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510(k) Data Aggregation
(83 days)
VS3-IR system
The 3D Endoscope Module of the VS3-IR System is intended for viewing internal surgical sites during general surgical procedures, for use in visualization of ventricles and structures within the brain during neurological surgical procedures, viewing internal surgical sites during and posterior spinal procedures, such as nucleotomy, discectomy, and foraminotomy, and shoulder and knee arthroscopic procedures.
The MMS configuration of the Iridium Module of the VS3-IR System is intended for capturing fluorescent images for the visual assessment of blood flow, as an adjunctive method for the evaluation of tissue perfusion, and related tissue-transfer circulation in tissue and free flaps used in plastic. micro- and reconstructive surgical procedures.
The Endoscope configuration of the Iridium Module of the VS3-IR System is intended to provide real-time endoscopic visible and near infrared fluorescence imaging. Iridium Endoscope enables surgeons to perform routine visible light endoscopic procedures as well as further visually assess vessels, blood flow and related tissue perfusion with near infrared imaging during minimally invasive surgery.
The VS3-IR System is made up of the following components:
- VS3 3D Endoscope (K123467, K141002, K131434)
- VS3-IR-MMS & ICG Kit (K150018)
- VS3-IR-Endoscope & ICG Kit (not yet assigned).
The VS3 3D endoscopes (cleared in K123467, K131434, and K141002) are based on the proximal camera concept with a stereoscopic camera block on the proximal side of the endoscope (the handle). The stereoscopic images are transmitted from the visual field at the distal tip of the endoscope to the proximal camera block through an optical transmission system to PC workstations or external display monitors for enhanced viewing or capturing. VS3 includes reusable endoscopes which are cleaned and sterilized using the same methods and are indicated for the same lifecycle.
In addition to traditional endoscopic procedures, VS3-IR system includes support for Infrared (IR) Fluorescence visualization (hereafter referred to as Iridium utilizes the VS3 system with scopes that support IR fluorescence visualization. VS3 Iridium Miniature Microscope (VS3-IR-MMS) which was cleared in K150018 is positioned 20cm to 45cm above the patient during an open procedure. The proposed Iridium Endoscopes (VS3-R-Endoscope) is used during laparoscopic minimally invasive procedures. VS3 Iridium MMS and Endoscopes are designed to work with an approved IR fluorescence dve (Indocvanine Green or ICG), which has excitation at 805nm and emission band between 825nm and 850nm. VS3 Iridium (VS3-IR) provides excitation light to the surgical field to excite the dye molecules and captures emission from the dye using an IR camera.
Both the Iridium MMS and Iridium Endoscope utilize the left channel of the VS3 imaging system (camera and image processor) for IR fluorescence imaging and the right channel for visible light imaging. This structure allows fluorescence imaging to use the same acquisition and processing pathways as the approved 3D endoscopes (cleared in K123467, K131434, and K141002).
The provided document describes the acceptance criteria and study for the Visionsense VS3-IR System, specifically focusing on the VS3-IR-Endoscope component.
Here's a breakdown of the requested information:
1. Table of Acceptance Criteria and Reported Device Performance
The document does not explicitly present a table of "acceptance criteria" with quantitative metrics alongside "reported device performance" in a separate column. Instead, it states that the device "met all performance acceptance criteria" during bench testing. The closest we can get to structured criteria are the functional requirements and the successful detection and visualization described.
Feature/Parameter | Acceptance Criteria (Implied) | Reported (Achieved) Performance |
---|---|---|
Able to function with no camera | Not applicable (requires camera for function) | No |
Working distance | 2cm – 7cm from tissue | Verified to function within 2cm – 7cm from tissue |
Direction Of View | 0°, 30° | Verified to support 0°, 30° |
Software Functionality | Performs as intended per pre-specified requirements | The system software was validated and performs as intended per the pre-specified requirements. |
Detection and Visualization | Detect and visualize anatomy and blood flow per intended uses | Bench testing verified that the subject device can detect and visualize anatomy and blood flow per the proposed indications for use of the Iridium Module. In all instances, the VS3-IR System using the VS3-IR-Endoscope functioned as intended and met all performance acceptance criteria (including laser excitation triggering IR fluorescence in ICG molecules, and fluorescence light being detected by an image sensor to produce an IR image, fused with a visible light image to produce a composite image showing blood flow). |
Standard Conformance | Conforms to IEC 60601-1-2, 60601-1, 60601-1-4, and Laser Safety | The subject device conforms to these recognized standards. |
2. Sample Size Used for the Test Set and the Data Provenance
The document describes bench testing, which typically does not involve a "test set" in the sense of clinical cases or data. The testing involved simulating a surgical field.
- Sample Size: Not applicable in the context of clinical data. The testing was conducted on the device itself and its ability to perform certain functions in a simulated environment.
- Data Provenance: Not applicable as it's bench testing, not clinical data. The testing was performed by Visionsense Ltd.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts
- Number of Experts: Not mentioned. Bench testing usually relies on engineering and scientific personnel to verify device function against specifications.
- Qualifications of Experts: Not specified.
4. Adjudication Method for the Test Set
- Adjudication Method: Not applicable. Bench testing for functional verification does not typically involve an adjudication process by human experts in the same way clinical data evaluation would.
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
- MRMC Study: No, an MRMC comparative effectiveness study was not done. The document describes bench testing of the device's functional performance, not a study of human reader improvement with or without AI assistance. The device is for visualization, not an AI diagnostic tool that assists human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Standalone Performance: The study focuses on the standalone performance of the device's imaging capabilities. It verified that the device, without human interpretation for evaluation of its own core function, could detect and visualize fluorescence. However, the device itself is a "human-in-the-loop" tool, as it's an endoscope for surgeons to use for visualization. The bench testing verified the device's ability to produce the images that a human user would then interpret.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- Type of Ground Truth: For the bench testing, the "ground truth" was established by the physical and chemical principles of fluorescence (ICG excitation and emission) and the known properties of the simulated surgical field. The expectation was that the device would accurately capture and display this known phenomenon. It's a functional ground truth, verified by the correct operation of the system (laser excitation triggering fluorescence, detection by IR camera, and appropriate image fusion).
8. The sample size for the training set
- Sample Size for Training Set: Not applicable. This document describes the functional testing of a medical device (endoscope), not the development or training of an AI algorithm from a dataset.
9. How the ground truth for the training set was established
- Ground Truth for Training Set: Not applicable as no training set for an AI algorithm is mentioned or implied.
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