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The NvisionVLE Imaging System is indicated for use as an imaging tool in the evaluation of human tissue microstructure, including esophageal tissue microstructure, by providing two-dimensional, cross-sectional, real-time depth visualization and may be used to mark areas of tissue. The software provides segmentation and display of common imaging features, including hyper-reflective surface, layering, and hypo-reflective structures.

The NvisionVLE® Imaging System is intended to provide an image of tissue microstructure. The safety and effectiveness of this device for diagnostic analysis (i.e. differentiating normal versus specific abnormalities) in any tissue microstructure or specific disease has not been evaluated.

The NinePoint Medical NvisionVLE® Imaging System is a high-resolution volumetric imaging system based on optical coherence tomography (OCT). In an analogous fashion to ultrasound imagery, OCT images are formed from the time delay and magnitude of the signal reflected from the tissue of interest. The NvisionVLE Imaging System employs an advanced form of OCT known as sweptsource OCT (SS-OCT), or Optical Frequency Domain Imaging (OFDI), in combination with a scanning optical probe to acquire high-resolution, cross-sectional, real-time imagery of tissue called Volumetric Laser Endomicroscopy (VLE).

In addition to the imaging capability, the device provides a means of marking areas of tissue with an additionally integrated 1470nm laser. The ability to create temporary laser marks directly on tissue enables a clinician to place visual reference marks on tissue regions of clinical interest immediately following their identification via VLE. The device consists of the following five main components and accessories: (i) a mobile NvisionVLE Console with an integrated computer and two touch-screen interfaces; (ii) proprietary NvisionVLE Software used to acquire, process, and visualize VLE images; (iii) a single-use, sterile NvisionVLE Marking Probe that is inserted through the working channel of an endoscope; (iv) a single-use, sterile NvisionVLE Inflation System that is used to inflate the Marking Probe's balloon to facilitate placement; and (v) a Probe Lock Accessory to prevent longitudinal motion of the Marking Probe within the endoscope.

The purpose of this 510(k) submission is to add an artificial intelligence software tool referred to as Image and Visualization Enhancements (IVE) to the previously cleared, predicate NvisionVLE Imaging System (K153479). The IVE software module allows enhanced visualization (segmentation and colorized display) of the following commonly observed image features (also referred to as IVE features): (1) hyper-reflective surface, (2) layering and (3) hypo-reflective structures. The segmentation algorithm was developed using an artificial intelligence machine learning technique known as deep learning. Here, an artificial neural network was trained with manually labelled examples of each feature and then locked for realtime inference on new image data acquired by the device. Display of each feature can be toggled via the user interface, where a respective color overlay is presented. The default display of the IVE features is disabled and the standard VLE image data displayed per the cleared NvisionVLE Imaging System. Segmentation of these structures are based on existing image features, and IVE simply increases the conspicuity via the color overlays, thus aiding image review. It is a convenience tool and a resource for the clinician and as such, it does not alter the standard of care or the role of the physician in reviewing and assessing images generated by the system.

The provided text describes the acceptance criteria and a study proving the device meets those criteria. Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document states that "The target true positive and true negative detection fractions were prospectively set." However, the specific target values for these fractions are not explicitly listed in numerical form in the provided text. Instead, it states that the observed results *exceeded their target value with a significance level a

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The NvisionVLE Imaging System is indicated for use as an imaging tool in the evaluation of human tissue microstructure, including esophageal tissue microstructure, by providing two-dimensional, cross-sectional, real-time depth visualization.

The NinePoint Medical NvisionVLE® Imaging System is a high-resolution volumetric imaging system based on optical coherence tomography (OCT). In an analogous fashion to ultrasound imagery, OCT images are formed from the time delay and magnitude of the signal reflected from the tissue of interest. The NvisionVLE® Imaging System employs an advanced form of OCT known as swept-source OCT (SS-OCT), or Optical Frequency Domain Imaging (OFDI), in combination with a scanning optical probe to acquire high-resolution, crosssectional, real-time imagery of tissue called Volumetric Laser Endomicroscopy (VLE).

