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Ambu® aScope™ 5 Broncho HD is intended for endoscopic procedures and examination within the airways and tracheobronchial tree.

Ambu® aScope™ 5 Broncho HD is intended to provide visualization via a compatible Ambu® displaying unit, and to allow passing endotherapy instruments via its working channel.

The aBox™ 2 is intended to display live imaging data from compatible Ambu visualization devices.

The Ambu aScope 5 Broncho HD System is a combination of the displaying unit, Ambu aBox 2, and a compatible Ambu endoscope, the Ambu aScope 5 Broncho HD 5.0/2.2 or the Ambu aScope 5 Broncho HD 5.6/2.8.

The Ambu aScope 5 Broncho HD endoscopes are single-use endoscopes designed to be used with Ambu displaying units, endotherapy instruments and other ancillary equipment for endoscopy within the airways and tracheobronchial tree.

The insertion portion is inserted into the patient airway through the mouth, nose, or a tracheostomy. It is lubricated with a water-soluble medical grade lubricant to ensure the lowest possible friction when inserted into the patient. There is a working channel system within the endoscope for use with endotherapy instruments. An introducer (luer lock adaptor), which is supplied together with the endoscope, can be attached to the working channel port during use. Suctioning of blood, saliva, and mucus from the airway is possible through the suction system.

Ambu aScope 5 Bronco HD features an integrated camera module, with built-in dual LED illumination. The image module provides a cropped 800x800 Pixels signal from the 1280x800 (1 megapixel) sensor.

The Ambu aBox 2, also referred to as displaying unit, is a non-sterile digital monitor intended to display live imaging data from Ambu visualization devices. The product consists of a base unit with a 12.8" LCD screen mounted on the top. The device is powered by an integrated power supply and comes with country specific power cables.

Ambu® aBox 2 displaying unit has the following physical and performance characteristics:
Displays the image from Ambu® aScope™ 5 Broncho HD endoscope on the screen. Can record snapshots or video of image from Ambu® aScope™ 5 Broncho HD endoscope. Can connect to an external monitor. Reusable device.

This document describes a 510(k) premarket notification for the Ambu aScope 5 Broncho HD system. The acceptance criteria and the study proving the device meets these criteria are primarily based on bench testing and adherence to international standards for endoscopes, rather than a clinical study evaluating AI performance.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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

The document describes bench testing and adherence to international standards for device performance, biocompatibility, electromagnetic compatibility, and electrical safety. It does not refer to a "test set" in the context of a clinical study with patient data (e.g., images). Therefore:

• Sample size for the test set: Not applicable in the context of clinical data. The "samples" would be the devices and materials tested according to the listed standards. The exact number of devices or material samples used for each bench test is not specified.
• Data provenance: Not applicable in the context of clinical data. The data is generated from laboratory bench tests and material analyses.

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

This is not applicable as the provided document focuses on bench testing and engineering performance evaluations, not diagnostic accuracy studies involving expert interpretation of medical images or data. Ground truth for these types of tests is generally based on objective measurements by calibrated instruments and adherence to established engineering standards.

4. Adjudication method for the test set

This is not applicable. Adjudication methods like "2+1" or "3+1" are used in clinical studies where expert consensus is needed to establish ground truth for ambiguous cases. The testing described here involves objective pass/fail criteria based on physical and electrical properties, and compliance with standards.

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, a multi-reader multi-case (MRMC) comparative effectiveness study with human readers and AI assistance was not done or reported in this submission summary. The device described (a bronchoscope and display unit) is a visualization and instrument delivery system, not an AI-powered diagnostic tool. The submission focuses on the safety and effectiveness of the hardware itself.

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

No, a standalone algorithm-only performance study was not done. This device is a medical device hardware system, not an AI algorithm.

7. The type of ground truth used

The ground truth used for these tests is based on objective measurements against established engineering and safety standards (e.g., ISO 8600 series, IEC 60601 series, ISO 10993 series parameters for field of view, suction performance, electrical safety, biocompatibility limits, etc.). It is not derived from expert consensus, pathology, or outcomes data in the traditional sense of clinical diagnostic ground truth.

8. The sample size for the training set

Not applicable. This submission is for a medical device (bronchoscope system), not an AI algorithm that requires a training set.

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

Not applicable. As above, this is not an AI algorithm, so there is no training set or associated ground truth establishment process in this context.

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This 3D Visualization System is intended to compose the imaging signals from video system center and convert them into 3D signals displayed on the monitor.

