(16 days)
QLAB Quantification Software is a software application package. It is designed to view and quantify image data acquired on Philips Medical Systems ultrasound products.
OLAB Quantification software is available either as a stand-alone product that can function on a standard.PC, on board a dedicated workstation, or on-board Philips' ultrasound systems. It can be used by trained healthcare professionals for the on-line and off-line review and quantification of ultrasound studies in healthcare facilities/hospitals.
The QLAB Quantification software application package is designed to view and quantify image data acquired on Philips ultrasound products. Cardiac Motion Quantification (CMQ) is a plug-in included in Philips QLAB Quantification software.
The CMO plug-in is an application within OLAB intended to provide cardiac motion quantification. OLAB Quantification software is intended for use in healthcare facilities/hospitals by trained healthcare professionals.
OLAB CMO modifications were implemented to provide clients with improved reproducibility and consistency between users, as well as to provide users with a reduction of workflow steps. The modifications described in this Special 510(k) submission do not alter the intended use of the OLAB Quantification software with the CMO plug-in.
Here's a breakdown of the acceptance criteria and study information for the QLAB CMQ Plug-in Modifications, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria (Modified CMQ vs. Unmodified CMQ) | Reported Device Performance |
|---|---|
| Improved workflow: fewer mouse clicks for typical assessment | Verification and validation testing concluded the modification achieved this. |
| Improved workflow: decreased average time for typical assessment | Verification and validation testing concluded the modification achieved this. |
| Decreased intra-observer variability of assessments | Verification and validation testing concluded the modification achieved this. |
| Decreased inter-observer variability of assessments | Verification and validation testing concluded the modification achieved this. |
| Safe and effective release, no new risks introduced | Verification and validation testing concluded the modification achieved this. |
| Meets all defined reliability requirements and performance claims | Testing demonstrated this. |
2. Sample Size and Data Provenance
The document does not explicitly state the sample size used for the test set or the data provenance (e.g., country of origin of the data, retrospective or prospective). It mentions "Philips verification and validation processes" and "system level tests, performance tests, and safety testing from hazard analysis," but lacks specific details on the datasets used in these tests.
3. Number of Experts and Qualifications
The document does not specify the number of experts used to establish the ground truth for the test set or their qualifications. It states that the device "can be used by trained healthcare professionals," implying expert users, but doesn't detail their involvement in the testing.
4. Adjudication Method
The document does not describe any specific adjudication method (e.g., 2+1, 3+1, none) for establishing ground truth or evaluating the test set.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
The document does not describe a multi-reader multi-case (MRMC) comparative effectiveness study. It focuses on the improvements of the modified CMQ plugin over the unmodified CMQ plugin in terms of workflow and variability, rather than comparing it to human-only performance or quantifying an effect size of human improvement with AI assistance.
6. Standalone (Algorithm Only) Performance
The device itself is a "plug-in" within a larger software suite (QLAB). While it's a "quantification software" that can function "either as a stand-alone product that can function on a standard PC, on board a dedicated workstation, or on-board Philips' ultrasound systems," the performance claims are related to its function within the QLAB environment, and specifically the modifications made to the CMQ plug-in. The provided text doesn't explicitly detail a standalone algorithm-only performance study contrasting its output against a ground truth without human interaction beyond the general claims of decreased intra-observer and inter-observer variability. The "modifications ... were implemented to provide clients with improved reproducibility and consistency between users," which implies human interpretation is still integral, but the device assists this process.
7. Type of Ground Truth
The document explicitly states the intent to "provide clients with improved reproducibility and consistency between users, as well as to provide users with a reduction of workflow steps" and to achieve "Decreased intra-observer variability of assessments; and Decreased inter-observer variability of assessments." This strongly suggests that the ground truth for evaluating these improvements was based on expert consensus or comparative measurements performed by experts, where the goal was to minimize the deviation of measurements between and within experts, facilitated by the software. It does not mention pathology or outcomes data as the primary ground truth for the specific performance claims of this modification.
8. Sample Size for the Training Set
The document does not include any information about the sample size used for a training set. As this is a "Special 510(k) Premarket Notification" for modifications to an already cleared device, it's possible that the core algorithm was trained previously, and this submission focuses on validation of the changes.
9. How Ground Truth for Training Set was Established
Since no training set information is provided, there is no description of how ground truth for a 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).