K203699 · Siemens Medical Solutions USA, Inc. · JAK · Apr 30, 2021 · Radiology
Device Facts
Record ID
K203699
Device Name
syngo. CT Extended Functionalities
Applicant
Siemens Medical Solutions USA, Inc.
Product Code
JAK · Radiology
Decision Date
Apr 30, 2021
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.1750
Device Class
Class 2
Attributes
AI/ML
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
Lung lobe segmentation
—
—
Average DICE coefficients 0.94 to 0.96
—
—
250 datasets from multiple sites across the US and Europe
—
Pulmonary opacity detection
—
—
93.0% of PO values within the 95%-Limits of Agreement
—
—
150 datasets from multiple sites across the US and Europe
>1 (human readers)
Indications for Use
syngo.CT Extended Functionality is intended to provide advanced visualization tools to prepare and process medical images for diagnostic purpose. The software package is designed to support technicians and physicians in qualitative and quantitative measurements and in the analysis of clinical data that was acquired and reconstructed by Computed Tomography (CT) scanners, and possibly other medical imaging modalities (e.g. MR scanners). An interface shall enable the connection between the syngo.CT Extended Functionality software package and the interconnected CT Scanner system. Resulting images created with the syngo.CT Extended Functionality software package can be used to assist trained technicians or physicians in diagnosis.
Device Story
Software bundle providing advanced visualization and measurement tools for medical images (CT/MR). Features include Pulmonary Density analysis, Oncology extensions, and other clinical modules. Pulmonary Density feature uses AI to segment lung lobes and identify opaque regions (ground glass, consolidations, crazy-paving); calculates percentage of opacity per lobe/lung; assigns 0-4 severity scores per lobe; sums scores (0-20). Oncology extension supports nodule localization, orthogonal measurements, and lesion segmentation. Used in clinical settings by physicians and technicians. Output assists in diagnostic decision-making by providing quantitative lung parenchyma and lesion data. Operates on SOMARIS/8 platform.
Clinical Evidence
Clinical data-based software validation performed. Lung lobe segmentation validated on 250 datasets; DICE coefficients 0.94-0.96. Opaque region segmentation validated on 150 datasets; 93.0% of percentage of opacity (PO) values fell within 95%-Limits of Agreement (LoA) compared to human reads. Consistent performance observed across population subgroups and technical parameters.
Technological Characteristics
Software-based image processing suite. Connectivity via DICOM (PS 3.1-3.20). Operates on SOMARIS/8 VB51 platform. Features AI-based segmentation (lung lobes, opaque regions) and threshold-based analysis (-200 HU). Complies with IEC 62304 (software lifecycle), ISO 14971 (risk management), and IEC 62366-1 (usability).
Indications for Use
Indicated for use by trained technicians and physicians to provide advanced visualization, qualitative and quantitative measurements, and analysis of clinical data acquired and reconstructed by CT or other medical imaging modalities (e.g., MR) to assist in diagnosis.
Regulatory Classification
Identification
A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.
{0}------------------------------------------------
April 30, 2021
Image /page/0/Picture/1 description: The image contains the logos of the Department of Health & Human Services and the U.S. Food & Drug Administration (FDA). The Department of Health & Human Services logo is on the left, featuring a stylized emblem. To the right is the FDA logo, with the letters 'FDA' in a blue square, followed by 'U.S. FOOD & DRUG' and 'ADMINISTRATION' in blue text.
Siemens Medical Solutions USA, Inc. % Alaine Medio Regulatory Affairs Professional 810 Innovation Drive KNOXVILLE TN 37932
Re: K203699
Trade/Device Name: syngo.CT Extended Functionality Regulation Number: 21 CFR 892.1750 Regulation Name: Computed tomography x-ray system Regulatory Class: Class II Product Code: JAK Dated: March 29, 2021 Received: March 30, 2021
Dear Alaine Medio:
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/cfpmp/bmn.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 devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see
{1}------------------------------------------------
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 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,
Michael D. O'Hara
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
{2}------------------------------------------------
## Indications for Use
510(k) Number (if known) K203699
Device Name syngo.CT Extended Functionality
#### Indications for Use (Describe)
syngo.CT Extended Functionality is intended to provide advanced visualization tools to prepare and process medical images for diagnostic purpose. The software package is designed to support technicians and physicians in qualitative and quantitative measurements and in the analysis of clinical data that was acquired and reconstructed by Computed Tomography (CT) scanners, and possibly other medical imaging modalities (e.g. MR scanners).