The 3D Visualization System can convert 2D endoscopic images synchronously. It is equipped HD-SDI and HDMI outputs ports which are compatible with 3D monitors of various interfaces. The 3DVS-S100 series 3D Visualization System includes 5 models, which are 3DVS-S100A, 3DVS-S100B, 3DVS-S100C, 3DVS-S100D and 3DVS-S100E. The differences between the models are in the number and type of imaging modes supported (single-lens endoscope with enhanced or standard 3D effects, and dual-lens endoscope with enhanced or standard 3D effects). The system should be used with endoscopic image processors which have HDMI or SDI output interface, and monitors which have SDI, HDMI or DVI interface. The device is provided non-sterile and for repeat use, does not have patient-contact, and is intended for use by a qualified healthcare professional and is not for home use.

The provided document describes the Scivita Medical Technology Co., Ltd. 3D Visualization System (K183675). The document clarifies that this device is intended to process imaging signals from a video system center and convert them into 3D signals for display on a monitor. The FDA's 510(k) clearance process focuses on substantial equivalence to a predicate device, rather than explicit acceptance criteria with numerical performance targets for the proposed device itself. However, the document does describe non-clinical testing conducted to demonstrate this equivalence and ensure the device meets design specifications.

Here's an analysis of the acceptance criteria and study information provided:

1. Table of Acceptance Criteria and Reported Device Performance

• IEC 60601-1-2005+CORR.1:2006+CORR.2:2007+A1:2012 (General requirements for basic safety and essential performance)
• IEC 60601-1-2:2014 (Electromagnetic compatibility)
• IEC 60601-2-18:2009 (Particular requirements for endoscopic equipment) |
  | Software Validation | The software was validated in accordance with FDA guidance documents:
• "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices"
• "Off-The-Shelf Software Use in Medical Devices"
• "Cybersecurity for Networked Medical Devices Containing Off-the-Shelf (OTS) Software"
• "General Principles of Software Validation" |
  | Image Quality Equivalence (2D and 3D) | Image quality performance tests were conducted to quantitatively compare the proposed device and predicate devices for both 2D and 3D images.
  Parameters evaluated:
• Field of view
• Direction of view
• Depth of field
• Geometric distortion
• Noise and dynamic range
• Intensity uniformity
• Artifacts
• Image frame frequency and system delay

Result: The image quality of the proposed device was equivalent to that of the predicate device (OLYMPUS LTF-190-10-3D ENDOEYE FLEX 3D DEFLECTABLE VIDEOSCOPE, MAJ-YO154 3D PROCESSOR, OLYMPUS CV-190, EVIS EXERA III VIDEO SYSTEM CENTER - K123365). This equivalence was tested across all four modes of the proposed device in both described combinations. |
| Substantial Equivalence to Predicate Device (K123365) | The non-clinical performance testing summarized supported a substantial equivalence determination, demonstrating the subject device is as safe and as effective as the legally marketed predicate device. |

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

The document does not specify the sample size (e.g., number of images, cases, or videos) used for the image quality performance tests. It vaguely states "image quality performance tests were conducted to quantitatively compare the proposed device and predicate devices."

The data provenance (country of origin, retrospective/prospective) is also not mentioned. Given the manufacturer is based in China, it's plausible the testing was conducted there, but this is not explicitly stated.

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

The document does not mention the use of experts or any process for establishing ground truth as typically understood in a clinical study (e.g., for diagnostic accuracy). The testing described is purely technical and comparative against a predicate device's performance characteristics.

4. Adjudication Method for the Test Set

As no expert review or human assessment of diagnostic accuracy is mentioned, there is no adjudication method described.

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

No MRMC comparative effectiveness study is mentioned. The study described is a non-clinical, technical performance comparison between the proposed device and a predicate device, focusing on image quality characteristics, not on human reader performance with or without AI assistance. The device's function is to convert existing video signals into 3D signals, not to provide AI-assisted diagnostic capabilities.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

Yes, a form of standalone performance was assessed. The "image quality performance tests" were conducted on the device itself, comparing its output directly to the predicate device's output based on various technical image parameters. This is an evaluation of the algorithm's output (3D visualization) in isolation from human interpretation for diagnostic purposes.

7. Type of Ground Truth Used

For the non-clinical image quality tests, the "ground truth" was implicitly derived from technical performance metrics of the predicate device and established engineering standards for image quality. It was a comparative measurement against the performance characteristics of the legally marketed predicate device, not against clinical outcomes, pathology, or expert consensus on a diagnostic task.

8. Sample Size for the Training Set

The document does not mention a training set. This device is a "3D Visualization System" that converts video signals. It does not appear to be an AI/ML-driven diagnostic or image analysis tool that would typically involve a "training set" in the machine learning sense. Its function is signal processing and conversion.

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

As no training set is mentioned, this section is not applicable.

