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The Mobile MIM software program is used for the viewing, registration, fusion, and/or display for diagnosis of medical images from the following modalities: SPECT, PET, CT, MRI, X-ray and Ultrasound.

Mobile MIM can be used to review images, contours, DVH, and isodose curves from radiation treatment plans. Mobile MIM can be used to approve these plans.

Mobile MIM provides wireless and portable access to medical images. This device is not intended to replace full workstations and should be used only when there is no access to a workstation.

This device is not to be used for mammography.

Mobile MIM (RT) extends the Mobile MIM software application previous cleared under K103785. In addition to SPECT. PET. CT. MRI modalities. Mobile MIM can be used for the viewing and/or display for diagnosis of X-ray and Ultrasound medical images.

It also provides functionality for the review of medical images, contours. DVH, and isodose curves from radiation treatment plans. In addition. Mobile MIM (RT) will allow permitted users the ability to approve reviewed radiation treatment plans.

The provided text describes the 510(k) summary for the Mobile MIM (RT) software, which is an extension of the existing Mobile MIM software. The document details the device's intended use, substantial equivalence to predicate devices, and performance data.

Here's an analysis of the provided information regarding acceptance criteria and the studies conducted:

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state quantitative (numerical) acceptance criteria. Instead, it describes general qualitative goals for the performance studies. The reported device performance is also qualitative, affirming that the software met these general expectations.

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

• X-ray and Ultrasound Diagnostic Viewing Study:

  • Sample Size: Not specified. The document states "multiple studies" were performed by "qualified radiologists" evaluating "the two additional modalities of X-ray and Ultrasound."
  • Data Provenance: Not specified. It does not mention the country of origin or if the data was retrospective or prospective.

• Radiation Therapy Plan Review Study:

  • Sample Size: Not specified. It mentions evaluating "multiple areas of treatments" and using "plan data from 3 major vendors."
  • Data Provenance: Not specified. It does not mention the country of origin or if the data was retrospective or prospective.

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

• X-ray and Ultrasound Diagnostic Viewing Study:

  • Number of Experts: Not specified, but referred to as "qualified radiologists."
  • Qualifications of Experts: "qualified radiologists." No further details on experience (e.g., "10 years of experience") are provided.

• Radiation Therapy Plan Review Study:

  • Number of Experts: Not specified, but referred to as "trained medical professionals."
  • Qualifications of Experts: "dosimetrists and radiation oncologists." No further details on experience are provided.

4. Adjudication Method for the Test Set

The document does not describe any specific adjudication method (e.g., 2+1, 3+1, none) for either study. The studies appear to be based on expert evaluations, but the mechanism for resolving disagreements or establishing a consensus ground truth is not detailed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

No MRMC comparative effectiveness study is explicitly mentioned. The studies described are focused on assessing the standalone performance or equivalence of the Mobile MIM (RT) display capabilities to a full workstation, rather than measuring human reader improvement with AI assistance. Therefore, no effect size for human reader improvement with AI vs. without AI assistance is provided.

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

The performance studies described in the document are primarily focused on the human-in-the-loop performance, where radiologists, dosimetrists, and radiation oncologists are using the Mobile MIM (RT) software to evaluate images and plans. The studies assess the software's ability to display information adequately for human interpretation and decision-making. No "algorithm only" standalone performance is discussed, as the device is a viewing and review software, not an AI diagnostic algorithm in the modern sense.

7. The Type of Ground Truth Used

• X-ray and Ultrasound Diagnostic Viewing Study: The ground truth for evaluating "diagnostic image viewing capabilities" would likely be the consensus opinion of the qualified radiologists regarding the diagnostic quality of the images displayed on the Mobile MIM (RT), presumably compared to "gold standard" interpretations or full workstation views. This is an inferred-expert consensus.
• Radiation Therapy Plan Review Study: The ground truth for evaluating "display quality for of isodose curves, DVH graphs, and contours" and "review and approval of radiation therapy plans" would be the consensus opinion of the trained medical professionals (dosimetrists and radiation oncologists), compared to views on a "full workstation." This is an inferred-expert consensus and comparison to a recognized standard (full workstation).

