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The Designs for Vision Melide Fiberoptic Light is indicated for use in surgery and medical applications where high intensity illumination is required.

The Designs for Vision Melide Fiberoptic Light (Melide Fiberoptic Light) is a modification of other legally marketed Designs for Vision surgical headlight systems. The Melide Fiberoptic Light consists of a lamp mounted in a chassis that also holds the AC power supply, dimmer for light intensity control, and a 530 nm filter. Light is passed through a fiberoptic cable to a set of optics in the headlight. The Melide Fiberoptic Light is compatible with all of the headsets available for use with the Designs for Vision surgical headlight systems described in K032283.

Here's an analysis of the provided text regarding the Designs for Vision Melide Fiberoptic Light, focusing on acceptance criteria and study details.

Important Note: The provided text is a 510(k) summary for a medical device submitted to the FDA. 510(k) summaries primarily focus on demonstrating substantial equivalence to a predicate device, not necessarily on detailed clinical trial-style acceptance criteria and studies as one might find for a novel drug or a high-risk device requiring a PMA.

The document primarily describes a modification to an existing device (a change in the light source bulb) and demonstrates its equivalence to a predicate device. Therefore, the "acceptance criteria" here are largely implicit in demonstrating that the new light source maintains safety and effectiveness and that its performance, particularly intensity, is within a desired and pre-defined range or matches a predicate.

Acceptance Criteria and Reported Device Performance

Study Details

Given the nature of the 510(k) for a device modification, the "study" is referred to as "Performance Testing" rather than a comprehensive clinical trial.

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

   • Sample Size: Not specified. "Performance testing was conducted," but no details on the number of units tested are given.
   • Data Provenance: Not specified, but generally, such testing for a US 510(k) would be conducted internally by the manufacturer or a contracted lab, likely in the US.
   • Retrospective or Prospective: Likely prospective, as it involved testing of the modified device.

2. 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 Applicable. This type of expert-based ground truth is typically for image-based diagnostic or assessment devices (e.g., AI for radiology). For a surgical light, "ground truth" would be established through objective physical measurements (e.g., light meters, electrical safety checks) against industry standards or internal specifications, not expert consensus on performance.

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

   • Not Applicable. See point 2. Adjudication methods are relevant for subjective assessments, particularly in clinical trials or evaluations of diagnostic accuracy.

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. This is a surgical light, not an AI-assisted diagnostic device. MRMC studies are used to evaluate the impact of an AI algorithm on human reader performance, which is not relevant here.

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

   • Not Applicable. This device does not involve an algorithm.

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

   • The "ground truth" for this device would be based on objective physical measurements (e.g., light intensity in foot-candles, electrical safety parameters, thermal performance) compared against established engineering specifications, safety standards, and the performance characteristics of the predicate device. It is a functional device, not one that generates data requiring human interpretation for accuracy.

7. The sample size for the training set

   • Not Applicable. This device does not involve machine learning or AI, so there is no training set.

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

   • Not Applicable. See point 7.

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The DVI Curing Light is a dental curing light that is intended for the photopolymerization of dental resins.

The DVI Curing Light consists of three major components; a handpiece, curved fiber optic end tip, and cradle. The handpiece contains the LED light source and a fiber optic light guide that directs light to the treatment area on the patient. The handpiece is placed in a cradle, which is connected via a plug-in transformer to an AC outlet for charging. A Protective light-shield and Fiber-optic end-tips are accessories provided with the DVI Curing Light, which support the operation and maintenance of the device.

The DVI curing light initiates curing (polymerization) of materials that are activated by photo initiators with an absorption in the wavelength range of between 405 to 470 nm. It is recommended that materials manufacturer's directions be followed for curing times. It is recommended that curing times be extended when curing through the tooth structure or when the distance from the curing light end tip to the material exceeds 3 mm.

The provided text describes a 510(k) summary for the Designs for Vision Inc. Curing Light (DVI Curing Light). However, it does not contain specific acceptance criteria or detailed results of a study proving the device meets acceptance criteria.

The document indicates that performance testing was conducted, but only generally lists the types of tests without providing the criteria or outcomes. Therefore, most of the requested information cannot be extracted from the provided text.

Here is what can be inferred or explicitly stated from the text, with limitations noted:

1. Table of Acceptance Criteria and Reported Device Performance

Limitations: The document states what kinds of tests were performed (software/hardware V&V, electrical safety/EMC, resin polymerization times), but does not provide the specific acceptance criteria for these tests or the detailed numerical results that demonstrate these criteria were met. It only provides a general statement that "The test results confirm that the proposed DVI Curing Light is safe and effective for use as a curing light."

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

• Sample Size (Test Set): Not specified.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective).

3. Number of Experts Used and Their Qualifications for Ground Truth

• This type of device (dental curing light) typically undergoes engineering and performance testing as described in Section 7, rather than ground truth established by experts.
• Therefore, the number and qualifications of experts for ground truth are not applicable in the context described in this document.

4. Adjudication Method for the Test Set

• Not applicable, as expert-based ground truth and adjudication methods are not relevant for the type of device performance testing described.

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

• No, a MRMC comparative effectiveness study was not done. This type of study is relevant for diagnostic devices where human readers interpret images or data, often comparing human performance with and without AI assistance. The DVI Curing Light is a functional medical device, not a diagnostic one.

6. Standalone (Algorithm Only) Performance Study

• No, a standalone (algorithm only) performance study was not done. This concept is primarily relevant for AI/ML-based software devices. The DVI Curing Light is a hardware device with an LED light source; while it has "software and hardware verification and validation," this refers to its internal operational software, not a diagnostic algorithm.

