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The VISIONAIR™ system is a software application intended to be used with third-party endoscopic systems in the measurement of the nasal respiratory airway. The VISIONAIR™ system measures the nasal respiratory airway from the endoscopic images taken in the region of the internal nasal valve (INV) and nasal cavum (NC).

The VISIONAIR™ software can be utilized to automatically measure the cross-section area of the Internal Nasal Valve (INV) and Nasal Cavum (NV) and measure the nasal respiratory airway in this region of the anatomy. The VISIONAIR™ system consists of the following components: - The VISIONAIR™ algorithm which performs the Internal Nasal Valve and Nasal Cavum cross-section area segmentations. - The VISIONAIR™ Graphical User Interface (GUI) used for data entry, view the endoscopic image from third party endoscopes and display the data analysis to the user. - A smart device such as tablet or laptop which runs on Windows 10 or a later operating system with the VISIONAIR™ application installed. - A cloud service that runs in the background and can be activated by the user when a particular dataset for a case is desired to securely and anonymously be stored to the Cloud Server (REAI). - USB memory used to encrypt and anonymize the patient information, whether the data is stored locally or to the cloud, and stores the credits needed to activate the VISIONAIR™ software for each case. The VISIONAIR™ application interfaces with third-party endoscopic systems via the ports located on the smart device. The smart device ports enable the third-party systems endoscopic video display to be streamed on the VISIONAIR™ application endoscopic video display. In this 510(k) submission, a FDAcleared endoscope (K970247) was selected as the reference device to support the scientific methodology. The VISIONAIR™ application automatically analyzes the endoscopic images using its trained AI algorithm to measure the nasal valve and nasal cavum surface areas. The VISIONAIR™ application also provides a database file system to manage the data and interface securely and anonymously with the cloud server via the REAl module.

The provided FDA 510(k) summary for the VISIONAIR™ system offers details on its intended use and comparison to a predicate device, as well as a list of non-clinical tests performed. However, it does not explicitly state specific acceptance criteria (e.g., minimum accuracy thresholds) or present the detailed results of a study designed to prove the device meets those criteria with statistical significance.

Instead, it lists tests performed, implying that these tests confirmed design specifications and functionality. The "Substantial Equivalence Table" focuses on comparing attributes to a predicate device and concluding that differences do not raise new safety or effectiveness concerns.

Therefore, many of the requested details about acceptance criteria, specific study results, sample sizes, ground truth establishment, expert qualifications, and MRMC studies are not present in the provided text.

Based on the available information, here's what can be extracted and what is missing:

Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria (e.g., "accuracy > 90%"). Instead, the "Non-clinical Performance Data" section lists various tests performed to ensure the device functions according to design specifications and for substantial equivalence in terms of safety and effectiveness. The "reported device performance" is largely implied by the statement that these tests were "performed" and that the device is deemed "substantially equivalent."

• System Level Test: Confirmation of Windows OS, processor, RAM, ports, wireless connectivity.
• System Interface and Connectivity Test: Confirmation of application to USB device (cloud key, credits) and connections to other devices.
• VISIONAIR™ Application Test: Confirmed connectivity to external endoscopes, cloud server, successful launch, and interaction tests.
• Endoscopic Display Test: Endoscopic view verification of image capture, video recording, and other functions. |
  | Data Management & Security | Confirmed successful execution of data handling and security features:
• Patient Database Verification Test: Confirmation of data stored, anatomical marking, and successful encryption/decryption of the database.
• Report Generation Test: Confirmation of successful report generation in pdf, csv, and other formats. |
  | AI (Segmentation) Accuracy | Evidence of comparison and verification:
• Nasal Respiratory Airway Analysis Test: VISIONAIR™ AI application confirmation of successful segmentation of the Internal Nasal Valve and Nasal Cavum, and image manipulation/loading functions.
• CT vs Segmentation Accuracy Test: Comparison of endoscopic image cross-sectional areas segmented by VISIONAIR™ vs. cross-sectional areas of the same anatomical regions marked on CT scans (details of comparison not provided).
• VISIONAIR™ AI Segmentation Accuracy Test: Comparison of segmented endoscopic images by VISIONAIR™ vs. segmented endoscopic images by experienced clinicians (details of comparison not provided). |
  | User Validation | User Validation Test: Validation of the entire VISIONAIR™ system by clinicians, including successful verification of all accessible features. |
  | Substantial Equivalence | Concluded to be substantially equivalent to the predicate device in indication for use, performance, technology, features, principles of operation, and components. |