8. The Sample Size for the Training Set

The document does not describe the development or training of an AI algorithm or machine learning model. Mobile MIM (RT) is presented as an image viewing and review software application. Therefore, there is no mention of a "training set" in the context of an AI model. The "performance data" section focuses on testing the usability and display quality of the software for its stated functions.

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

As there is no mention of a training set for an AI algorithm, this information is not applicable. The device is software for viewing and interacting with medical images and plans, not an AI system that learns from a training set.

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The Mobile MIM software program is used for the registration, fusion, and/or display for diagnosis of medical images from only the following modalities: SPECT, PET, CT, and MRI.

Mobile MIM provides wireless and portable access to medical images. This device is not intended to replace full workstations and should be used only when there is no access to a workstation.

This device is not to be used for mammography.

The Mobile MIM software program is used for the registration, fusion, and/or display for diagnosis of medical images from only the following modalities: SPECT, PET, CT, and MRI.

Mobile MIM provides wireless and portable access to medical images. This device is not intended to replace full workstations and should be used only when there is no access to a workstation.

The software is not to be used for mammography.

It includes the capability to measure distance and image intensity values such as Standardized Uptake Value, displays measurement lines, annotations and regions of interest, and provides window/level, zoom/pan, and fusion blending control functionality.

Mobile MIM retrieves patient image data securely via a network connection with a MIM workstation or server. Processed DICOM images from the workstation or server are losslessly compressed for network transfer and downloaded by Mobile MIM for display.

Mobile MIM operates on "off-the-shelf" portable hardware devices and is therefore subject to factors not typical for reading room workstations (e.g. screen size, environmental variability, network dependencies, etc.). It is therefore required that the user follows the operating instructions properly and utilizes the risk mitigation features in order to make decisions safely and effectively.

The provided document describes the Mobile MIM software, a medical imaging software for display and diagnosis of medical images (SPECT, PET, CT, and MRI). It is intended for wireless and portable access when a full workstation is unavailable and is not for mammography.

Here's a breakdown of the acceptance criteria and study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

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

The document does not explicitly state the sample size used for the test set (number of images or cases).
The data provenance is also not explicitly detailed, but the studies were conducted internally by MIM Software Inc. with "qualified radiologists" and "a variety of modalities, specifically MRI, CT, SPECT, and PET." No information on the country of origin or whether the data was retrospective or prospective is provided.

3. Number of Experts and Qualifications for Ground Truth Establishment:

The document mentions "multiple studies with qualified radiologists." It does not specify the exact number of radiologists or their specific qualifications (e.g., years of experience, subspecialty) beyond being "qualified."

4. Adjudication Method for the Test Set:

The document does not specify any adjudication method (e.g., 2+1, 3+1, none) for establishing ground truth from the radiologists' readings. It simply states that "results of these studies affirm the diagnostic image viewing capabilities."

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

The document does not explicitly mention a multi-reader, multi-case (MRMC) comparative effectiveness study to assess how much human readers improve with AI vs. without AI assistance. The testing focused on the standalone performance and diagnostic viewing capabilities of Mobile MIM.

6. Standalone Performance Study:

Yes, a standalone study (algorithm only without human-in-the-loop performance) was done for display performance, measuring contrast response, luminosity, resolution, and noise using objective standards (IEC 62563-1 and TG18 guidelines). The document also mentions "functional testing on the Mobile MIM software" which implies standalone software performance evaluation.

7. Type of Ground Truth Used:

For the "diagnostic image viewing capabilities" studies, the ground truth was implicitly established by expert consensus/opinion from "qualified radiologists" who affirmed the capabilities. For display performance, the ground truth was based on objective measurements against established standards (IEC 62563-1 and TG18 guidelines).

8. Sample Size for the Training Set:

The document does not provide any information about the sample size for a training set. Given that Mobile MIM is described as medical imaging software for display, registration, fusion, and measurement, rather than an AI-driven diagnostic algorithm, it's highly probable that a "training set" in the machine learning sense was not applicable or not the primary focus of these performance data. The device's function is more akin to a viewing and manipulation tool than an automated diagnostic tool requiring extensive AI model training.

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

As no training set is mentioned or implied for an AI model, the method for establishing ground truth for a training set is not applicable and not provided in the document.

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