K132165 · Philips Ultrasound, Inc. · LLZ · Aug 9, 2013 · Radiology
Device Facts
Record ID
K132165
Device Name
QLAB QUANTIFICATION SOFTWARE
Applicant
Philips Ultrasound, Inc.
Product Code
LLZ · Radiology
Decision Date
Aug 9, 2013
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.2050
Device Class
Class 2
Attributes
Software as a Medical Device, 3rd-Party Reviewed
Indications for Use
QLAB Quantification Software is a software application package. It is designed to view and quantify image data acquired on Philips Healthcare ultrasound products.
Device Story
QLAB Quantification software processes ultrasound image data; functions as standalone PC application, workstation-based, or on-board ultrasound system. Modified plug-ins (a2DQ, aCMQ, MVN, Heart Model) provide semi-automated quantification; a2DQ performs semi-automated border detection for cardiac chambers/vessels; aCMQ uses speckle-tracking for myocardial velocity, strain, and displacement; MVN provides task-guided segmentation for mitral valve structures; Heart Model enables one-click 3D volume quantification of cardiac chambers. Healthcare professionals review outputs (measurements, waveforms, bull's eye plots) to assess cardiac function (EF, volumes, wall motion). Modifications focus on workflow efficiency and semi-automation. Output assists clinicians in diagnostic decision-making; benefits include reduced analysis time and standardized quantification of cardiac parameters.
Clinical Evidence
Bench testing only. Verification and validation activities, including requirements review, design review, risk management, and system-level performance testing, confirmed that modified Q-Apps meet reliability and performance requirements relative to predicate devices.
Technological Characteristics
Software-based image processing application. Operates on standard PCs, dedicated workstations, or Philips ultrasound systems. Features include semi-automated border detection, speckle-tracking analysis, and 3D volume segmentation. Connectivity via standard ultrasound data formats. No specific hardware materials or energy sources; software-only modification.
Indications for Use
Indicated for trained healthcare professionals in clinical settings for the review and quantification of ultrasound image data acquired on Philips ultrasound systems.
Regulatory Classification
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.
Special Controls
*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).
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K132165
Special 510(k) Premarket Notification
QLAB Quantification Modifications
# 510(k) Summary
This summary of safety and effectiveness is provided as part of the Premarket Notification in compliance with 21 CFR. Part 807.92.
1 ) Submitter's name, address, telephone number, contact person
Philips Ultrasound, Inc. 3000 Minuteman Road Andover, MA 01810-6302 Penny Greco, Regulatory Affairs Specialist Tel: (978) 659-4615 Fax (978) 975-7324 E-mail: penny.greco@philips.com
AUG
09 2013
Date prepared: June 12, 2013
2) Name of the device, including the trade or proprietary name if applicable, the common or usual name, and the classification name, if known:
Common/Usual Name: Picture Archiving and Communications Systems Workstation
QLAB Quantification Software Proprietary Name: Classification Name: CFR 892.2050, system, image processing, radiological, 90 LLZ, Class II
# 3) Substantially Equivalent Devices
Philips Ultrasound believes that the modified QLAB a2DQ, aCMQ, MVN, and Heart Model Q-Apps are substantially equivalent to the previously cleared iU22 with 2DO (K042540), QLAB with MVQ (K070792), QLAB CMQ (K120525), and QLAB Heart Model (130159).
# 4) Device Description
QLAB 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. The four modified plug-ins, a2DO, aCMQ , MVN, and Heart Model are applications within Philips QLAB Quantification software.
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# Automated 2D Quantification (a2DQ)
The 2DQ O-App for the display of 2D ultrasound images was originally submitted with Philips iU22 Ultrasound system (K042540). 2DQ has been renamed a2DQ. It computes areas, volumes and advanced parameters for LV systolic and diastolic function including: LV Ejection Fraction (EF), Peak Ejection Rate (PER), Peak Rapid Filling Rate (PRFR) and Atrial Filling Fraction (AFF). It also computes End Systolic Volume (ESV) and End Diastolic Volume (EDV). The Color Kinesis (CK) tool provides color-coded visualization of global and regional wall motion. a2DQ has been modified to improve workflows including semi-automated border detection for cardiac chambers and vessel cavities.
# Automated Cardiac Motion Quantification (aCMQ)
CMQ modifications were last addressed in QLAB 510(k) K120525. CMQ has been renamed aCMQ aCMQ provides an angle-independent analysis of regional myocardialtissue velocity, displacement, strain, and strain rate, using the speckle-tracking technology. It generates measurements of the global and regional functions and reports them in a table, a 17-segment bull's eye, and a variety of waveform displays. It additionally computes LV Ejection Fraction (EF), End Systolic Volume (ESV) and End Diastolic Volume (EDV). aCMQ has been modified to automatically draw a region of interest based on the selected anatomical view, (user can edit the ROI if desired).
