(91 days)
Viz CTP is an image processing software package to be used by trained professionals, including but not limited to physicians and medical technicians. The software runs on a standard "off-the-shelf" computer or a virtual platform, such as VMware, and can be used to perform image processing, analysis, and communication of computed tomography (CT) perfusion scans of the brain. Data and images are acquired through DICOM-compliant imaging devices.
Viz CTP provides both analysis and communication capabilities for dynamic imaging datasets that are acquired with CT Perfusion imaging protocols. Analysis includes calculation of parameters related to tissue flow (perfusion) and tissue blood volume. Results of image processing which include CT perfusion parameter maps generated from a raw CTP scan are exported in the standard DICOM format and may be viewed on existing radiological imaging viewers.
Viz CTP is a standalone software package that is comprised of several modules including DICOM receiving and sending modules, a study processor, image analysis algorithm, as well as software system components including a DICOM storage database and system health-monitoring. Viz CTP allows for bi-directional communication of data and may be implemented to allow a DICOM-compliant device to send files directly from the imaging modality, through a node on a local network, or from a PACS server. The device is designed to automatically receive, identify, extract, and analyze a CTP study of the head embedded in DICOM image data. The software outputs parametric maps related to tissue blood flow (perfusion) and tissue blood volume that are written back to the source DICOM. Following such analysis, the software automatically sends the results of analysis to a preconfigured destination point. The software allows for repeated use and continuous processing of data and can be deployed on a supportive infrastructure that meets the minimum system requirements.
Viz CTP image analysis includes calculation of the following perfusion related parameters:
- Cerebral Blood Flow (CBF)
- Cerebral Blood Volume (CBV)
- Mean Transit Time (MTT)
- Residue function time-to-peak (TMax)
- Arterial Input Function (AIF)
The primary users of Viz CTP are medical imaging professionals who analyze dynamic CT perfusion studies. The results of image analysis produced by Viz CTP should be viewed through appropriate diagnostic viewers when used in clinical decision making.
Here's a summary of the acceptance criteria and the study that proves the Viz CTP device meets those criteria, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criterion (Performance Goal) | Reported Device Performance |
|---|---|
| Accurate AIF detection | Achieved |
| Accurate soft matter extraction | Achieved |
| Accurate Cerebral Blood Flow (CBF) | Achieved |
| Accurate Cerebral Blood Volume (CBV) | Achieved |
| Accurate Mean Transit Time (MTT) | Achieved |
| Accurate Time to Maximum Residue (TMax) | Achieved |
2. Sample Size Used for the Test Set and Data Provenance
The study used a "commercially available simulated dataset (digital phantom) generated by simulating tracer kinetic theory."
- Sample Size: Not explicitly stated as a number of cases or images.
- Data Provenance: This was a simulated dataset, not derived from real patient scans. It was designed to include a "wide range of clinically relevant values of perfusion parameters as ground truth."
3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications
- Number of Experts: Not applicable. The ground truth was established by the design of the simulated digital phantom itself, which was "generated by simulating tracer kinetic theory" and included "a wide range of clinically relevant values of perfusion parameters as ground truth."
- Qualifications of Experts: Not applicable.
4. Adjudication Method for the Test Set
- Adjudication Method: Not applicable. The ground truth was inherent in the simulated dataset, not determined by expert reviewers.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size
- MRMC Study: No, an MRMC comparative effectiveness study involving human readers was not mentioned. The performance study focused on the algorithm's standalone accuracy against a simulated ground truth.
- Effect Size of Human Readers Improve with AI vs without AI Assistance: 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 Study: Yes, a standalone performance study was done. The document states, "Viz.ai Inc. performed software verification and validation testing of the device and additional performance testing on a commercially available simulated dataset (digital phantom)..." and "Correlations between the output of the Viz CTP device and the ground truth values were calculated, and compared to published correlations between the ground truth and the outputs of 7 other commercially available and academic CTP post-processing software." This evaluates the algorithm's performance directly.
7. The Type of Ground Truth Used
- Type of Ground Truth: The ground truth was based on "commercially available simulated dataset (digital phantom) generated by simulating tracer kinetic theory," which includes "a wide range of clinically relevant values of perfusion parameters as ground truth." This is a simulated, theoretical ground truth.
8. The Sample Size for the Training Set
- Sample Size for Training Set: The document does not specify the sample size or details of any training set used for the algorithm development. It focuses solely on the performance testing.
9. How the Ground Truth for the Training Set Was Established
- Ground Truth for Training Set: Not mentioned in the provided text.
§ 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).