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The IMI Spectrum V.0 is a medical diagnostic system that allows the processing, review, and analysis of multi-dimensional digital images acquired from CT imaging devices. The IMI Spectrum V.0 is not meant for primary image interpretation in mammography.

The IMI Spectrum V.0 is intended to receive patient specific data sets of CT images and can be used for:

• . 3D presentation of complex anatomical relationships and specified structures with the complete data set;
• . System generation of a 3D model of the desired anatomical structure;
• . Viewing of the volume rendered and Multiplanar Reconstruction (MPR) representations of the desired anatomical structure providing additional supplemental information to support interpretation and treatment planning;
• Viewing the inner and outer surfaces of organs as well as within their wall providing . additional supplemental information to support interpretation and treatment planning;
• Planning and following a navigation path through the desired anatomical structure; .
• Programmed and interactive navigation and flythrough within the 3D volume including . specified organs and structures;
• . Measurement of position and length of anatomical structures within the 3D volume; and
• Common core technology with specialized interfaces for different anatomical structures.

IMI Spectrum V.0 is a medical diagnostic device that allows the processing, review, and analysis of multi-dimensional digital images acquired from a variety of imaging devices.

The IMI Spectrum V.0 contains all the required hardware and software to provide an interactive 3D and 2D views of diagnostic CT images. The views include both inner and outer surface 3D volume rendered images as well as orthogonal and multiplanar reformatted 2D images. This ability to view the dataset in different perspectives from which it was acquired is performed by first transferring DICOM images from the CT scanners to the IMI Spectrum V.O, semi-automatically identifying regions of interest and displaying these regions to the user in the above mentioned views. The user can navigate both freely within the dataset/region of interest, or follow automatically computed paths to move through or move around the outside of the structure. Measurements of the viewed anatomical structure can be made.

The IMI Spectrum V.0 provides multi-dimensional visualization of digital images to aid clinicians in their analysis of anatomy and pathology. The IMI Spectrum V.0 user interface follows typical clinical workflow patterns to process, review, and analyze digital images, including:

• Select images for closer examination from a gallery of up to six 2D or 3D views .
• Interactively manipulate an image in real-time to visualize anatomy and . pathology
• Annotate, tag, measure, and record selected views .

Here's a summary of the acceptance criteria and study details for the Intrinsic Medical Imaging Spectrum V.0, based on the provided 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Phantom Test Set: The document mentions "phatoms with structures of a known size and distance from the start inserted into the phantom." It does not specify the exact number of phantoms or structures.
• Clinical Test Set: The document states "previously scanned, anonymized patient CT data." It does not specify the number of patient CT datasets used.
• Data Provenance: Not explicitly stated for either test set (e.g., country of origin). The clinical data was "anonymized," implying it was retrospective.

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

• Phantom Test Set: "An independent reviewer then compared the test results with the actual phantoms and made an assessment as to accuracy." No specific qualifications are provided for this reviewer other than being "independent."
• Clinical Test Set: "The clinical data was reviewed by a radiologist who determined that the rendering is accurate and medically useful." Only one radiologist is explicitly mentioned for this review. No specific years of experience are provided.

4. Adjudication Method for the Test Set

• Phantom Test Set: A single "independent reviewer" compared test results to actual phantom characteristics. This suggests a direct comparison, not a consensus-based adjudication.
• Clinical Test Set: A single "radiologist" made the determination. No formal adjudication process (like 2+1 or 3+1) is mentioned.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

• No, an MRMC comparative effectiveness study was not done. The studies described focus on assessing the device's accuracy and functionality against known ground truth (phantoms) and expert review (clinical data), rather than comparing human reader performance with and without AI assistance.

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

• Yes, a standalone evaluation was performed. Both the phantom testing and the clinical testing describe the system's performance in processing and visualizing images. The clinical testing specifically states "the system/software performs as intended," indicating an assessment of the algorithm's output. While a human radiologist reviewed the output, the core assessment was on the system's ability to render accurate and useful images.

7. The Type of Ground Truth Used

• Phantom Test Set: The ground truth was known physical characteristics (size and location of structures within the phantoms).
• Clinical Test Set: The ground truth was expert consensus/opinion by a radiologist, who determined the rendering to be "accurate and medically useful."

8. The Sample Size for the Training Set

• The document does not specify the sample size for any training set. The descriptions focus on testing and validation.

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

• Since a training set size is not provided, the method for establishing its ground truth is also not described. The focus of the 510(k) summary is on the testing used to demonstrate substantial equivalence, not the development or training process of the software.

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