(241 days)
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, MR, CR, DX, MG, US, SPECT, PET and XA as supported by ACR/NEMA 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 evaluation, and treatment planning.
- Evaluation of cardiac left ventricular function and perfusion, 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, transferring 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).
- Calculating absorbed radiation dose as a result of administering a radionuclide.
- Assist with the planning and evaluation of ablation procedures by providing visualization and analysis, including energy zone visualization through the placement of virtual ablation devices validated for inclusion in MIM-Ablation. The software is not intended to predict specific ablation zone volumes or predict ablation success.
When using the device clinically, within the United States, the user should only use FDA approved radiopharmaceuticals. If used with unapproved ones, this device should only be used for research purposes.
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 an 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 - Monte Carlo Dosimetry (K232862) extends the features of MIM - Ablation (K220256). It is designed for use in medical imaging and operates on Windows, Mac, and Linux computer systems. The intended use and indications for use in MIM - Monte Carlo Dosimetry are unchanged from the predicate device, MIM - Ablation (K220256).
MIM - Monte Carlo Dosimetry (K232862) is a standalone software application that extends the functionality of the predicate device by providing:
- Dose calculation of radionuclides performed using a Monte Carlo method
Here's a summary of the acceptance criteria and the study that proves the device meets them, based on the provided text:
Device: MIM - Monte Carlo Dosimetry (K232862)
Acceptance Criteria and Reported Device Performance:
| Criteria / Comparison Type | Acceptance Criteria (Implicit) | Reported Device Performance |
|---|---|---|
| Comparison to Model-Based Dosimetry (OLINDA/EXM - K033960) | Agreement with predicate device (OLINDA/EXM) for mean absorbed doses across various structures and isotopes, with differences within expected ranges. | For Lu-177, I-131, and Y-90 activity maps, the average, absolute percent difference between MIM - Monte Carlo Dosimetry and OLINDA/EXM was 4.3% across all structures and isotopes. Excluding lung doses (due to known limitations of OLINDA's model), the average difference dropped to 2.5%. This is within the expected range, citing a similar study with 177Lu-DOTATATE data that showed a 5% average difference. Lung dose differences were higher (18.1%, 10.8% for Lu-177, I-131, and Y-90 respectively) but attributed to OLINDA's underestimation due to cross-dose from nearby tumors and differences in patient-specific lung geometry. |
| Comparison to Voxel S-value (VSV) Dosimetry (MIM – Ablation - K220256) | Agreement with predicate VSV method, accounting for known differences due to tissue inhomogeneities. | The average, absolute percent difference was 6.0% across all structures and isotopes. This is consistent with previously published results for other commercial VSV software (~10%). Excluding the I-131 lung dose (61% difference, attributed to VSV overestimation in low-density tissue like lungs), the average difference dropped to 4.0%. This large lung difference was expected and within reported discrepancies (30-60%) for VSV methods when compared to Monte Carlo in inhomogeneous tissues. |
| Comparison to a Well-Established Monte Carlo Algorithm (GATE) | High agreement with a benchmark Monte Carlo algorithm. | The two methods (MIM - Monte Carlo Dosimetry and GATE) were in high agreement, with an average, absolute difference of 1.4% across all structures and isotopes. Monte Carlo calculations differed by 2-3% for Lu-177, I-131, and Y-90. |
| Characterization of User Inputs (Particle Histories) | Default settings should provide accurate dose calculations with acceptable uncertainty. | The default setting for 1 x 10^9 particle histories is found to be appropriate, resulting in less than 1% uncertainty in regions of interest and less than 1% difference between results when running multiple simulations with random simulation seeds. |
Study Details:
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Sample size used for the test set and the data provenance:
- The test set used "an existing CT scan of the patient that was of height (1.7m) and weight (77kg) similar to the default Adult Male model in OLINDA (1.7m, 70kg)."
- The data provenance is not explicitly stated as retrospective or prospective, nor is the country of origin. However, the use of "an existing CT scan" suggests it was retrospective. The patient data was used for all three main comparison studies.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- The document describes comparisons against established dosimetry methods (OLINDA/EXM, MIM-Ablation's VSV, and GATE), which serve as the reference for "ground truth" in this context. It does not mention human experts establishing ground truth for the test set, as the evaluation is based on quantitative comparison of calculated doses.
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Adjudication method for the test set:
- Not applicable as the ground truth wasn't based on expert adjudication of diagnostic interpretations, but rather on computational agreement with established dosimetry methods.
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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 MRMC comparative effectiveness study was done. This device is a dose calculation software, not an AI diagnostic assistant for human readers.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Yes, the performance evaluation described (comparison to OLINDA/EXM, VSV, and GATE, along with particle history characterization) is a standalone algorithm-only performance assessment. The "MIM - Monte Carlo Dosimetry" is described as a "standalone software application."
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The type of ground truth used:
- Computational Ground Truth: The ground truth was established by comparing the device's calculations to:
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The sample size for the training set:
- The document does not mention a training set, as this is a physics-based dose calculation software, not a machine learning or AI model that requires a labeled training set in the typical sense. Its development would rely on physical models and algorithms rather than statistical learning from data.
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How the ground truth for the training set was established:
- Not applicable, as there is no specific "training set" mentioned or implied for this type of software.
§ 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).