An interface shall enable the connection between the syngo.CT Extended Functionality software package and the interconnected CT Scanner system.
Resulting images created with the syngo.CT Extended Functionality software package can be used to assist trained technicians or physicians in diagnosis.
| Type of Use (Select one or both, as applicable) |
|-------------------------------------------------|
|-------------------------------------------------|
X Prescription Use (Part 21 CFR 801 Subpart D)
| Over-The-Counter Use (21 CFR 801 Subpart C)
### CONTINUE ON A SEPARATE PAGE IF NEEDED.
This section applies only to requirements of the Paperwork Reduction Act of 1995.
### *DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.*
The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:
> Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff(@fda.hhs.gov
"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."
{3}------------------------------------------------
# K203699 510(k) Summary FOR syngo.CT Extended Functionality
Identification of the Submitter
### Importer/Distributor Siemens Medical Solutions USA, Inc. 40 Liberty Boulevard Malvern, PA 19355 Establishment Registration Number 2240869
### Manufacturing Site
l.
Siemens Healthcare GmbH Siemensstr 1 D-91301 Forchheim, Germany
### Establishment Registration Number
3004977335
### Submitter Contact Person:
Alaine Medio Regulatory Affairs Specialist Siemens Medical Solutions, Inc. USA 810 Innovation Drive Knoxville, TN 37932 Phone: (865) 206-0337 Fax: (865) 218-3019 Email: alaine.medio@siemens-healthineers.com
#### II. Device Name and Classification
| Product Name: | syngo.CT Extended Functionality |
|-----------------------|----------------------------------|
| Propriety Trade Name: | syngo.CT Extended Functionality |
| Classification Name: | Computed Tomography X-ray System |
| Classification Panel: | Radiology |
| CFR Section: | 21 CFR §892.1750 |
| Device Class: | Class II |
| Product Code: | JAK |
{4}------------------------------------------------
#### lll. Predicate Device
#### Primary Predicate Device
| Trade Name: | syngo.CT Extended Functionality |
|-----------------------|----------------------------------|
| 510(k) Number: | K192402 |
| Clearance Date: | 09/20/2019 |
| Classification Name: | Computed Tomography X-ray System |
| Classification Panel: | Radiology |
| CFR Section: | 21 CFR §892.1750 |
| Device Class: | Class II |
| Product Code: | JAK |
#### Secondary Predicate Device
| Trade Name: | Al-Rad Companion (Pulmonary) |
|-----------------------|----------------------------------|
| 510(k) Number: | K183271 |
| Clearance Date: | 07/26/2019 |
| Classification Name: | Computed Tomography X-ray System |
| Classification Panel: | Radiology |
| CFR Section: | 21 CFR §892.1750 |
| Device Class: | Class II |
| Product Code: | JAK |
#### Reference Device
| Trade Name: | syngo.CT Pulmo 3D |
|-----------------------|----------------------------------|
| 510(k) Number: | K123540 |
| Clearance Date: | 08/29/2013 |
| Classification Name: | Computed Tomography X-ray System |
| Classification Panel: | Radiology |
| CFR Section: | 21 CFR §892.1750 |
| Device Class: | Class II |
| Product Code: | JAK |
#### IV. Device Description
syngo.CT Extended Functionality is a software bundle that offers tools to support special clinical evaluations. The "tools" are represented by the so-called Extensions. syngo.CT Extended Functionality can be used to create advanced visualizations and measurements on clinical data that was acquired and reconstructed by Computed Tomography (CT) scanners or other medical imaging modalities (e.g. MR scanners) by using the Extensions. Advanced visualizations and measurements are listed as follows. The subject device in the current software version SOMARIS/8 VB51 has been extended by the Extension Pulmonary Density.
