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MIM software is used by trained medical professionals as a tool to aid in evaluation and information management of digital medical images. The medical image modalities include, but are not limited to, CT. MRI. CR. DX. MG. US. SPECT. PET and XA as supported by ACRNEMA DICOM 3.0. MIM assists in the following indications:

• · Receive, transmit, store, retrieve, display, print, and process medical images and DICOM objects.
• · Create, display and print reports from medical images.
• · Registration, fusion display, and review of medical images for diagnosis, treatment planning,
  · Evaluation of cardiac left ventricular function, including left ventricular end-diastolic volume, end-systolic volume, and ejection fraction.
  · Localization and definition of objects such as tumors and normal tissues in medical images.
  · Creation, transformation, and modification of contours for applications including, but not limited to, quantitative analysis, aiding adaptive therapy, transfering contours to radiation therapy treatment planning systems, and archiving contours for patient follow-up and management.
  · Quantitative and statistical analysis of PET/SPECT brain scans by comparing to other registered PET/SPECT brain scans.
  · Planning and evaluation of permanent implant brachytherapy procedures (not including radioactive microspheres).
• · Post-treatment dose calculation of permanent Yttrium-90 (Y90) microsphere implants.
  Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary image interpretations. Images that are printed to film must be printed using a FDA-approved printer for the diagnosis of digital mammography images. Mammographic images must be viewed on a display system that has been cleared by the FDA for the diagnosis of digital mammography images.

The software is not to be used for mammography CAD.

MIM - SPECTRA Quant is a feature of MIM. It is designed for use in medical imaging and operates on both Windows and Mac computer systems. MIM - SPECTRA Quant extends the functionality MIM - Y90 Dosimetry (K172218) software. The following functions have been added to allow quantitative reconstructions of Single Photon Emission Computed Tomography (SPECT) scans:

• Allows for decay correction of activity back to time of injection ●
• Allows for correction of photon attenuation ●
• . Allows for correction of photon scatter
• Allows for correction of collimator detector resolution effects ●
• Allows for camera sensitivity calibration providing output in Becquerels per ml (Bq/ml) .

Here's a breakdown of the acceptance criteria and study details for MIM - SPECTRA Quant based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The acceptance criterion for MIM – SPECTRA Quant is a quantitative error of smaller or equal to 10% in regions that are large enough not to be affected by the partial volume effect.

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

• Test Set Description: The test set included "standard quality control phantoms, a Liver phantom, and simulated phantoms based on the NEMA IEC Body Phantom." It also involved "clinical data."
• Sample Size: The exact number of phantoms or clinical cases is not specified in the provided text.
• Data Provenance: The document does not explicitly state the country of origin for the data or whether it was retrospective or prospective. It only mentions the use of "physical and simulated phantoms as well as with clinical data." It's likely that the phantom data would be generated in-house or sourced from standard organizations.

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

• Number of Experts: "Board certified clinicians" performed "validation testing" and "qualified Nuclear Medicine professionals" rated reconstructions of clinical data. The exact number of clinicians or Nuclear Medicine professionals is not specified.
• Qualifications: "Board certified clinicians" and "qualified Nuclear Medicine professionals." Specific experience level (e.g., "10 years of experience") is not specified.

4. Adjudication Method for the Test Set

The document states that "All reconstructions of clinical data were rated as acceptable for clinical use by the qualified Nuclear Medicine professionals." This suggests an expert review process. However, a specific adjudication method (like 2+1, 3+1) for resolving disagreements among multiple experts, if multiple were involved, is not described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• Was it done? The document mentions "clinicians using MIM – SPECTRA Quant performed validation in comparison to independently implemented, industry-standard solutions." This suggests a comparison. However, it does not explicitly state that a formal Multi-Reader Multi-Case (MRMC) comparative effectiveness study was conducted with a focus on human reader improvement with vs. without AI assistance. The focus described is on the software's performance compared to standard solutions.
• Effect Size: No effect size or quantification of how much human readers improve with AI vs. without AI assistance is provided.

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

Yes, a standalone performance evaluation was done. The "Quantitative Accuracy Verification of MIM - SPECTRA Quant" table directly measures the "Quantitative Error" of the software itself (the algorithm) against predefined acceptance criteria using phantoms. This is a direct measure of the algorithm's standalone performance.

7. The Type of Ground Truth Used

The ground truth for the quantitative accuracy assessment (the core of the reported performance data) was established based on the known properties of the phantoms. Phantoms are designed to have known concentrations of radioactive isotopes, which serve as the ground truth for measurement accuracy. For "clinical data," the ground truth of "acceptability for clinical use" was established by "qualified Nuclear Medicine professionals" (expert review).

8. The Sample Size for the Training Set

The document does not provide any information about the sample size used for the training set. This is a key omission for understanding the AI model's development.

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

The document does not provide any information on how ground truth was established for a training set. Given the lack of mention of a training set, it's possible the quantitative accuracy features (decay, attenuation, scatter, resolution corrections) are based on physical models and algorithms rather than a trained machine learning model, or if a model was used, its training details are not disclosed.

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