3D brain MR images collected from one domestic institution.
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—
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Indications for Use
Veuron-Brain-pAb3 is software for the registration, fusion, display, and analysis of medical images from multiple modalities including MRI and PET. The software aids clinicians in the assessment and quantification of pathologies from PET Amyloid scans of the human brain. It enables anatomic analysis and visualization of amyloid protein concentration through the calculation of standard uptake volume ratio (SUVR) within target regions of interest and comparison to those within the reference regions. The software is deployed via medical imaging workplaces and is organized as a series of workflows which are specific to use with radio-tracer and disease combinations.
Device Story
Standalone software for quantitative analysis of PET amyloid brain scans; inputs include MRI and PET images (DICOM/NIfTI). Device performs image registration, fusion, and automatic calculation of Standardized Uptake Value Ratio (SUVR) using a Convolutional Neural Network (CNN) for brain volume segmentation. Users select specific beta-amyloid tracers (18F-Flutemetamol, 18F-Florbetapir, 18F-Florbetaben) to identify appropriate reference regions. Output includes visualized amyloid concentration maps, SUVR values, and reports (PNG/CSV) for clinical review. Used in hospital settings by medical professionals to support dementia diagnosis. Device includes a patient worklist for workflow management. Clinical benefit derived from accurate, standardized quantification of amyloid protein concentration to assist in diagnostic decision-making.
Clinical Evidence
No clinical data. Bench testing only. Software verification and validation confirmed that new functions (worklist, tracer selection) perform as intended and meet all system requirements.
Technological Characteristics
Standalone software package; operates on off-the-shelf hardware. Connectivity via network or USB. Standards: ISO 14971, IEC 62304, IEC 62366. Segmentation uses a Convolutional Neural Network (CNN) trained on 3D brain MR images. Compatible with DICOM and NIfTI formats.
Indications for Use
Indicated for clinicians to assess and quantify pathologies from PET Amyloid brain scans in patients undergoing dementia evaluation.
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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Image /page/0/Picture/0 description: The image contains the logos of the Department of Health & Human Services and the Food and Drug Administration (FDA). The Department of Health & Human Services logo is on the left, and the FDA logo is on the right. The FDA logo includes the agency's name, "U.S. Food & Drug Administration," in blue text.
October 13, 2023
Heuron Co., Ltd. % John J. Smith, M.D., J.D. Partner Hogan Lovells US LLP Columbia Square 555 Thirteenth Street NW Washington, District of Columbia 20004
Re: K231642
Trade/Device Name: Veuron-Brain-pAb3 Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: LLZ Dated: September 13, 2023 Received: September 13, 2023
Dear John Smith:
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 (the 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. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database available at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. 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.
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Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30. Design controls; 21 CFR 820.90. Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
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 of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
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For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely,
D. Rayfield
Daniel M. Krainak, Ph.D. Assistant Director DHT8C: Division of Radiological Imaging and Radiation Therapy Devices OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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# Indications for Use
510(k) Number (if known) K231642
Device Name Veuron-Brain-pAb3
Indications for Use (Describe)
Veuron-Brain-pAb3 is software for the registration, fusion, display, and analysis of medical images from multiple modalities including MRI and PET. The software aids clinicians in the assessment and quantification of pathologies from PET Amyloid scans of the human brain. It enables anatomic analysis and visualization of amyloid protein concentration through the calculation of standard uptake volume ratio (SUVR) within target reqions of interest and comparison to those within the reference regions. The software is deployed via medical imaging workplaces and is organized as a series of workflows which are specific to use with radio-tracer and disease combinations.
| Type of Use (Select one or both, as applicable) |
|-------------------------------------------------------------------------------------|
| <span style="font-size:100%;">☒</span> Prescription Use (Part 21 CFR 801 Subpart D) |
— Over-The-Counter Use (21 CFR 801 Subpart C)
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## 510(k) SUMMARY Heuron Co., Ltd.'s Veuron-Brain-pAb3
Submitter Information Company Name: Heuron Co., Ltd. Address:10F, C, 150, Yeongdeungpo-ro, Yeongdeungpo-gu, Seoul, 07292, Republic of Korea
Contact Person: John J. Smith, M.D., J.D. Phone: +1 202 637 3638 Facsimile: +1 202 637 5910 Date Prepared: September 5, 2023
Name of Device: Veuron-Brain-pAb3 Common or Usual Name: Medical Imaging Software Classification Name: System, Image Processing, Radiological Regulatory Class: 21 CFR 892.2050 Product Code: LLZ
## Predicate Device
Manufacturer name: Heuron Co., Ltd. Device's trade name: Veuron-Brain-pAb2 510(K) number: K213801 Regulatory Class: 21 CFR 892.2050 Product Code: LLZ
#### Device Description
The Veuron-Brain-pAb3 is a standalone software for quantitative analysis of the PET amyloid by automatically calculating the "Standardized Uptake Value Ratio (SUVR)". The calculated result is only used as a reference to support the accuracy of the medical professional's diagnosis of dementia in patients. It also helps with accurate visual interpretation through visualization functions. Various PET amyloid images can be processed by using diverse options provided for users to choose in the image process.
#### Intended Use / Indications for Use
The Veuron-Brain-pAb3 is a software for the registration, display and analysis of medical images from multiple modalities including MRI and PET. The software aids clinicians in the assessment and quantification of pathologies from PET amyloid scans of the human brain. It enables automatic analysis and visualization of amyloid concentration through the calculation of standard uptake value ratio (SUVR) within target regions of interest and comparison to those within the reference regions. The software is deployed via medical imaging workplace and is organized as a series of workflows which are specific to use with radio tracer and disease combinations.
