrics and thresholds for "higher resolution," "lower noise," and "improvement in image quality" are not provided, a detailed table cannot be constructed.

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

• Not available in the provided text. The document mentions "validation studies" but does not specify sample sizes or data provenance.

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 available in the provided text.

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

• Not available in the provided text.

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 and not available. This device is an imaging system (hardware modification), not an AI algorithm for interpretation. Therefore, a multi-reader multi-case study comparing human readers with AI assistance would not be relevant to this specific device modification.

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

• Not applicable. This relates to an imaging system, not a standalone algorithm.

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

• Not explicitly stated for the validation study. The document implies that the validation focused on "imaging, software validation, and third-party safety testing" to address the risk of "unintended x-ray exposure" and demonstrate "higher resolution and lower noise." The ground truth for these types of evaluations would likely involve physical measurements (e.g., MTF, DQE for resolution/noise, dosimeter readings for x-ray exposure) rather than clinical expert consensus or pathology, as this is a hardware modification improving image capture, not diagnostic interpretation.

8. The sample size for the training set

• Not applicable and not available. This device represents a hardware modification to an X-ray imager, not an AI model that would require a training set.

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

• Not applicable. As a hardware modification, there is no "training set" in the context of machine learning.

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The CCD area image sensor is intended to capture an intraoral x-ray image, when exposed to x-rays, for dental diagnostic purposes.

The proposed and predicated devices use similar components and are similar in design, technical characteristics and mode of operation. All the systems include a scintillator coupled to a digital image sensor, electronic circuits to analyze the digital image and transmit the digital image to a personal computer for viewing and further management of the file.

The provided document is a 510(k) premarket notification for the Dentron Sensor. This type of submission is a declaration of substantial equivalence to a predicate device, not typically a full clinical study with detailed performance data against specific acceptance criteria.

Based on the document, here's what can be extracted and what information is not available:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state acceptance criteria in terms of specific performance metrics (e.g., sensitivity, specificity, accuracy, resolution targets) for the Dentron Sensor. Instead, it relies on demonstrating substantial equivalence to legally marketed predicate devices.

The "Comparison Table" provided in the document outlines technical characteristics of the Dentron Sensor and its predicates. Here's a summary of those technical characteristics, which could be considered "performance" in the context of a 510(k) in comparison to predicates, but not against predefined acceptance criteria for a novel clinical claim.

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

• The document does not report specific sample sizes for a test set in the context of clinical performance evaluation.
• The document refers to mechanical, electrical, and electromagnetic compatibility testing standards (UL 60601-1, EN 60601-1-2, IEC 60601-1-4) with associated test reports (e.g., IMQ S.p.A. Test report nº 27SE00094). These tests typically involve device units, not patient-derived data sets.
• Data provenance is not applicable in the sense of clinical data (e.g., country of origin, retrospective/prospective) because such a study is not described.

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

• Not applicable. The submission does not describe a clinical study requiring ground truth derived from expert consensus on a test set. The focus is on technical equivalence and compliance with safety standards.

4. Adjudication method for the test set:

• Not applicable. No clinical test set and subsequent adjudication method are described in this 510(k) submission.

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

• Not applicable. This device is a digital intraoral X-ray sensor, not an AI-powered diagnostic aid. No MRMC study is mentioned or expected for this type of device.

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

• Not applicable. This device is hardware (a sensor) for capturing images, not a standalone algorithm.

7. The type of ground truth used:

• For the technical characteristics comparison, the "ground truth" implicitly relies on established specifications and performance of the predicate devices and general industry standards for intraoral imaging. There is no specific clinical "ground truth" (e.g., pathology, outcomes data) reported for this 510(k) submission. Compliance with international safety and electrical standards (UL, EN, IEC) forms part of the "ground truth" for safe operation.

8. The sample size for the training set:

• Not applicable. This device is a hardware sensor; therefore, there is no "training set" in the context of machine learning or AI models.

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

• Not applicable. As there is no training set for an AI/ML model, the concept of establishing ground truth for it does not apply here.

In summary:

This 510(k) submission for the Dentron Sensor focuses on demonstrating substantial equivalence to predicate devices based on:

1. Similar intended use: Capturing intraoral X-ray images for dental diagnostic purposes.
2. Similar technological characteristics: As detailed in the comparison table regarding sensor type, resolution, connection, etc.
3. Compliance with recognized voluntary standards: UL 60601-1, EN 60601-1-2, and IEC 60601-1-4 for safety and EMI/EMC.

The phrase "The proposed and predicated devices are substantially equivalent, similar devices that have been used by dentists in the US since 1989 and well accepted" directly addresses how the device meets the regulatory hurdle for market entry, rather than through a traditional clinical study with defined acceptance criteria for diagnostic performance metrics.

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The EnVision Intraoral Dental X-Ray Machines (Wall Mounted and Mobile) are intended to be used only for intraoral radiography of dental anatomy for diagnostic purposes performed by professionally trained and licensed personnel on the use of the system.

The EnVision Intraoral Dental X-Ray Machine (Wall Mounted and Mobile) is intended to be used for intraoral radiography of dental anatomy for diagnostic purposes performed by professionally trained and licensed personnel on the use of the system. The EnVision Intraoral Dental X-Ray Machine is a highly efficient user-friendly Constant-potential radiation system that produces, clear, sharp radiography with minimal elapsed exposure time. Includes 2 versions- integrated and remote, that are compatible to open to open to and the (30 cm round, and equipped with rectangular SSD's available as optional).

