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The Surgical Tissue Management System is intended to be used with the Ultrasonic Generator (USG-400), the Electrosurgical Generator (ESG-400), the THUNDERBEAT Transducer (TD-TB400), the SONICBEAT Transducer (TD-SB400), the THUNDERBEAT, and / or the SONICBEAT for open, laparoscopic (including single-site surgery), and endoscopic surgery to cut (dissect) or coagulate soft tissue or to ligate (seal and cut) vessels.

The Surgical Tissue Management System has three output modes, Seal & Cut (THUNDERBEAT), Seal (THUNDERBEAT) and Ultrasonic (SONICBEAT). The Seal & Cut mode provides combined HF bipolar and ultrasonic energy, the seal mode provides only HF bipolar energy and the Ultrasonic mode provides only ultrasonic energy.

This system has not been shown to be effective for tubal sterilization or tubal coagulation for sterilization procedures, and should not be used for these procedures.

The Surgical tissue management system has been designed to be used for open, laparoscopic, and endoscopic procedures in surgery. With the Ultrasonic Generator (USG-400) as the main component, the system is composed of the Electrosurgical Generator (ESG-400, K103032), the THUNDERBEAT (TB-0545PC, 0535PC, 0545IC, 0535IC, 0520IC, 0510IC), the SONICBEAT (SB-0545PC, 0535PC, 0545IC, 0535IC, 0520IC, 0510IC), and the Transducer (TD-TB400, TD-SB400).

Here's an analysis of the provided text regarding the acceptance criteria and study proving the device meets them:

The document (K111202) describes the Olympus Surgical Tissue Management System, which combines ultrasonic and HF bipolar energy for cutting, coagulating, and ligating tissue and vessels. The key study supporting its substantial equivalence involves non-clinical (bench) and preclinical (animal) testing.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implicitly defined by demonstrating substantial equivalence to predicate devices, particularly regarding sealing performance, thermal spread, coagulation, and cutting speed. The non-clinical and preclinical studies directly evaluate these aspects.

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

• Test Set Description: The test set for pre-clinical evaluation consisted of:
  • Ex vivo: Excised porcine carotid, splenic, renal arteries, mesenterium, and jejunum.
  • In vivo (acute): Porcine models (for overall hemostasis, cutting speed, lateral thermal spread).
  • In vivo (chronic/survival): Canine models (for maintaining hemostasis, tissue healing, blood testing).
• Sample Size: The document does not explicitly state the numerical sample size (e.g., number of vessels, number of animals) for each test. It refers to "excised porcine" and "porcine models" and "canine models."
• Data Provenance: The data comes from preclinical animal studies using porcine and canine models, and bench testing using excised porcine tissue. The country of origin is not explicitly stated, but the applicant (Olympus Medical Systems Corp.) is in Japan, and the official correspondent (Olympus America Inc.) is in the USA. The testing aligns with international standards. These studies are prospective in nature, as they were conducted to evaluate the performance of the new device.

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

The document does not mention the use of human "experts" to establish ground truth in the context of these preclinical studies. The "ground truth" for the performance evaluation (e.g., burst pressure, thermal spread measurement, histological analysis) would be established by:

• Quantitative measurements: Using calibrated equipment to measure parameters like burst pressure, cutting speed, and thermal spread.
• Histological analysis: Performed by veterinary pathologists or similar specialists, though their specific number and qualifications are not detailed.
• Observation by researchers/veterinarians: For evaluating overall hemostasis and tissue healing in animal models.

The study relies on objective physiological measurements and established scientific methods rather than expert consensus on subjective evaluations.

4. Adjudication Method for the Test Set

No adjudication method in the context of human expert review is mentioned, as the studies are primarily quantitative and animal-based. The assessments are direct measurements and observations, likely performed by trained technicians and scientists following defined protocols.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. MRMC studies are typically performed for diagnostic imaging devices where multiple human readers interpret medical images and their performance is compared with and without AI assistance. This device is a surgical instrument, and its effectiveness is evaluated through direct performance metrics (sealing strength, cutting speed, thermal spread) in animal and bench models, not through human interpretation of cases.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

This question is not directly applicable to the device described. The Surgical Tissue Management System is a medical instrument used directly by a surgeon (human-in-the-loop). It is not an AI algorithm designed to operate autonomously or provide diagnostic interpretations. The "performance" described is that of the physical device as it interacts with tissue, not an algorithm's output.

7. The Type of Ground Truth Used

The ground truth used in these studies is primarily:

• Physiological Measurements: Objective measurements of physical parameters such as vessel burst pressure, cutting speed (time taken), and temperature (for thermal spread).
• Histopathology: Microscopic examination of tissue samples from chronic animal studies to assess healing and tissue damage.
• Direct Observation: For parameters like overall hemostasis in acute animal models.

This is a combination of objective physiological data and pathological assessment from preclinical models, rather than expert consensus on qualitative observations or outcomes data from human patients.

8. The Sample Size for the Training Set

The concept of a "training set" is not applicable here because this device is a physical medical instrument, not an AI algorithm that undergoes machine learning training. The studies described are for verification and validation of its mechanical, electrical, and functional performance, not for training a model.

9. How the Ground Truth for the Training Set Was Established

Not applicable, as there is no training set for this type of device.

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