(260 days)
AccuCTP 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, and can be used to perform image viewing, processing and analysis of brain images. Data and images are acquired through DICOM compliant imaging devices.
AccuCTP provides both viewing and analysis capabilities for functional and dynamic imaging datasets acquired with CT Perfusion (CT-P), which can visualize and analyze dynamic imaging data, showing properties of changes in contrast over time. This functionality includes calculation of parameters related to tissue blood volume.
AccuCTP is a standalone software package that provides visualization and study of changes of tissue perfusion in digital images captured by CT (Computed Tomography). The software provides viewing, quantification, analysis and reporting capabilities, and it allows repeated use and continuous processing of data and can be deployed on a supportive customer's PC that meets the minimum system requirements.
AccuCTP works with the DICOM compliant medical image data. AccuCTP provides tools for performing the following types of analysis:
- volumetry of threshold maps .
- time intensity plots for dynamic time courses .
- . measurement of mismatch between rCBF and Tmax threshold volumes obtained from the same scan.
The provided text, a 510(k) Summary for the AccuCTP device, focuses on demonstrating substantial equivalence to a predicate device (RAPID) rather than providing detailed acceptance criteria and the results of a statistically powered clinical study. However, it does outline performance validation activities.
Here's an analysis of the available information regarding acceptance criteria and performance studies, structured according to your request, with limitations noted due to the nature of the document:
1. Table of Acceptance Criteria and Reported Device Performance
The document states: "Parameter map and Volume results were quantitatively analysed and met the pre-defined pass/fail criteria." However, the specific numerical pre-defined pass/fail criteria are not explicitly stated in this document. The performance is reported in terms of agreement with a "ground truth" (phantom data) and agreement with the predicate device (RAPID CTP).
| Acceptance Criteria (General) | Reported Device Performance (as stated in document) |
|---|---|
| Parameter map results met pre-defined pass/fail criteria | "Parameter map...results were quantitatively analysed and met the pre-defined pass/fail criteria." |
| Volume results met pre-defined pass/fail criteria | "Volume results were quantitatively analysed and met the pre-defined pass/fail criteria." |
| Agreement with ground truth in phantom test | Achieved, "Parameter map and Volume results were quantitatively analysed and met the pre-defined pass/fail criteria." |
| Agreement with predicate device (RAPID CTP) for parameter maps and volume results | A "calculation performance validation was conducted to evaluate the agreement between AccuCTP and RAPID CTP in calculating the parameter maps as well as the volume results... met the pre-defined pass/fail criteria." |
2. Sample Size Used for the Test Set and Data Provenance
- Test Set Sample Size: The document mentions a "group of phantoms" for the phantom test and a "calculation performance validation" using data to compare with RAPID CTP. However, the exact numerical sample size (number of CT perfusion studies or phantoms) used in these validation studies is not specified.
- Data Provenance: The document does not specify the country of origin for the data used in the "validation study" that compared AccuCTP to RAPID CTP. It also does not explicitly state whether the data was retrospective or prospective. The phantom study clearly used synthetic data.
3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications
The document does not mention the use of human experts to establish ground truth for the test sets.
- For the phantom test, the ground truth was inherently known from the design of the phantoms.
- For the "validation study" comparing AccuCTP to RAPID CTP, the ground truth was effectively the output of the predicate device (RAPID CTP), implying a comparison for concordance rather than independent expert adjudication.
4. Adjudication Method for the Test Set
No adjudication method involving human experts is described since the ground truth for the validation was either known from phantoms or based on the predicate device's output.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- Was it done? No, the document does not describe an MRMC study. The validation described focuses on the agreement of AccuCTP's output (parameter maps and volumes) with physical phantoms and with the predicate device's output. There is no mention of human readers or AI assistance in diagnostic tasks.
- Effect Size of Human Improvement: Not applicable, as no MRMC study was conducted.
6. Standalone (Algorithm Only) Performance
Yes, the studies described are standalone performance evaluations of the AccuCTP algorithm. The phantom test directly evaluated the algorithm's accuracy against known physical properties, and the comparison with RAPID CTP assessed the algorithm's concordance with another software's output. The device is described as "a standalone software package."
7. Type of Ground Truth Used
- Phantom Test: The ground truth was known physical properties/measurements derived from the design of the phantoms.
- Validation Study (comparison with RAPID CTP): The "ground truth" for this comparison was effectively the results/output of the predicate device (RAPID CTP). This is a comparison of computational results for substantial equivalence, not a clinical ground truth for diagnostic accuracy (e.g., pathology, clinical outcomes).
8. Sample Size for the Training Set
The document does not specify the sample size of the training set used for developing or training the AccuCTP algorithm. Performance data in this section refers to validation testing, not training data.
9. How Ground Truth for the Training Set Was Established
The document does not provide any information on how the ground truth for the training set (if supervised learning was used) was established, as it doesn't discuss the training phase of the algorithm development.
§ 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).