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G.o.c.c.l.e.s. is intended to be used by a qualified health-care providers to enhance the identification and visualization of the oral mucosal abnormalities that may not be apparent or visible to the naked eye, such as oral cancer and premalignant dysplasia. G.o.c.l.e.s. eyewear is reusable filtered eyewear that is worn by a health care professional to enhance the visual effects of blue light during oral exam.

The G.o.c.c.l.e.s device consist of one eyewear with specific filtering features that shall be used with the G.o.c.c.l.e.s. light proprietary light source (emission range 440-490nm), in order to allow the examination of autofluorescence of the oral cavity and consequently detect oral abnormalities such as dysplastic or anaplastic lesions (carcinomas of the oral mucosa).

The device looks like a pair of glasses, characterized by reduced dimensions, good wearability, easy portability and proper filtering performances in order to allow to filter the fluorescence emission, resulting from the fluorophore of interest (Flavin Adenine Dinucleotide (FAD)), which in its oxidized form responds to a light of 450nm (blue-violet) emitting a fluorescence wavelength of around 515nm (green).

Here's a breakdown of the acceptance criteria and study information for the G.o.c.c.l.e.s. device, based on the provided FDA 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

The FDA 510(k) summary for G.o.c.c.l.e.s. primarily focuses on demonstrating substantial equivalence to predicate devices rather than setting explicit quantifiable acceptance criteria as one might see for a novel device. However, the performance data highlights specific characteristics that serve as de facto acceptance criteria for its optical properties and its ability to detect oral abnormalities.

• Transmittance % remains over 90% of its max value (60%) from 500nm to 541nm, covering the 515-530 nm range for FAD. |
  | - Compatible with light sources emitting in the FAD excitation peak (around 450 nm). | - G.o.c.c.l.e.s. light emission range: 440-490 nm (includes 450 nm).
• Demonstrated performance with other light sources (Optilux 501, Eliparfreelight) that also emit in a range including FAD's excitation peak. |
  | Clinical Performance (Ability to identify oral abnormalities): | |
  | - Ability to detect autofluorescence changes indicative of oral abnormalities. | - Study 1 (A. Moro et al.): Out of 15 suspected cancers detected by autofluorescence, 14 were confirmed by histological analysis.
• Study 2 (Multicenter Study): G.o.c.c.l.e.s. identified loss of fluorescence in 35 cases, of which 29 were confirmed by histological analyses to be dysplasia, carcinoma in situ, or invasive cancer (True Positive Rate: 82.8%). No relevant differences in performance with different compatible light sources. |

2. Sample Size and Data Provenance

• Test Set Sample Size:
  • Study 1 (A. Moro et al.): 32 patients (12 with potentially malignant diseases, 20 previously operated for oral cancer).
  • Study 2 (Multicenter Study): Number of patients not explicitly stated, but "a total of 35 cases" of fluorescence loss identified. Thus, at least 35 cases were part of the diagnostic assessment.
• Data Provenance:
  • The document does not explicitly state the country of origin for the clinical studies.
  • Both clinical studies appear to be prospective as they involve patient recruitment and subsequent clinical and histological analysis based on the device's findings ("underwent autofluorescence test," "surgical excision," "recruiting patients").

3. Number of Experts and Qualifications for Ground Truth

• Number of Experts: Not explicitly stated how many experts were involved in diagnosing the lesions or performing the surgical excisions/histological analyses.
• Qualifications of Experts: The studies mention "qualified health-care providers" and "histological analyses," implying the involvement of oral pathologists and surgeons, but specific qualifications (e.g., years of experience) are not provided.

4. Adjudication Method

• The document does not explicitly describe an adjudication method (like 2+1 or 3+1 consensus) for establishing the ground truth.
• The ground truth was established by histological analysis of surgically excised lesions, which is generally considered the gold standard for definitive diagnosis of oral cancer and dysplasia. This implies that the histological diagnosis was taken as the definitive truth, rather than requiring further expert consensus on the initial clinical findings.

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

• No, an MRMC comparative effectiveness study was not explicitly conducted to measure human reader improvement with AI vs. without AI assistance.
• The studies described assess the device's standalone performance in aiding visualization and identifying abnormalities that are then confirmed by histology. The focus is on the G.o.c.c.l.e.s. eyewear's ability to facilitate detection, rather than quantifying the improvement in human reader performance when using the device compared to not using it. While the device enhances visualization, it's not positioned as an AI-powered independent diagnostic tool in this context, but rather an enhancement for human examination.

6. Standalone (Algorithm Only) Performance

• Yes, standalone performance was done for the device in the sense that the G.o.c.c.l.e.s. eyewear, in conjunction with a light source, was used to identify abnormalities, and these findings were then validated against a ground truth (histology).
• The device itself is a passive optical filter (eyewear) that enhances visualization, it's not an "algorithm" in the typical AI sense. The performance tests ("Results" sections of the clinical studies) present how many lesions the G.o.c.c.l.e.s. system identified before histological confirmation, indicating its standalone diagnostic utility as an enhancement tool.

