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510(k) Data Aggregation
(144 days)
SYSTEMS INTEGRATION ENDOALPHA (MEDICAL CONTROL UNIT FOR ENDOSURGERY UCES-3) Software Version 2
The Systems Integration ENDOALPHA has been designed to be used with an Olympus endoscope and ancillary equipment for central operation, central display, automatic initial setting, and interlocking operation of the ancillary equipment.
UPGRADE KIT FOR UCES-3 (Version 2) MAJ-1943
This equipment has been designed to install software on the ENDOALPHA UCES-3, MAJ-1831, MAJ-1832, MAJ-1834, and MAJ-1862.
The Systems Integration ENDOALPHA has been designed to be used with an Olymous endoscope and ancillary equipment for central operation, central display, automatic initial setting, and interlocking operation of the ancillary equipment.
The ENDOALPHA integrated electrosurgical system has the following system functions.
- Centralized control from a non-sterilized area
- Centralized control from a sterilized area
- Centralized display
- Message display
- Voice reply
- Automatic settings
- Scene settings
- Display customization
- Still image viewing
- Automatic smoke evacuation
The Olympus Medical Systems Corp. 510(k) summary for the SYSTEMS INTEGRATION ENDOALPHA (MEDICAL CONTROL UNIT FOR ENDOSURGERY UCES-3) Software Version 2 describes design verification and software validation activities rather than a clinical study with human subjects. The device is a system for central operation, display, and control of ancillary endosurgery equipment, performing functions like centralized control, display customization, and automatic settings, with software modifications including additional compatible devices, improved interfacing, increased surgical light capacity, reduced startup time, and an additional language setting.
Here's the breakdown of the acceptance criteria and study information:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria Category | Specific Tests / Criteria | Reported Device Performance |
|---|---|---|
| Risk Analysis | Based on ISO 14971:2007 (established in-house acceptance criteria). | Design verification tests performed as a result of risk analysis assessment. |
| Design Verification (Hardware & Integration) | Operation/verification testing for improved interfacing between UCES-3 and the Advanced System. | Implied successful, as the summary states the modifications are "minor and substantially equivalent" and have "similar technological characteristics" and "performance." No specific performance metrics or pass/fail rates are provided beyond the statement that tests were performed. |
| Operation/verification testing for new compatible ancillary equipment. | Implied successful. | |
| Operation/verification testing for the increase in the maximum number of connectable surgical lights. | Implied successful. | |
| Performance testing for the startup time of the UCES-3. | Implied successful, as reduced startup time is listed as a modification. | |
| Operation testing for additional language setting for text indications. | Implied successful. | |
| Software Validation (FDA Guidance) | Unit level testing (Module verification). | Implied successful. The software validation activities were performed in accordance with the FDA Guidance, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices." |
| Integration level testing (Task verification). | Implied successful. | |
| System level testing (System verification). | Implied successful. | |
| Simulated use testing (Validation). | Implied successful. |
2. Sample Size Used for the Test Set and Data Provenance
The document describes software validation and design verification tests, not a clinical study involving human patients or a traditional "test set" of patient data. Therefore, information regarding human sample size or data provenance (country of origin, retrospective/prospective) is not applicable or provided. The "test set" in this context refers to the system itself, its components, and its software functions.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
Not applicable. The "ground truth" for this type of device (an integration system for endosurgery equipment) is based on engineering specifications, functional requirements, and safety standards rather than expert clinical consensus on patient data.
4. Adjudication Method for the Test Set
Not applicable, as this was not a study involving human readers or interpretation of medical images. The acceptance of testing results for design verification and software validation would have been based on engineering and quality assurance protocols.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No, an MRMC comparative effectiveness study was not done. The device is a control system for endosurgery equipment, not a diagnostic or AI-assisted interpretation tool that would involve human readers or image analysis.
6. Standalone Performance Study
Yes, the testing described appears to be for the standalone system in a simulated environment. The "Operation/verification testing" and "Performance testing" for various aspects like interfacing, new equipment compatibility, surgical light capacity, startup time, and language settings, along with "Unit level testing," "Integration level testing," "System level testing," and "Simulated use testing" for software, all represent standalone performance evaluation of the device's functionality. This is "algorithm only without human-in-the-loop performance" in the sense that the system's functions are verified independently of live clinical use.
7. Type of Ground Truth Used
The ground truth used for this type of device is primarily based on:
- Engineering Specifications: Adherence to defined parameters for electrical, mechanical, and communication characteristics, as well as operational principles.
- Functional Requirements: Verification that the system performs its designed functions (e.g., centralized control, display, automatic settings, smoke evacuation) as intended.
- Safety Standards: Compliance with relevant medical device safety standards like ISO 14971:2007 for risk management.
- Software Design Documents: Verification against software requirements specifications and design documents.
8. Sample Size for the Training Set
Not applicable. This device is a control system, not an AI/ML algorithm that requires a "training set" of data in the typical sense (e.g., for image recognition or clinical prediction). The software developed for this system follows conventional software engineering principles rather than machine learning.
9. How the Ground Truth for the Training Set Was Established
Not applicable, as there was no training set for an AI/ML algorithm.
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