This feature provides the possibility to segment opacity regions of CT images of the lungs using an Al algorithm. Pulmonary Density counts image voxels inside opacity regions and calculates the percentages of these voxels relative to the total number of voxels per lobe, lung and in total. Afterwards, each of the five lung lobes is assigned a score ranging from 0 to 4 based on the percentage of opacity as follows: 0 (0%), 1 (1%-25%), 2 (26%-50%), 3 (51%-75%), or 4 (76%-100%). Then a summation of the five lobe scores (range of possible scores, 0–20) are generated in the device outputs.
{5}------------------------------------------------
#### V. Indications for Use
syngo.CT Extended Functionality is intended to provide advanced visualization tools to prepare and process medical images for diagnostic purpose. The software package is designed to support technicians and physicians in qualitative and quantitative measurements and in the analysis of clinical data that was acquired and reconstructed by Computed Tomography (CT) scanners, and possibly other medical imaging modalities (e.g. MR scanners).
An interface shall enable the connection between the syngo.CT Extended Functionality software package and the interconnected CT Scanner system.
Resulting images created with the syngo.CT Extended Functionality software package can be used to assist trained technicians or physicians in diagnosis.
#### Comparison of Technological Characteristics with the Predicate Device VI.
The differences and similarities between the above referenced predicate device are listed at a highlevel in the following table:
| Feature | Subject Device | Primary Predicate Device | Secondary Predicate Device |
|----------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| | syngo.CT Extended<br>Functionality<br>(SOMARIS/8 VB51) | syngo.CT Extended<br>Functionality<br>(SOMARIS/8 VB40) | Al-Rad Companion<br>(Pulmonary)<br>(VA10) |
| 1. Pulmonary Density | | | |
| - Segmentation of<br>Lung | Creation of a lung<br>segmentation mask by<br>combining the<br>segmentation masks of 5<br>lung lobes.<br><br>The same algorithm as<br>cleared with the secondary<br>predicate device has been<br>trained with more data. | N/A | The device's algorithm<br>creates a lung segmentation<br>mask by combining the<br>segmentation masks of 5<br>lung lobes. |
| - Segmentation of<br>Lobes | Computation of<br>segmentation masks of the<br>five lung lobes (right upper<br>(RUL), right middle (RML),<br>right lower (RLL), left upper<br>(LUL) and left lower (LLL)<br>lobe) for a given CT data set<br>of the chest.<br><br>The same algorithm as<br>cleared with the secondary<br>predicate device has been<br>trained with more data. | N/A | Computation of<br>segmentation masks of the<br>five lung lobes (right upper<br>(RUL), right middle (RML),<br>right lower (RLL), left upper<br>(LUL) and left lower (LLL)<br>lobe) for a given CT data set<br>of the chest. |
| - Opacity Detection | Al-based identification of<br>areas with elevated<br>Hounsfield values.<br><br>Threshold-based<br>identification of highest<br>elevated Hounsfield values<br>inside these elevated<br>regions, by a predefined<br>threshold of -200 HU. | N/A | Secondary predicate device<br>(Al-Rad Companion<br>(Pulmonary)):<br>Identification of areas with<br>lower Hounsfield values<br>inside both lungs in<br>comparison to a predefined<br>threshold of -950 HU. |
| Feature | Subject Device | Primary Predicate Device | Secondary Predicate Device |
| | syngo.CT Extended<br>Functionality<br>(SOMARIS/8 VB51) | syngo.CT Extended<br>Functionality<br>(SOMARIS/8 VB40) | Al-Rad Companion<br>(Pulmonary)<br>(VA10) |
| | Equivalent to the reference<br>device syngo.CT Pulmo 3D<br>(K123540): the areas of<br>elevated Hounsfield values<br>are found by the deep<br>learning approach as<br>described above instead of<br>threshold-based.<br>The threshold-based<br>segmentation of high<br>opacity regions is same to<br>the parenchyma analysis<br>already cleared with the<br>predicate device Al-Rad<br>Companion Pulmonary<br>(K183271) and syngo.CT<br>Pulmo 3D (K123540). | | Reference device (syngo.CT<br>Pulmo 3D):<br>Pulmo 3D: Identification of<br>areas with lower or elevated<br>Hounsfield values inside<br>both lungs in comparison to<br>a predefined threshold. |
