(218 days)
iNtuition-TDA, TVA, and Parametric Mapping are software modules which supports assessment of time-dependent behavior of image intensity, dimensions or volume of regions of interest over time, for volumetric or planar dynamic image types such as CT or MR. Parametric mapping tools encode in color various parameters derived from the temporal or spatial characteristics of the planar or volumetric data.
Support is provided for digital image processing to derive metadata or new images from input image sets, for internal use or for forwarding to other devices using the DICOM protocol. Image processing tools are provided to extract metadata to derive parametric images from combinations of multiple input images.
iNtuition-TDA, TVA and Parametric Mapping are iNtution based software features with dedicated workflows and basic tools and thus support post-processing, displaying and manipulation of reports and medical images from acquisition devices and visualization in 2D, 3D and 4D for single or multiple datasets, or combinations thereof.
iNtuition-TDA, TVA, Parametric Mapping are designed for use by healthcare professionals and are intended to assist the physician in diagnosis, who is responsible for making all final patient management decisions.
iNtuition - TDA. IVA. Parametric Mapping are post-processing modules, part of iNtuition, which is a software device generally used with off-the-shelf hardware. offered in various configurations, with the simplest configuration being a stand-alone workstation capable of image review, communications, archiving, database maintenance, remote review, reporting and basic 3D capabilities. It can also be configured as a server with some, all, or none of its optional features disabled. A fully-configured iNtuition system is capable of various image processing and visualization functions to support the physician in medical image reviewing.
iNtuition - TDA, TVA, Parametric Mapping intended used is to provide solutions to various medical image analysis and viewing problems, which come about as modalities generate more and more images. They also support image distribution over networks, and are DICOM compliant.
iNtuition Time-Dependent Analysis (TDA) and Time-Volume Analysis (TVA) features can obtain quantitative information relating to the evolution of the intensity, density or dimensions of certain regions of CT. MR or other images over time. Statistical analysis such as a histogram representation of the image density values in an image is supported, and analysis of changes in volume over time from multi-phase volumetric images; for example, eiection fraction and stroke volume measurement calculation can be performed using the Time-Volume Analysis tools.
iNtuition Parametric Mapping tools encode in color various parameters derived from the temporal or spatial characteristics of the planar or volumetric data.
iNtuition - TDA, TVA and Parametric Mapping are iNtuition-based optional features, and employ all standard features offered by iNtuition, such as convenient tools to support creation of a report, transmitting and storing this report in digital form, and tracking historical information about the studies analyzed with the software.
These three modules can be sold separately or as a part of the bigger iNtuition package.
The provided text does not contain detailed acceptance criteria for quantitative device performance or a study explicitly proving the device meets such criteria. Instead, it focuses on demonstrating substantial equivalence to predicate devices and adherence to internal company procedures and voluntary industry standards.
Here's an analysis based on the information available:
1. Table of Acceptance Criteria and Reported Device Performance:
No specific, measurable acceptance criteria with corresponding performance metrics are reported in the document. The general acceptance is that the device "fully satisfies all expected and previously defined system requirements and features" and is "substantially equivalent to and perform as well as the predicate devices."
| Acceptance Criteria (Not Explicitly Stated as Measurable Metrics) | Reported Device Performance |
|---|---|
| Satisfies all expected and previously defined system requirements and features | "Test results support the conclusion that actual device performance satisfies the design intent and is equivalent to its predicate devices." |
| Substantially equivalent to predicate devices for intended use and technological characteristics | "In all material aspects, iNtuition-TDA, TVA, Parametric Mapping is substantially equivalent to the predicate devices." |
| No new significant safety and effectiveness concerns | "The introduction of iNtuition-TDA, TVA, Parametric Mapping has no significant concerns of safety and efficacy." |
| Adheres to internal company procedures for software testing and validation | "Performance testing was carried out according to internal company procedures. Software testing and validation were done according to written test protocols established before testing was conducted." |
| Adheres to voluntary standards (e.g., DICOM) | "voluntary standards such as DICOM, various in-house standard operating procedures are in place and utilized in the production of the software." |
2. Sample size used for the test set and the data provenance:
- Sample size for the test set: Not specified. The document states "Software testing and validation were done according to written test protocols." It doesn't mention a specific test set size (e.g., number of cases or images).
- Data provenance: Not specified. Since clinical studies were not required, it's unlikely that the "test set" involved patient data in a formal clinical trial sense. It likely refers to internal software testing using simulated or previously acquired anonymized data that were part of the predicate device's validation.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Not applicable. The document states that clinical studies were not required. The "ground truth" for the software testing would have been based on the expected outputs as defined by the design requirements, rather than expert interpretation of medical images for diagnostic accuracy. "Test results were reviewed by designated technical professionals." Their qualifications are not specified beyond "technical professionals."
4. Adjudication method for the test set:
Not applicable. No mention of an adjudication method, as it wasn't a study involving human interpretation of medical images with a diagnostic endpoint.
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, an MRMC comparative effectiveness study was not done. The document explicitly states: "The subject of this traditional 510k notification, iNtuition-TDA. TVA, Parametric Mapping, did not require clinical studies to show safety and effectiveness of the software." Therefore, there is no information on the effect size of human reader improvement with or without AI assistance.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
The performance testing described is likely a standalone assessment of the software's functionality and accuracy against its design specifications. The document states, "Test results support the conclusion that actual device performance satisfies the design intent and is equivalent to its predicate devices." However, it doesn't quantify this performance in medical terms (e.g., sensitivity, specificity for a particular pathology), but rather in terms of meeting functional requirements. The device is intended to "assist the physician in diagnosis, who is responsible for making all final patient management decisions," implying it is not a standalone diagnostic device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
Given the lack of clinical studies, the "ground truth" for the software's internal testing would have been defined by the expected computational results based on the software's design and algorithms. For example, if the software calculates ejection fraction, the ground truth would be the mathematically correct ejection fraction from a given input, based on a reference method or calculation. It would not be based on expert medical consensus, pathology, or outcomes data in a clinical validation context.
8. The sample size for the training set:
Not applicable. This is a post-processing software module, not a machine learning or AI algorithm that typically requires a large training set for model development. The document does not mention any machine learning components, and thus, no training set or its size is provided. The comparison is based on "similar technological characteristics" to predicate devices.
9. How the ground truth for the training set was established:
Not applicable, as there is no mention of a training set for machine learning.
§ 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).