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The VisAR System is intended as an aid for precisely locating anatomical structures in either open or percutaneous spine procedures. VisAR is indicated for any medical condition in which the use of stereotaxic surgery may be appropriate, and where reference to at least one rigid anatomical structure, such as the spine or iliac crests, can be identified relative to CT imagery of the anatomy. This can include guidance for procedures, such as Posterior Pedicle Screw Placement in the thoracic and sacro-lumbar region.

VisAR displays a virtual screen for stereoscopic 3D images acquired from CT sources. It is intended to enable users to segment previously acquired 3D datasets, overlay, and register these 3D segmented datasets with the anatomy of the patient in order to support intraoperative analysis and guidance.

The virtual screen is indicated for displaying the virtual instrument location to the virtual anatomy to assist in visualization and trajectory planning for both open and percutaneous surgeries.

The VisAR system is an image-guided navigation system that is designed to assist surgeons in placing pedicle screws accurately, during open or percutaneous spinal surgery. The system consists of Novarad's immersive augmented reality software running on the Microsoft Hololens 2 headset, image visible ARTags (AprilTags), a pre-operative planning workstation and the Novarad PACS server. It uses optical tracking technology to co-localize the virtual 3D image datasets to the patient and displays to the surgeon the location of pre-operatively planned operative tracks and the tracked surgical instruments relative to the acquired intraoperative patient's scan, onto the surgical field. The 3D scanned image, along with tracking information, are projected to the surgeons' retina using a transparent near-eye display stereoscopic headset, allowing the surgeon to both look at the navigation data at the same time.

Here's a summary of the acceptance criteria and the study proving the device meets them, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

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The purpose of Visaris Vision® is to acquire, store, communicate, display and process medical X-ray images. These radiographic systems are intended for use by a qualified/trained physician or both adult and pediatric subjects for taking diagnostic x-rays. Not for mammography, interventional, or fluoroscopy use.

Visaris Vision combines our Visaris Avanse® cleared PACS software (K150725) with all the other components required to make a complete digital diagnostic X-ray system, including tube stands, tube heads, collimators, generators, tables, and (already cleared) digital X-ray panels. Visaris Avanse®, the software component, is a digital radiography imaging, control and management software (for imaging consoles) that works with DR flat panel detector technology. Visaris Avanse® PACS provides functionality for digital radiography examinations from patient search and entry, generator control, image acquisition and processing to DICOM data archiving and export. Visaris Avanse® PACS can also include a number of Digital Radiology modules such as network DICOM archive (PACS module), DICOM modality worklist module and diagnostic workstation software to turn it into digital radiology department on a PC for small clinics. Visaris Avanse ® is autonomous software and involves no hardware. It runs under the MS Windows XP/7/8 operating system on any hardware platform meeting the minimum system requirements. These models are available: Vision C: A universal digital system employing an Overhead Tube Crane, a table, and a wall stand. Vision U: A universal U-Arm system Vision V: A floor mounted tube system Vision X: A universal straight Arm system All of these come with the previously cleared Visaris 360, the integrated digital radiology workflow system. (Visaris Avance, K150725)

This document describes a 510(k) premarket notification for the "Visaris Vision" digital X-ray system. This system is a collection of components, including X-ray tubes, generators, collimators, tables, and digital X-ray panels, controlled by the Visaris Avanse® PACS software. The submission seeks to demonstrate substantial equivalence to a predicate device, the Siemens Multix Fusion (K121513).

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

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

The provided document does not explicitly present a dedicated table of "acceptance criteria" for the Visaris Vision system in the way one might expect for a specific performance metric (e.g., sensitivity, specificity for a diagnostic algorithm). Instead, the acceptance criteria are implicit in demonstrating substantial equivalence to the predicate device and compliance with recognized standards.

The "Comparison Table" in Section 4 (Page 5) compares the technological characteristics of the Visaris Vision with the predicate device (Siemens Multix Fusion K12113). While not framed as "acceptance criteria," these represent the benchmarks the device must meet to be considered substantially equivalent.

