Materialise Mimics Enlight is intended for use as a software interface and image segmentation system for the transfer of DICOM imaging information from a medical scanner to an output file. It is also intended as a software to aid interpreting DICOM compliant images for structural heart and vascular treatment options. For this purpose. Materialise Mimics Enlight provides additional visualisation and measurement tools to enable the user to screen and plan the procedure. The Materialise Mimics Enlight output file can be used for the fabrication of physical replicas of the using traditional additive manufacturing methods. The physical replica can be used for diagnostic purposes in the field of cardiovascular applications. Materialise Mimics Enlight should be used in conjunction with other diagnostic tools and expert clinical judgement.
Device Story
Software interface for structural heart/vascular procedure planning; imports DICOM images from medical scanners. Workflow-based approach: 1) Analyze anatomy; 2) Plan device; 3) Plan delivery; 4) Output. Performs 3D reconstruction of anatomy from 2D images; provides visualization/measurement tools. Output files used for additive manufacturing of physical diagnostic replicas. Used by cardiologists/clinical specialists in clinical settings. Enhances procedure screening/planning; aids clinical decision-making via improved anatomical visualization and measurement accuracy. Benefits patient through personalized pre-surgical planning and diagnostic physical models.
Clinical Evidence
Bench testing only. Geometric accuracy of virtual models and 3D-printed physical replicas assessed against acceptance criteria. Validation of semi-automatic neo-LVOT tool demonstrated improved interrater consistency/repeatability compared to manual methods. No clinical prospective/retrospective studies reported.
Technological Characteristics
Software-based image processing system. Functions: DICOM import, 3D segmentation, measurement, and 3D model export for additive manufacturing. Guided workflow architecture. Connectivity: DICOM compliant. Software verification/validation per FDA guidance.
Indications for Use
Indicated for use by medical professionals (e.g., cardiologists, clinical specialists) to interpret DICOM images for structural heart and vascular treatment planning, including visualization, measurement, and creation of 3D anatomical models for diagnostic physical replicas.
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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June 5, 2019
Materialise N.V. % Mieke Janssen Quality Engineer Technologielaan 15 Leuven, 3001 BELGIUM
Re: K190874
Trade/Device Name: Materialise Mimics Enlight Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: LLZ Dated: April 1, 2019 Received: April 11, 2019
Dear Mieke Janssen:
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. 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 located 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.
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 803) for
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devices or postmarketing safety reporting (21 CFR 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 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
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 https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about mediation-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.
For
Thalia T. Mills, Ph.D. Director Division of Radiological Health OHT7: Office of In Vitro Diagnostics and 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) K190874
Device Name Materialise Mimics Enlight
### Indications for Use (Describe)
Materialise Mimics Enlight is intended for use as a software interface and image segmentation system for the transfer of DICOM imaging information from a medical scanner to an output file.
It is also intended as a software to aid interpreting DICOM compliant images for structural heart and vascular treatment options. For this purpose. Materialise Mimics Enlight provides additional visualisation and measurement tools to enable the user to screen and plan the procedure.
The Materialise Mimics Enlight output file can be used for the fabrication of physical replicas of the using traditional additive manufacturing methods. The physical replica can be used for diagnostic purposes in the field of cardiovascular applications.
Materialise Mimics Enlight should be used in conjunction with other diagnostic tools and expert clinical judgement.
Type of Use (Select one or both, as applicable)
| <span style="font-family: sans-serif;"> <svg height="12" width="12"> <rect fill="none" height="12" stroke="black" width="12" x="0" y="0"></rect> <path d="M2,2 L10,10 M2,10 L10,2" stroke="black"></path> </svg> </span> Prescription Use (Part 21 CFR 801 Subpart D) |
|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| <span style="font-family: sans-serif;"> <svg height="12" width="12"> <rect fill="none" height="12" stroke="black" width="12" x="0" y="0"></rect> </svg> </span> Over-The-Counter Use (21 CFR 801 Subpart C) |
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# 510(k) Summary
# K190874
| Company name | Materialise N.V. |
|-----------------------------------|-----------------------------------|
| Establishment registration number | 3003998208 |
| Street Address | Technologielaan 15 |
| City | Leuven |
| Postal code | 3001 |
| Country | Belgium |
| Phone number | +32 16 744 571 |
| Fax number | +32 16 39 66 06 |
| Principal Contact person | Mieke Janssen |
| Contact title | Regulatory Affairs Manager |
| Contact e-mail address | Regulatory.Affairs@materialise.be |
| Additional contact person | Isabel Helena de Brito Manique |
| Contact title | Regulatory Affairs Consultant |
| Contact e-mail address | Regulatory.Affairs@materialise.be |
The following section is included as required by the Safe Medical Devices Act (SMDA) of 1990 and 21CFR 807.92
## Submission date
The date of the Traditional 510(k) submission is April 1, 2019.
## Submission information
| Trade Name | Materialise Mimics Enlight |
|-----------------------------|----------------------------------------|
| Common Name | Image processing system |
| Classification Name | System, Image processing, Radiological |
| Classification product code | LLZ (892.2050) |
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#### Description and functioning of the device
Materialise Mimics Enlight for structural heart and vascular planning is a software interface that is organized in a workflow approach. High level, each workflow in the field of structural heart and vascular will follow the same kind of structure of 4 steps which will enable the user to plan the procedure:
- 1. Analyse anatomy
- 2. Plan device
- 3. Plan delivery
- 4. Output
To perform these steps the software provides different methods and tools to visualize and measure based on the medical images.