The device consists of the following main components and accessories: (i) a mobile NvisionVLE Console with an integrated computer and two touchscreen interfaces; (ii) proprietary NvisionVLE Software used to acquire, process, and visualize VLE images; (iii) a single-use, sterile NvisionVLE Optical Probe that is inserted through the working channel of an endoscope: (iv) a single-use, sterile NvisionVLE Inflation System that is used to inflate the balloon as required, to facilitate placement; and (v) a Probe Lock Accessory to prevent longitudinal motion of the Probe within the endoscope.

This document is an FDA 510(k) clearance letter for the NvisionVLE Imaging System. It primarily focuses on demonstrating substantial equivalence to a predicate device, rather than providing detailed clinical study results for a new AI/ML-based device.

Therefore, many of the requested elements for describing acceptance criteria and a study proving a device meets them (especially those related to AI/ML performance metrics like sensitivity, specificity, MRMC studies, or training/test set details for AI) are not present in this type of regulatory document.

However, I can extract information related to the device's functional and non-clinical performance, which serve as its "acceptance criteria" in the context of this 510(k) pathway.

Here's a breakdown based on the provided document:

1. A table of acceptance criteria and the reported device performance:

Note on "Acceptance Criteria" for this specific 510(k): For this Special 510(k), the "acceptance criteria" are primarily focused on demonstrating that the modification (addition of balloon-less low-profile optical probes) does not adversely affect the fundamental safety and effectiveness of the device, and that it maintains the performance characteristics expected of the original cleared device. There are no clinical diagnostic performance metrics (e.g., sensitivity, specificity for disease detection) because the device's cleared indication for use explicitly states that its safety and effectiveness for diagnostic analysis (differentiating normal vs. specific abnormalities) has not been evaluated.

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

• Sample Size: Not specified for any specific functional or non-clinical test. The testing described is general "functional testing" and "tensile testing" which implies a sufficient number of samples were tested to ensure design verification, but specific numbers are not disclosed in this summary.
• Data Provenance: Not applicable in terms of patient data. The testing involves device components and systems (e.g., probes, consoles). This is non-clinical performance data, likely gathered at the manufacturer's testing facilities.

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

• Not applicable. This 510(k) describes non-clinical and functional testing of device characteristics, not clinical performance or diagnostic accuracy assessed by experts.

4. Adjudication method for the test set:

• Not applicable. This is not a clinical study involving human interpretation of results.

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:

• No. This is explicitly stated: "The safety and effectiveness of this device for diagnostic analysis (i.e. differentiating normal versus specific abnormalities) in any tissue microstructure or specific disease has not been evaluated." This device is an imaging tool to visualize microstructure, not a diagnostic AI.

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

• No. The device is for human visualization of microstructure. It does not perform standalone diagnostic analysis.

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

• For the non-clinical tests described, the "ground truth" would be engineering specifications and established test methodologies (e.g., correct image display, specified resolution ranges, material strength limits, proper mechanical function). This is not a clinical ground truth like pathology.

8. The sample size for the training set:

• Not applicable. This document is for a medical imaging device, not an AI/ML product developed with a training set of data.

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

• Not applicable. (See #8)

Summary of what this document does tell us about "acceptance criteria":

For the NvisionVLE Imaging System, particularly concerning this Special 510(k) for new probe configurations, the acceptance criteria are entirely based on functional and non-clinical performance. The study "proving" the device meets these criteria involved a battery of engineering and bench tests, including:

• Image quality confirmation on the console.
• Quantitative measurements of optical performance (lateral resolution, back reflection, transmission rate) to ensure they meet specified levels.
• Mechanical integrity testing of components (e.g., tensile testing of probes).
• Verification of proper device operation (e.g., probe loading and withdrawal).
• Compliance with recognized voluntary consensus standards for quality, safety, and manufacturing.