Detailed Study Information (Based on available text):

1. Sample Size used for the test set and the data provenance:

   • Test Set Sample Size: Not specified for any of the listed tests.
   • Data Provenance: Not specified (e.g., country of origin). The document mentions "endoscopic images" and "CT scans" were used, but no details on their origin or whether they were retrospective/prospective.

2. 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):

   • Number of Experts: Not specified.
   • Qualifications of Experts: The "VISIONAIR™ AI Segmentation Accuracy Test" mentions "experienced clinicians" were used for comparison, but their specific qualifications (e.g., specialty, years of experience) are not provided.

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

   • Not specified. The document only mentions "comparison" in the segmentation accuracy tests.

4. 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: Not explicitly described as an MRMC comparative effectiveness study where human readers' performance with and without AI assistance is measured.
   • Effect Size: Not provided. The document mentions "User Validation Test" by clinicians and "comparison of segmented endoscopic images by VISIONAIR™ application vs. segmented endoscopic images by experienced clinicians," but not an assessment of human reader improvement.

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

   • The "VISIONAIR™ AI application confirmation of successful segmentation" in the Nasal Respiratory Airway Analysis Test, and the "CT vs Segmentation Accuracy Test" and "VISIONAIR™ AI Segmentation Accuracy Test" imply a standalone evaluation of the algorithm's performance in segmentation against various ground truths (CT scans, experienced clinicians' segmentations). However, exact methodology and metrics are not detailed.

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

   • CT Scans: Used as a ground truth for cross-sectional areas in the "CT vs Segmentation Accuracy Test." This implies measurements from CT scans were considered the reference.
   • Experienced Clinician Segmentations: Used as a ground truth for segmented endoscopic images in the "VISIONAIR™ AI Segmentation Accuracy Test." This suggests individual or consensus segmentations by clinicians served as the reference.
   • Implicitly, other tests depend on functional specifications and user observation.

7. The sample size for the training set:

   • Not specified in the document. The document refers to the "trained AI algorithm" but does not give details about its training data.

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

   • Not specified in the document.

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The ECCOVISION™ is intended to measure the upper respiratory airway by means of acoustic reflection.

The Eccovision™ device is used to obtain an objective measurement of the upper respiratory airway. The device uses acoustic signal processing technology to provide graphical representation of the airway patency as a function of distance from the airway opening. The system consists of a control unit (which connects to customer owned personal computer), and software application, wave tube (one each for the Pharyngometer and Rhinometer) and electronic platform, mouthpieces and nose tips and filter strips. The device performs a dynamic test that determines the dimension of the oral airway past the glottis while the patient is breathing thorough either the mouthpiece or nose tip. A customer provided computer with the loaded Eccovision™ application software then processes the incident and reflected sound signals provides an area-distance curve representing the lumen together with minimal crosssectional area and volume. A measurement is obtained by passing a signal along a probe positioned in the mouth or nose then recover a signal by use of two (2) microphones in the wave tube. The signal is processed by the software and displayed on a screen or relayed to a printer, detailing the cross-sectional area of the airway as a function of distance from the teeth.

Here's a breakdown of the acceptance criteria and study information 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

The text explicitly mentions:

• Approach to show equivalency between new core & legacy core using a model (fixed ADP)
• Approach to show that the new system is equivalent to legacy system on real patients.

However, the sample size for "real patients" is not specified in this document. The data provenance (country of origin, retrospective or prospective) is also not specified.