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 mentions a "clinical evaluation" was performed. However, it does not specify a distinct "test set" with a given sample size for this evaluation in terms of patient numbers or image counts, nor does it provide details on data provenance (country of origin, retrospective/prospective). The clinical evaluation's primary objective seems to be system verification and risk assessment rather than a quantitative performance evaluation of a specific diagnostic output.

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)

The document does not mention the use of experts to establish ground truth for a test set. The clinical evaluation focused on "verification in the normal working conditions" and "determination of all adverse effects," implying system functionality and safety checks rather than a diagnostic accuracy study requiring expert-derived ground truth.

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

No adjudication method is mentioned as a "test set" for diagnostic performance was not 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

No such MRMC comparative effectiveness study is mentioned. This device is an X-ray system, not an AI-powered diagnostic algorithm designed to assist human readers. The software component, Visaris Avanse®, is described as "a digital radiography imaging, control and management software... provides functionality for digital radiography examinations from patient search and entry, generator control, image acquisition and processing to DICOM data archiving and export." This suggests image acquisition and management, not AI-driven interpretation assistance.

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

A "standalone" performance for an algorithm is not applicable here as the device is an X-ray imaging system, not a diagnostic algorithm that provides standalone interpretations. The system's "performance" is tied to its ability to acquire, store, and process medical X-ray images, as demonstrated by non-clinical testing against standards and successful integration of components.

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

Given that no diagnostic accuracy study is described, there's no mention of ground truth established through expert consensus, pathology, or outcomes data. The "clinical evaluation" appears to focus on verifying the device's functional specifications and safety in a real-world setting.

8. The sample size for the training set

This information is not provided and is not applicable in the context of this 510(k) submission, which is for an X-ray imaging system, not a machine learning or AI algorithm requiring a training set in the typical sense. The software component (Visaris Avanse) was "used unmodified from our clearance obtained in K150725," implying that any development/training specific to that software would have been addressed in its prior submission.

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

As there's no described training set for a diagnostic algorithm, this information is not provided.

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The purpose of Visaris Avanse® is to acquire, store, communicate, display and process medical X-ray images. It offers features (e.g. window leveling, zoom, measurements, annotations etc.) routinely used by medical professionals, such as radiologists and radiographers. Visaris Avanse supports printing to DICOM compatible printers. Within a network environment Visaris Avanse may provide other modalities with a DICOM worklist and a DICOM worklist service. Images and worklists can be sent and received using the DICOM protocol. Visaris Avanse has a modular system architecture. It consists of the basic application, processing and viewing as well as a number of other modules for image and worklist management, archiving, search and display. Beside the basic functionality Visaris Avanse also provides a user interface for generator control and image acquisition of medical images DR detectors.

Visaris Avanse® is a digital radiography imaging, control and management software (for imaging consoles) that works with DR flat panel detectors technology. Visaris Avanse® PACS provides functionality for digital radiography examinations from patient search and entry, generator control, image acquisition and processing to DICOM data archiving and export. Visaris Avanse® PACS can also include a number of Digital Radiology modules such as network DICOM archive (PACS module). DICOM modality worklist module and diagnostic workstation software to turn it into digital radiology department on a PC for small clinics. Visaris Avanse ® is autonomous software and involves no hardware. It runs under the MS Windows XP/7/8 operating system on any hardware platform meeting the minimum system requirements.

This document is a 510(k) premarket notification for the "Visaris Avanse®" device, which is a software for digital radiography imaging, control, and management. It focuses on establishing substantial equivalence to a predicate device, not on proving meeting acceptance criteria through a specific study with quantitative performance metrics.

Therefore, many of the requested elements for describing "acceptance criteria and the study that proves the device meets the acceptance criteria" cannot be fully extracted or are not directly applicable in the typical sense of AI/CADe device performance studies.

Here's a breakdown of what can be inferred and what is not available:

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

The document does not provide a table of explicit quantitative "acceptance criteria" and "reported device performance" in the context of clinical efficacy or diagnostic accuracy. Instead, the "acceptance criteria" for this submission are demonstrated through a comparison of technological characteristics with a predicate device, and verification/validation testing against in-house criteria.

