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The Televere Digital Dental Imaging System is intended for radiographic examination by a dental professional to assist in the diagnosing of diseases of the teeth, jaw and oral structures. Not for mammography. Not for fluorosopy.

The Televere Digital Dental Imaging System is an extraoral digital x-ray system comprised of two previously cleared individual components: (1) an intraoral detector component (K162619) which connects to a PC via a USB port and (2) and image management software package (i.e., Tigerview Professional, K061035). The device detector comes in two sizes: 600mm² (Hamamatsu CMOS area image sensor, S11684-12) and 884mm² (Hamamatsu CMOS area image sensor, S116845-12). X-ray generators that can integrate with the Televere Digital Dental Imaging System are wall-mounted x-ray generators (both AC and DC) with a tube current between 1 and 15mA inclusive, and with a tube voltage between 50 and 100kV inclusive, with built in controls to set exposure parameters. Generators allow variable mA/kV to be selected, all will control the exposure time. The device and software cannot act as an x-ray generator controller. All control of xray generation is done by controls built into the generator itself. There is no connection between the device and the x-ray generator. The device is an x-ray receiver and does not control the generator.

The provided text describes a 510(k) premarket notification for the "Televere Digital Dental Imaging System." The application aims to demonstrate substantial equivalence to a legally marketed predicate device rather than undergoing a de novo classification or a PMA. As such, the information provided focuses on the device's technical specifications and how they compare to the predicate, rather than detailed acceptance criteria and a "study" in the traditional clinical trial sense with statistical performance metrics against a defined ground truth.

Here's an analysis of the provided text in the context of your request:

Key Takeaway: This submission is a 510(k) for a digital dental imaging system (hardware + software), where the primary demonstration of safety and effectiveness relies on showing substantial equivalence to existing cleared components (an intraoral detector and image management software). It's not a diagnostic AI/CAD device that interprets images or provides a diagnosis, and therefore, the testing described is not a performance study against a clinical ground truth for diagnostic accuracy.

Based on the provided document, here's what can be inferred/extracted regarding acceptance criteria and "study" that proves the device meets them:

The "acceptance criteria" in this context are implicitly that the new device is as safe and effective as the predicate device and raises no new technical issues of safety or effectiveness. The "study" isn't a complex MRMC or standalone performance study measuring diagnostic accuracy of an AI, but rather a demonstration of technical equivalence and image quality to show non-inferiority.

1. Table of Acceptance Criteria and Reported Device Performance

Strictly speaking, the document does not present acceptance criteria in a quantitative, pre-defined table with numerical targets for diagnostic performance (e.g., sensitivity, specificity, AUC) because it's a 510(k) for an imaging system, not a diagnostic AI.

Instead, the "acceptance criteria" are qualitative and comparative:

• Safety and Effectiveness: "new device is as safe and effective as the predicate device."
• Image Quality: "Clinical images highlight equal or better image quality as compared to the predicate."
• No New Technical Issues: "no new technical issues of safety or effectiveness raised by substitution of the imaging software component."
• Clinical Acceptability: "Professional evaluation of imaging samples were of excellent quality, high resolution, clinically acceptable and substantially equivalent to the predicate device."

Reported Device Performance (Comparative):

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

• Test Set Sample Size: The document mentions "Sample clinical images from the new device were also provided" but does not specify the exact number of images/cases. It states they "were not necessary to demonstrate substantial equivalence," implying a limited set or perhaps general examples rather than a statistically powered test set for diagnostic accuracy.
• Data Provenance: Not specified (country of origin). The document does not indicate if the data was retrospective or prospective. Given the nature of a 510(k) for an imaging system, it's likely pre-existing generic clinical images or images taken during testing.

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

• Number of Experts: Not explicitly stated. The document refers to "Professional evaluation of imaging samples," which implies at least one, but no specific number is given.
• Qualifications of Experts: Not specified beyond "Professional evaluation." It's assumed to be dental professionals as per the device's indications for use.

4. Adjudication Method for the Test Set

• Adjudication Method: Not applicable/not described. This level of detail in adjudication (e.g., 2+1, 3+1) is typically associated with studies establishing ground truth for diagnostic AI, which is not the primary purpose of this 510(k). The evaluation appears to be a qualitative assessment of image quality for substantial equivalence.

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

• MRMC Study: No, an MRMC comparative effectiveness study was not done or described. The submission is focused on demonstrating substantial equivalence of an imaging system, not the diagnostic performance improvement of human readers using an AI algorithm.

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

• Standalone Performance: Not applicable. This device is an imaging system (hardware and software), not an AI algorithm designed to generate a diagnosis or detection result on its own. The "software" component (Tigerview Professional) is a PACS-like image management software with basic adjustment features, not a diagnostic AI.

