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The BiZact device is a bipolar instrument intended for use in open surgical procedures where ligation and division of vessels, tissue bundles, and lymphatics is desired.

The tissue fusion function of the device can be used on vessels (arteries and veins) and lymphatics up to and including 3 mm diameter. The BiZact device is indicated for use in open general surgical procedures.

It is also indicated for adult ENT procedures, including tonsillectomy, for the ligation and division of vessels, tissue bundles and lymphatics 2-3 mm away from unintended thermally sensitive structures.

The BiZact device has not been shown to be effective for tubal sterilization or tubal coagulation for sterilization procedures. Do not use for these procedures.

The BiZact Open Sealer/Divider is sterile, single use, hand-held electrosurgical device that incorporates RF tissue fusion technology for a desired tissue effect when used with the Valleylab™ LS10 Vessel Sealing Generator for ligation of vessels, tissue bundles, and lymphatics during open general surgical procedures.

The BiZact attaches to the Valleylab LS10 Vessel Sealing Generator with a 10 foot cord containing a connector. The generator is able to identify the BiZact device via the RFID tag embedded in the connector. The generator delivers precise energy through the device to tissue for a controlled tissue response to achieve complete and permanent tissue fusion by incorporating tissue sensing circuitry to constantly measure the electrical resistance of the tissue and instantaneously adjust the generator output to maintain the desired power.

This document is a 510(k) Summary for the BiZact Open Sealer/Divider, and as such, it focuses on demonstrating substantial equivalence to a predicate device rather than detailing a study proving the device meets specific acceptance criteria in the way a clinical trial for a novel AI device might. Therefore, many of the requested elements (like sample size for test sets, number of experts, adjudication methods, MRMC studies, standalone performance, training set details) are not applicable or not provided in this regulatory submission for a medical device.

However, I can extract the available information as it relates to demonstrating the device's performance through testing.

Acceptance Criteria and Reported Device Performance

The document does not explicitly state "acceptance criteria" in a table format with numerical targets that were then met by the device. Instead, it lists various performance testing categories to demonstrate that the device performs as intended and is substantially equivalent to its predicate. The "reported device performance" is summarized as having "demonstrated that the BiZact Open Sealer/Divider performs as intended and is substantially equivalent to its predicate, LF1212A."

Here's a table based on the testing categories provided, with the "reported device performance" being the implicit successful completion of these tests.

Study Details:

1. Sample size used for the test set and the data provenance:

   • The document mentions "Performance Testing Bench Tissue burst testing" and "Performance Testing In-vivo acute... and chronic". However, specific sample sizes for these tests (e.g., number of tissue samples, number of animal subjects) are not provided in this summary.
   • Data provenance: Not explicitly stated, but "In-vivo" testing typically implies animal studies conducted under controlled laboratory conditions, usually retrospective for data analysis.

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

   • This information is not applicable in the context of this device's testing. The ground truth for bench and in-vivo performance testing of a surgical device like this is typically established by direct measurement (e.g., burst pressure, thermal spread measurement, visual assessment of hemostasis by trained researchers/veterinary staff), not an expert panel reviewing data in the way an AI diagnostic device would.

3. Adjudication method for the test set:

   • Not applicable. As the "ground truth" is based on direct measurements and observable outcomes, an adjudication method in the sense of resolving disagreements among experts is not typically used for this type of device testing.

4. 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 an electrosurgical instrument, not an AI-powered diagnostic device. Therefore, MRMC studies involving human readers and AI assistance are not relevant.

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

   • Not applicable. This is a hardware-based surgical device; there is no "algorithm only" performance to evaluate. The device itself is the standalone entity.

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

   • For Performance Testing Bench Tissue burst testing, In-vivo acute, and In-vivo chronic, the ground truth would be based on direct physiological/biological measurements and observations (e.g., actual burst pressures measured, direct observation and measurement of thermal spread, assessment of hemostasis by trained personnel). In some cases, histology/pathology might be used to confirm tissue effects, but it's not explicitly stated as the primary ground truth source.

7. The sample size for the training set:

   • Not applicable. This summary describes a physical medical device, not an AI/machine learning algorithm that requires a training set.

8. How the ground truth for the training set was established:

   • Not applicable. As above, no training set is involved for this type of device.

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