• Acceptance Criteria (Implicitly based on Predicate Equivalence and Functional Testing):
  • Maintain same essential indications for use.
  • Utilize same kind of platform (Windows PC).
  • Perform similar software validation and panel testing.
  • Be DICOM compatible.
  • Handle JPEG images.
  • Meet all in-house criteria demonstrated by Verification and Validation plan.
  • Produce images of excellent diagnostic quality.
• Reported Device Performance (Implicit, Qualitative, and Comparative):
  • "The Visaris Avanse® has the same essential indications for use as the predicate and uses the same kind of platform (Windows PC) to perform its functions." (Substantial Equivalence Discussion)
  • "The same kind of software validation and panel testing has been performed." (Substantial Equivalence Discussion)
  • "It is DICOM compatible like the predicate and handles jpeq images like the predicate." (Substantial Equivalence Discussion)
  • "The complete Visaris Avanse® PACS system configuration has been assessed and tested at the factory and has passed all in-house criteria." (Non clinical testing)
  • "Validation testing indicate that as required by risk analysis, designated individuals performed all verification and validation activities and that the result demonstrated that the predetermine acceptance criteria were met." (Non clinical testing)
  • "The images were evaluated by a board certified radiologist and were found to be of excellent diagnostic quality." (Clinical testing)

2. Sample size 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 explicitly stated. The "Clinical testing" section mentions "clinical images were obtained using each of the declared compatible digital panels." It does not specify the number of images or patients.
• Data Provenance: Not specified. It only states "clinical images were obtained." Whether this was retrospective or prospective, or the country of origin is not mentioned.

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)

• Number of Experts: "A board certified radiologist" (singular) was used.
• Qualifications: "Board certified radiologist." Specific experience (e.g., 10 years) is not provided.

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

• Adjudication Method: Not specified. Given there was only "a board certified radiologist," an adjudication method involving multiple readers is unlikely. This appears to be a single-reader evaluation.

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

• MRMC Comparative Effectiveness Study: No, an MRMC comparative effectiveness study was not done. This submission is for a software device that acquires, stores, communicates, displays, and processes X-ray images, and provides a user interface for generator control. It is not an AI/CADe device designed to assist human readers in diagnosis or detection, so a study comparing human readers with and without AI assistance is not relevant to this device's function as described.

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

• Standalone Study: No, this is not an AI/CADe algorithm for diagnosis. The "device" is the software itself, which facilitates image management and viewing. Its "performance" is assessed functionally (e.g., compatibility, image quality), not as a diagnostic algorithm. The clinical testing verifies the diagnostic quality of the images produced by the system, not the diagnostic performance of an algorithm.

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

• Type of Ground Truth: The "ground truth" for the clinical testing appears to be the qualitative assessment by a board-certified radiologist that the images were "of excellent diagnostic quality." There's no mention of pathology, outcomes data, or a formal consensus process.

8. The sample size for the training set

• Sample Size for Training Set: Not applicable/not provided. This device is not an AI/ML algorithm that requires a training set in the conventional sense. It's a general-purpose image acquisition, processing, and management software.

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

• How Ground Truth for Training Set was Established: Not applicable, as there is no mention of an AI/ML training set.

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Imaging of:

• The Whole Body (including head, abdomen, breast, heart, pelvis, joints, neck, TMJ, spine, blood vessels, limbs, and extremities). [Application terms include MRCP (MR Cholangiopancreatography), MR Urography, MR Myelography, MR Fluoroscopy, SAS (Surface Anatomy Scan), Dynamic Scan, Cine Imaging, and Cardiac tagging.]
• Fluid Visualization
• 2D/3D Imaging
• MR Angiography/MR Vascular Imaging
• Blood Oxygenation Level Dependent (BOLD) Imaging

This submission consists of a software upgrade to the MRT-50GP/E2 (FLEXARTTM), MRT-50GP/H2 (FLEXARTTM/Hyper), MRT-150/F1 (VISARTTM), MRT-150/F2 (VISARTTM/Hyper)

Here's an analysis of the provided 510(k) summary relating to acceptance criteria and the study conducted:

Disclaimer: The provided document (K983110) is a 510(k) Premarket Notification summary from 1998 for a software upgrade to existing Magnetic Resonance Diagnostic Devices (FLEXART™ and VISART™). It focuses on demonstrating substantial equivalence to previously cleared devices. It primarily discusses safety parameters and imaging performance specifications rather than a typical clinical study with acceptance criteria for a new AI/CAD device.