## Mitral Valve Navigator (MVN)
The MVQ plug-in was submitted in QLAB 510(k) K070792. The application, renamed Mitral Valve Navigator (MVN), was originally designed as a manual segmentation interface that would allow for detailed segmentation of the mitral valve annulus, leaflets, and papillary muscle. However, as segmentation using the interface is entirely manual, the approximate time to complete the segmentation ranges from 5-15 minutes, depending on the user's familiarity with the interface, the quality of the image, and the user's knowledge of the mitral valve and experience in interpreting 3D echo images. The modification to MVN (MVQ) updates the application with improved task guidance and semi-automation for greater efficiency and ease of use. The modification focused primarily on decreasing the required workflow time by identifying bottlenecks in the workflow.
## Heart Model Quantification (HM)
The Heart Model O-App (K130159) provides one-click visualization of all four cardiac chambers, and quantifies the left ventricle (LV) and left atrium (LA) using a 3D Volume image from an apical four-chamber view. It provides the LV and LA volume, stroke volume, and LV ejection fraction (EF) at end-systole and end-diastole (ED) for adult hearts. It easily delivers the routine 2D views from the 3D volume. Measurements are closely correlated to cardiac MR and are exported to the report. The modified Heart Model application allows users to override border placement. The user may edit the border by clicking and dragging the border to the desired location. Numeric quantification will be updated based upon user placement of borders.
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#### Special 510(k) Premarket Notification
QLAB Quantification Modifications
The OLAB modifications described in this Special 510(k) submission do not alter the intended use of the QLAB Quantification software with the modified a2DQ, aCMQ, MVN, and Heart Model Q-Apps.
## 5) Indications for Use
QLAB Quantification software is a software application package. It is designed to view and quantify image data acquired on Philips Healthcare ultrasound products.
# 6) Technological characteristics
The QLAB Quantification software with the modified Q-Apps has the same technological characteristics as the legally marketed device.
## 7) Non-clinical performance data
No performance standards for PACS systems or components have been issued under the authority of Section 514. The a2DQ, aCMQ, MVN, and Heart Model modifications were tested in accordance with Philips verification and validation processes. Verification and validation data support the modified QLAB software for the a2DQ, aCMQ, MVN, and Heart Model software relative to the unmodified QLAB software.
Design Control activities to assure the safe and effective performance of the modified plug-ins included, but were not limited to:
- Requirements Review .
- Design Review .
- Risk Management .
- Verification and Validation Testing .
Verification and Validation testing concluded that the modified QLAB O-Apps are safe and effective and introduced no new risks.
# 8) General Safety and Effectiveness Concerns
The device labeling contains operating instructions for the safe and effective use of the QLAB Quantification software with the modified Q-Apps.
## 9) Conclusions
Verification and Validation activities required to establish the performance, functionality, and reliability characteristics of the modified QLAB Q-Apps with respect to the predicate were performed. Testing involved system level tests, performance tests, and safety testing from hazard analysis. Testing performed demonstrated that the QLAB Quantification software with modified Q-Apps meets all defined reliability requirements and performance claims.
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Image /page/3/Picture/12 description: The image shows a partial view of a logo. The logo includes the words "HEALTH & HUMAN SERVICES USA" arranged in a circular pattern. To the right of the text is a stylized graphic consisting of three curved lines.
Public Health Service
Food and Onig Administration 10903 New Hampshire Avenue Document Comrol Center - WO66-G609 Silver Spring, MD 20993-002
August 9, 2013
Philips Ultrasound, Inc. % Mr. Mark Job Responsible Third Party Official 1394 25" Street NW BUFFALO MN 55313
Re: K132165
> Trade/Device Name: QLAB Quantification Software Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: LLZ Dated: July 10, 2013 Received: July 12. 2013
Dear Mr. Job:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food: Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market,the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA). it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations. Title 21. Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting (reporting of medical device-related adverse events) (21 CFR 803); good manufacturing practice requirements as set
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Page 2 - Mr. Job
forth in the quality systems (QS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please contact the Division of Small Manufacturers, International and Consumer Assistance at its tollfree number (800) 638-2041 or (301) 796-7100 or at its Internet address http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm. Also. please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm for the CDRH's Office of Surveillance and Biometrics/Division of Postmarket Surveillance.
You may obtain other general information on your responsibilities under the Act from the Division of Small Manufacturers, International and Consumer Assistance at its toll-free number (800) 638 2041 or (301) 796-7100 or at its Internet address http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm.
Sincerely yours,
Sm.h.7)
for
Janine M. Morris Director, Division of Radiological Health Office of In Vitro Diagnostics and Radiological Health Center for Devices and Radiological Health
Enclosure
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# Indications for Use
510(k) Number (if known): K132165
QLAB Quantification Software Device Name:
Indications for Use:
QLAB Quantification Software is a software application package. It is designed to view QCAD Quantify image data acquired on Philips Healthcare ultrasound products.
Prescription Use X (Part 2) CFR 801 Subpart D) AND/OR
Over-The-Counter Use (21 CFR 807 Subpart C)
(PLEASE DO NOT WRITE BELOW THIS LINE-CONTINUE ON ANOTHER PAGE IF NEEDED)
Concurrence of CDRH, Office of In Vitro Diagnostics and Radiological Health (OIR)
(Division Sign Off) Division of Radiological Health Office of In Vitro Diagnostic and Rediological Health
510(k)_K132165
Page 1 of 1
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.