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510(k) Data Aggregation
(264 days)
KARL STORZ Endoscopic ICG Imaging System
The KARL STORZ Endoscopic ICG Imaging System is intended to provide real-time endoscopic visible and nearinfrared fluorescence imaging. The KARL STORZ ICG Imaging System enables surgeons to perform minimally invasive surgery using standard endoscopic visible light as well as visual assessment of vessels, blood flow and related tissue perfusion, and at least one of the major extra-hepatic bile duct, common bile duct and common hepatic duct), using near-infrared imaging.
Fluorescence imaging of biliary ducts with the KARL STORZ Endoscopic ICG Imaging System is intended for use with standard of care white light and, when indicated, intraoperative cholangiography. The device is not intended for standalone use for biliary duct visualization.
The KARL STORZ Endoscopic ICG Imaging System is used to provide real-time high definition (HD) endoscopic video images of visible (VIS) and near-infrared (NIR) indocyanine green (ICG) dye fluorescence during minimally invasive surgery. The system components are rigid ICG Endoscopes for VIS and NIR illumination and imaging, a light source with foot switch for emission of VIS and NIR illumination, a 3 CCD (charge coupled device) color video camera head capable of capturing both VIS and NIR imaging, and KARL STORZ Indocyanine Green (ICG Kit). Additional accessories used with the KARL STORZ Endoscopic ICG Imaging System include a standard fiber-optic light cable for transmission of VIS and NIR light and the Image 1 SPIES Camera Control Unit (CCU) cleared in K131953. The KARL STORZ Endoscopic ICG Imaging System can be used with any medical grade HD monitor with a DVI-D or 3G-SDI input. The KARL STORZ Endoscopic ICG Imaging System is a Class II device under 21 CFR 876.1500.
This document is a 510(k) summary for the KARL STORZ Endoscopic ICG Imaging System (K152583). It explicitly states that clinical performance data was not required to demonstrate substantial equivalence to the predicate device. Therefore, no studies were conducted to prove the device meets specific acceptance criteria based on human performance. The following information is based on the provided text, and many sections will indicate that the information is not available as no clinical study was performed.
1. A table of acceptance criteria and the reported device performance
Since no clinical study was performed to establish performance against acceptance criteria in a clinical setting, this table cannot be populated with device performance. The non-clinical performance data focused on functional and safety aspects.
Acceptance Criteria (Clinical) | Reported Device Performance (Clinical) |
---|---|
Not established/applicable (No clinical study performed) | Not applicable (No clinical study performed) |
The document mentions non-clinical performance data:
- "The KARL STORZ Endoscopic ICG Imaging System has been successfully tested for its functions and performance, including verification that the spectral characteristics of the ICG system illumination light source, light transmission system and endoscope enable a selective visualization of the ICG fluorescence signal as detected by the camera system."
- "Furthermore, a GLP animal study was successfully performed by the NAMSA testing facility to evaluate the performance of the KARL STORZ Endoscopic ICG Imaging System in the porcine minimally-invasive laparoscopy model."
- Safety testing: IEC 60601-1 and 60601-2-18 (electrical safety), IEC 60601-1-2 (electromagnetic compatibility), ISO 10993 (biocompatibility).
- Additional validations for system software, manual cleaning method, and sterilization process.
These are functional and safety-related performance measures, not clinical efficacy or diagnostic accuracy metrics typically found in acceptance criteria for AI/diagnostic devices.
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
Not applicable, as no clinical test set was used for human performance evaluation. A GLP animal study was performed in a porcine model. The specific sample size for the animal study is not provided, nor is the country of origin.
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)
Not applicable, as no clinical test set requiring expert ground truth was used.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable, as no clinical test set was used.
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. No MRMC study was done, as clinical testing was not required and the device is an imaging system, not explicitly an AI/diagnostic algorithm that enhances human reader performance in a comparative study.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This device itself is an imaging system. It performs a standalone function of capturing and displaying images. However, the FDA states, "The device is not intended for standalone use for biliary duct visualization," meaning it requires a human surgeon's interpretation in conjunction with white light imaging and potentially intraoperative cholangiography. No 'algorithm-only' performance was assessed independently of the visual output for a human.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
For the non-clinical functional tests, the ground truth would have been established by engineering specifications and physical measurements. For the GLP animal study, the "performance" evaluation would likely involve visual assessment by qualified personnel regarding the visualization of ICG fluorescence in the porcine model. There is no mention of pathology or outcomes data as ground truth.
8. The sample size for the training set
Not applicable. This device is an imaging system, not an AI/ML algorithm that requires a training set in the conventional sense.
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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