Here's an analysis of the provided text regarding the acceptance criteria and study for the Flow X-Ray Corporation's EnVision Intraoral Dental X-Ray Machines:

1. Table of Acceptance Criteria and Reported Device Performance:

Based on the provided document, no specific numerical acceptance criteria (e.g., minimum accuracy, sensitivity, or specificity) or performance metrics are stated for the EnVision Intraoral Dental X-Ray Machine. The document focuses on establishing substantial equivalence to a predicate device, not on meeting specific, quantifiable performance targets for diagnostic accuracy.

The reported device performance, therefore, is primarily in relation to its equivalence to the predicate:

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

• Sample Size: Not applicable. The document states that "Discussion of Clinical Tests Performed: Not Applicable." This indicates that no clinical test set was used to evaluate the device's diagnostic performance.
• Data Provenance: Not applicable. As no clinical tests were performed, there's no data provenance to report.

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

• Number of Experts: Not applicable. Since no clinical tests were performed, no experts were used to establish ground truth for a test set.
• Qualifications of Experts: Not applicable.

4. Adjudication Method for the Test Set:

• Adjudication Method: Not applicable. No clinical test set was used that would require adjudication.

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

• MRMC Study Done? No. The document explicitly states "Discussion of Clinical Tests Performed: Not Applicable," indicating no clinical studies were conducted, including MRMC studies.
• Effect Size: Not applicable. Without an MRMC study, there is no effect size to report.

6. Standalone (Algorithm Only) Performance Study:

• Standalone Study Done? No. This device is an X-ray machine (hardware), not an algorithm. Its performance is evaluated through bench testing and its ability to achieve substantial equivalence to a predicate device, not through an "algorithm only" study.

7. Type of Ground Truth Used:

• Type of Ground Truth: Not applicable for diagnostic performance. The "ground truth" in this submission relates to the device meeting engineering and safety standards and replicating the functionality of a predicate device. This is primarily established through bench testing and software validation, which confirm its technical specifications and operational safety.

8. Sample Size for the Training Set:

• Sample Size: Not applicable. This device is an x-ray machine, not an AI or machine learning algorithm that requires a training set of data.

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

• Ground Truth Establishment: Not applicable. As it's not an AI/ML device, there's no training set or associated ground truth for a training set.

Summary of Study Type:

The submission for the EnVision Intraoral Dental X-Ray Machines is a substantial equivalence (SE) submission. This means the primary "study" involved demonstrating that the new device is as safe and effective as a legally marketed predicate device (K#896024, MDT/Castle Model HDX Dental X-Ray Machine) that is already on the market. This demonstration was achieved through:

• Bench Testing: To confirm technical specifications and performance.
• Software Validation: To ensure the proper functioning of the machine's control software, particularly with the new preset exposure time feature.
• Compliance with Voluntary Standards: Adherence to established safety and risk management standards (IEC 60601-1, IEC 60601-2-7, ISO 14971:2000).

No clinical studies, diagnostic performance studies, or AI/ML specific evaluations (like training sets or standalone performance) were conducted or reported in this 510(k) summary.

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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 x-ray images of a patient's mouth while reducing the necessary x-ray dosage.

The device and its predicate are small digital imaging receptors that may be used in place of dental x-ray film. The new control mechanism differs from the predicate in that image acquisition may additionally be triggered through a hardwire to an x-ray tube. This modification allows for a quicker x-ray response time and may improve ergonomics as it eliminates the need for a standalone remote module. The existing firmware has been altered to support the modified and additional hardware. The new remote module may be housed within a specified x-ray source. The modification in no way effects the fundamental technology governing image acquisition.

Based on the provided document, here's an analysis of the acceptance criteria and the study (or lack thereof) to prove the device meets them:

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

The document does not provide specific, quantifiable acceptance criteria or reported device performance in a table format. It states generally:

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

The document does not specify the sample size used for any test set or the data provenance.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

The document does not provide information about any experts used to establish ground truth or their qualifications.

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

The document does not describe any adjudication method for a test set.

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

A multi-reader, multi-case (MRMC) comparative effectiveness study was not conducted. The device in question is a digital X-ray imager, not an AI-assisted diagnostic tool.

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

This document describes a modification to a digital dental X-ray imaging system, which is a hardware and firmware update to improve image acquisition and ergonomics. It is not an algorithm-only or AI device, so a standalone performance study in that context is not applicable and was not performed. The "standalone" aspect in this context refers to the elimination of a "standalone remote module."

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

The document does not describe the type of ground truth used, as it doesn't detail specific performance studies where ground truth would be established for diagnostic accuracy. The focus of this 510(k) submission is on demonstrating that a modification to an existing system maintains its safety and effectiveness relative to its predicate, rather than establishing primary diagnostic efficacy with new clinical data. The "ground truth" implicitly would be that the modified system continues to produce images suitable for dental x-ray examination without increased risk of unintended x-ray exposure.

8. The sample size for the training set

The document does not discuss a training set. This is not an AI/machine learning device that would require such data.

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

Not applicable, as there is no training set for an AI/machine learning model mentioned in the document.

Summary of the Document's Focus:

This 510(k) submission focuses on a device modification to an already cleared Computed Oral Radiology System. The modification involves a change in the control mechanism (allowing image acquisition to be triggered via a hardwire to an x-ray tube rather than a standalone remote module) and corresponding firmware alterations.

The document emphasizes demonstrating substantial equivalence to the predicate device. The "studies" mentioned are risk analysis, bench testing, and third-party safety testing, which focused on ensuring the modification did not introduce new risks (specifically unintended X-ray exposure) or alter the fundamental technology or indications for use. The acceptance criteria were therefore primarily related to safety and the maintenance of equivalence to the predicate, rather than new performance benchmarks for diagnostic accuracy.

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