Search Results

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 Nvision VLE Imaging System is a general imaging system comprised of the Nvision VLE Console, Nvision VLE Catheter and the Nvision VLE Inflation Accessory Kit.

This 510(k) summary for the NinePoint Medical Nvision VLE Imaging System describes general performance data but does not contain the specific information required to complete your request for acceptance criteria and a study proving quantitative device performance against those criteria.

Here's what the document states and what it lacks:

1. Table of Acceptance Criteria and Reported Device Performance:

• Acceptance Criteria (General): The document lists voluntary standards the device will be tested against and comply with. These are primarily safety and regulatory standards, not quantitative performance metrics for image quality or diagnostic accuracy.
  • IEC 60601-1, General Safety
  • IEC 60601-1-2, Electromagnetic Compatibility
  • IEC 60601-1-4, Programmable Electrical Medical Systems
  • IEC 60601-2-18, Endoscope
  • IEC 60601-2-22, Laser Safety
  • IEC 60825-1, Laser Safety
  • ISO 10993-1, Biological Evaluation of Medical Devices
  • ISO 10993-7, Biological Evaluation of Medical Devices, Ethylene Oxide Sterilization residual testing
  • ISO 11135-1, Sterilization of Health Care Products, Ethylene Oxide
• Reported Device Performance: The document states: "In-vitro and clinical testing have been performed and all components, subassemblies and/or full devices and systems have met the required specifications for the completed tests." However, it does not provide any specific quantitative performance results (e.g., sensitivity, specificity, resolution, accuracy, etc.) against any performance-based acceptance criteria for its imaging capabilities. The FDA letter explicitly limits the device's use for diagnostic analysis, stating, "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 indicates that the device's diagnostic performance, which would typically be measured against specific criteria, was not part of this clearance.

Therefore, a table of quantitative acceptance criteria and reported device performance cannot be generated from the provided text.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

• The document states "In-vitro and clinical testing have been performed," but it does not provide any details on the sample size of the test set, the provenance of the data (country of origin), or whether the study was retrospective or prospective.

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

• Since no specific performance metrics or diagnostic claims are being made and evaluated, the document does not mention the use of experts to establish ground truth or their qualifications. The FDA explicitly noted that the device's effectiveness for diagnostic analysis has not been evaluated.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

• Due to the lack of details on a diagnostic performance test set or expert evaluation, no adjudication method is described.

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:

• This document describes an Optical Coherence Tomography (OCT) imaging system, not an AI or CAD system. Therefore, no MRMC comparative effectiveness study involving human readers with or without AI assistance was mentioned.

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

• As this is an imaging system and not an AI algorithm, no standalone algorithm performance study was discussed.

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

• Given the device's current indication as an imaging tool "in the evaluation of human tissue microstructure" and the FDA's explicit statement that its safety and effectiveness for diagnostic analysis "has not been evaluated," the document does not specify a type of ground truth established for diagnostic performance. The "clinical testing" mentioned likely refers to safety and basic image acquisition rather than diagnostic accuracy against a histological or expert-derived ground truth.

8. The sample size for the training set:

• This device is an imaging system, not a machine learning algorithm that requires a training set in the typical sense. Therefore, no training set sample size is mentioned.

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

• As there's no mention of a machine learning training set, this information is not applicable and not provided.

In summary, the provided submission focuses on the substantial equivalence of the Nvision VLE Imaging System to a predicate device based on technological characteristics and compliance with general safety and regulatory standards. It does not include a quantitative performance study measuring imaging or diagnostic accuracy against specific acceptance criteria, nor does it involve AI or machine learning components that would necessitate training and test set specifics as you've requested.

Ask a specific question about this device

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

The NinePoint Medical Nvision VLE™ Imaging System is a general imaging system The Niler offit Wediod Nivision VLE TM Console, NVISion VLE™ Catheter and the Nvision VLE™ Inflation Accessory Kit.

The submission describes a labeling change for the Nvision VLE™ Imaging System, specifically an increase in the maximum recommended inflation pressure for the catheter balloon from 5 psi to 30 psi. The study conducted to support this change is a burst pressure test of the balloons.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance:

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

• Sample Size: Samples from two balloon manufacturing lots were characterized. The exact number of individual balloons tested is not specified beyond "samples from two lots."
• Data Provenance: The data is prospective, as the burst pressure testing was performed specifically to support this labeling change. The country of origin of the data is not explicitly stated, but given the submission is to the FDA in the US, it is likely that the testing was conducted either in the US or in a manner compliant with US regulatory standards.