The user is a medical professional, like cardiologists or clinical specialists. To start the workflow DICOM compliant medical images will need to be imported. The software will read the images and convert them into a project file. The user can now start the workflow and follow the steps visualized in the software. The base of the workflow is to create a 3D reconstruction of the anatomy based on the medical images to use this further together with the 2D medical images in the workflow to plan the procedure.
#### Indications for use
Materialise Mimics Enlight is intended for use as a software interface and image segmentation system for the transfer of DICOM imaging information from a medical scanner to an output file.
lt is also intended as a software to aid interpreting DICOM compliant images for structural heart and vascular treatment options. For this purpose, Materialise Mimics Enlight provides additional visualization and measurement tools to enable the user to screen and plan the procedure.
The Materialise Mimics Enlight output file can be used for the fabrication of physical replicas of the output file using traditional or additive manufacturing methods. The physical replica can be used for diagnostic purposes in the field of cardiovascular applications.
Materialise Mimics Enlight should be used in conjunction with other diagnostic tools and expert clinical judgement.
#### Predicate Devices
The primary predicate device to which substantial equivalence is claimed, which has been cleared for marketing in the United States, and which has not been subject to a design-related recall:
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| Trade or proprietary or model name | Mimics Medical |
|------------------------------------|------------------|
| 510(k) number | K183105 |
| Decision date | March 27, 2019 |
| Classification product code | LLZ (892.2050) |
| Manufacturer | Materialise N.V. |
One of the reference predicate devices to which substantial equivalence is claimed, which has been cleared for marketing in the United States, and which has not been subject to a design-related recall:
| Trade or proprietary or model name | 3mensio Workstation |
|------------------------------------|--------------------------|
| 510(k) number | K153736 |
| Decision date | May 27, 2016 |
| Classification product code | LLZ (892.2050) |
| Manufacturer | Pie Medical Imaging B.V. |
The other reference predicate device to which substantial equivalence is claimed, which has been cleared for marketing in the United States (under K173619) and which has not been subject to a design-related recall:
| Trade or proprietary or model name | Mimics inPrint |
|------------------------------------|------------------|
| 510(k) number | K173619 |
| Decision date | March 21, 2018 |
| Classification product code | LLZ (892.2050) |
| Manufacturer | Materialise N.V. |
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## Technological Characteristics
# Comparison of technological characteristics with the predicate device (Mimics, K183105) and the reference device (Mimics inPrint, K173619)
The subject device Mimics Enlight employs similar fundamental technologies as Mimics inPrint. Technological similarities include:
- Device functionality:
- Imaging information: All devices import DICOM compliant imaging types. C
- O Image segmentation: All devices share the same image segmentation functionalities.
- Processing to output file: All devices generate an output file that can be used for the fabrication o of physical replicas.
- Measuring and planning: All devices have functionalities to perform measurements and pre- O surgical planning.
- . Device design: The subject device, like the reference device, originated from the same code base as the predicate device.
The following technological differences exist between the subject device and the predicate device:
- Device functionality:
- o Software organization: The subject device shares the technology and functionality of the predicate and reference device. However, for the subject device, functionality was organized as a guided workflow.
Comparison of technological characteristics with the one of the two reference devices (3mensio, K153736):
The subject device Mimics Enlight employs similar fundamental technological similarities include:
- Device functionality:
- O lmaging information: The subject and reference device both import DICOM compliant imaging types.
- Measuring and planning: The subject and predicate device both have functionalities to perform O measurements and pre-surgical planning.
- Software organization: The subject and reference device are both organized in a guide workflow. O
The following technological differences exist between the subject device and the predicate device:
- Device functionality:
- lmage segmentation: While both devices allow to segment anatomy in the cardiovascular field, O Mimics Enlight provides more controls to the user to review and fine-tune the segmentation.
- Processing to output file: While both devices allow to export an output file, Mimics Enlight O validated its output on a set of 3D printers to support the use of physical replicas for diagnostic purposes.
- NeoLVOT measurement: While both devices include a manual NeoLVOT area measurement, the O subject device also includes a semi-automated NeoLVOT area measurement.
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### Performance Data
Software verification and validation were performed, and documentation was provided following the "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices." This includes verification against defined requirements, and validation against user needs. Both end-user validation and bench testing were performed.
The geometric accuracy of virtual models created in the subject device Mimics Enlight was assessed via Bench testing. Accuracy of the virtual models was compared for the subject and predicate device. Deviations were within the acceptance criteria. This shows that for creating virtual models, Mimics Medical is substantially equivalent to the predicate device.
Apart from geometric accuracy of virtual models, also geometric accuracy of the physical replicas (produced by 3D printing virtual models) was assessed. This was conducted for cardiovascular models. The physical replicas were compared to the virtual models. Deviations were within the acceptance criterial models can accurately be printed when using one of the compatible 3D printers.
Validation of the semi-automatic neo-LVOT (neo-Left Ventricular Outflow Tract) tool demonstrated a higher interrater consistency/repeatability.
In conclusion, all performance testing conducted device performance and substantial equivalence to the predicate device.
### Summary
The characteristics that determine the functionality and performance of the subject device Mimics Enlight are substantially equivalent to the device cleared under Mimics Medical (K183105), the primary predicate device, and also substantially equivalent to its reference predicate device 3mensio Workstation (K153736) and to its other reference predicate device Mimics inPrint (K173619). The non-clinical testing indicates that the subject device is as safe, as effective, and performant as the predicate device.
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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.
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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.
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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.
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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.
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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.
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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.
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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.