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The Medline ReNewal Reprocessed Sonicision Cordless Ultrasonic Dissector model SCD13 is indicated for soft tissue incisions when bleeding control and minimal thermal injury are desired. The device can be used as an adjunct to or substitute for electrosurgery, lasers, and steel scalpels in general, plastic, pediatric, gynecologic, urologic, exposure to orthopedic structures (such as spine and joint space) and other open and endoscopic procedures. The Sonicision Cordless Ultrasonic Dissection Device can be used to coagulate isolated vessels up to 5 mm diameter.
The Sonicision 13-cm device is also indicated for use in otorhinolaryngologic (ENT) procedures.

The Medline ReNewal Reprocessed Sonicision Cordless Ultrasonic Dissector model SCD13, is a sterile, single-use component to which the Sonicision Reusable Generator and Reusable Battery Pack attach. (The Sonicision Reusable Generator and Reusable Battery Pack are not included in this submission and will not be reprocessed by Medline ReNewal.) This component provides control for device functions such as selecting power levels, blade placement and position, grasping, coagulating and dissecting tissue. The Cordless Ultrasonic Dissection Device can coagulate vessels up to 5 mm in diameter. Furthermore, it is designed to be inserted and extracted through a compatible 5 mm trocar, when used endoscopically.

The provided FDA 510(k) summary for the Medline ReNewal Reprocessed Sonicision Cordless Ultrasonic Dissector, model SCD13 (K173627), does not contain information about acceptance criteria and the study that proves the device meets those criteria in the format requested, particularly for AI/ML-based devices. This submission is for a reprocessed surgical instrument and focuses on demonstrating substantial equivalence to a predicate device through functional, performance, and biocompatibility testing, rather than presenting clinical study results with acceptance criteria typical for diagnostic or AI-powered devices.

However, I can extract information related to performance testing and the type of evidence used to support the substantial equivalence claim. Since this is not an AI/ML device, many of the requested fields (like effect size with/without AI, sample size for test set/training set for AI, number of experts for ground truth, adjudication method, etc.) are not applicable.

Here's an adaptation of the requested table and information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a reprocessed device demonstrating substantial equivalence to a predicate, the "acceptance criteria" are implicitly that the reprocessed device performs comparably to the original predicate device across various functional and safety aspects. The reported performance aims to show this comparability.

2. Sample Size Used for the Test Set and Data Provenance

The document does not specify a "sample size" in the context of a "test set" for diagnostic performance, as this is a surgical instrument.
For the performance testing:

• Bench tests: The number of devices or trials tested for each bench criterion (e.g., simulated use, grasping force, cutting effectiveness, cleaning, drop test, device integrity, tissue sticking, prolonged cutting/coagulation evaluation, thermal spread) is not explicitly stated in the summary.
• Acute ex vivo: Tissue types and vessel sizes evaluated are listed (Hypogastric, Short Gastric, Gastrosplenic, Ovarian Pedicle for A/V Bundle, Splenic, Renal for Isolated Arteries or Veins, all up to 5mm diameter), but the number of vessels or tissue samples tested is not provided.
• Chronic in vivo: A single 21-day chronic in vivo study was conducted using a porcine model. The number of animals used is not specified.

Data Provenance: The studies are described as bench tests, ex vivo (tissue samples, likely animal or cadaveric), and in vivo (porcine model). The country of origin for these studies is not specified in the provided summary.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

There is no mention of "experts" establish a "ground truth" for a diagnostic test set, as this is related to a surgical instrument's functional performance and reprocessing safety. The evaluation would have been performed by qualified laboratory personnel and veterinary surgeons (for in vivo studies), but not "experts" in the context of diagnostic interpretation.

4. Adjudication Method for the Test Set

Not applicable, as this is not a diagnostic test requiring adjudication of interpretations.

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 reprocessed surgical instrument, not an AI-assisted diagnostic tool.

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

Not applicable. This is not an algorithm or AI device. The device's performance is standalone in the sense that its functional capabilities are evaluated independently, but it is ultimately used by a human surgeon.

7. The type of ground truth used

The "ground truth" for this type of device is established through:

• Direct measurement: For physical properties (e.g., grasping force, cutting effectiveness, device integrity, cleaning efficacy).
• Histopathology/Morphometry: For tissue effects like thermal spread and absence of injury in collateral structures.
• Direct observation and assessment: For simulated use and in vivo studies (e.g., visual assessment of vessel sealing, absence of hemorrhage).
• Laboratory assays: For biocompatibility (cytotoxicity, endotoxins).
• Comparison to predicate device: The ultimate "ground truth" for substantial equivalence is demonstrating that the reprocessed device performs as safely and effectively as the original, legally marketed predicate device.

8. The sample size for the training set

Not applicable. This device does not use machine learning or AI, and therefore has no "training set."

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

Not applicable, as there is no training set for an AI/ML model for this device.

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