7. Type of Ground Truth Used

• Histology (Pathology): In both clinical studies, "histological analyses" of surgically excised lesions were used to confirm the diagnosis of suspected tumors, dysplasia, carcinoma in situ, or invasive cancer. This is explicitly stated as the method for confirming the findings from the autofluorescence inspection.

8. Sample Size for the Training Set

• The document does not mention any training set or any machine learning/AI models that would require one. The G.o.c.c.l.e.s. device is a passive optical system, not an AI/ML algorithm. The "studies" described are performance validation studies, not studies for training or validating an algorithmic model.

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

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

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The TUTU ™ LED intraoral curing light is designed to polymerize visible light cure (VLC) dental materials including dental pit and fissure sealants, bonding adhesives, cements, restorative or luting materials

The TuTu7 is a LED curing light that is small and easy to use, vet powerful and swift in curing. It has a compact, lightweight hand piece, with a curved and contoured tip, to allow the light to be positioned and applied anywhere in the oral cavity. The TuTu has 3 different functioning modes, continuous, pulse and ramp. The device peeps every 3 seconds for precise timing of exposure, regardless of mode setting. The rechargeable battery is a Lithium lon, which at full charge can last up to 120 minutes. The TuTu is provided with a battery charger, which also acts as a storage holder for the device. A silicone sheath is provided to refract the light and protect the eyes of the operator.

Here's an analysis of the acceptance criteria and study information for the Invisible Technology TuTu 7 Dental Curing Light, based on the provided 510(k) summary:

This device (TuTu 7 Dental Curing Light) is a physical device, not an AI/Software as a Medical Device (SaMD). Therefore, the concepts of "acceptance criteria" and "study that proves the device meets the acceptance criteria" as typically applied to AI/SaMD (which involve performance metrics like sensitivity, specificity, F1 score, etc., against a ground truth) are not fully applicable in the same way.

For a physical medical device like a dental curing light, acceptance criteria generally relate to technical specifications, safety, and functional performance benchmarks that demonstrate substantial equivalence to predicate devices. The "study" here would be various tests and measurements conducted to show the device meets these technical specifications and performs its intended function safely and effectively.

Based on the provided text, the "acceptance criteria" are implied by the comparison to the predicate devices and the physical specifications of the TuTu 7. The 510(k) process primarily focuses on demonstrating substantial equivalence to a currently marketed predicate device, rather than proving efficacy through a large-scale clinical study in the way an AI/SaMD would.

Here's an attempt to structure the information as requested, adapting for a physical device:

Acceptance Criteria and Device Performance for Invisible Technology TuTu 7 Dental Curing Light

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size for Test Set and Data Provenance

This information is not applicable in the context of an AI/SaMD's "test set" for performance evaluation against a dataset. For a physical device like a curing light, "testing" refers to laboratory bench testing, electrical safety tests, optical power measurements, etc. The 510(k) summary provided does not detail the specific sample sizes for these types of engineering tests, nor does it specify data provenance in terms of country of origin or retrospective/prospective studies. The "data" would be the results of the engineering and performance testing of the device itself.

3. Number of Experts and Qualifications for Ground Truth

This concept is not applicable as described for an AI/SaMD. There is no "ground truth" established by experts in the context of evaluating the predictive accuracy of a dental curing light. The performance is assessed through objective physical measurements and comparisons to established standards for power, wavelength, and functional operation.

4. Adjudication Method

This concept is not applicable for a physical device. Adjudication methods (like 2+1, 3+1) are used to resolve disagreements among human annotators when establishing a "ground truth" for a dataset, which is not relevant here.

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

This is not applicable for a dental curing light. MRMC studies are designed to assess the impact of a diagnostic aid (like a CAD system) on human reader performance, which doesn't apply to a device that directly performs a therapeutic function (light curing).

6. Standalone (Algorithm Only) Performance Study

This is not applicable as the TuTu 7 is a physical device, not an algorithm or software. It does not have an "algorithm-only" mode separate from human interaction, nor does it generate diagnostic outputs that would be evaluated for standalone performance.

7. Type of Ground Truth Used

The "ground truth" for this type of device is implicitly defined by:

• Engineering specifications and standards: Wavelength range, power output, beam uniformity, heat generation, battery life.
• Performance of predicate devices: The TuTu 7 is compared against known, legally marketed predicate devices (SmartLite PS Pen-Style LED Curing Light and Elipar FreeLight) to demonstrate similar fundamental technology and performance characteristics.
• Material polymerization efficacy: While not explicitly detailed as a "study" in this summary fragment, the ability of the light to cure dental materials effectively to industry standards would be a critical aspect of its performance validation. This would typically involve testing with various depths/materials to ensure adequate cure.

