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The SCAR 3 scanner, when used with DEKA CO2 lasers, is indicated for ablation, vaporization, excision, and coagulation of soft tissue in dermatology and plastic surgery.

The SCAR 3 scanner, when used with DEKA CO2 lasers, is indicated for use in the performance of specific applications in dermatology and plastic surgery as follows:

-The ablation, vaporization, excision, and coagulation of soft tissue in the performance of laser burn debridement

-Laser skin resurfacing (ablation and/or vaporization) for treatment of:

· Wrinkles, rhytids, and furrows (including fine lines and texture irregularities)

-Laser skin resurfacing (ablation and/or vaporization) of soft tissue for the reduction, removal, and/or treatment of:

• Acne scars
• · Surgical scars

The SCAR 3 scanning unit is an optional scanner that can be connected to DEKA CO2 lasers.

The SCAR 3 is composed of the following components:

• HiScan SCAR 3 head

• HiScan SCAR 3 cable

Laser emission parameters are selected through the GUI of the DEKA laser device to whom the scanner is connected.

Shape and size of the scanning area may also be selected by using the three keys on the scanning head.

The modification to the device consists in the extension of the DEKA CO2 laser whom the SCAR 3 scanner can be connected to. The predicate device SCAR 3 (K211362) has been cleared to be used specifically in conjunction with DEKA Smartxide family; the proposed SCAR 3 scanner can be connected to all DEKA CO2 lasers.

The indications for use of the modified device remain the same. Modification only extends the range of CO2 laser the scanner can be used with.

Here's an analysis of the provided text regarding the acceptance criteria and study for the SCAR 3 device:

Based on the provided text, the device in question (SCAR 3 scanner) is not an AI/ML powered device, but rather a laser scanning unit. The document describes a 510(k) submission for a modification to an existing device (SCAR 3, K211362), primarily extending its compatibility with a broader range of DEKA CO2 lasers.

Therefore, many of the typical questions related to AI/ML device studies (such as sample size for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, training set details) are not applicable to this submission.

The "acceptance criteria" and "study that proves the device meets the acceptance criteria" in this context refer to engineering and safety performance tests for the medical device itself, not an AI algorithm's diagnostic or predictive performance.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample size used for the test set and the data provenance: Not applicable. These are engineering and safety tests performed on the device itself, not on a dataset of patient data for an algorithm.

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. This device is not an AI/ML diagnostic or prognostic tool requiring expert-labeled ground truth from medical images or patient records.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.

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. This is a laser hardware device, not an AI assistance tool.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable to an AI context. The "ground truth" for this device's performance is adherence to established international and national safety standards (e.g., IEC 60601 series) and its own design specifications (e.g., laser emission validation).

8. The sample size for the training set: Not applicable (no AI/ML algorithm involved).

9. How the ground truth for the training set was established: Not applicable (no AI/ML algorithm involved).

In Summary:

The provided document describes a Special 510(k) submission for a modification to an existing medical laser scanning unit (SCAR 3). The "study" proving it meets acceptance criteria consists of a series of engineering and safety verification tests demonstrating compliance with relevant international standards and ensuring the modification (expanded compatibility with DEKA CO2 lasers) does not negatively impact the device's safety or effectiveness compared to its predicate. It is not an AI/ML device, and thus the questions related to AI algorithm validation studies are not relevant here.

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The SCAR 3 scanner, when used with DEKA Smartxide family lasers (K180193), is indicated for ablation, vaporization, excision, incision, and coagulation of soft tissue in dermatology and plastic surgery.

The SCAR 3 scanner, when used with DEKA Smartxide family lasers (K180193), is indicated for use in the performance of specific applications in dermatology and plastic surgery as follows:

-The ablation, vaporization, excision, incision, and coagulation of soft tissue in the performance of laser burn debridement

-Laser skin resurfacing (ablation and/or vaporization) for treatment of:

· Wrinkles, rhytids, and furrows (including fine lines and texture irregularities)

-Laser skin resurfacing (ablation and/or vaporization) of soft tissue for the reduction, removal, and/or treatment of:

• Acne scars
• · Surgical scars

The SCAR 3 scanning unit is an optional scanner that can be connected to the Deka SmartXide family lasers (K180193).

The SCAR 3 is composed of the following components:

• HiScan SCAR 3 head
• HiScan SCAR 3 cable

Laser emission parameters are selected through the GUI of the DEKA laser device to whom the scanner is connected.

Shape and size of the scanning area may also be selected by using the three keys on the scanning head.

This document is a 510(k) summary for the SCAR 3 scanner, a medical laser scanning unit. The document focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study that proves the device meets specific acceptance criteria. Therefore, many of the requested fields cannot be directly extracted from the provided text.

Here is the information that can be extracted, acknowledging the limitations of the document's purpose:

1. Table of acceptance criteria and the reported device performance

The document does not present specific quantitative acceptance criteria or detailed device performance metrics in a readily extractable table format for clinical efficacy. Instead, it relies on demonstrating substantial equivalence to a predicate device by comparing indications for use, principle of operation, and technological characteristics.

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

The document explicitly states "Clinical Performance Data: None." and discusses "Non-Clinical Performance Data." Therefore, there is no test set in the context of clinical performance data used for this submission. The non-clinical performance data consisted of testing against recognized standards (see point 1 and 8).

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 no clinical performance study with a test set requiring expert-established ground truth was conducted.

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

Not applicable, as no clinical performance study with a test set requiring adjudication was conducted.

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. This device is a laser scanning unit, not an AI-powered diagnostic or assistive tool for human readers. No MRMC study was conducted.

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

Not applicable. This device is a physical laser scanning unit, not an algorithm. Performance was evaluated through non-clinical testing against standards.

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

For the non-clinical performance testing (compliance with standards), the "ground truth" was compliance with the specified requirements and criteria outlined in the standards (e.g., electrical safety limits, electromagnetic compatibility limits, laser safety classifications). This is determined by engineering measurements and tests.

8. The sample size for the training set

Not applicable, as no clinical performance or machine learning study involving a training set was conducted for this submission. The device is a physical medical instrument.

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

Not applicable, as no training set was used.

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