7. The Type of Ground Truth Used

• Type of Ground Truth: The concept of "ground truth" as a clinical diagnosis confirmed by pathology or outcomes data is not applicable here. The "ground truth" (or basis for comparison) was the clinical acceptability and image quality of the predicate device. The new device's images were evaluated against the expectation of quality for dental X-ray images and in comparison to what the predicate device produces. This is a qualitative assessment of imaging system performance, not diagnostic accuracy.

8. The Sample Size for the Training Set

• Training Set Sample Size: Not applicable. This is not a machine learning/AI device where a training set is used to develop an algorithm. The software component, Tigerview Professional, is a previously cleared PACS software (K061035) and is "unchanged" for this new device.

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

• Ground Truth for Training Set: Not applicable, for the same reasons as #8. There is no mention of an algorithm being trained, hence no training set ground truth established.

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The Televere Podiatry X-Ray System HF is intended for use by qualified clinicians for the x-ray of hands and feet. Not for mammography. Not fluoroscopy.

The Televere Podiatry X-Ray System HF consists of a combination of previously cleared Tigerview digital imaging software (K061035), a high frequency X-Ray generator (X-CEL MODEL HF 718BD, K160857), a PC-based computer and a power supply. Tigerview software provides an exposure control upgrade of the previously cleared HF x-ray generator by replacing the manual touchscreen of the Predicate Device (K160857) with the Tigerview computer software interface. Tigerview software provides basic image adjustment features as well as x-ray exposure control settings. An image adjustment system allows the physician to acquire, display, edit (e.g., resize, adjust contrast, crop, etc.), review, store, print, and distribute medical images within a Picture Archiving and Communication System (PACS) environment. Tigerview software runs on standard PC-compatible computers and is compatible with capture devices which attach to the computer using a Network Adaptor, USB port, PCI slot, parallel port, memory card, S-video port on a video capture card, or SCSI card.

The provided text is a 510(k) premarket notification for the Televere Podiatry X-Ray System HF. It focuses on demonstrating substantial equivalence to a predicate device, rather than presenting a study to prove the device meets specific acceptance criteria for diagnostic performance.

Therefore, the document does not contain the detailed information required to fill out a table of acceptance criteria and reported device performance as it would for a new AI/CAD device. Specifically:

• No specific acceptance criteria for diagnostic performance are stated. The submission focuses on regulatory compliance and technical specifications.
• No numerical performance metrics (e.g., sensitivity, specificity, AUC) are reported for diagnostic tasks. The "device performance" mentioned refers to electrical and safety aspects.
• No information on sample size for test sets, data provenance, number or qualifications of experts for ground truth, adjudication methods, MRMC studies, standalone performance, or ground truth types (pathology, outcomes data) is provided. These are typical for studies assessing diagnostic accuracy.
• No information on training set sample size or how training ground truth was established is provided. This is because the device is an X-ray system, not a machine learning algorithm requiring a training set for diagnostic tasks.

The document states:

• "The results of clinical image inspection, bench, and laboratory test results demonstrate that the new device is as safe and effective as the predicate device. Clinical images highlight equal or better image quality as compared to the predicate." (Page 4, Section 6)
• "Sample clinical images from the new device were also provided however they were not necessary to demonstrate substantial equivalence." (Page 5, Section 8)

This indicates that clinical images were reviewed, but a formal study with detailed acceptance criteria and quantitative diagnostic performance metrics was not conducted or deemed necessary for this 510(k) submission, which primarily addresses hardware and software integration.

The "Acceptance Criteria" provided in the document relate to the technical performance of the X-ray system itself (e.g., kVp accuracy, mA accuracy, timer accuracy, reproducibility, leakage radiation) and compliance with various electrical safety and radiation standards. These are listed under "Performance Accuracy" and "X-ray Beam Quality Metrics" in the Substantial Equivalence Chart on Page 5.

Summary of available information related to performance/acceptance criteria:

Missing Information (as per your request, not available in the document):

1. Sample size used for the test set and the data provenance: Not applicable for a diagnostic performance study as described in the prompt. Clinical images were inspected, but details like sample size or origin for that inspection are not provided.
2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable, as no formal diagnostic performance study is presented.
3. Adjudication method for the test set: Not applicable.
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: Not applicable, as this is solely an X-ray system, not an AI/CAD diagnostic aid.
5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
6. The type of ground truth used: For technical performance, the ground truth would be precise measurements and compliance with regulatory standards. For the "clinical image inspection," the ground truth would be expert visual assessment, but details are not provided.
7. The sample size for the training set: Not applicable, as this is an X-ray system, not a machine learning model.
8. How the ground truth for the training set was established: Not applicable.

In essence, the document serves as a regulatory submission demonstrating technical and safety equivalence, not a publication detailing a diagnostic performance study for a machine learning or CAD device.

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