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The Auris Robotic Endoscopy System (ARES) is intended to provide bronchoscopic visualization of patient airways.

The Auris Robotic Endoscopy System (ARES) is intended to be used by qualified physicians to provide visualization to the Bronchial Tree during Bronchoscopic procedures. The ARES consists of four major components, (1) the Patient Side System (PSS), (2) Controller Cart, (3) Surgeon Console (also known as the Master Device Workstation) and (4) the Bronchoscope and Accessories.

The Patient Side System (PSS) includes the robot cart, two robot arms, both Endoscope and Sheath IDMs, IDS. servo drives box, Endoscope camera control box, power control box. illumination controller, and necessary cabling between the IDM/IDS and the robot cart.

The Controller Cart houses the electronic systems required to power and operate the robotic systems. The Controller Cart is broken into two smaller carts, the system controller cart, and the arm controller cart.

The Master Device Workstation is the workstation from which the surgeon drives the ARES. The console consists of a pendant that allows the surgeon to control various aspects of the system during a procedure.

The system is based on a master - slave model, where the user (i.e. physician) is controlling the robots (slaves) using a pendant (master). The flexible bronchoscope is attached at the end effector of a robotic arm with multiple degrees of freedom. The flexible bronchoscope has a working channel and a camera at the tip. The Bronchoscope has an articulated tip that can bend in four directions. The working channel of the Bronchoscope is used for irrigation and aspiration.

Each Slave includes a robotic arm with 6 degrees of freedom and an IDM (Instrument Drive Mechanism) with 4 actuated axes. The robotic arms are used to steer the Bronchoscope.

The provided text is a 510(k) Premarket Notification for the Auris Robotic Endoscopy System (ARES). It details the device's indications for use, comparison to predicate devices, and testing completed. However, it does not contain specific acceptance criteria, reported device performance data, information about sample sizes for test sets, data provenance, number or qualifications of experts, adjudication methods, MRMC studies, standalone performance data, or details about the training set.

The document focuses on demonstrating substantial equivalence to predicate devices through technical comparisons and compliance with relevant medical device standards.

Therefore, I cannot fulfill the request to describe the acceptance criteria and study proving the device meets them with the level of detail requested, as that information is not present in the provided text.

Here is what can be extracted or inferred from the text related to your request, with significant limitations:

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

This information is not explicitly stated in the document. The document mentions "Preclinical testing included standard bench or in vitro testing confirming functionality and durability (e.g., tensile and other durability and functional evaluation)." and "Verification and validation testing was completed in compliance with the following standards: ... All clinical input requirements were validated." These statements imply that acceptance criteria were met, but the specific criteria and corresponding performance results are not provided.

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

• Sample Size for Test Set: Not specified for bench or in vitro testing.
• Data Provenance: The document states that a "Porcine animal model was used to validate system performance in vivo." This indicates some in vivo testing was performed in an animal model, but no details on the number of animals or the country of origin are provided. The broader preclinical testing would be considered prospective for the device's development.

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):

This information is not provided. Given the nature of the preclinical and animal model testing described, "ground truth" would likely be established by veterinary pathologists or engineers, but no specifics are given.

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

This information is not provided.

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 device is not an AI/CAD-based diagnostic system. It is a robotic endoscopy system for visualization. Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance would not be applicable to this type of device and is not mentioned or implied.

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

This device is a robotic system that is explicitly described as a "master - slave model, where the user (i.e. physician) is controlling the robots (slaves) using a pendant (master)." Therefore, it is inherently a "human-in-the-loop" device, and a standalone algorithm-only performance study would not be applicable. Its performance is tied directly to the physician's control.

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

For the "in vivo" validation mentioned, the ground truth would likely be based on direct observation, procedural success (e.g., successful navigation, visualization), and potentially post-procedure pathology or findings in the porcine model. However, the document does not specify the exact nature of the ground truth. For the in vitro testing, ground truth would be based on engineering measurements and specifications.

8. The sample size for the training set:

The document mentions "Preclinical testing" and "Verification and validation testing." These types of studies are typically performed after development (which includes training/optimization) is complete. The document does not provide any information about a "training set" or how the device's control algorithms or visual processing might have been "trained." This is not an AI/machine learning device in the context of typical training sets.

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

As no training set is described, this information is not provided.

In summary, the provided document details the regulatory submission (510(k)) for a robotic endoscopy system, focusing on its substantial equivalence to predicate devices and compliance with safety and performance standards. It broadly states that "clinical input requirements were validated" and "Preclinical testing included standard bench or in vitro testing confirming functionality and durability" and an "animal model was used to validate system performance in vivo." However, it does not provide the specific quantitative acceptance criteria or detailed study results for these tests that would address most of the points in your request.

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