(32 days)
The Q LAB Quantification software is a Windows 2000/Windows XP software application package. It is designed to view and quantify image data acquired on Philips Medical Systems ultrasound products.
The Q LAB software provides a means of opening and displaying image files, creating AVI and BMP files from the image data displayed by the software. The Strain Rate quantification plug-in module is designed to operate within the QLAB software by creating a "line of interest" (called "M-Line") that is overlaid on the image data displayed by the software. The plug-in analyzes the content of the image data contained within the M-Line figure, presenting the velocity, strain-rate and strain data in XY graphic and virtual M-Mode format. The software provides a means of exporting the data generated by the plugin module in a form accessible to the end user.
The provided 510(k) summary for K023877, "Q LAB Quantification Software with Strain Rate Quantification Plug-in," describes a Picture Archiving and Communications Systems (PACS) workstation software that includes a plug-in for strain rate quantification from ultrasound image data. However, the document does not contain specific acceptance criteria, comprehensive performance studies with detailed results, or the other requested information for a device that relies on clinical performance metrics.
The document mainly focuses on:
- Device Description: How the software functions – displaying images, creating AVI/BMP files, and the strain rate plug-in creating an "M-Line" to analyze image data for velocity, strain-rate, and strain, then presenting this data graphically and in virtual M-Mode.
- Safety and Effectiveness: Stating that the software follows documented processes for design, verification, and validation, and that a risk assessment was completed.
- Substantial Equivalence: Claiming substantial equivalence to GE's Strain-Rate software.
- Regulatory Compliance: Citing compliance with voluntary standards (MSDN, JPEG) and United States and international standards for image display and quantification.
Therefore, based solely on the provided text, I cannot complete a table of acceptance criteria and reported device performance, nor can I provide information regarding sample sizes, ground truth establishment, expert qualifications, adjudication methods, or MRMC studies because this information is not present in the given document.
This device appears to be cleared based on its equivalence to existing PACS systems and similar quantification software, focusing on its technical function as a display and quantification tool rather than a diagnostic aid with specific clinical performance targets (like sensitivity/specificity for disease detection). The FDA clearance letter also confirms that it was reviewed for substantial equivalence to legally marketed predicate devices, not requiring rigorous clinical performance claims or studies as would be typical for a device making diagnostic claims.
Summary of what can be extracted from the document related to performance and validation (though it doesn't meet all your requested criteria):
- No specific acceptance criteria or quantitative performance results are provided in the document.
- No detailed study results or data are presented to "prove" the device meets acceptance criteria. The document states "Software development for the Q LAB software follows documented processes for software design, verification and validation testing," indicating internal testing, but no public-facing details of these tests are provided.
Here’s a table reflecting the available (or explicitly missing) information:
| Information Category | Details from Document (K023877) |
|---|---|
| 1. Acceptance Criteria & Reported Device Performance | Acceptance Criteria: Not explicitly stated in the document. The document mentions compliance with "voluntary standards" (MSDN, JPEG) and "United States and international standards for the display and quantification of images." It also states the software "is designed and manufactured to meet United States and international standards for the display and quantification of images acquired on Phillips Ultrasound devices." |
| Reported Device Performance: No quantitative performance metrics (e.g., accuracy, precision, sensitivity, specificity for quantification results) are reported in the summary. The device's function is described: creating a "line of interest" (M-Line) on image data, analyzing content within the M-Line, and presenting velocity, strain-rate, and strain data in XY graphic and virtual M-Mode format. | |
| 2. Sample Size & Data Provenance (Test Set) | Not provided. The document implies internal "verification and validation testing" but does not detail any specific test sets, their sizes, or data provenance. |
| 3. Number & Qualifications of Experts (Ground Truth) | Not applicable/Not provided. Clinical performance for a diagnostic claim is not made. Ground truth establishment by experts for a test set is not described. |
| 4. Adjudication Method (Test Set) | Not applicable/Not provided. |
| 5. MRMC Comparative Effectiveness Study | No MRMC study is mentioned. The device is a quantification tool, not a diagnostic aid where human reader improvement with AI assistance would typically be measured. The substantial equivalence claim is made against GE's Strain-Rate software, implying functional equivalence rather than enhanced human performance. |
| 6. Standalone Performance Study | No standalone (algorithm-only) performance study results are provided in this summary. The device is software designed to operate within a PACS workstation for image display and quantification. Its performance would ideally be measured by the accuracy of its quantification against a reference, but these details are not supplied. |
| 7. Type of Ground Truth Used | Not applicable/Not provided within the scope of this summary. For quantification software, ground truth for performance assessment would typically involve comparing the software's measurements (velocity, strain-rate, strain) to a gold standard obtained through alternative, highly accurate methods or expert manual measurements on validated datasets. Such details are absent. |
| 8. Sample Size for Training Set | Not provided. As this is an older submission (2002) and likely a rule-based or conventional image processing algorithm rather than a deep learning AI, the concept of a "training set" in the modern AI sense might not be directly applicable, or its size not typically disclosed for such devices at the time. |
| 9. How Ground Truth for Training Set was Established | Not applicable/Not provided. If internal validation involved comparing algorithm outputs to known values (e.g., from meticulously annotated images or physical phantoms), that methodology is not described here. |
§ 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).