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MiDi-SRS is intended for use in dermatological procedures requiring the coagulation of soft tissue.

MiDi-SRS is designed to provide laser energy (1550nm) for use in a variety of dermatology and general surgery procedures. The product consists of main body, a tablet PC, a foot switch, an interlock switch and a key switch. The device fires a 1550nm Er- glass Fiber laser beam which is then split into a number of microscopic beams, producing tiny dot, or pixel-like treatment zones within the selected target area of the skin, leaving the other zones within it perfectly intact.

Here's an analysis of the provided text regarding the MiDi-SRS device's acceptance criteria and studies:

Based on the provided 510(k) summary, the device under review, MiDi-SRS, is a laser surgical unit intended for use in dermatological procedures requiring the coagulation of soft tissue. The summary focuses on demonstrating substantial equivalence to a predicate device (SellaS by Dinona Company, Ltd., K080382) rather than outlining specific, quantifiable acceptance criteria with a statistical study.

Acceptance Criteria and Reported Device Performance

The document does not explicitly state specific quantifiable acceptance criteria for performance metrics in a table. Instead, it relies on demonstrating that the device performs "as well as the predicate device" through non-clinical bench tests and an in vivo animal study.

The primary "performance" reported are histological measurements from in vivo animal testing.

Table 1: Histological Performance of MiDi-SRS (Porcine Model)

Note on Acceptance Criteria: The document states that "All the test results met pre-set criteria and support substantial equivalence to the predicate devices" for the bench tests. For the animal study, it notes that the results "supports that the subject device would perform as well as the predicate device." However, the specific numerical "pre-set criteria" for the bench tests or the comparative histological criteria against the predicate are not detailed.

Study Details

Given the nature of a 510(k) summary, which focuses on substantial equivalence rather than a detailed clinical trial, many of the requested details are not explicitly provided.

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

• Test Set Sample Size: The document mentions "in vivo animal testing using porcine models." It does not specify the number of animals or the number of lesions created within those animals.
• Data Provenance: The study was conducted in a porcine model. The country of origin for the data is not mentioned, though the applicant is from the Republic of Korea. The study appears to be prospective as it involves creating lesions and then observing them at specified time points (immediately, 3-5 days, 10-14 days post-treatment).

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)

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified. The document only states "histological data of values," implying evaluation by appropriately qualified personnel (e.g., pathologists), but their number or qualifications are not detailed.

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

• Adjudication Method: Not specified. It is likely that histological assessments are typically reviewed by individual pathologists, potentially with consensus if discrepancies arise, but no specific method is described here.

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

• MRMC Study: No. This device is a laser surgical instrument, not an AI-assisted diagnostic tool. Therefore, an MRMC study related to human reader improvement with AI is not applicable and was not performed.

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

• Standalone Performance: Not applicable in the context of diagnostic AI. This device is a surgical tool. The performance described (histological outcomes) is the direct result of the device's action on tissue, which is its standalone performance as a surgical tool. The device functions independently in applying laser energy.

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

• Ground Truth Type: Pathology (histological data). The measurements of microscopic treatment zones, measured width, depth, and thermal zones were obtained from tissue samples immediately post treatment; 3-5 days post treatment; and 10-14 days post treatment.

8. The sample size for the training set

• Training Set Sample Size: Not applicable. This document describes a medical device, not an AI/machine learning algorithm that requires a "training set." The device's performance is based on its physical and biological effects, not on being trained on a dataset.

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

• Ground Truth for Training Set: Not applicable, as there is no "training set" for this type of medical device submission.

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