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RTist is a software application, intended to display and visualize 2D & 3D multimodality (i.e. CT, MRI, and PET) medical image data. The user may process, render, review, store, print and distribute DICOM 3.0 compliant medical image data within the system and/or across computer networks at distributed locations utilizing standard PC hardware.

The volume and linear measurement functions are intended for evaluation and quantification of turnor measurements, location/displacement study, analysis and evaluation of both hard and soft tissues. The software also supports interactive segmentation of the region of interest (ROI), automated contouring of multi-slice ROI and labeling of 'avoidance' structure(s) during critical evaluation.

Typical users of this system are trained professionals, including but not limited to radiologists, clinicians and technicians. When interpreted by a trained physician, reviewed images may be used as an element for diagnosis.

The RTist is a software application acting as a stand alone Picture Archiving and The relise is a betting (PACS). It may be marketed as the software only as well as packaged with a standard 'off the shelf' PC Hardware. It is in effect a 'plug in' publication to the Fusion 7D/ Miraview / Reveal - MVS software platform (reference K020546) but is effectively 'vendor' neutral and as such an enhancement to many other medical image/ data management systems.

The comprehensive array of features provided by the software allows the medical professional to visualize, review, interpret, manipulate, render and distribute medical image data stored in DICOM format. The networking component of the product allows the exchange of medical image data with any other DICOM-compatible or FTPcompatible server over a standard TCP/IP network.

The RTist receives images in DICOM format, which are then converted into volume data format using core software technology. The RTist viewer provides interactive orthogonal and multi-planar reformatting which enables the user to evaluate abnormality or malformation displayed in the image. The volume and linear measurement features provided by the software enable evaluation and quantification of region of interest volume, linear measurements and location/displacement.

The software also supports interactive segmentation of the region of interest (ROI), automated contouring of multi-slice ROI and labeling of structure(s) during critical evaluation.

RTist processes an array of medical images including anatomical images (e.g. CT and conventional MRI), and functional images (e.g. SPECT and PET).

The RTist software incorporates standard visualization features to display the input DICOM data and the results of the registration operations.

The provided text is a 510(k) summary for the RTist software application. It describes the device, its intended use, and lists predicate devices. However, it does not contain any information about acceptance criteria, device performance studies, sample sizes, ground truth establishment, or expert qualifications.

Therefore, I cannot fulfill your request for a table of acceptance criteria and reported device performance or details about a study proving the device meets acceptance criteria based on the provided text. The document is essentially a regulatory submission summary, not a clinical trial report or a performance validation study.

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Fusion7D registers pairs of anatomical and functional volumetric images (e.g. MRI-SPECT, MRI-PET, CT-SPECT, CT-PET), or pairs of anatomical volumetric images (e.g. MRI-MRI, CT-CT and MRI-CT) as a means to ease the comparison of image volume data by the clinician. The result of the registration operation aims to help the clinician obtain a better understanding of the joint information that would otherwise have to be compared visually. This is useful for a wide range of clinical and therapeutic applications. It is important to note that the clinician retains the ultimate responsibility for making the pertinent diagnosis based on their standard procedures including visual comparison of the separate unregistered images. Fusion7D is a complement to these standard procedures.

Fusion7D is a software program running on a PC platform, which brings into alignment (registers) pairs of images from different imaging modalities. Fusion7D also includes functionality to read, display, and save the original volumetric data and the results of the registration operation by means of a graphic user interface that includes visualization, file browsing and control of input and output as described in the following text.

The provided text describes Fusion7D, a software program for registering and fusing medical images. However, it does not include detailed acceptance criteria or a study that specifically proves the device meets such criteria in terms of quantitative performance metrics, sample sizes, expert involvement, or statistical analysis.

The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to predicate devices, rather than providing a detailed performance study with acceptance criteria.

Therefore, the following information cannot be extracted from the provided text:

• A table of acceptance criteria and the reported device performance: This information is not present. The document describes the device's capabilities and intended use but does not quantify performance against specific criteria.
• Sample size used for the test set and the data provenance: No performance study details are given.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not mentioned.
• Adjudication method for the test set: Not mentioned.
• If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs without AI assistance: This type of study is not described. The device is a registration tool, not an AI diagnostic aid in the sense of improving human reader performance on a diagnostic task, although it aims to "ease the comparison of image volume data."
• If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not explicitly stated or quantified in terms of performance. The document implies automated registration capabilities but doesn't provide a standalone performance evaluation against a gold standard.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not mentioned.
• The sample size for the training set: No training data or set is mentioned, as this is more a description of the final device functionality rather than its development.
• How the ground truth for the training set was established: Not applicable, as no training set is described.

Summary of what can be inferred about "acceptance criteria" and "study" implicitly from the document:

The "acceptance criteria" for Fusion7D, as implied by the 510(k) process, primarily revolve around demonstrating substantial equivalence to legally marketed predicate devices in terms of intended use, technological characteristics, and safety/effectiveness. The "study" largely consists of the submission itself, detailing the device's functionality and comparing it to existing, approved devices.

The document states:

• "Fusion7D is a software program running on a PC platform, which brings into alignment (registers) pairs of images from different imaging modalities."
• It supports "manual," "semi-automatic," and "automatic" registration, limited to "rigid body deformation."
• It provides "standard visualization facilities" and allows "registration results to be displayed in a variety of ways."
• Intended Use: "Fusion7D registers pairs of anatomical and functional volumetric images... as a means to ease the comparison of image data."

The FDA's approval letter confirms that the device was found "substantially equivalent" based on its comparison to the predicate devices listed (K010336, K983256, K992654). This substantial equivalence is the de facto "acceptance criteria" for this 510(k) submission, and the "study" is the submission argument itself.

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