K120472 · Hologic, Inc. · LLZ · Jun 22, 2012 · Radiology
Device Facts
Record ID
K120472
Device Name
QUANTRA
Applicant
Hologic, Inc.
Product Code
LLZ · Radiology
Decision Date
Jun 22, 2012
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.2050
Device Class
Class 2
Attributes
Software as a Medical Device, Real-World Evidence
Real-World Evidence
Submission
Device
Sponsor
RWD Sources
RWE Use Summary
Key Tags
K120472 · Jun 22, 2012
QUANTRA
Hologic, Inc.
Retrospective clinical database of digital mammography images (approx. 1,000 patients); Radiologist-assigned BI-RADS density ratings
The device used a large retrospective clinical database to establish reference mean values for volumetric breast density scores and to validate the software's density categorization against the consensus of 15 radiologists.
Retrospective database; Breast density; BI-RADS; Clinical imaging cohort
Patients undergoing digital mammography; Sample Size: Approximately 1,000 patients
15 radiologists' BI-RADS density ratings
Volumetric breast density (Vbd) and fibroglandular tissue volume (Vfg) scores; BI-RADS-like breast composition categories
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
Volumetric breast density
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Validation study comparing Quantra values with MRI cases and BI-RADS density ratings from 15 radiologists on a large database of cases, and population distribution comparison across Hologic, GE, and Siemens FFDMs
15 (radiologists)
Area breast density
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Validation study comparing Quantra values with hand-drawn dense areas annotated by an expert using Sectra IDS5 workstation, BI-RADS density ratings from 15 radiologists, and population distribution comparison across Hologic, GE, and Siemens FFDMs
15 (radiologists) + 1 (expert)
BI-RADS-like breast composition
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Evaluation based on comparison of Quantra scores with BI-RADS values assigned by 15 radiologists on a large set of digital mammography cases and population distribution comparison across Hologic, GE, and Siemens FFDMs
15 (radiologists)
Indications for Use
Quantra™ is a software application intended for use with images acquired using digital breast X-ray systems. Quantra calculates volumetric breast density as a ratio of fibroglandular tissue and total breast volume estimates; and area breast density as a ratio of fibroglandular tissue area and total breast area estimates. It segregates breast density into BI-RADS-like breast composition categories, which may be useful in the reporting of consistent breast composition values as mandated by certain state regulations. Quantra provides these numerical values for each image, breast, and subject, to aid radiologists in the assessment of breast tissue composition. Quantra produces adjunctive information; it is not an interpretive or diagnostic aid. Quantra runs on a Windows platform.
Device Story
Quantra is a software application for digital mammography systems; it processes digital breast X-ray images to estimate breast tissue composition. The software calculates volumetric breast density (ratio of fibroglandular tissue to total breast volume) and area breast density (ratio of fibroglandular tissue area to total breast area). It categorizes density into BI-RADS-like composition groups and generates Vbd and Vfg scores based on a reference database of approximately 1,000 patients. The device runs on a Windows platform and is intended for use by radiologists as an adjunctive tool; it does not provide diagnostic or interpretive results. By providing standardized numerical values, it assists clinicians in reporting consistent breast composition as required by state regulations. The software does not contact the patient or control life-sustaining equipment.
Clinical Evidence
No clinical trials were performed. Evidence consists of bench testing and validation studies. Volumetric breast density (Vbd) was validated via correlation with MRI cases and comparison to the mode BI-RADS density ratings from 15 radiologists. Area breast density was validated by comparing Quantra values against expert-annotated dense areas on the Sectra IDS5 workstation. Performance was evaluated across a large database of cases from Hologic, GE, and Siemens FFDMs to ensure distribution consistency. Statistical evaluation confirmed consistency between CC/MLO views and left/right breasts.
Technological Characteristics
Software application for Windows platform. Processes digital mammography images (FFDM). Calculates volumetric and area-based breast density metrics and BI-RADS-like composition categories. Developed per ISO 14971 (risk management) and ISO 62304 (software life cycle). No patient contact. Standalone software.
Indications for Use
Indicated for use by radiologists to aid in the assessment of breast tissue composition from digital breast X-ray images. Provides volumetric and area-based breast density measurements and BI-RADS-like composition categories. Not for diagnostic or interpretive use.
