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The Tuxedo Digital Dental Sensor is a CMOS sensor for the capturing of digital diagnostic x-ray images on a patient for evaluation by an appropriately trained oral healthcare professional.

The TUXEDO Dental Digital Sensor is used in the detection and diagnosis of anomalies in dental anatomy, as well as for the evaluation of performed treatment in dental care. The primary use is by general dental practitioners to detect the presence and extent of carious legions in the dentin and enamel of a tooth. Two different sized sensors (size 1 and size 2) are utilized to image different anatomy and different patient sizes. The TUXEDO Dental Digital Sensor functions by being placed in a patient's mouth lingually by a licensed dental practitioner, and is designed to capture collimated radiation which is converted into a digital image for viewing by a licensed dental practitioner. The capturing of the radiation is done within the TUXEDO sensor casing which contains a scintillator used to convert the radiation into visible light, and this visible light is immediately captured by the internal CMOS sensor. The digital image is transferred to a computer via USB 2.0 and can be viewed in most common imaging software programs, including LED Imaging Software. A software driver is available from LED Dental which will allow the TUXEDO sensor to be used in these software programs. The software supplied with the Tuxedo Digital Dental Sensor was cleared separately by FDA by Apteryx, Inc. The sensor is intended to be used with a disposable barrier sheath that should be replaced between patients. This is to reduce cross contamination between patients. The sensor is also sealed in a way that the portion of the device that is placed in the patient's mouth can be sterilized with liquid without the device being damaged.

Here's a breakdown of the acceptance criteria and study information for the Tuxedo Digital Dental Sensor, based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't present explicit "acceptance criteria" in a typical table format with pass/fail thresholds. Instead, it compares the Tuxedo Digital Dental Sensor's technological characteristics and performance against a legally marketed predicate device (RIO Sensor (RIS 500), K143000) to demonstrate substantial equivalence. The "Comparison Results" column effectively acts as the performance assessment against the predicate.

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

• Test Set (Clinical Images):
  • Sample Size: A single "Phantom equivalent to a 51-year-old male" (DXTTR III Dental X-Ray Phantom (Human Skull)) was used.
  • Data Provenance: This was a simulated, prospective test using a phantom in a laboratory setting. The origin of the phantom itself is not specified as a country.

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

• The document states, "All images acquired demonstrated excellent diagnostic imaging quality on both the size #1 and the size #2 sensor." However, it does not specify the number or qualifications of experts who made this determination for the phantom images. It implies an internal assessment.

4. Adjudication Method for the Test Set

• The document does not describe an explicit adjudication method for the phantom images. The assessment of "excellent diagnostic imaging quality" appears to be a general conclusion rather than a formal adjudication process involving multiple readers.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

• No, an MRMC comparative effectiveness study was not done. The study's purpose was to demonstrate substantial equivalence to a predicate device, not to compare AI-assisted performance with unassisted human readers or to quantify an effect size for human improvement with AI. The device itself is a digital dental sensor, not an AI diagnostic tool.

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

• Yes, in essence, standalone performance was assessed though not in the context of an "algorithm." The device's imaging performance (MTF, DQE, theoretical resolution, stability of sensitivity, dark output, offset value) was tested independently of a human interpreter, using standardized methodologies (IEC6220-1). The phantom imaging also represents a standalone assessment of the device's image capture capabilities.

7. The Type of Ground Truth Used

• For the technical performance aspects (MTF, DQE, resolution), the ground truth is based on physical measurements and standardized testing protocols (IEC6220-1).
• For the "clinical images" using the phantom, the ground truth is implied to be the known anatomical structures and potential anomalies within the DXTTR III Dental X-Ray Phantom, against which the captured images were visually assessed for diagnostic quality. This is a form of expert assessment of image quality against a known physical standard, though detailed methodology is not provided.

8. The Sample Size for the Training Set

• Not Applicable (N/A). The Tuxedo Digital Dental Sensor is a hardware device (CMOS sensor) for image capture, not an AI algorithm that requires a training set of data. The document does not mention any machine learning or AI components that would necessitate a training set.