#### Summary of Technological Characteristics
Image load and SUVR calculation is the technological principle for both the subject and predicate devices. Both devices load the MR and PET images, and calculate SUVR for the brain. At a high level, the subject and predicate devices are based on the following same technological elements:
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- Image load ●
- Overlay .
- SUVR calculation ●
- Report .
The following technological differences exist between the subject and predicate devices:
- . Addition of a worklist. Veuron-Brain-pAb3 includes a worklist showing the user of the list of patients.
- . Addition of a tracer option. With Veuron-Brain-pAb3, users can select the tracer for beta amyloid. By providing an option (reference region) for tracer, helps users identify appropriate brain regions for analysis.
| | Subject device | Predicate device (K213801) |
|----------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Device name | Veuron-Brain-pAb3 | Veuron-Brain-pAb2 |
| Manufacturer | Heuron Co., Ltd. | Heuron Co., Ltd. |
| Product code | LLZ | LLZ |
| Indications for use | The Veuron-Brain-pAb3 is software for<br>the registration, fusion, display, and<br>analysis of medical images from multiple<br>modalities including MRI and PET. The<br>software aids clinicians in the<br>assessment and quantification of<br>pathologies from PET Amyloid scans of<br>the human brain. It enables anatomic<br>analysis and visualization of amyloid<br>protein concentration through the<br>calculation of standard uptake volume<br>ratio (SUVR) within target regions of<br>interest and comparison to those within<br>the reference regions. The software is<br>deployed via medical imaging<br>workplaces and is organized as a series<br>of workflows which are specific to use<br>with radio-tracer and disease<br>combinations. | The Veuron-Brain-pAb2 is software<br>for the registration, fusion, display,<br>and analysis of medical images from<br>multiple modalities including MRI<br>and PET. The software aids<br>clinicians in the assessment and<br>quantification of pathologies from<br>PET Amyloid scans of the human<br>brain. It enables automatic analysis<br>and visualization of amyloid protein<br>concentration through the calculation<br>of standard uptake volume ratio<br>(SUVR) within target regions of<br>interest and comparison to those<br>within the reference regions. The<br>software is deployed via medical<br>imaging workplaces and is organized<br>as a series of workflows which are<br>specific to use with radiotracer and<br>disease combinations. |
| Target anatomical site | Brain | Brain |
| Where used | Hospital | Hospital |
| Design features | Import DICOM data<br>Perform automatic post-processing<br>Provide the user confirmation<br>Export the resulting data through a<br>network or USB | Import DICOM data.<br>Perform automatic post-processing.<br>Provide the user confirmation<br>Export the resulting data through a<br>network or USB |
| Physical characteristics | Software package | Software package |
| | Subject device | Predicate device (K213801) |
| | Operates on off-the-shelf hardware<br>(multiple vendors) | Operates on off-the-shelf hardware<br>(multiple vendors) |
| Operating system | Server: Linux (Ubuntu 18.04 LTS or<br>higher)<br>Client: Windows 10 or higher | Server: Ubuntu 16.04 LTS or higher<br>Client: Windows 10, 64-bit |
| Standards | ISO 14971<br>IEC 62304<br>IEC 62366 | ISO 14971<br>IEC 62304<br>IEC 62366 |
| Software verification and validation | Tested in accordance with verification<br>and validation process and planning. The<br>testing results support that all the system<br>requirements have met their acceptance<br>criteria and are adequate for its intended<br>use. | Tested in accordance with<br>verification and validation processes<br>and planning. The testing results<br>support that all the system<br>requirements have met their<br>acceptance criteria and are<br>adequate for its intended use. |
| Compatible input data format and<br>modality | DICOM & NIfTI<br>PET, MRI | DICOM & NIfTI<br>PET, MRI |
| Input patient data | Manual through keyboard/mouse | Manual through keyboard/mouse |
| Output patient data | Picture: PNG<br>Report: PNG, csv | Picture: PNG<br>Report: csv |
| Study list functionality | Search<br>Importing<br>Exporting | Search<br>Importing<br>Exporting |
| Worklist | Yes | No |
| | Yes, can select the tracer for beta amyloid | No, cannot select the tracer for beta<br>amyloid |
| Tracer option | Tracer list<br>• 18F-Flutemetamol (FMM)<br>• 18F-Florbetapir (FBP)<br>• 18F-Florbetaben (FBB) | |
| Segmentation Algorithm | • Calculate the volume by using a<br>Convolutional Neural Network<br>(CNN) model.<br>• CNN model has trained 3D brain MR<br>images were collected from one<br>domestic institution | • Calculate the volume by using a<br>Convolutional Neural Network<br>(CNN) model.<br>• CNN model has trained 3D<br>brain MR images were collected<br>from one domestic institution. |
A table comparing the key features of the subject and predicate devices is provided below.
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## Non-Clinical Performance Testing
Software verification and validation was performed to demonstrate the new functions perform as intended. No clinical testing was conducted.
#### Conclusions
The Veuron-Brain-pAb3 is as safe and effective as the Veuron-Brain-pAb2. The Veuron-Brain-pAb3 has the same intended uses and indications, it has similar technological characteristics, and principles of operation as its predicate device. In addition, the minor technological differences between the Veuron-Brain-pAb3 and its predicate devices raise no new issues of safety or effectiveness.
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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.