(72 days)
MIM 4.1 (SEASTAR) software is intended for trained medical professionals including, but not limited to, radiologists, oncologists, physicians, medical technologists, dosimetrists and physicists.
MIM 4.1 (SEASTAR) is a medical image and information management system that is intended to receive, transmit, store, retrieve, display, print and process digital medical images, as well as create, display and print reports from those images. The medical modalities of these medical imaging systems include, but are not limited to, CT, MRI, CR, DX, MG, US, SPECT, PET and XA as supported by ACR/NEMA DICOM 3.0.
MIM 4.1 (SEASTAR) 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 ACR/NEMA DICOM 3.0. MIM 4.1 (SEASTAR) 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
MIM 4.1 (SEASTAR) is a software package designed for use in diagnostic imaging. It is a stand-alone software package which operates on Windows 2000/XP. Its intended function and use is to provide medical professionals with the means to display, register and fuse medical images from multiple modalities including DICOM PET, ECAT PET, SPECT, CT and MRI. Additionally, it evaluates cardiac left ventricular function and perfusion including left ventricular end-diastolic volume, end-systolic volume, ejection fraction, volumetric curve, Region of Interest (ROI) contouring, and quantitative/statistical analysis of PET/SPECT brain scans through nonlinear registration to template space.
MIM 4.1 (SEASTAR) aids the efficiency of medical professionals in the creation of contours defining, but not limited to, normal and tumor tissues. The software automatically generates contours using a deformable registration technique which registers pre-contoured patients to target patients. Registrations are either between a serial pair of intra-patient volumes or between a pre-existing atlas of contoured patients and a patient volume. This process facilitates contour creation or re-contouring for adaptive therapy.
MIM 4.1 (SEASTAR) additionally functions as a medical image and information management system intended to receive, transmit, store, retrieve, display, print and process digital medical images, as well as create, display and print reports from those images. The system has the ability to send data to DICOM-ready devices for image storage, retrieval and transmission.
The provided document, K071964, describes the MIM 4.1 (SEASTAR) medical imaging software. However, it does not contain specific details regarding acceptance criteria for its performance or a detailed study proving it meets such criteria. The document is a 510(k) summary, which focuses on demonstrating substantial equivalence to predicate devices rather than providing extensive performance study results.
The document states: "MIMvista has conducted performance and functional testing on the MIM 4.1 (SEASTAR) software. In all cases, the software passed its performance requirements and met specifications." This is a high-level statement without specific metrics or details of the study.
Therefore, many of the requested details cannot be extracted from this document.
Here's an attempt to answer the questions based only on the provided text, indicating where information is not available:
Acceptance Criteria and Device Performance Study
1. A table of acceptance criteria and the reported device performance
| Feature/Metric | Acceptance Criteria | Reported Device Performance |
|---|---|---|
| Overall Performance | Not specified | "Passed its performance requirements and met specifications." |
| Functional Testing | Not specified | "Passed its performance requirements and met specifications." |
| Specific quantitative metrics | Not specified | Not specified |
Note: The document broadly states that the software "passed its performance requirements and met specifications," but it does not define what those requirements or specifications were, nor does it provide any quantitative performance data (e.g., accuracy, precision, speed, etc.) for any specific feature.
2. Sample size used for the test set and the data provenance
- Sample Size: Not specified.
- Data Provenance: Not specified (e.g., country of origin, retrospective or prospective).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
Not specified. The document does not mention the use of experts for establishing ground truth in any performance study.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not specified.
5. 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
- MRMC Study: Not mentioned as performed.
- Effect Size: Not applicable, as no MRMC study or AI assistance comparison is described.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
The device is software intended for use by "trained medical professionals." While it performs automated tasks (e.g., image registration, contour generation, quantitative analysis), the document describes it as a "tool to aid in evaluation and information management," implying human oversight and interaction. A standalone performance study for "algorithm only" is not explicitly described with specific results or metrics.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
Not specified.
8. The sample size for the training set
Not specified. The document does not explicitly mention a "training set" in the context of machine learning. It describes a "deformable registration technique which registers pre-contoured patients to target patients" and "between a pre-existing atlas of contoured patients and a patient volume," implying the use of pre-existing data, but details about the size or nature of this data are not provided.
9. How the ground truth for the training set was established
Not specified.
§ 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).