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ARTIS is a family of dedicated angiography systems developed for single plane and biplane diagnostic imaging and interventional procedures including, but not limited to, pediatric and obese patients.

Procedures that can be performed with the ARTIS family include cardiac angiography, neuro-angiography, general angtography, rotational angiography, multipurpose angiography and whole body radiographic/fluoroscopic procedures as well as procedures next to the table for i.e. patient extremities. This does not include projection radiography.

Additional procedures that can be performed include angiography in the operating room, image guided surgery by X-ray, by image fusion, and by navigation systems. The examination table as an integrated part of the system can be used for Xray imaging, surgery and interventions.

The ARTIS systems can also support the acquisition of position triggered imaging for spatial data synthesis.

The ARTIS systems include also the software option DynaCT with following indications for use:

DynaCT is an X-ray imaging software option, which allows the reconstruction of two-dimensional images acquired with a standard angiographic C-arm device into a three-dimensional image format.

DynaCT is intended for imaging both hard soft tissues as well as other internal body structures for diagnosis, surgical planning, interventional procedures and treatment follow-up.

The ARTIS pheno (VE30A) is a multi-axis system, specifically designed to meet the growing demands of high-end imaging for interventional radiology, interventional cardiology, and minimally invasive and hybrid surgery procedures. The stand allows positioning in angular, orbital, lateral, longitudinal, and vertical directions, leveraging the flexible isocenter. The ARTIS pheno (VE30A) is equipped with a robotic multi-axis floor stand, C-arm, flat panel detector, x-ray tube, collimator, high voltage generator, patient table, and image post-processing. The ARTIS pheno is partially coated with an optional anti-microbial coating. syngo Application Software is optional, and available for the support of dedicated clinical workflows.

The ARTIS pheno (VE30A) covers the complete range of angiographic applications, cardiac angiography, neuro-angiography, general angiography, surgery and surgical angiography, multipurpose angiography, rotational angiography, radiographic/fluoroscopic procedures.

The following components are configured to create the floor configuration:

• (1) Floor stand with C-arm, X-ray tube assembly and FD
• (2) Patient table
• (3) Display ceiling suspension with displays
• (4) Footswitch for releasing radiation
• (5) Control console for controlling the stand, patient table, collimator, and imaging system

lmages and operating elements are displayed on screens. Different display variants are used to visualize image and information content. Panoramic display configurations or large displays can be used, configurable to visualize multiple images and information content in various layouts.

Post-processing can be done in the exam room or in the control room that offers monitors as well, with a footswitch location in the exam room or the control room. The ARTIS pheno (VE30A) is capable of 2D and 3D imaging.

Other systems and software synqo Application Software, syngo X Workplace, Sensis Vibe, and or third-party systems may also be integrated into the ARTIS pheno (VE30A) screen configuration. Different screen configurations and layouts are possible in the examination room and the control room.

The provided text describes modifications to an existing device, ARTIS pheno (VE21) to create ARTIS pheno (VE30A). The study is primarily a non-clinical performance evaluation focused on verifying that the changes introduced in VE30A do not negatively impact the safety and effectiveness compared to the predicate device.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly list a table of "acceptance criteria" alongside specific "reported device performance" values in a quantitative manner for most of the listed modifications. Instead, it generally states that "All testing results passed" and "All test results met all acceptance criteria" for various tests performed on the modifications.

However, based on the descriptions, we can infer some general acceptance criteria and the reported performance as "met" or "passed".

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

The document does not specify a quantitative sample size for any test set (e.g., number of images, number of patients, number of cases). The testing appears to be primarily focused on system-level verification and validation of the software and hardware modifications rather than a clinical study involving patient data.

• Test Set: Not explicitly stated as a distinct "test set" in the context of clinical data. The testing involved "software functional, verification, and System validation testing," "NOMSIE algorithm, overlay, configuration, vessel presentation DSA, and roadmap testing," and "CNR image Quality exposure control, fluoro auto exposes values cardiology, DR, CNR, DSA, and neuro testing." These are likely performed on test harnesses, simulated data, and potentially a limited number of test cases or phantoms.
• Data Provenance: Not applicable in the context of clinical data. The testing is non-clinical.

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

This information is not provided. Since the study is a non-clinical performance evaluation, it did not involve clinical experts establishing ground truth in the traditional sense for a diagnostic AI device. The "ground truth" for the non-clinical tests would be the expected functional and performance outcomes defined by engineering specifications.

4. Adjudication method for the test set

Not applicable. There is no indication of multiple readers or an adjudication method for establishing ground truth from human experts, as this was not a clinical study involving diagnostic interpretations.

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 was not done. The device is an image-intensified fluoroscopic x-ray system, and the changes are related to system software, hardware, and workflow features, not a diagnostic AI component intended for human reader assistance.

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

The device itself is an imaging system. The "algorithms" mentioned (e.g., NOMSIE, Structure Scout) are integrated parts of the overall imaging functionality. While these algorithms perform specific tasks (like image quality enhancement, reconstruction, element identification), their "standalone" performance isn't described in isolation from the system's output. The performance evaluation is inherently within the context of the ARTIS pheno system. It's not an AI model providing a separate diagnostic output.

7. The type of ground truth used

The ground truth used for these non-clinical tests would be based on:

• Engineering specifications and requirements for software functionality.
• Expected image quality parameters (e.g., CNR for Structure Scout) as measured by phantoms or controlled test conditions.
• Defined operational workflows for usability features.
• Compliance with recognized standards for electrical safety, performance, and EMC.

It is not based on expert consensus, pathology, or outcomes data.