The FDA's clearance indicates that these non-clinical tests demonstrate the modified device is "as safe and effective as the predicate device" and does "not raise any new or different questions of safety or effectiveness." It is crucial to reiterate that the device's cleared indication for use specifically states that its diagnostic capability for differentiating abnormalities has not been evaluated, meaning it's primarily a visualization tool.

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The Nvision VLE Imaging System is indicated for use as an imaging tool in the evaluation of human tissue microstructure, including esophageal tissue microstructure, by providing two-dimensional, cross-sectional, real-time depth visualization.

The NinePoint Medical NvisionVLE™ Imaging System is a general imaging system comprised of the NvisionVLETM Console, NvisionVLETM Optical Probe and the NvisionVLE™ Inflation Accessory Kit. The NvisionVLE™ Optical Probe is made up of an optical probe subassembly and a quide sheath. The optical probe subassembly is a fiber optic probe assembly secured inside a flexible, stainless steel torque shaft. The distal optics are housed in a stainless steel hypotube which is attached to the torque shaft. The proximal end of the optical fiber and torque shaft terminate in a standard fiber optic connector and catheter connector which interfaces with the system console. The optical probe subassembly transmits the optical signal and detects the reflected optical signal for image reconstruction of the targeted tissue. The guide sheath is a coaxially-designed balloon sheath. The sheath is composed of a PET balloon and a nylon shaft. The inner lumen of the sheath is sealed, enclosing the optical probe subassembly. The guide sheath is positioned within the organ structure of interest and allows the probe to rotate in a helical pattern while positioned in the inner lumen allowing for image reconstruction of the targeted tissue.

Here's a breakdown of the acceptance criteria and the study that proves the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size:
  • Initial Engineering Test Samples: 5 K120800 Controls, 5 Proposed Enhancements (Total = 10 samples)
  • Manufacturing Build Samples: 10 K120800 Controls, 7 Proposed Enhancements (Total = 17 samples)
  • Overall Reported (summary): 15 control samples, 13 enhanced samples (This slightly differs from the sum of the detailed tables (15 controls vs 17 controls; 13 enhanced vs 12 enhanced). The summary likely refers to the effective number of control samples that experienced failure across the two tables combined, and the number of enhanced samples that successfully completed the most rigorous testing.)
• Data Provenance: The data appears to be retrospective in the sense that it evaluates modifications to an already cleared device and compares them against the previously cleared device. It's an internal engineering and manufacturing evaluation. The country of origin is not explicitly stated, but the company is based in Cambridge, Massachusetts, USA, suggesting the testing was likely conducted in the US.

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

Not applicable. This study is a performance test on device durability and mechanical integrity, not an evaluation of diagnostic accuracy requiring expert interpretation of images or patient outcomes. The "ground truth" for this test is the physical failure of the device (binding, fiber fracture, signal loss) under simulated tortuosity.

4. Adjudication Method for the Test Set

Not applicable. The outcome (pass/fail) is objectively determined by whether the device's optical fiber fractured or the torque coil bound, leading to a loss of signal. This is a direct physical outcome rather than an interpretation requiring adjudication.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No. This study assesses the physical durability and mechanical performance of the device's components (optical probe and guide sheath), not its effectiveness in diagnostic tasks with human readers.

6. Standalone Performance Study (Algorithm Only)

Yes, in a sense. This is a standalone device performance study focusing on the mechanical durability of the device itself, rather than an algorithm. The "algorithm" aspect of imaging systems (image reconstruction, etc.) is not evaluated here, only the physical integrity of the probe.

7. Type of Ground Truth Used

The ground truth used is physical device failure (failure of the torque coil to bind, fracture of the optical fiber, and subsequent failure to transmit signal) under defined simulated conditions of tortuosity.

8. Sample Size for the Training Set

Not applicable. This study does not involve a "training set" in the context of machine learning. It's a physical engineering and manufacturing test of device durability.

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

Not applicable, as there is no training set for an algorithm. The "ground truth" for the test set (physical failure) was established by observing the operational state of the device under stress in a test fixture.

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