(167 days)
The FuncTool option to the Advantages Windows workstation is a software module that provides supplemental information to those images extracted from CT and MR temporal datasets.
FuncTool is a functional Imaging software package which allows to display the temporal variation in dynamic CT and MR datasets. Single or multi-slice datasets, with equally spaced time intervals are used for input. The purpose is to provide Time Intensity Curves and parametric images that provide clinical information for diagnosis purposes. This software is used during post-processing of MR and CT images on GE's CT and MR Systems.
This document is a 510(k) summary of safety and effectiveness for the FuncTool Option to the Advantage Windows workstation. It primarily focuses on demonstrating substantial equivalence to previously marketed devices rather than presenting a study with specific acceptance criteria and performance data for a new device's efficacy.
Therefore, many of the requested sections about acceptance criteria, detailed study design, and performance metrics cannot be filled from the provided text. The document is a regulatory submission for a software module, which often relies on demonstrating equivalence rather than conducting efficacy trials with specific performance targets in the same way a new medical measurement device might.
Here's an attempt to answer the questions based only on the provided text, highlighting where information is absent:
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Table of acceptance criteria and the reported device performance
This document does not specify quantitative acceptance criteria or provide a table of reported device performance in the way a clinical efficacy study would. The acceptance criteria for this 510(k) submission appear to be based on demonstrating "substantial equivalence" to predicate devices, meaning it does not introduce new indications for use or new potential hazards.
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Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
Not applicable/Not provided. The document describes a software module and its indications for use, but does not detail a study involving a test set of data or its provenance.
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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)
Not applicable/Not provided. There is no mention of a study involving expert-established ground truth. The software provides "supplemental information" and "clinical information for diagnosis purposes," implying it assists medical professionals, but not that its performance was evaluated against expert ground truth in a formal study described here.
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Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable/Not provided.
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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
Not applicable/Not provided. This document does not describe an MRMC study. The software "automates what is presently done manually," suggesting it might improve efficiency or consistency, but no comparative effectiveness study with human readers is mentioned here.
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If a standalone (i.e. algorithm only without human-in-the loop performance) was done
While the FuncTool is a "functional Imaging software package," this document does not describe a standalone performance study. Its purpose is to "provide Time Intensity Curves and parametric images that provide clinical information for diagnosis purposes," used "during post-processing of MR and CT images." This implies it's a tool for clinical use, rather than a diagnostic algorithm designed for standalone performance evaluation in the context of this submission.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc)
Not applicable/Not provided. There is no mention of ground truth as part of a performance evaluation study.
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The sample size for the training set
Not applicable/Not provided. This document describes a software product, not a machine learning model for which a training set size would typically be specified.
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How the ground truth for the training set was established
Not applicable/Not provided.
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).