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

The document mentions that testing was performed by an "Evaluator" familiar with the business case, but does not specify the number of experts, nor their qualifications (e.g., medical specialists, years of experience).

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1).

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study is not mentioned in the provided text. The study focuses on demonstrating equivalence to predicate devices, not on comparing human readers with and without AI assistance.

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

The device is an "ECCOVISION™ Pharyngometer, SGS Eccovision™ Rhinometer, SGS Eccovision™ Rhino/Pharyngometer" which is a measurement device, not an AI algorithm generating readings for humans to interpret. Therefore, the concept of "standalone performance" in the context of an AI algorithm doesn't directly apply here. The device itself performs measurements; the software processes the signals and displays results. The tests aimed to show that the new system's measurements are equivalent to the predicate devices.

7. The Type of Ground Truth Used

The ground truth for the "fixed ADP model" test would be based on the characteristics of that model. For the "real patients" test, the ground truth for "volume measurements" would likely be derived from the predicate devices, as the goal was to show equivalence to the measurements produced by those established devices. The document implies that the measurements from the predicate devices served as a reference for establishing the acceptability of the new device's measurements. There is no mention of pathology or outcomes data as ground truth.

8. The Sample Size for the Training Set

The document does not specify a training set sample size. This device is described as an acoustic reflection measurement device, and the testing focuses on its measurement accuracy compared to predicate devices, not on training a machine learning model.

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

As no training set is mentioned in the context of machine learning, this question is not applicable.

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A Rhinomanometer is a medical instrument, intended to measure nasal airway pressure up to 5 centimeters H2O. (500Pa) and air flow up to 1000 ml/s. (2001 a) and in the now ap to roove. which is useful to the physician in studying the nasal decongestion of the nasal This is a not it as re procedures, before and after surgical procedures, responses to medications, presence or absence of polyps, deviated septums, enlarged adenoids, etc.

The RhinoStream Rhinomanometer module is designed to objectively and quickly measure and quantify a dynamic measure of the patient ability breath through the nasal airway passages.

The provided text describes a 510(k) summary for the RhinoStream Rhinomanometer and its substantial equivalency comparison to a predicate device. However, it does not contain information about acceptance criteria, specific studies, or performance metrics in a way that allows for the detailed breakdown requested.

The document focuses on:

• Device Description and Intended Use: Explains what the RhinoStream Rhinomanometer does.
• Substantial Equivalency Comparison: Compares the RhinoStream to the Mercury Medical Rhinomanometer based on device description, indications, and technological characteristics (e.g., pressure and airflow measurement ranges, software, data storage).
• FDA Clearance Letter: Confirms the device's 510(k) clearance based on substantial equivalence.
• Indications for Use Statement: Reiterates the intended use in a regulatory format.

The absence of performance data, study designs, sample sizes, and expert review details is typical for a 510(k) summary, which primarily emphasizes substantial equivalence to a legally marketed predicate device rather than presenting detailed clinical performance studies for novel claims.

Therefore, I cannot provide the requested information in the structured table and points as the input document does not contain that level of detail.

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Objective measurement device in "blocked nose" situations Deviated septums e.g. Allergic rhinitis Enlarged adenoids With the possibility of absolute and pre/post surgical or treatment comparisons.

A1 Acoustic Rhinometer

This document appears to be an FDA 510(k) clearance letter for the "A1 Acoustic Rhinometer", dated September 30, 1998. It confirms that the device is substantially equivalent to legally marketed predicate devices.

However, the provided text does not contain any information regarding specific acceptance criteria, a study proving device performance against those criteria, or details about training/test sets, ground truth establishment, or expert involvement.

The letter primarily focuses on the regulatory aspects of substantial equivalence for marketing purposes, rather than detailing the technical validation study results. Therefore, I cannot fulfill your request for a table of acceptance criteria, study details, sample sizes, or ground truth establishment based on the provided input.

To answer your request, you would need to provide the actual 510(k) submission document or a separate technical report detailing the performance testing.

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