Bonelogic software is intended to be used by specialized medical practitioners to assist in the characterization of human anatomy with 3D visualization and specific measurements. The medical image modalities intended to be used in the software are computed tomography (CT) images, cone beam computed tomography (CBCT) images and weight-bearing cone beam CT (WBCT) images. The intended patient population is adults over 16 years of age. Bonelogic software contains the measurement template with a set of distance and angular measurements can be used for diagnostic purposes. The three dimensional (3D) models are displayed and can be manipulated in the software. Together, the information from the measurements and the 3D visualization can be used for treatment planning in the field of orthopedics (foot and ankle, and hand wrist). The 3D models can be outputted from the software for traditional or additive manufacturing. The physical models generated based on the 3D digital models are not intended for diagnostic use.
Device Story
Bonelogic is a software tool for specialized medical practitioners to process CT, CBCT, and WBCT images. It imports DICOM data; segments anatomy using semi-automatic or fully automatic algorithms; generates 3D models; and performs distance/angular measurements. Used in clinical settings for orthopedic treatment planning (foot, ankle, hand, wrist). Output includes 3D models for traditional or additive manufacturing and measurement data. Clinicians use visualizations and measurements to assist in diagnosis and surgical planning. Benefits include improved anatomical characterization and pre-surgical planning capabilities.
Clinical Evidence
Bench testing and clinical validation performed. Geometric accuracy of 3D models compared against predicate device using foot/ankle DICOM images. Measurement accuracy and repeatability assessed by clinicians comparing manual measurements against Bonelogic-generated measurements using hand/wrist DICOM images. Validation confirmed device performance against user needs and requirements.
Technological Characteristics
Software-based image processing system. Inputs: DICOM-compliant CT, CBCT, and WBCT images. Functionality: Semi-automatic and fully automatic segmentation, 3D model generation, and measurement tools. Architecture: Modular. Connectivity: Standalone software for image viewing, processing, and export for third-party Finite Element Analysis or manufacturing. No hardware components.
Indications for Use
Indicated for adults over 16 years of age requiring characterization of human anatomy, trauma, or deformity identification, and treatment planning in orthopedics (foot, ankle, hand, wrist) using CT, CBCT, or WBCT images.
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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February 5, 2021
Image /page/0/Picture/1 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, with the letters "FDA" in a blue square, followed by the words "U.S. FOOD & DRUG" in blue, and the word "ADMINISTRATION" in a smaller font below.
Disior Oy (Ltd.) % Markku Laitinen COO Lapinlahdenkatu 16 Helsinki, 00180 FINLAND
Re: K203290
Trade/Device Name: Bonelogic Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: LLZ Dated: November 6, 2020 Received: November 9, 2020
Dear Markku Laitinen:
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) K203290
Device Name Bonelogic
#### Indications for Use (Describe)
Bonelogic software is intended to be used by specialized medical practitioners to assist in the characterization of human anatomy with 3D visualization and specific measurements. The medical image modalities intended to be used in the software are computed tomography (CT) images, cone beam computed tomography (CBCT) images and weight-bearing cone beam CT (WBCT) images. The intended patient population is adults over 16 years of age.
Bonelogic software contains the measurement template with a set of distance and angular measurements can be used for diagnostic purposes. The three dimensional (3D) models are displayed and can be manipulated in the software. Together, the information from the measurements and the 3D visualization can be used for treatment planning in the field of orthopedics (foot and ankle, and hand wrist). The 3D models can be outputted from the software for traditional or additive manufacturing. The physical models generated based on the 3D digital models are not intended for diagnostic use.
Type of Use (Select one or both, as applicable)
| Prescription Use (Part 21 CFR 801 Subpart D) | <span style="font-family: DejaVu Sans, sans-serif">☑</span> |
|----------------------------------------------|-------------------------------------------------------------|
| Over-The-Counter Use (21 CFR 801 Subpart C) | ☐ |
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Image /page/3/Picture/0 description: The image shows the word "DISIOR" in a bold, sans-serif font. The "D" is white and set against a black square. The remaining letters, "ISIOR", are black and placed to the right of the black square. The overall design is simple and modern.
Disior Oy Maria 01, Building 2 Lapinlahdenkatu 16 00180 Helsinki Finland www.disior.com
# 510(k) Summary
K203290 510 (k) number: Dated:
January 12th, 2021
The following section is included as required by the Safe Medical Devices Act (SMDA) of 1990 and 21CFR 807.92.
| Company Name: | Disior Oy |
|------------------------------------|--------------------|
| Establishment Registration Number: | N/A |
| Street Address: | Lapinlahdenkatu 16 |
| City: | Helsinki |
| Postal Code: | 00180 |
| Country: | FINLAND |
| Phone Number: | +358 405430673 |
| Principal Contact Person: | Markku Laitinen |
| Contact email: | markku@disior.com |
## Submission information
| Trade Name: | Bonelogic |
|------------------------------|----------------------------------------|
| Common Name: | Image Processing System |
| Classification Product Name: | System, Image processing, Radiological |
| Classification Product Code: | LLZ (892.2050) |
## Predicate device
The primary predicate device to which substantial equivalence is claimed:
| 510(K) No. | K183105 |
|------------------------------|----------------------------------------|
| Clearance Date: | March 27, 2019 |
| Device Name: | Mimics Medical |
| Manufacturer: | Materialise N.V. |
| Classification Product Name: | System, Image processing, Radiological |
| Classification Product Code: | LLZ (892.2050) |
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Image /page/4/Picture/0 description: The image shows the word "DISIOR" in black and white. The letter "D" is white and is set against a black square. The remaining letters, "ISIOR", are black and are set against a white background. The font is sans-serif and appears to be bold.