| - Measurement Results | Lung lesion, lung<br>parenchyma, and<br>pulmonary density<br>measurements (output).<br>The Measurement results<br>are unchanged with the<br>exception of displaying the<br>Pulmonary Density<br>measurements. | N/A | Lung lesion, lung<br>parenchyma measurements<br>(output). |
| 2. Oncology Extension | The oncology extension<br>offers tools for localization<br>and evaluation of nodules<br>supporting the following<br>main functionalities<br>• Orthogonal<br>measurements<br>of maximum length and<br>width of anatomical<br>structures<br>• Navigation Tool for<br>LungCAD results<br>• Lung Lesion<br>Segmentation<br>Minor modifications to the | The oncology extension<br>offers tools for localization<br>and evaluation of nodules<br>supporting the following<br>main functionalities<br>• Diameter and WHO Area<br>• Lung CAD Series<br>• Lung Lesion<br>Segmentation | Al-Rad Companion<br>(Pulmonary) offers tools for<br>localization and evaluation<br>of nodules supporting the<br>following main<br>functionalities<br>• Lung CAD Series<br>• Lung Lesion<br>Segmentation |
| | Oncology Extension were<br>made. | | |
{6}------------------------------------------------
The remaining functions in Syngo.CT Extended Functionality remain unchanged compared to the predicate version.
- Interactive Spectral Imaging Display different representations of Dual Energy data. •
- Vascular Extensions - The user can perform a vascular evaluation supporting the following main functionalities: Measuring vessels, Creating DICOM snapshots or result series for
{7}------------------------------------------------
documenting findings and Working on images that are acquired with CT or MR scanner systems constituting one or more volumes of vascular structures
- . Osteo Extension - Evaluation of Bone Mineral Density (BMD) values (mg CA-HA/ml).
- Neuro DSA Extension - Selective bone removal from a CT angiography dataset
- . ROI HU Threshold Extension – Evaluation of HU Value distributions
- . Dual Energy Extension – Simultaneous evaluation for low and high kV dual energy images
- Endoscopic Viewing Extension – Interactive fly through tubular structures that are filled by either low-intensity or high-intensity material
- . General (Extension Independent features) — Multiphase support for merged 4D series and editing tool for pre-generated results.
The core modification of the subject device as compared to its predicate device (syngo.CT Extended Functionality (SOMARIS/8 VB40)) is the new feature Pulmonary Density.
#### VII. Performance Data
The following performance data were provided in support of the substantial equivalence determination.
#### Non-Clinical Testing
This submission contains performance tests (Non-clinical test reports) to demonstrate continued conformance with special controls for medical devices containing software. Non-clinical tests (integration and functional) were conducted for syngo.CT Extended Functionality during product development. These tests have been performed to test the ability of the included features of the subject device. The results of these tests demonstrate that the subject device performs as intended. The result of all conducted testing was found acceptable to support the claim of substantial equivalence.
### Clinical Evaluation of the Al-based Algorithms
Clinical Data Based Software Validation
To validate the syngo.CT Extended Functionality clinical workflow, the following algorithms underwent a scientific evaluation:
- . Segmentation of lung lobes
The lung lobe segmentation algorithm computes segmentation masks of the five lung lobes (right upper (RUL), right middle (RML), right lower (RLL), left upper (LUL) and left lower (LLL) lobe) for a given CT data set of the chest.
- . Identification of opaque regions (Al-based) The algorithm computes masks of opaque regions in the lung for a given CT data set of the chest. The opaque regions include ground glass opacities, consolidations, and crazy-paving patterns. The calculation is done for each lobe as well as for the complete lung.
