(45 days)
NovaPACS is intended for the viewing, archiving, analysis, annotation, distribution, editing, fusion, and processing of digital medical images and data acquired from diagnostic imaging devices and all DICOM devices, including mammography.
NovaPACS is intended for use by trained healthcare professionals, including radiologists, physicians, technologists, clinicians, and nurses. NovaPACS allows the end user to display, manipulate, archive, and evaluate images.
Mobile devices are not intended to replace a full workstation and should be used only when there is no access to a workstation. They are not to be used for mammography or fMRI. Mobile devices are used for diagnosis of medical images from different modalities including CT, MR, US, CR/DX, NM, PT, and XA. For a list of compatible mobile platforms see NovaPACS Diagnostic Viewer User Manual.
While NovaPACS full workstation provides tools to assist the healthcare professional determine diagnostic viability, it is the user's responsibility to ensure quality, display contrast, ambient light conditions, and to confirm image compression ratios are consistent with the generally accepted standards of the clinical application.
NovaPACS is intended for providing analysis and visualization of functional MRI data of the human brain, presenting derived properties and parameters in a clinically useful context.
NovaPACS is a picture archiving and communication system software that retrieves, archives, and displays images and data from all common modalities. NovaPACS uses a variety of workstations, including a Technologist Workstation, Enterprise Radiologist Workstation, Cardio Viewer and Workstation, NovaMG Workstation, and NovaWeb Web Viewer.
The NovaPACS software makes images and data available in digital format from all common modalities. The images are viewed on a computer monitor or portable device. NovaPACS tools/features include the following: window, level, zoom, pan, digital subtraction, ejection, cross localization, note-taking ability, voice dictation, and other similar tools. It includes the capability to measure distance and image intensity values, such as standardized uptake value. NovaPACS displays measurement lines, annotations, regions of interest, and fusion blending control functionality. Advanced features include 3D image rendering, virtual fly-through, time domain imaging, vessel analysis, and blood oxygen level dependent (BOLD) fMRI.
BOLD fMRI analysis is used to highlight small susceptibility changes in the human brain in areas with altered bloodflow resulting from neuronal stimulation. The Functional Processing Software includes features such as scalp stripping, 3D motion correction, smoothing, coregistration, normalize images to MNI templates, and warping.
Images and data are stored on a digital archive with multiple redundances; images and data are available on-site and off-site. Novarad provides all software, including third party software (i.e. Windows® OS). NovaPACS software resides on third party hardware, which may vary depending on the client's PACS needs. All hardware is connected to the radiology department local area network.
NovaPACS integrates with NovaRIS and may integrate with any other third party RIS software that has HL7 interface capabilities.
NovaPACS integrates with Novarad Mobile Rad application and web viewers to display data on 3rd party mobile platforms. Mobile devices are not intended to replace full workstation and should be used only when there is no access to a workstation. They are not to be used for mammography or fMRI.
The provided text describes NovaPACS, a picture archiving and communication system (PACS) software, and its substantial equivalence to predicate devices. However, the document does not contain a detailed study with specific acceptance criteria and reported device performance in the format requested. It mentions performance testing for the fMRI software features but lacks quantitative data for a table.
Here's a breakdown of the information that can be extracted, and where there are gaps:
1. Table of Acceptance Criteria and Reported Device Performance
This information is not provided in the document in a quantifiable manner that allows for a table comparing acceptance criteria against specific performance metrics (e.g., sensitivity, specificity, accuracy, or other benchmarked values). The document states:
- "Nineteen test cases were run on the NovaPACS to fulfill the fMRI requirements. All 19 test cases passed."
- "NovaPACS software passes all performance requirements and meets all specifications prior to release, including:
- All requirements in the iteration have a test case and the test case has run and passed.
- All Acceptance tests have passed
- All Current tests have passed
- All high-impact bugs have been corrected and verified by Quality Assurance
- Any unresolved anomalies have been assessed in a risk meeting, and it has been found that they do not pose a safety risk to the end user (or their patients) and do not substantially affect the performance of NovaPACS software."
These are general statements about successful internal testing and meeting requirements, but they do not disclose the specific "acceptance criteria" (e.g., a specific numerical threshold for an imaging performance metric) or the "reported device performance" against those criteria.
2. Sample size used for the test set and the data provenance
- Sample size for test set: The document mentions "Nineteen test cases were run on the NovaPACS to fulfill the fMRI requirements." It does not specify the number of cases (e.g., patient studies or images) within these test cases, nor does it detail the specific characteristics or provenance of the data used in these tests.
- 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
This information is not provided. The document does not mention the involvement of experts for establishing ground truth during the performance testing.
4. Adjudication method for the test set
This information is not provided.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, and the effect size of how much human readers improve with AI vs without AI assistance
- MRMC study: No, an MRMC comparative effectiveness study was not done. The document explicitly states: "There are no clinical tests to compare NovaPACS and predicate devices, as they are software products that send and store images and information."
- Effect size of human reader improvement: Not applicable, as no MRMC study was performed.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Standalone performance: The testing described focuses on the functionality and safety of the NovaPACS fMRI software features ("Nineteen test cases were run on the NovaPACS to fulfill the fMRI requirements. All 19 test cases passed."). This implies standalone testing of the algorithm's performance against predefined requirements, as no human-in-the-loop study is mentioned. However, specific metrics of this standalone performance are not shared beyond "all passed."
7. The type of ground truth used
The document does not specify the type of ground truth used for performance testing (e.g., expert consensus, pathology, outcomes data). It broadly refers to "fMRI requirements," suggesting that the tests validated the software's ability to correctly process and display fMRI data according to established functional MRI analysis methodologies, rather than a diagnostic ground truth.
8. The sample size for the training set
This information is not provided. The document describes NovaPACS as "a picture archiving and communication system software," and its fMRI analysis component. It does not explicitly state that the fMRI feature relies on machine learning or AI models that would require a "training set" in the conventional sense. The focus appears to be on general software functionality and adherence to fMRI processing standards.
9. How the ground truth for the training set was established
This information is not provided, as a training set is not explicitly mentioned or implied for an AI/ML model.
§ 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).