8. The sample size for the training set

This information is not applicable and not provided. The document describes modifications to an existing x-ray system, implying traditional software and hardware development and testing, not the training of a machine learning model from a distinct "training set" of data.

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

This information is not applicable and not provided as no machine learning training set is mentioned.

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The iNod Ultrasound Guidance Console is intended to be used with iNod Ultrasound Guided Biopsy Needle, to observe and to store real-time ultrasound images of endobronchial lesions, peripheral lung nodules, or lung masses located in airways and tracheobronchial tree.

The iNod Ultrasound Guided Biopsy Needle is intended for use through a flexible bronchoscope for intraluminal sonographic imaging in the tracheobronchial tree and retrieval of specimens with endobronchial lesions, peripheral lung nodules, or lung masses.

The proposed iNod Ultrasound Guidance System (iNod System), comprises: the sterile, single use iNod Ultrasound Guided Biopsy Needle (also referred to as iNod Single Use Device (SUD), iNod Ultrasound Guidance Console (iNod Console) and the iNod Motor Drive Unit (iNod MDU). The proposed iNod Ultrasound Guidance System is intended to perform pulmonary needle biopsy under real-time visualization using Radial Endobronchial Ultrasound (R-EBUS).

The iNod single-use-device (iNod SUD) is a single use, sterile device that has combined functionality of a radial ultrasound probe and a biopsy needle. The iNod SUD allows real-time visualization of pulmonary lesions with radial ultrasound, while simultaneously allowing biopsy of the pulmonary lesions. The three main parts of iNod SUD are a handle, a radial ultrasound transducer, and biopsy needle. The biopsy needle is actuated at an angle that allows biopsy of eccentric and concentric nodules. A stainless-steel needle indicator strip is housed in the imaging window at distal tip, which provides an ultrasound signature, indicating the orientation of the needle to the user in the ultrasound image. The biopsy needle will exit the iNod SUD distal tip at 180 degrees relative to the needle indicator position visible in the ultrasound image. Once the needle is positioned to biopsy a nodule, the needle is unlocked by user to the exit ramp at 11° angle. Finally, when a sample is collected, the Nitinol stylet can be passed down the needle lumen to expel the sample.

The iNod Console is an electronic device that consists of:

• The iNod MDU, which rotates the ultrasound transducer in the iNod SUD to generate 360° images as well as provides patient isolation from the rest of the Console components.
• A software-based touchscreen tablet with battery, which can be mounted to a mobile pole yia . the pole docking station.
• A software-based Acquisition PC that interprets the received ultrasound signals from the iNod SUD and generates the image that is displayed on the tablet.
• Functionality that displays ultrasonic image received from iNod SUD through iNod MDU and Acquisition PC on the iNod tablet and
• . Ability to save and export procedure images and recordings.

The iNod MDU provides rotation of the iNod SUD's ultrasound transducer, required for generating a 360° ultrasound image. An electromechanical connector interface at the proximal end of the iNod SUD makes the connection to the MDU-catheter interface consists of an integrated mechanical drive hub and electrical connection. The iNod Console interfaces with the iNod SUD through the iNod Motor Drive Unit (iNod MDU), which provides the electromechanics for the rotating parts of the imaging catheter, and the interface between the iNod SUD and the iNod console. The iNod MDU is nearly identical in design to its predicate MDU5 Plus, which is currently used with Avvigo Guidance System II (K212490).

The information provided describes the acceptance criteria and a summary of the performance testing for the iNod Ultrasound Guidance System. However, it does not include details about a clinical study involving human subjects or AI performance. The provided document focuses entirely on bench testing and software verification without reporting any clinical efficacy or comparative effectiveness against human readers. Therefore, several requested sections, particularly those related to human reader studies, ground truth establishment for a test set, and MRMC studies, cannot be addressed from the given text.

Here's the information extracted and organized based on your request:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are implied by the "Product Specification" in the table, and the reported performance is simply "Pass" for all criteria. Specific numerical acceptance limits are not detailed for each specification in the provided document, but the outcome indicates they were met.

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

The provided document describes non-clinical (bench) testing and software tests. It does not mention a "test set" in the context of clinical data or patient images for evaluating algorithm performance. The testing involved various units of the iNod SUD, Console, and MDU, as well as their components, but not patient data.

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

Not applicable. The testing described is bench testing and software verification, not clinical studies involving expert interpretation of medical images.

4. Adjudication method for the test set

Not applicable. The testing described is bench testing and software verification, not clinical studies requiring adjudication of expert interpretations.

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 MRMC comparative effectiveness study was done, nor is there any mention of AI assistance in the document. The device is an ultrasound guidance system and needle, not an AI-powered diagnostic tool.

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

This is not an AI algorithm. The device, the iNod Ultrasound Guidance System, is a medical instrument (hardware and software for imaging and biopsy). The "Product Specifications" for the various components (iNod SUD, iNod Console, iNod MDU) indicate tests performed on the physical and functional aspects of the device itself (e.g., Device Passability, Needle Extension Length, Imaging Depth, DICOM Archiving Performance, Rotational Speed). These are standalone tests of the device's inherent capabilities, not an algorithm's performance.

7. The type of ground truth used

For the physical and functional performance of the device (iNod SUD, Console, MDU), the "ground truth" would be the engineering specifications and established test methodologies (e.g., ISO standards, internal design requirements) that define the acceptable range or value for each "Product Specification." The tests determine if the device meets these pre-defined engineering and performance criteria.

8. The sample size for the training set

Not applicable. This is not an AI/machine learning device that requires a training set.

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

Not applicable. This is not an AI/machine learning device that requires a training set.

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