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[Indications for use of Q-switched Nd:YAG Laser]
1064 nm (including RTP 1064 mode):

• Incision, excision, ablation, vaporization of soft tissue for general dermatology
• Removal or lightening of unwanted hair with or without adjuvant preparation
• Treatment melasma
• Treatment of Pigmented Lesions
• · nevus of ota
• Skin resurfacing procedures for the treatment of acne scars and wrinkles
• Tattoo Removal
• dark ink: black, blue and brown

532 nm:

• Treatment of Vascular Lesions
• · port wine birthmarks
• · telangiectaias
• · spider angioma
• · cherry angioma
• · spider nevi
• Treatment of Pigmented Lesions
• · café-au-lait birthmarks
• · solar lentiginos
• · senile lentiginos
• · becker's nevi
• · freckles
• nevus spilus
• nevus of ota
• Skin resurfacing procedures for the treatment of acne scars and wrinkles
• Tattoo Removal
• · light ink: red, sky blue, green, tan, purple, and orange

[Indications for use of FR mode in Nd:YAG Laser]

• Removal of unwanted hair, for stable long term or permanent hair reduction and treatment of PFB (Pseudofollicultis Barbae). The laser is indicated for all skin types, Fitzpatrick I-VI, including tanned skin
• Photocoagulation and hemostasis of pigmented and vascular lesions, such as but not limited to port wine stains, cherry angioma, Hemangiomas, warts, telangiectasias, rosacea, leg veins, and spider veins
• Coagulation and hemostasis of soft tissue
• Treatment of wrinkles
  [Indications for use of Ti:Sapphire Laser]
  785nm:
• Removal of tattoos for Fitzpatrick skin types II-IV to treat the following tattoo colors: green and blue.
  *Q-switched Nd:YAG Laser and Ti:Sapphire Laser cannot be used simultaneously *

The flash lamp as a laser pumping source converts electric energy to light energy when a high voltage is applied. Nd:YAG crystal with the specific resonator emits an 1064nm single wavelength laser by absorbing light energy from the flash lamp. Q-switching mode is applied to the 1064nm laser resonator to amplify the 1064nm laser with about 10ns short pulse width.
The amplified O-switched 1064nm laser is secondarily amplified by an another Nd: YAG crystal and, then is converted to a second harmonic 532nm laser by passing through KTP crystal.
Finally a 785nm laser is emitted by the 785nm cavity with Ti:Sapphire crystal using the 532nm laser as a laser pumping source.
HELIOS 785 Pico Laser System can emit 1064nm, 532nm, and 785nm laser selectively by switching the wavelength conversion optical modules. The 1064nm laser is emitted by only Nd: Y AG crystal resonator and the 532nm laser can be emitted with the 1064nm laser and KTP crystal. The 785nm laser can be emitted by all optical modules.
The Q-switch mode normally produces polarized light, but it is also possible to set the FR(Free Running) mode, which emits light in all directions by removing the optics of the Q-switch module. Additionally, the RTP(Real Twin Pulse) mode can be set to generate two identical pulses with a very short interval instead of a single pulse.
The HELIOS 785 Pico laser system consists of:
a) A high voltage power supply, which converts and rectifies Alternating Current (AC) to provide regulated power for the flashlamp simmer current and main triggering pulse.
b) A cooling system consisting of an internal water flow circuit together with water-to-air heat exchanger.
c) The micro processor based controller unit, which regulates the functions of both lasers and allows parameter selection by the user.
d) The Nd: YAG laser + Ti:sapphire laser head.

This document is a 510(k) summary for the HELIOS 785 Pico (1754V2) laser system. It describes the device's characteristics and compares it to predicate devices to establish substantial equivalence. However, it does not contain explicit acceptance criteria, performance data from a specific study to prove the device meets acceptance criteria, or details regarding ground truth establishment, expert adjudication, or sample sizes for training and test sets in the context of an AI/algorithm performance study.

The "Performance Data" section (page 13) refers to non-clinical tests for safety and performance according to consensus standards, but these are general engineering and safety standards for laser products, not typical performance metrics for an AI medical device like sensitivity, specificity, or accuracy derived from clinical data.

Therefore, many requested points cannot be extracted from the provided text.

Here is the information that can be extracted, with notes for the missing information:

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

This information is not provided in the document. The document refers to non-clinical safety and performance tests against consensus standards (e.g., IEC 60601-1, IEC 60601-1-2, IEC 60825-1, ISO 14971, IEC 60601-1-6, IEC 60601-2-22) for the laser device itself, but it does not specify quantitative acceptance criteria or clinical performance metrics (like accuracy, sensitivity, specificity) for a specific medical indication, which would typically be included for an AI/algorithm-based device.

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. The document details the laser device's technical specifications and intended uses, but it does not mention a test set or data related to any clinical evaluation for performance.

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's no mention of a test set or clinical performance evaluation, there's no information on experts for ground truth establishment.

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

This information is not provided.

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

This information is not provided. The document is for a laser surgical instrument, not an AI-assisted diagnostic or treatment planning system that would typically undergo an MRMC study.

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

This information is not provided. The device is a laser system, not a standalone algorithm.

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

This information is not provided.

8. The sample size for the training set

This information is not provided.

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

This information is not provided.

