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The DP4 microneedling device is a microneedling device and accessories intended to be used as a treatment to improve the appearance of facial acne scars in Fitzpatrick skin types I, II, III, IV and V in adults aged 22 years or older.

DP4 Microneedling device is a Digital Automated Microneedling system. The DP4 system consists of the following components:

• 1. Handpiece
• 2. Needle Cartridge
• 3. DP4 Sleeve (barrier sleeve)
• 4. Battery Charger, 2 Batteries
• 5. AC/DC Power Adaptor
• 6. Desk Stand
• 7. DP4 US™ companion app.

The handpiece (1) contains a mains connector, a drive train, a digital display to relay information to the operator an ON/OFF button and 2 separate toggle buttons to adjust frequency and needle depth.
The handpiece receives its power via an external AC/DC power adaptor (input Voltage/Current is 100-240VAC, 1.0-0.5A,50-60Hz: Output Voltage/Current: 5V DC, 2.4A) or removable lithium ion battery (3.7 VDC). The battery does not need to be removed to make use of the mains power adaptor. The power adaptor connects to the handpiece via a custom DC connection (over-mold bayonet type).
The drive train encompasses a DC motor, eccentric cam and rotational to linear drive converter to oscillate the Cartridge needles.
The digital display shows battery status, cartridge status, sync/update notifications and bluetooth connectivity. The display also contains a digital dial to convey frequency or motor speed and a 3figure display showing current needle depth.
The frequency of oscillation can be set from 80-110Hz (+/-10 Hz(range 70-120Hz) and the needle depth from 0.2mm to 3mm.
The DP4 needle Cartridge (2) is a sterile, single use consumable designed to create micro incisions in the epidermis and dermis. Each cartridge contains 16, 3mm, 33-gauge surgical grade stainless steel needles, arranged in a circular pattern. Each needle cartridge employs a bayonet feature to securely connect it to the handpiece during operation. Internal and external seals assist in the prevention of cross contamination. Each needle Cartridge contains a Radio-frequency identification (RFID) tag encoded with a unique ID and a needle depth correction factor. This information is read from the cartridge when it is first inserted into the handpiece and prevents reuse of the cartridge once the cartridge is removed from the handpiece.
The DP4 sleeve (3) is a single use, sterile, biohazard barrier used to prevent contamination of the handpiece by bodily fluids generated during the treatment. It covers the extent of the handpiece, including the intersection between the handpiece and needle Cartridge.
The battery charger (4) is capable of charging 1 x 14500 Lithium cell. The system batteries can only be charged when removed from the handpiece and inserted into the battery charger.
The desk stand (5) is used for storage of device while not in use.
The DP4 US companion app software application (6) is an app. run on a Bluetooth enabled User device to enable the User to interact with the DP4 CRM system. The app contains no patient data and transmits no patient data. The equipment is not used to make measurements of any sort, or to draw any conclusions regarding the indication to treat.

The provided text describes the 510(k) summary for the DP4 Microneedling device. It outlines the device's characteristics, comparison to a predicate device, and the results of clinical studies to demonstrate safety and effectiveness.

However, the document does not contain the typical "acceptance criteria" and "reported device performance" table that would be used in the context of an AI/ML medical device, which is what your prompt specifically asks for. This document is for a physical microneedling device, and the clinical studies are designed to show improvements in a medical condition (acne scars) and safety, rather than the performance of an algorithm against pre-defined metrics.

Therefore, for aspects of your request related to AI/ML device performance metrics (like sensitivity, specificity, AUC), ground truth establishment for a model, training set size, and reader studies for AI assistance, the provided document does not contain this information.

I will attempt to extract information related to "acceptance criteria" by interpreting the effectiveness outcomes from the clinical studies as the criteria for "performance acceptability" for this physical device.

Here's an attempt to answer your questions based on the provided text, acknowledging that the context is a physical medical device, not an AI/ML algorithm:

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

The document does not explicitly state "acceptance criteria" in a quantitative table format as one would find for an AI/ML device (e.g., minimum sensitivity of X%). However, the "Effectiveness conclusions" section of Study #1 serves as the primary performance outcome demonstrating the device's efficacy. The implicit "acceptance" is the FDA's determination of substantial equivalence based on these results.

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

• Study #1:
  • Test Set Sample Size: 22 healthy patients (n=22).
  • Data Provenance: Not explicitly stated regarding country of origin, but the submission is to the US FDA, and the study details suggest a single center. The study was prospective as patients underwent treatments and follow-up specifically for the study.
• Study #2:
  • Test Set Sample Size: 20 healthy patients (n=20).
  • Data Provenance: Not explicitly stated regarding country of origin, but conducted by "the sponsor." The study design was an "open label study," implying a prospective design.

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

The "ground truth" for success was established by clinical assessment of acne scarring from photographic evidence.

• Study #1: Three independent blinded physicians were used to assess the scarring retrospectively from a randomized set of images using the Acne Scar Assessment Scale (ASAS). Their specific qualifications (e.g., "radiologist with 10 years of experience") are not provided.
• Study #2: Two independent blinded physicians were used to assess the scarring retrospectively from a randomized set of images using the Acne Scar Assessment Scale (ASAS) and the Goodman and Baron acne scar grading scale. Their specific qualifications are not provided.

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

The document describes assessments by multiple evaluators (3 in Study #1, 2 in Study #2) and presents their individual and averaged results. It does not describe an explicit adjudication method (like 2+1 or 3+1) to arrive at a single consensus ground truth for each case. The results are presented based on the evaluators' independent scoring or mean scores.

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, an MRMC comparative effectiveness study involving AI assistance for human readers was not done. This device is a physical microneedling device, not an AI-powered diagnostic or assistive tool.

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

Not applicable. This is a physical medical device, not an algorithm. Therefore, "standalone" performance in the context of an algorithm is irrelevant. Its performance is measured directly by its clinical effect on patients.

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

The ground truth for the effectiveness of the device in improving facial acne scars was based on:

• Expert Consensus/Opinion: Assessments by independent blinded physicians using standardized scales (Acne Scar Assessment Scale, Goodman and Baron acne scar grading scale) from photographic evidence.
• Patient Reported Outcomes: Patients' direct feedback on improvement, satisfaction, and willingness to recommend.
• Outcomes Data: Reduction in acne scarring appearance as measured by clinical scales.
• Safety Data: Incidence and severity of adverse events and patient-reported side effects.

8. The sample size for the training set

Not applicable. This is a physical medical device, not an AI/ML algorithm that requires a training set. The "training" for this device involved its design, engineering, and manufacturing.

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

Not applicable, as there is no "training set" in the AI/ML context for this physical device.

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