Disior Oy Maria 01, Building 2 Lapinlahdenkatu 16 00180 Helsinki Finland www.disior.com
### Description and functioning of the device
Bonelogic product is a software tool to be used by specialized medical practitioners. The software tool is aimed to help the user in the characterization of human anatomy, and identifying possible trauma or deformities, the diagnose and the treatment planning should always be based on the professional skills of the specialist doctor. The medical image modalities intended to be used in the software are computed tomography (CT) images, cone beam computed tomography (CBCT) images and weight-bearing cone beam CT (WBCT) images. Bonelogic software has got a modular architecture. The software includes following functionality:
- Importing medical images in DICOM format
- Viewing of DICOM data
- Selecting a region of interest using generic segmentation tools
- Segmenting specific anatomy using dedicated semi-automatic tools or fully automatic algorithms
- Verifying and editing a region of interest
- Calculating a digital 3D model and editing the model
- Measuring on 3D models
- Exporting images, measurements, and 3D models to third-party packages
- Planning treatments on the 3D models
- Interfacing with packages for Finite Element Analysis
#### Intended use
Bonelogic software is intended to be used by specialized medical practitioners to assist in the characterization of human anatomy with 3D visualization and specific measurements. The medical image modalities intended to be used in the software are computed tomography (CT) images, cone beam computed tomography (CBCT) images and weight-bearing cone beam CT (WBCT) images. The intended patient population is adults over 16 years of age.
#### Indications for use
Bonelogic software contains the measurement template with a set of distance and angular measures. The measurements can be used for diagnostic purposes. The three dimensional (3D) models are displayed and can be manipulated in the software. Together, the information from the measurements and the 3D visualization can be used for treatment planning in the field of orthopedics (foot and ankle, and hand and wrist). The 3D models can be outputted from the software for traditional or additive manufacturing. The physical models generated based on the 3D digital models are not intended for diagnostic use.
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Image /page/5/Picture/0 description: The image shows the word "DISIOR" in a bold, sans-serif font. The "D" is white and is set against a black square. The rest of the letters are black and are set against a white background. The letters are evenly spaced and are all the same size.
Disior Oy Maria 01, Building 2 Lapinlahdenkatu 16 00180 Helsinki Finland www.disior.com
### Comparison of Technological Characteristics with the Predicate Device
The subject device Bonelogic employs similar fundamental technologies as the predicate device.
Technological similarities include:
- Device functionality:
- Image segmentation: The subject and predicate device share the same image segmentation functionalities.
- Processing to output file: The subject and predicate device both generate an output file.
- Measuring and planning: The subject and predicate device both have functionalities to perform measurements and pre-surgical planning.
The following technological differences exist between the subject device and the predicate device:
- . lmaging information:
- Whereas the predicate device is more generally intended to import imaging information of a medical scanner, allowing both DICOM compatible images and standard imaging formats (such as RAW, TIFF, BMP and JPEG), the subject device is intended to import only DICOM compliant types.
- Device functionalities: ●
- Whereas the predicate device is creating Python scripts to automate workflows, the subject device is not supporting Python scripts.
- Device design:
- The design of the predicate device is organized in a toolbox fashion with manual steps in tissue segmentation and manual measurement tools, whereas the interface of the subject device specifically guides the user through a few predefined steps for obtaining a 3D output file and defined measurements.
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Image /page/6/Picture/0 description: The image shows the word "DISIOR" in a bold, sans-serif font. The "D" is white and set against a black square. The remaining letters, "ISIOR", are black and set against a white background. The overall design is simple and modern.
Disior Oy Maria 01, Building 2 Lapinlahdenkatu 16 00180 Helsinki Finland www.disior.com
### 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:
- | Subject device comparison with predicate device by comparing the geometric accuracy of outputted 3D models
- । Subject device comparison with predicate device by comparing repeatability of manual measurements and measurements created with subject device on radiographical parameters
- । Verification for the subject device against defined requirements via performance testing and clinical validation
- Validation for the subject device against user needs via clinical validation on usability of 3D models in clinical setting
End-user validation, clinical validation, and performance testing were performed.
The geometric accuracy of 3D virtual models created in the subject device Bonelogic software was assessed against similar virtual models created with predicate device. The comparison was made with DICOM images containing foot and ankle anatomy.
The measurement accuracy in the subject device Bonelogic software was assessed by comparing manual measurements of radiographical parameters against same measurements created in subject device. The manual measurements were performed by clinicians. The data set in the study included DICOM images containing hand and wrist anatomy.
The verification and validation of the subject device against defined requirements and against user need, was done via performance testing on measurements repeatability and with clinical validation for the accuracy of the 3D virtual models against original DICOM imaging data.
In conclusion, all performance testing conducted demonstrated device performance and substantial equivalence to the predicate device.
#### Summary
A comparison of intended use and technological characteristics combined with performance data demonstrates that Bonelogic software is substantially equivalent to the predicate device Mimics Medical (K183105). Minor differences in intended use and technological characteristics exist, but performance data demonstrates that Bonelogic software is as safe and effective and performs as well as the predicate device.
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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.