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[Indication for use of Q-switched Nd:YAG Laser]

• Incision, excision, ablation, vaporization of soft tissue for general dermatology (1064nm)
• Removal or lightening of unwanted hair with or without adjuvant preparation (1064nm)
• Tattoo Removal (1064nm, 532nm)
  dark ink : blue and black (1064nm)
  light ink : red, sky blue, green (532nm)
• Treatment of Benign Vascular Lesions (532nm)
  port wine birthmarks
  telangiectaias
  spider angioma
  cherry angioma
  spider nevi
• Treatment of Benign Pigmented Lesions (1064nm, 532nm)
  café-au-lait birthmarks (532nm)
  solar lentiginos (532nm)
  senile lentiginos (532nm)
  becker's nevi (532nm)
  freckles (532nm)
  nevus spilus (532nm)
  nevus of ota (1064nm)
  [Indication for use of Ti:Sapphire Laser]
  Removal of tattoos for Fitzpatrick skin types II-IV to treat the following tattoo colors: green and blue. (785nm)
  Q-switched Nd:YAG Laser and Ti:Sapphire Laser cannot be used simultaneously.

HELIOS 785 Pico consists of a Q-switched Nd:YAG (1064 nm) laser, frequency doubled KTP Nd:YAG (532 nm) laser, and Ti:Sapphire laser (785 nm). The device consists of a main body, color touch screen, articulated arm, foot switch and several handpieces, and is controlled by an embedded processor. The device uses focusing optics to deliver a pattern of thermal energy to the epidermis and dermis to achieve its intended purpose. It is for prescription use only.

The provided text is a 510(k) Premarket Notification submission for the HELIOS 785 Pico laser device. This document focuses on demonstrating substantial equivalence to existing predicate devices based on technical specifications and non-clinical testing, rather than presenting clinical study data to prove performance against specific acceptance criteria for an AI/software as a medical device (SaMD).

Therefore, the information requested in points 1-9 cannot be fully extracted or inferred from this document. This device is a laser surgical instrument, not an AI/SaMD, and its clearance pathway typically does not involve extensive clinical studies with human readers, ground truth consensus, or the specific types of performance metrics associated with AI algorithms.

Here's a breakdown of why the information is not present and what can be extracted:

Information Not Present in the Document:

• 1. Table of acceptance criteria and reported device performance (in the context of AI/SaMD): This document details technical specifications and non-clinical test validations (e.g., electrical safety, EMC, laser safety standards). It does not present acceptance criteria or performance metrics related to diagnostic accuracy, sensitivity, specificity, or other measures typically used for AI/SaMD.
• 2. Sample size and data provenance for a test set: Not applicable as there's no clinical test set for AI performance. Non-clinical tests were conducted on the device itself.
• 3. Number of experts and qualifications for ground truth: Not applicable.
• 4. Adjudication method: Not applicable.
• 5. Multi-reader multi-case (MRMC) comparative effectiveness study: The document explicitly states: "No clinical study is included in this submission." Therefore, no MRMC study or effect size for human reader improvement with AI assistance was performed or reported.
• 6. Standalone performance for an algorithm: Not applicable, as this is a hardware laser device, not a standalone algorithm.
• 7. Type of ground truth used: Not applicable.
• 8. Sample size for the training set: Not applicable, as there is no AI algorithm being trained.
• 9. How ground truth for the training set was established: Not applicable.

What can be extracted or inferred from the document:

• Device Type: Laser Surgical Instrument (specifically, a combination of Q-switched Nd:YAG and Ti:Sapphire lasers).
• Regulatory Class: Class II (Product Code: GEX).
• Indications for Use: Detailed for both Q-switched Nd:YAG Laser (incision, excision, ablation, vaporization of soft tissue; hair removal; tattoo removal of various colors; treatment of benign vascular lesions; treatment of benign pigmented lesions) and Ti:Sapphire Laser (removal of green and blue tattoos for Fitzpatrick skin types II-IV).
• Comparison to Predicate Devices: The submission is based on demonstrating substantial equivalence to the HELIOS IV 785 (K212663) as the primary predicate and PicoWay Laser System (K191685) as a reference predicate.
• Non-Clinical Testing: The document lists various non-clinical tests conducted to verify the device conforms to relevant mandatory performance standards and design specifications. These include:
  • IEC 60601-1:2005/A1:2012 (Medical Electrical Equipment General Requirements)
  • IEC 60601-1-2:2014 (Electromagnetic Compatibility)
  • IEC 60601-2-22:2012 (Specific Requirements for Laser Equipment)
  • IEC 60825-1: 2014 (Safety of laser products - Part 1: Equipment classification and requirements)
  • Biocompatibility evaluation per ISO 10993 and FDA guidance
  • Usability per IEC 60601-1-6 and IEC 62366
  • Risk management per ISO 14971
  • Software Validation & Verification Test
  • Bench Testing to verify the performance.
• No Clinical Study: The document explicitly states, "No clinical study is included in this submission." This indicates that the substantial equivalence determination for this device relies primarily on the demonstrated technical equivalence and non-clinical testing results, rather than clinical efficacy studies.

In summary, the provided document is a regulatory submission for a physical medical device (laser), not an AI/SaMD. Therefore, it does not contain the information typically associated with the acceptance criteria and study designs for proving AI device performance.

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