8. Sample Size for Training Set

This is not applicable. The device is not an AI/SaMD that requires a training set.

9. How Ground Truth for Training Set was Established

This is not applicable as there is no training set for a physical device like this.

Summary of the "Study" (Demonstration of Substantial Equivalence):

The information provided indicates that the "study" for the TuTu 7 Dental Curing Light primarily involved demonstrating its substantial equivalence to two predicate devices, the Dentsply International SmartLite PS Pen-Style LED Curing Light (K041372) and the 3M ESPE AG Elipar FreeLight (K011154).

This demonstration relied on:

• Comparative Table of Technological Characteristics: Showing that the TuTu 7 shares the same product code, CFR, and fundamental technology (LED blue light curing) as the predicates.
• Specification Comparison: Comparing key performance parameters like wavelength range, power output (watts mW-cm), battery type, weight, and features (e.g., multiple curing times) to the predicates. The TuTu 7 often met or exceeded the specifications of its predicates (e.g., higher power output, comparable wavelength range).
• Intended Use Alignment: Confirming that the intended use of the TuTu 7 is identical to that of legally marketed predicate devices.
• General Controls Compliance: The device is subject to the general controls provisions of the Act, which include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration.

The FDA's review and determination of substantial equivalence (as indicated in the letter K062735) signifies that the device meets the necessary criteria for market entry, primarily by demonstrating that it is as safe and effective as a legally marketed predecessor device.

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photo-polymerization in the 430-490 nm waveband of visible light cured (VLC) dental materials,
photo-polymerization in the 430-490 nm waveband of visible light cured (VLC) restorative composite materials, and
photo-polymerization in the 430-490 nm waveband of visible light cured (VLC) orthodontic brackets, and orthodontic bonding and sealing materials.

The Satelec Mini L.E.D. product is classified as an Ultraviolet Activator for Polymerization (21 C.F.R.§ 872.6070) because it is a device intended for the photopolymerization of light cured dental materials, restorative composite materials, and orthodontic bonding and sealing materials. The Mini L.E.D. is a universal photopolymerization light curing source working in cordless conditions and producing visible blue light in the 430 to 490 nm waveband of the spectrum with a power density comprised between 1,000 W/cm² (Universal 7.5 mm light-guide) and 2,000 W/cm² (BoosterTip 5.5 mm light-quide).

This Satelec Mini L.E.D. Polymerization Light-Curing Device 510(k) submission (K032465) focuses on demonstrating substantial equivalence to predicate devices rather than proving performance against specific acceptance criteria through a standalone study with a defined test set, ground truth, and expert adjudication.

Therefore, many of the requested details about acceptance criteria, study design, and performance metrics are not explicitly available or applicable in the provided 510(k) summary. The submission primarily relies on comparing the device's characteristics and intended use to already cleared devices.

Here's an attempt to answer the questions based on the provided text, indicating where information is not present:

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

The 510(k) summary does not present a formal table of acceptance criteria with corresponding device performance metrics in the way a clinical study or performance verification test would. Instead, the "performance" is implicitly demonstrated through the device's specifications and comparison to predicate devices, particularly regarding its ability to achieve sufficient power density within the stated wavelength band for polymerization.

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 submission does not describe a clinical or performance test set. The submission relies on technical specifications and comparison to predicate devices rather than new performance data from a "test set."

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 as there is no described test set or ground truth established by experts within the context of a performance study in the 510(k) summary.

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

This information is not provided as there is no described test set or adjudication process 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

A multi-reader multi-case (MRMC) comparative effectiveness study was not conducted as this is a dental polymerization light-curing device. This type of study is more relevant for diagnostic AI devices where human reader performance is being evaluated with and without AI assistance.

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

A "standalone" performance study in the context of an algorithm or AI is not applicable here. This device is a physical light-curing tool. Its performance is inherent to its physical properties (wavelength, power density) and its ability to cure dental materials, not an "algorithm only" performance.

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

The concept of "ground truth" as typically defined for diagnostic or AI-driven devices is not directly applicable here. The "truth" for this device's function is its physical specifications (power density, wavelength output) and its ability to effectively polymerize various dental materials. This is assessed through physical measurements and material science principles, not expert consensus or pathology on a clinical dataset. The implicit "ground truth" for showing effectiveness is the established ability of the predicate devices to cure materials effectively.

8. The sample size for the training set

This information is not provided and is not applicable to this type of device. The device does not involve a "training set" in the context of machine learning or AI.

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

This information is not provided and is not applicable to this type of device. There is no training set mentioned in the context of this 510(k) submission.

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