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

• Not Applicable (N/A). As mentioned above, there is no training set for this device in the context of AI/machine learning.

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VELscope Vx is intended to be used by a dentist or health-care provider as an adjunct to traditional oral examination by incandescent light to enhance the visualization of oral mucosal abnormalities that may not be apparent or visible to the naked eye, such as oral cancer and premalignant dysplasia.

VELscope Vx is further intended to be used by a surgeon to help identify diseased tissue around a clinically apparent lesion and thus aid in determining the appropriate margin for surgical excision.

The VELscope Vx system is a natural tissue fluorescence direct visualization system to be used as an adjunctive tool for oral mucosal examination.

The main components of VELscope are the Handpiece, incorporating light source, viewing optics and rechargeable battery. Charging Cradle and external power supply. The VELscope Handpiece emits a safe, visible, blue light into the oral cavity, which excites the oral tissue and causes it to fluoresce. The oral cavity can then be examined in real time and suspicious tissue that may require further investigation can be quickly identified. When viewed through the VELscope Handpiece, abnormal tissue typically appears as an irregular, dark area that stands out against the otherwise normal green fluorescence pattern of surrounding health tissue.

The document provided does not contain specific acceptance criteria outlined in a table or a detailed study proving the device meets particular numerical performance targets. Instead, it focuses on demonstrating substantial equivalence to a predicate device (VELscope, K070523).

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

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria:
The core "acceptance criteria" presented in this 510(k) summary are based on demonstrating substantial equivalence to the predicate VELscope device (K070523). The key "criteria" for equivalence are:

• Identical Indications for Use.
• Equivalent essential performance specifications, specifically:
  • Excitation band (400-460nm) is the same as the predicate.
  • Optical output power in that excitation band is comparable.
  • Emission (viewing) optics are identical to the predicate.
• Clinical equivalence demonstrated through comparative imaging of oral mucosal lesions between the new device and the predicate.

Reported Device Performance:

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

• Sample Size for Test Set: The document states that "Clinical photographs were taken of a variety of oral mucosal lesions." It does not specify the exact number of lesions or patients included in this "variety."
• Data Provenance: The patients were "referred to oral medicine and oral dysplasia clinics," suggesting a clinical setting. The country of origin is not explicitly stated, but the submitter's address is in Burnaby, BC, Canada. The data appears to be prospective in the sense that images were specifically "acquired" for the comparison, but it's not clear if these were newly diagnosed cases or existing cases.

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

This information is not provided in the document. The study relies on "conventional (white light) as well as fluorescence photographs" and a comparison of these images. There is no mention of independent experts evaluating the images or establishing ground truth.

4. Adjudication Method for the Test Set

The document does not specify an adjudication method. It states "A comparison of the predicate VELscope and VELscope Vx images supports the substantial equivalence," implying a qualitative assessment, but the process of this comparison (e.g., blinded, adjudicated, single reviewer) is not described.

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

No, a MRMC comparative effectiveness study was not done. The study's purpose was to demonstrate substantial equivalence between the new VELscope Vx and its predicate (VELscope) through comparative imaging, not to evaluate the improvement of human readers with AI assistance. The VELscope Vx is described as an "adjunct to traditional oral examination" and a "natural tissue fluorescence direct visualization system," not an AI-assisted diagnostic tool.

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

This question is not applicable as the VELscope Vx is a direct visualization device, not an algorithm. Its operation inherently involves a human observer (dentist or healthcare provider) viewing the fluorescence to identify abnormalities.

7. The Type of Ground Truth Used

The "ground truth" implicitly used is the visual identification of "oral mucosal lesions" and "diseased tissue" by conventional examination and the use of the predicate VELscope. The clinical context is "oral medicine and oral dysplasia clinics," suggesting that these lesions would have a known clinical or pathological status. However, the document does not explicitly state if pathology or outcomes data was used to confirm the nature of the "variety" of lesions imaged. The substantial equivalence is based on the visual comparability of images, not on a definitive ground truth of diagnosis for each lesion.