For each algorithm of syngo.CT Extended Functionality the analysis is structured as follows:
- . Algorithm Description: purpose, functionality, technical description
- . Data
- Training cohort: size and properties of data used for training O
- O Description of ground truth / annotations generation
{8}------------------------------------------------
- Validation cohort: size and properties of data used for testing/validation
- . Performance
- Choice of performance metric
- Actual performance results
- o Assessment of clinical relevance of achieved performance
- . Related clinical research, e.g. publications (if applicable)
The results of clinical data-based software validation for the subject device syngo.CT Extended Functionality demonstrated equivalent performance in comparison to the secondary predicate device for segmentation and lung parenchyma categorization. A complete scientific evaluation report is provided in support of the device modifications.
Performance of lung lobe segmentation of syngo.CT Extended Functionality device has been validated using 250 datasets from multiple sites across the US and Europe. Average DICE coefficients ranged from 0.94 to 0.96.
Performance of the segmentation of opaque regions of syngo.CT Extended Functionality device has been validated using 150 datasets from multiple sites across the US and Europe. Inter-readervariability of the percentage of opacity (PO) was assessed on a lung lobe level and 95%-Limits of Agreement (LoA) were established. The algorithm performance was compared against the human reads and 93.0% of the PO values were found within the LoA.
Additional analysis was performed for both population-specific subgroups and various technical parameters and consistent performance has been found for both algorithms across all subgroups.
#### Risk Analysis
The risk analysis was completed, and risk control implemented to mitigate identified hazards. The testing results support that all the software specifications have met the acceptance criteria. Testing for verification and validation of the device was found acceptable to support the claims of substantial equivalence.
Siemens hereby certifies that syngo.CT Extended Functionality will meet the following voluntary standards covering electrical and mechanical safety listed below, prior to introduction into interstate commerce:
| Recognition<br>Number | Product<br>Area | Title of Standard | Date of<br>Recognition | Standards<br>Development<br>Organization |
|-----------------------|--------------------------|------------------------------------------------------------------------------------------------------------|------------------------|------------------------------------------|
| 12-300 | Radiology | Digital Imaging and Communications in<br>Medicine (DICOM) Set; PS 3.1 - 3.20 | 06/27/2016 | NEMA |
| 13-79 | Software | Medical Device Software –Software Life Cycle<br>Processes; 62304:2006 (1st Edition)/A1:2016 | 01/14/2019 | AAMI, ANSI, IEC |
| 5-40 | Software/<br>Informatics | Medical devices – Application of risk<br>management to medical devices; 14971 Second<br>Edition 2007-03-01 | 06/27/2016 | ISO |
| 5-114 | General I<br>(QS/RM) | Medical devices - Part 1: Application of<br>usability engineering to medical devices<br>IEC 62366-1:2015 | 12/23/2016 | IEC |
{9}------------------------------------------------
### VIII. Conclusion
syngo.CT Extended Functionality has the same intended use and same indication for use as the primary predicate device. The technological characteristics such as image visualization, operating platform, and image measurement are the same as the predicate devices.
For the subject device, syngo.CT Extended Functionality, Siemens used the same testing with the same workflows as used to clear the primary predicate device. Siemens considers syngo.CT Extended Functionality to be as safe, as effective, and with performance substantially equivalent to the commercially available predicate devices.
Predicate graph will load when search results are available.
Embedding visualization will load when search results are available.
PDF viewer will load when search results are available.
Loading panels...
Select an item from Submissions
Click any panel, subpart, regulation, product code, or device to see details here.
Section Matches
Results will appear here.
Product Code Matches
Results will appear here.
Special Control Matches
Results will appear here.
Loading collections...
Loading
My Alerts
You will receive email notifications based on the filters and frequency you set for each alert.
Sort by:
Create Alert
Search Filters
Agent Token
Create a read-only bearer token for Claude, ChatGPT, or other agents that can call HTTP APIs.
Copy this now. It will not be shown again.
Connected apps
Apps you authorized through browser sign-in. Disconnecting revokes their access immediately.
Learn the FDA Browser
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.