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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120472
Hologic, Inc. 35 Crosby Drive, Bedford, MA 01730 USA Main: +1.781.999.7300 Fax: +1.781.280.0669 JUN: 2 2 2012
# B. Administrative Information
B.1 510(k) Summary of Safety & Effectiveness (as required by 21 CFR §807.92c)
## Date Prepared: February 15, 2012 Submitted by:
Hologic, Inc. 35 Crosby Drive Bedford, MA 01730 USA
## Name, Title and Phone Number of Contact:
Catherine A. Williams Director, Regulatory Affairs Phone: (408) 352-0201 FAX: (408) 352-0101 Email: catherine.williams@hologic.com
### Trade Name and Common Name:
| Trade Name: | Quantra™ |
|-------------------|---------------------------------------------|
| Software Version: | 2.0 |
| Common Name: | Picture Archiving and Communications System |
#### Device Classification:
| Regulatory Class: | II |
|-------------------------|------------------|
| Classification Panel: | Radiology |
| Image Processing System | 21 CFR §892.2050 |
| Product Code | 90-LLZ |
### Predicate Devices:
The predicate devices for Quantra software are certain software functions contained in the following devices:
K082483, September 12, 2008 K050196, February 24, 2005 K102556, October 7, 2010 Limited]
Quantra (Volumetric Assessment) [Hologic, Inc.] Sectra IDS5 Workstation [Sectra Imtec AB] Volpara Imaging Software [Matakina Technology
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# Device Description:
Quantra is a software application that estimates breast tissue volume and area density. The estimations are made from images acquired using digital breastray systems.
Quantra has been designed and will be manufactured in accordance with the following standards:
- · ISO 14971 Medical Devices - Application of Risk Management to Medical Devices
- ISO 62304: Medical Device Software - Software Life Cycle Processes
The performance of the software is also tested in accordance with Hologic's SOPs and testing procedures to demonstrate adequate performance.
## Intended Use:
· Quantra™ is a software application intended for use with images acquired using digital breast X-ray systems. Quantra calculates volumetric breast demsity as a minori fibroglandular tissue and total breast volume estimates; and area breast density as of fibroglandular tissue area and total breast area estimates. It segregates breast de into BI-RADS-like breast composition categories, which may be useful in the report of consistent breast composition values as mandated by certain state regul · provides these numerical values for each image "breast" and subject, to ai the assessment of breast tissue composition. Quantra produces adjunctive information is not an interpretive or diagnostic aid. Quantra runs on a Windows platform.
# Technological Characteristics:
Quantra is a software application that processes digital mammography images. The device does not contact the patient, nor does it control any life-sustaining devices.
## Performance/Bench Testing:
The volumetric breast density measures were validated by demonstrating correlation with the Quantra predicate device and with MRI cases of the same patients. The me also were compared to the mode (most common) BI-RADS density rating from 15 radiologists on a large database of cases. Finally, the Vbd values were compared a large population of cases from Hologic (Selenia and Dimensions), GE (Seniographe and similar. 11 - 1 - 1 - 1 - 1 - 1 - 1 - 1
The area breast density measure was validated using a correlation-based assessme compare Quantra values with dense area measurement based on hand-drawn dense areas annotated by an expert using the predicate device Sectra IDS5 workstation. mode (most common) BI-RADS density rating from 15 radiologists on a large database of cases. Finally, the Abd values were compared across. large population of cases from Hologic (Selenia and Dimensions), GE (Senographe and
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Essential), and Siemens (Mammomat Novation) FFDMs to ensure the distributions were similar.
The volumetric breast density (Vbd) and volume of fibroglandular tissue (Vfg) values. were used to create two scores (Vbd-score and Vfg-score), which reflect the number of standard deviations between a subject's V.bd or Vig value and the corresponding mean value of approximately 1,000 patients in a reference database.
The BI-RADS-like breast composition measure (O abd), similar to the density grade measure in the Matakina predicate device, was evaluated based on a comparison of Q abd with BI-RADS values assigned by 15 radiologists on a large set of digital mammography cases. The continuous q. abd score was compared to the mean value of the 15 radiologists on the same large database of cases described above. Finally, the q abd values were compared across a large population of cases from Hologic (Selenia and Dimensions), GE (Senographe and Essential), and Siemens (Mammomat Novation) FFDMs to ensure the distributions were similar.