7. Type of Ground Truth Used

• For the performance tests described (e.g., resin polymerization times, electrical safety, software/hardware V&V), the "ground truth" would be established by engineering specifications, regulatory standards, and established scientific principles of material science (for resin curing) and electrical/EMC safety. It is not based on expert consensus, pathology, or outcomes data in the way these terms are typically used for diagnostic or predictive devices.

8. Sample Size for the Training Set

• This concept is not applicable. The DVI Curing Light is a functional device, not an AI/ML device that requires a "training set" for an algorithm.

9. How Ground Truth for the Training Set Was Established

• Not applicable (see point 8).

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The Designs for Vision Fiberoptic Light is indicated for use in surgery and medical applications where high intensity illumination is required.

The Designs for Vision Fiberoptic Light is composed of a high intensity light source, fiberoptic cables, and fiberoptic headsets. The Designs for Vision headsets have been marketed since the early 1970s with a long history of safe use in the surgical suite. The headsets are coaxial, bifurcated, or focusable designs.

The light source includes a chuck for fiberoptic cable attachment. The Light source provides a 150-watt power output and contains a continuous illumination level adjustment, which provides 3200 K color temperature light.

The provided text is a 510(k) summary for the Designs for Vision Fiberoptic Light. It describes the device, its intended use, and its substantial equivalence to predicate devices. However, it does not contain the detailed information required to describe acceptance criteria and a study proving those criteria are met in the format requested.

Specifically, the document states: "Testing has been performed which demonstrates the electrical safety and electromagnetic compatibility characteristics of the Designs for Vision Fiberoptic Light." but it does not provide any specifics about this testing, performance outcomes, or acceptance criteria.

Therefore, I cannot populate the requested table and answer the study-specific questions based on the provided text.

Here is what I can extract based on the available information, noting the significant gaps:

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

Missing Information for Table:

• Specific quantitative or qualitative acceptance criteria for electrical safety and EMC.
• Detailed performance results for each criterion.

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

• Sample Size (Test Set): Not specified.
• Data Provenance: Not specified.

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 applicable as the document does not describe a study involving expert-established ground truth for a test set. The validation seems to be primarily through regulatory compliance and substantial equivalence to existing devices.

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

• Not applicable (see point 3).

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 or AI-assisted study is mentioned. This device is a fiberoptic light, not an AI diagnostic tool.

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

• Not applicable (see point 5).

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

• Not applicable. The "ground truth" for this device appears to be functional safety (electrical, EMC) and meeting its intended purpose as a light source, likely assessed through engineering tests and comparison to predicate devices, rather than a diagnostic performance ground truth.

8. The sample size for the training set

• Not applicable. This device is not an AI/machine learning model that would require a training set.

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

• Not applicable (see point 8).

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The Daylite Xenon Light Source is indicated for use in surgery and medical applications where high intensity illumination is required

The Daylite XeNon Light Sources are comprised of high intensity xenon light sources, fiberoptic cables and fiberoptic headsets. The Designs for Vision Daylite Light Sources are supplied with headsets that were first placed into service prior to 1976 and are preamendment devices. The Designs for Vision headsets have been marketed since the early 1970's with a long history of safe use in the surgical suite. The headsets are either coaxial, bifurcated, or focusable designs. The light source includes a universal chuck for fiberoptic cable attachment. The universal chuck accepts various sizes of light cables. The XeNon Light sources provide either 180-watt or 300-watt power output and contain a continuous illumination level adjustment which provides 6000°K color temperature light.

The provided document K013880 is a 510(k) summary for the Designs for Vision, Inc. Daylite XeNon Light Sources. This document is a premarket notification for a medical device and describes its substantial equivalence to predicate devices, focusing on regulatory compliance rather than extensive clinical performance studies.

Therefore, many of the requested details about acceptance criteria, detailed study design, and ground truth establishment are not typically found in such a regulatory submission. A 510(k) primarily demonstrates that the new device is as safe and effective as a legally marketed predicate device.

Based on the provided text, here is the information that can be extracted or inferred:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not provide a table of explicit acceptance criteria or detailed performance metrics. Instead, it relies on demonstrating electrical safety characteristics and substantial equivalence to predicate devices.

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

The document states "Testing has been performed which demonstrates the electrical safety characteristics." However, it does not specify a sample size or data provenance (e.g., country of origin, retrospective/prospective) for any test set. This type of detail is usually found in detailed test reports, not the 510(k) summary itself. The testing mentioned would likely involve a limited number of manufactured units to verify electrical safety standards rather than a clinical trial with patient data.

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

Not applicable. This device is a light source, not a diagnostic or AI-driven decision support system that requires expert-established ground truth from clinical cases. The "testing" referred to is against engineering and safety standards (e.g., electrical safety), not medical interpretation.

4. Adjudication Method for the Test Set

Not applicable. As the testing relates to electrical safety and compliance with existing standards for medical devices, there would not be an "adjudication method" in the sense of resolving discrepancies in expert interpretation of clinical data.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and effect size.

No, an MRMC comparative effectiveness study was not done. This type of study is relevant for diagnostic imaging or AI algorithms where human reader performance is being evaluated or augmented. The Daylite XeNon Light Source is an illumination device.

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

Not applicable. This is a hardware medical device (a light source), not an algorithm or AI system. Therefore, standalone algorithm performance is not relevant.

7. The Type of Ground Truth Used

The "ground truth" for this device would be its adherence to established electrical safety standards and its functional specifications (e.g., power output, color temperature, continuous illumination adjustment) as compared to its own design specifications and general medical device requirements. These are engineering and performance specifications, not clinical outcomes or expert consensus on medical findings.

8. The Sample Size for the Training Set

Not applicable. This device is a hardware light source, not a machine learning model or AI system that requires a "training set."

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

Not applicable. As there is no training set for a machine learning model, there is no ground truth established for it in this context.

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