Search Results

AcroDTI Visualizer is an image processing software that allows the user to calculate and display DTI from diffusion MRI (dMRI) data. This software is intended to be utilized by trained physicians to visually evaluate the DTI index maps.

AcroDTI Visualizer is a software for processing and viewing Diffusion Tensor Imaging (DTI) from dataset of Diffusion Weighted Imaging (DWI) acquired with Magnetic Resonance Imaging (MRI). AcroDTI Visualizer calculates and displays DTI maps which reveal diffusion properties of local tissue. The software displays the DTI maps in axial, coronal, and sagittal views, and is able to adjust the image brightness and contrast to assist visual evaluation.

AcroDTI Visualizer provides support for automated processing of diffusion MRI data in Digital Imaging and COmmunications in Medicine (DICOM) format. The software reads DICOM files in DVD (or CD) exported either from the MR scanner or from a Picture Archiving and Communications System (PACS).

The AcroDTI Visualizer is an image processing software that calculates and displays Diffusion Tensor Imaging (DTI) from diffusion MRI (dMRI) data, intended for visual evaluation by trained physicians. The submission states that performance comparison studies were conducted to support substantial equivalence.

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

1. Table of Acceptance Criteria and Reported Device Performance

The document broadly states that "all the software specifications have met the acceptance criteria" and "AcroDTI Visualizer meets the pre-specified acceptance criteria." However, specific quantitative acceptance criteria for performance metrics (e.g., accuracy, sensitivity, specificity, or specific error ranges for DTI calculations) are not detailed in the provided text. The performance is primarily described in terms of "high similarity with the legally marketed devices" in comparative studies.

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

The document states, "The performance comparison studies between subject device and legally marketed devices were conducted using qualitative and quantitative methods respectively."
However, the sample size for the test set is not explicitly mentioned. The data provenance is also not specified (e.g., country of origin, retrospective or prospective).

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

The text mentions that "Experienced physicians were recruited to evaluate the performance between subject device and legally marketed devices."
The exact number of experts is not specified, nor are their qualifications (e.g., years of experience, specific sub-specialty).

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1) for establishing ground truth or resolving discrepancies among the experienced physicians.

5. 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

The document describes "performance comparison studies between subject device and legally marketed devices" involving "experienced physicians" to "evaluate the performance." This suggests a comparative study involving readers. However, it does not mention an MRMC study designed to measure the improvement of human readers with AI assistance versus without AI assistance. The AcroDTI Visualizer is described as an "image processing software that allows the user to calculate and display DTI," implying it's a visualization tool rather than an AI-assisted diagnostic aid that directly improves reader performance on a diagnostic task compared to a non-AI workflow. Therefore, an effect size of human readers improving with AI vs. without AI assistance is not applicable or provided.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The device is positioned as "image processing software that allows the user to calculate and display DTI from diffusion MRI (dMRI) data," and is "intended to be utilized by trained physicians to visually evaluate the DTI index maps." This directly implies a human-in-the-loop scenario. While "software verification and validation testing were conducted," these are typically foundational tests for software functionality and reliability, not a standalone performance evaluation in a diagnostic context. Therefore, a standalone performance study (algorithm only without human-in-the-loop performance) is not explicitly described or implied for a diagnostic claim. The performance comparison was with legally marketed devices, with physicians evaluating the output.

7. The Type of Ground Truth Used

The document indicates that "Experienced physicians were recruited to evaluate the performance between subject device and legally marketed devices." This suggests that the ground truth or "reference standard" for comparison was effectively derived from the evaluations and interpretations of these experienced physicians when using the legally marketed predicate devices, and then comparing the AcroDTI Visualizer's output to that. It is not explicitly stated if pathology, outcomes data, or an independent expert consensus (beyond the comparison itself) was used as an absolute ground truth.

8. The Sample Size for the Training Set

The provided text does not contain any information about a training set or its sample size. The AcroDTI Visualizer appears to be a deterministic image processing and visualization tool (calculates and displays DTI maps) rather than a machine learning model that requires a specific training set to learn from data.

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

Since there is no mention of a training set, the method for establishing ground truth for a training set is not applicable or provided.

Ask a specific question about this device