All Quantra density measures were evaluated statistically between CC and MLO views of the same breast and left and right breasts of the same women, using a substantially large number of images from Hologic (Selenia and Selenia Dimensions), GE (Senographe and Senographe Essential), and Siemens (Mammomat Novation) digital breast X-rav systems).
### General Safety and Effectiveness Concerns:
The device labeling contains instructions for use and any necessary cautions and warnings to provide for safe and effective use of this device. Risk management is ensured via a risk analysis, which is used to identify potential hazards. These potential hazards are, controlled via software development, verification and validation testing.
#### Conclusion:
The 510(k) Premarket Notification for Quantra contains adequate information and data to enable FDA/CDRH to determine substantial equivalence to the predicate devices:
The submission contains the results of a hazard analysis and the "Level of Concern" for potential hazards has been classified as "Moderate".
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Image /page/3/Picture/0 description: The image shows the logo for the Department of Health & Human Services USA. The logo features a stylized eagle with three curved lines representing its wings and body. The words "DEPARTMENT OF HEALTH & HUMAN SERVICES USA" are arranged in a circular pattern around the eagle.
# DEPARTMENT OF HEALTH & HUMAN SERVICES
Public Health Service
Food and Drug Administration · 10903 New Hampshire Avenue Document Control Room - WO66-G609 Silver Spring, MD 20993-0002
JUN 2 2 2012
Ms. Catherine A. Williams Director, Regulatory Affairs Hologic, Inc. 35 Crosby Drive BEDFORD MA 01730
Re: K120472
Trade/Device Name: QuantraTM Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications svstem Regulatory Class: II Product Code: LLZ Dated: May 18, 2012 Received: May 21, 2012
Dear Ms. Williams:
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.
If your device is classified (see above) into class II (Special Controls), it may be subject to such additional controls. Existing major regulations affecting your device can be found in Title 21, Code of Federal Regulations (CFR), Parts 800 to 895. 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 or any I vith all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Parts 801 and 809); medical device reporting (reporting of
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medical device-related adverse events) (21 CFR 803); and good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820). This letter will allow you to begin marketing your device as described in your Section 510(k) premarket while and to finding of substantial equivalence of your device to a legally marketed predicate device results in a classification for your device and thus, permits your device to proceed to the market.
If you desire specific advice for your device on our labeling regulation (21 CFR Parts 801 and 11 July 11 Species and the Office of In Vitro Diagnostic Device Evaluation and Safety at (301) 796-5450. Also, please note the regulation entitled, "Misbranding by reference to premarket s 150. First 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/cdrh/industry/support/index.html.
Sincerely Yours,
Janine M. Morris
Janine M. Morris Acting Director Division of Radiological Devices Office of In Vitro Diagnostic Device Evaluation and Safety Center for Devices and Radiological Health
Enclosure
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# B.2 Indication(s) for Use Statement
510(k) Number (if known): K120472
Device Name:
Quantra™M
### Indications for Use:
Quantra™ is a software application intended for use with images acquired using digital breast X-ray systems. Quantra calculates volumetric breast density as a ratio of fibroglandular tissue and total breast volume estimates; and area breast density as a ratio of fibroglandular tissue area and total breast area estimates. It segregates breast density into BI-RADS-like breast composition categories, which may be useful in the reporting of consistent breast composition values as mandated by certain state regulations. Quantra provides these numerical values for each image, breast, and subject, to aid radiologists in the assessment of breast tissue composition. Quantra produces adjunctive information; it is not an interpretive or diagnostic aid. Quantra runs on a Windows platform.
Prescription Use X (Part 21 CFR§801 Subpart D) Over-The-Counter - Use (21 CFR §807 Subpart C)
(PLEASE DO NOT WRITE BELOW THIS LINE-CONTINUE ON ANOTHER PAGE IF NEEDED)
AND/OR .
Concurrence of CDRH, Office of In Vitro Diagnostic Device Evaluation and Safety (OVD)
Division Sign-
Divisiókf Radiologica: Devices
Office of In Vitro Diagnostic Device Evaluation and Safety.
K120472
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.