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

Not applicable. This study does not involve human experts establishing ground truth for image interpretation or clinical outcomes. It is an engineering performance test assessing the physical integrity of a component.

4. Adjudication Method for the Test Set:

Not applicable. This is a direct measurement of physical properties (burst pressure) and does not involve adjudication by experts.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size:

No. This is not an MRMC comparative effectiveness study. It is a performance test of a device component's physical characteristic.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

Not applicable. This device is an imaging system, but the study described is a component-level performance test, not an evaluation of the imaging algorithm's standalone performance. The submission refers to a "labeling change only," implying the imaging algorithm itself was cleared in the predicate device (K112770).

7. The Type of Ground Truth Used:

The ground truth used is the measured burst pressure of the catheter balloons. This is a direct physical measurement.

8. The Sample Size for the Training Set:

Not applicable. There is no machine learning "training set" for this type of engineering performance test.

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

Not applicable. As there is no training set for a machine learning algorithm, there is no ground truth established in this context. The "ground truth" for the burst pressure test is the physical measurement itself.

Ask a specific question about this device

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

The NinePoint Medical Nvision VLE Imaging System is a general imaging system comprised of the Nvision VLE Console, Nvision VLE Catheter and the Nvision VLE Inflation Accessory Kit.

The provided 510(k) summary for the NinePoint Medical Nvision VLE Imaging System indicates that this device is an Optical Coherence Tomography (OCT) system, which is a general imaging system. While the document mentions compliance with several general safety and performance standards (like IEC and ISO), it does not contain details about specific acceptance criteria related to a clinical performance study for image interpretation, nor does it present the results of such a study.

The "Performance data" section (Section 7) primarily states that:

• The device will be tested against and comply with a list of voluntary standards (related to general safety, electromagnetic compatibility, biological evaluation, sterilization, etc.).
• "In-vitro and clinical testing have been performed and all components, subassemblies and/or full devices and systems have met the required specifications for the completed tests."

This statement is very general and does not provide any specific quantitative acceptance criteria or detailed results of these tests that would be relevant to evaluating the device's diagnostic performance (e.g., accuracy, sensitivity, specificity for identifying specific tissue microstructures).

Therefore, based solely on the provided text, the extensive information requested in the prompt regarding acceptance criteria and a study proving those criteria cannot be extracted.

Here's a breakdown of why and what information is missing:

1. Table of acceptance criteria and reported device performance: This information is not provided. The document lists general manufacturing and safety standards but not performance criteria for image quality or diagnostic accuracy.
2. Sample size used for the test set and data provenance: No details about a specific test set, its size, or provenance are mentioned for clinical performance.
3. Number of experts used to establish the ground truth for the test set and their qualifications: No information is provided about expert readers or ground truth establishment for a diagnostic performance study.
4. Adjudication method for the test set: No adjudication method is described.
5. Multi-Reader Multi-Case (MRMC) comparative effectiveness study: No such study is mentioned, nor is an effect size for human readers improving with AI assistance (which is not relevant as this is an imaging device, not an AI diagnostic tool in the context of what's described).
6. Standalone performance (algorithm only without human-in-the-loop performance): This is an imaging system, not an algorithm being evaluated without human interpretation. No separate algorithm-only performance is described.
7. Type of ground truth used: No ground truth type is specified as there's no detailed diagnostic performance study described.
8. Sample size for the training set: The product is an imaging system, not an AI/ML algorithm that typically requires a "training set" in the same way. The document doesn't mention an AI component that would have a training set.
9. How the ground truth for the training set was established: Not applicable, as no AI model training is described.

In summary: The provided 510(k) summary focuses on establishing substantial equivalence to predicate devices based on technological characteristics and compliance with general safety and voluntary standards. It does not contain the detailed clinical performance study data that would typically include specific acceptance criteria and detailed results related to diagnostic accuracy, which is what your questions are seeking.

Ask a specific question about this device