(42 days)
Based on Intravascular ultrasound (IVUS) and/or optical coherence tomography (OCT) images CAAS IntraVascular enables quantification of artery and/or stent dimensions.
CAAS IntraVascular is a stand-alone software application intended to run on a PC with a Windows operating system. CAAS IntraVascular is designed for viewing and analyzing DICOM data from intravascular ultrasound (IVUS) and optical coherence tomography (OCT) studies. CAAS Intravascular provides (semi-)automatic detection of vessel and stent structures and quantitative analysis of the dimensions of these structures. CAAS IntraVascular is designed for use in clinical practice to support the physician to diagnose the patient.
The provided document is a 510(k) summary for the CAAS IntraVascular device, which is a software application for viewing and analyzing DICOM data from intravascular ultrasound (IVUS) and optical coherence tomography (OCT) studies.
Here's an analysis of the acceptance criteria and study information based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance:
The document broadly states that "Performance Data Testing includes software verification and validation. The tests were made to evaluate CAAS IntraVascular and yield accuracy and precision results within the predetermined specifications." However, it does not explicitly list specific quantitative acceptance criteria (e.g., specific accuracy thresholds or error margins) or provide detailed numerical performance results for the device against these criteria.
Instead, the conclusion focuses on "Substantial Equivalence" to a predicate device.
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Accuracy and Precision (of measurements and detections) | "Yield accuracy and precision results within the predetermined specifications." |
| Functional Equivalence (to predicate device) | "Substantial equivalent to the predicate device in terms of intended use, indications for use, technological characteristics, measurements and operating environment." |
| No new safety and effectiveness issues (compared to predicate) | "All found differences raise no new safety and effectiveness issues or concerns." |
2. Sample Size Used for the Test Set and Data Provenance:
The document mentions "software verification and validation" and "tests were made to evaluate CAAS IntraVascular," but it does not specify the sample size used for the test set (number of cases, images, or measurements).
Data Provenance: The document does not explicitly state the country of origin of the data or whether the data was retrospective or prospective.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts:
The document does not provide information on the number of experts used to establish ground truth or their qualifications.
4. Adjudication Method for the Test Set:
The document does not provide information on any adjudication methods used for the test set.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done, and the Effect Size:
The document does not indicate that an MRMC comparative effectiveness study was performed. The focus is on demonstrating substantial equivalence to a predicate device, not on measuring human reader improvement with AI assistance.
6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) was done:
The device is described as "a stand-alone software application" with "(semi-)automatic detection" and "quantitative analysis." This implies that the software itself performs these functions, suggesting that its standalone performance was likely evaluated as part of the verification and validation, but specific performance metrics for this standalone functionality are not detailed.
7. The Type of Ground Truth Used:
The document does not explicitly state the type of ground truth used (e.g., expert consensus, pathology, outcomes data). Given the device's function in quantitative analysis of anatomical structures (vessel and stent dimensions from IVUS/OCT images), it's highly probable that some form of "expert-drawn contours" or "manual measurements" by qualified individuals served as the ground truth for evaluating the software's accuracy and precision.
8. The Sample Size for the Training Set:
The document does not provide information on the sample size used for the training set. The descriptions of "(semi-)automatic detection" imply the use of algorithms that would typically require training data, but no specifics are given.
9. How the Ground Truth for the Training Set was Established:
The document does not provide information on how the ground truth for the training set was established.
§ 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).