This document predates widespread AI in medical imaging and the standard AI/CAD study structure. Therefore, many of the requested fields (like sample size for test/training sets, ground truth establishment methods, MRMC studies, effect sizes, and standalone performance) are not directly addressed in the provided text as they pertain to a different type of device evaluation.

1. Table of Acceptance Criteria and Reported Device Performance

Given the nature of the document, the "acceptance criteria" are more akin to specifications that the software upgrade maintains, and the "reported device performance" indicates that these specifications are met or comparable to the predicate devices.

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Imaging of:

• The Whole Body (including head, abdomen, pelvis, limbs and extremities, spine, neck, TMJ, -The whole body (including reast). [Application terms include MR Fluoroscopy, MR Irography, MRCP (MR Cholangiopancreatography), MR Myelography, SAS (Surface Anatomy Scan), Dynamic Scan and Cine Imaging.]
• Fluid Visualization -
• 2D/3D Imaging -
• MR Angiography/MR Vascular Imaging -

This submission consists of three upgrades to the MRT-150/H1 and MRT-150/F1 (VISART™) system. The first upgrades the software from V3.1 (which was the software cleared with the VISART™ in K961092) to V3.5. The second is the introduction of the VISART™/Hyper system, which increases the gradient field strength over that of the standard VISART™ with V3.5 software. The third is the introduction of optional phased array coils.

The provided text describes a 510(k) summary for a Magnetic Resonance Device (MRT-150/H1, MRT-150/F1, MRT-150/H2, MRT-150/F2, marketed as VISART and VISART/Hyper). It introduces upgrades to the software (from V3.1 to V3.5) and hardware (VISART/Hyper system with increased gradient field strength and optional phased array coils).

Here's an analysis based on the information provided, specifically addressing the questions you've posed:

1. Table of Acceptance Criteria and Reported Device Performance:

The document describes safety and imaging performance parameters for the device. While explicit "acceptance criteria" for a study aren't clearly defined as pass/fail thresholds in the typical sense for a clinical study, the specifications listed for the upgraded devices represent the targeted performance that was demonstrated to be met.

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Imaging of the whole body (including the head, abdomen, heart, pelvis, spine, blood vessels, limbs and extremities), fluid visualization, 2D/3D Imaging, MR Angiography, MR. Fluoroscopy

The VISART™ consists of two model upgrades to the MRT-150A system which provide increased gradient field strength, more ergonomic computer architecture, improved scan parameter specifications and a lighter magnet than the MRT-150A.

This is a pre-amendment 510(k) submission for the VISART™ Magnetic Resonance Device, MRT-150A/H1 and MRT-150A/F1 models. The submission primarily focuses on demonstrating substantial equivalence to an existing device (MRT-150A) by highlighting hardware and software upgrades that improve performance without introducing new safety or effectiveness questions. The provided text, however, does not contain details about a specific study testing device performance against defined acceptance criteria in the manner typically seen for algorithmic or AI-based devices.

The submission describes general increases in imaging performance parameters and safety parameters compared to the predicate device. It also mentions that "Sample phantom images and clinical images were presented for all new sequences demonstrating conformance with consensus standards requirements for Signal-to-Noise ratio Uniformity, Slice Profiles, Geometric Distortion and Slice Thickness/Interslice Spacing." This indicates that some form of evaluation was performed, but the specifics of a structured study with statistical outcomes are not detailed.

Given the information provided, I cannot fully answer your request in the format you've outlined for an AI/algorithm-driven device's acceptance criteria and study. However, I can extract the relevant information as much as possible based on the provided text.

Here's an attempt to address your request based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" for the upgraded models in a quantitative, pass/fail manner. Instead, it highlights improvements over the predicate device (MRT-150A) and states conformance with "consensus standards requirements."

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