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iNtuition-T1 Mapping and T2/T2* Mapping are software modules that support the derivation and quantification of T1, T2 and T2* values from MR DICOM image pixel intensities and header information. The quantification of these parameters can be used to characterize tissues. Support is provided to overlay the T1, T2, and T2* values using colormaps on related MR images.

Support is provided for using different colormaps to overlay different ranges of T1, T2 or T2* values and restrict the overlay to region of interest on the images can be of simple planar scan like a single slice or volumetric or 4D scans of a body part. iNtuition-T1 Mapping and T2/T2* Mapping are iNtuition software features that can be used in multiple workflows or be used as basic tools for cardiac functionality, the overlaid images can be captured and forwarded to other systems using standards such as DICOM or http protocol. Quantitative analysis is derived and available as text and graphical display.

iNtuition- T1 Mapping and T2/T2* Mapping qualitation can be used in a clinical setting on MR images of an individual patient and can be used to support the clinical decision making for the patient. iNtuition- T1 Mapping and T2/T2* 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-T1 Mapping and T2/T2* Mapping is an optional image post-processing module, part of iNtuition (K121916), which is software only device generally used with the off-the-shelf hardware, offered in various configuration, 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. Whether provided as a workstation or a server, the iNtuition software is designed to provide access by a local user physically sitting at the computer hosting the iNtuition server software, and/or by one or more remote users who concurrently connect to the server using a freely-downloadable thin client application or through a zero-footprint web viewer (with conference capabilities) over local network or internet.

iNtuition-T1 Mapping and T2/T2* Mapping feature can derive quantitative values from intensities and header information of specific MR scan sequences that are specifically coded to enable such derivation (such as Look-Locker and MOLLI for T1.) The quantification of these parameters can be used to derive clinical value such as T2*.. Post-processing such as computation of statistics like volume, area, min/max or various combinations of the derived values, over regions of interests or overlay the derived values using a colormap on related images or a region of the images. The region of interests can be defined by the user through manual, semi-automatic or automatic segmentation techniques provided by iNtuition. The derivation and post-processing can be used with planar, volumetric or 4D scan sequences for cardiac functionality.

iNtuition-T1 Mapping and T2/T2* Mapping is an iNtuition based optional features, and employ all standard features offered by iNtuition such as convenient image manipulation tools like drawing region of interest, manual or automatic segmentation of structures and tools that support creation of a report, transmitting and storing this report in digital form, and tracking historical information about the studies analyzed by the software.

This device is intended only to assists the operator in making decisions. The software is not intended to replace the skill and judgment of a qualified medical practitioner and should only be used by people that have been trained in the software's function (iNtuition), capabilities and limitations. The device is intended to provide supporting analytical tools to a physician, to speed decision-making and to improve communication, but the physician's judgment is paramount and it is normal practice for physicians to validate theories and treatment decisions multiple ways before proceeding with a risky course of patient management.

iNtuition-T1 Mapping and T2/T2* Mapping modules may be sold separately or as an extension of iNtuition.

This submission for K180916 does not provide specific acceptance criteria or a study demonstrating that the device meets those criteria, as it is a Traditional 510(k) stating the product is substantially equivalent to a predicate device and did not require clinical studies.

Therefore, many of the requested details cannot be extracted from the provided text.

However, based on the principle of substantial equivalence, the "acceptance criteria" are generally that the device performs as well as the predicate device across its intended use and technological characteristics.

Here's a breakdown of what can be inferred or stated from the document:

1. Table of Acceptance Criteria and Reported Device Performance:

Since no specific performance metrics or acceptance criteria are listed, this table cannot be populated directly. The document repeatedly states that the device is "substantially equivalent" to its predicate and "performs as well as the predicate device" in terms of its intended use and technological characteristics.

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

• Sample Size for Test Set: Not specified.
• Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). The document mentions "Software verification and validation was completed in accordance with internal processes" and "Performance testing was carried out according to internal company procedures." This implies internal testing rather than a large-scale external test set with specific patient data.

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

• Number of Experts: Not specified.
• Qualifications of Experts: Not specified. Software testing was reviewed by "designated technical professionals."

4. Adjudication Method for the Test Set:

• Adjudication Method: Not specified.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

• MRMC Study: No. The document explicitly states: "The subject of this traditional 510k notification, iNtuition-T1 Mapping and T2/T2* Mapping, did not require clinical studies to show safety and effectiveness of the software." Therefore, no MRMC study was conducted.
• Effect Size of Human Readers Improvement with AI vs. Without AI Assistance: Not applicable, as no MRMC study was performed.

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

• Standalone Study: Not explicitly detailed as a separate "study" with performance metrics. The document describes the software's functionality in deriving and quantifying T1, T2, and T2* values, and mentions "Software verification and validation" and "Performance testing" were conducted internally to ensure it met design intent and was equivalent to the predicate. This would constitute standalone testing of the algorithm's output against expected results, but the specifics are not provided.

7. Type of Ground Truth Used:

• Type of Ground Truth: Not explicitly stated. For internal performance testing of quantitative measurements (like T1/T2/T2* values), ground truth would likely be established through:
  • Reference standards/phantoms: Using known values.
  • Comparison to predicate device's output: Ensuring the new device's output matches that of the already cleared predicate.
  • Manual calculations/expert evaluation: For regions of interest.

The document indicates the software supports "derivation and quantification of T1, T2 and T2* values from MR DICOM image pixel intensities and header information," suggesting the ground truth for these values would be based on the principles of MRI physics and potentially established clinical methods for calculating these parameters.

8. Sample Size for the Training Set:

• Sample Size for Training Set: Not specified. The document describes the software as an "optional image post-processing module" that derives quantitative values from specific MR scan sequences. This doesn't inherently suggest a machine learning model that requires a "training set" in the common sense (i.e., for supervised learning). It's more about algorithmic derivation and quantification. If any machine learning components were involved, the training set details are not disclosed.

9. How the Ground Truth for the Training Set was Established:

• How Ground Truth for Training Set was Established: Not applicable/not specified, as training set details are not provided and the primary function described is algorithmic derivation rather than machine learning inference.

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