8. The Sample Size for the Training Set

This information is not applicable/not provided. The VELscope Vx is a medical device, not an AI/machine learning algorithm that requires a "training set." The engineering and design of the device would have been based on established principles of fluorescence and previous knowledge from the predicate device.

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

This information is not applicable as there is no "training set" in the context of this device.

Ask a specific question about this device

VELscope is intended to be used by a dentist or health-care provider as an adjunct to traditional oral examination by incandescent light to enhance the visualization of oral mucosal abnormalities that may not be apparent or visible to the naked eye, such as oral cancer or premalignant dysplasia.

VELscope is further intended to be used by a surgeon to help identify diseased tissue around a clinically apparent lesion and thus aid in determining the appropriate margin for surgical excision.

VELscope is a natural tissue fluorescence direct visualization system to be used as an adjunctive tool for oral mucosal examination.

The main components of VELscope are the Light Source Unit (LSU) and the viewing Handpiece. The VELscope Handpiece emits a safe, visible, blue light into the oral cavity, which excites the oral tissue and causes it to fluoresce. The oral cavity can then be examined in real time and suspicious tissue that may require further investigation can be quickly identified. When viewed through the VELscope Handpiece, healthy tissue typically shows up as a brighter green color while suspicious tissue can cause a loss of fluorescence, which thus appears dark.

Here's an analysis of the provided text regarding the VELscope device, focusing on the acceptance criteria and the study details:

The provided text does not explicitly state acceptance criteria in a table format nor does it describe a specific study (with detailed methodology, sample sizes, expert qualifications, etc.) that directly proves the device meets pre-defined quantitative acceptance criteria.

Instead, the submission refers to "peer-reviewed and published scientific studies" as evidence to support the expanded indications for use. This suggests that the regulatory body (FDA) is relying on external, previously conducted research rather than a de novo clinical study described within the 510(k) submission itself.

Here's a breakdown of the requested information based on the provided text, with notes on what is not available:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not specified.
• Data Provenance (country of origin, retrospective/prospective): Not specified. The submission refers generally to "peer-reviewed and published scientific studies," which would contain this information, but it's not present in the 510(k) summary itself.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified.

4. Adjudication method for the test set

• Adjudication Method: Not specified.

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

• MRMC Study: Not specified. The VELscope is a direct visualization system, not an AI software. The concept of "human readers improve with AI" does not directly apply here. It's an adjunctive tool for a human healthcare provider.
• Effect Size: Not applicable/not specified.

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

• Standalone Performance: Not applicable. VELscope is a direct visualization tool used by a human healthcare provider; it's not an algorithm that provides an output independently.

7. The type of ground truth used

• Type of Ground Truth: Not explicitly stated within the provided text. However, given the nature of the device (detecting cancerous/dysplastic lesions and aiding surgical margins), the ground truth in the underlying studies would most likely be pathology results (histopathologic diagnosis) obtained from biopsies. Outcomes data (e.g., long-term patient follow-up) could also contribute.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable/not specified. The VELscope is not an AI/machine learning device that requires a training set in the conventional sense. Its function relies on the physical properties of tissue fluorescence.

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

• Ground Truth Establishment for Training Set: Not applicable, as detailed above.

Summary of what the K070523 submission does say about evidence:

The FDA 510(k) summary for VELscope (K070523) states that its expanded indications for use are "based on recently published clinical data in peer-reviewed publications." It further asserts that these publications provide evidence that:

• "VELscope is effective in helping detect occult cancerous and dysplastic lesions."
• "VELscope can help an oral surgeon assess the extent of occult diseased tissue... and thus aid in determining the appropriate margin for surgical excision."

This implies that the burden of proof for effectiveness, and thus meeting an implicit acceptance criteria of being "effective" and "helpful," was satisfied by referencing existing scientific literature rather than by conducting and detailing a new, specific clinical trial within this 510(k) submission. The exact quantitative acceptance criteria and detailed study methodologies would need to be found within those referenced "peer-reviewed and published scientific studies" themselves, which are not included in this document.

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