K220583 · Radformation, Inc. · IYE · Aug 23, 2022 · Radiology
Device Facts
Record ID
K220583
Device Name
ClearCheck Model RADCC V2
Applicant
Radformation, Inc.
Product Code
IYE · Radiology
Decision Date
Aug 23, 2022
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.5050
Device Class
Class 2
Attributes
Software as a Medical Device
Indications for Use
ClearCheck is intended to assist radiation therapy professionals in generating and assessing the quality of radiotherapy treatment plans. ClearCheck is also intended to assist radiation treatment planners in predicting when a treatment plan might result in a collision between the treatment machine and the patient or support structures.
Device Story
Software-only application; runs on Windows OS; used by radiation oncology personnel in clinical settings. Inputs: treatment data, image data, structure sets from Treatment Planning Systems (TPS) via APIs. Function: performs dosimetric/plan evaluation; calculates BED/EQD2; manages prescriptions; evaluates dose on deformed image sets; simulates gantry/applicator/OBI arm geometry to detect collisions with patient/support structures. Output: plan quality metrics, collision alerts, 3D/2D visual collision inspection. Benefits: assists clinicians in plan validation, improves workflow efficiency, enhances patient safety by identifying potential mechanical collisions.
Clinical Evidence
No clinical trials performed. Bench testing only. Validation of BED/EQD2 functionality compared results against manual calculations (passing criteria: 0.5% dose, 3% volume). Deformed dose functionality validated against known dose deformations using qualitative DVH analysis and quantitative Dmax/Dmin comparison (passing criteria: +/-3%). All verification and validation test cases passed.
Technological Characteristics
Computer-based software; Windows OS; standalone application. Uses TPS/API-provided data (CT, structure sets, treatment plans). Collision detection models linac components (gantry, SRS/electron cones) as cylinders/prisms. Connectivity via TPS APIs. No energy delivery. Software-only.
Indications for Use
Indicated for radiation therapy professionals and treatment planners to assist in generating/assessing radiotherapy treatment plan quality and predicting collisions between treatment machines and patients/support structures.
Regulatory Classification
Identification
A medical charged-particle radiation therapy system is a device that produces by acceleration high energy charged particles (e.g., electrons and protons) intended for use in radiation therapy. This generic type of device may include signal analysis and display equipment, patient and equipment supports, treatment planning computer programs, component parts, and accessories.
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Radformation, Inc. % Kurt Sysock Co-founder/CEO 335 Madison Avenue, 4th Floor NEW YORK NY 10017
Re: K220583
Trade/Device Name: ClearCheck Model RADCC V2 Regulation Number: 21 CFR 892.5050 Regulation Name: Medical charged-particle radiation therapy system Regulatory Class: Class II Product Code: IYE Dated: July 20, 2022 Received: July 22, 2022
Dear Kurt Sysock:
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/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 devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see
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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,
for
Julie Sullivan. 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) K220583
R220963
Device Name ClearCheck
#### Indications for Use (Describe)
ClearCheck is intended to assist radiation therapy professionals in generating and assessing the quality of radiotherapy treatment plans. ClearCheck is also intended to assist radiation treatment planners in predicting when a treatment plan might result in a collision between the treatment machine and the patient or support structures.
| Type of Use (Select one or both, as applicable) | |
|---------------------------------------------------------------------------------------|--|
| <span style="font-size: large;">☑</span> Prescription Use (Part 21 CFR 801 Subpart D) | |
| <span style="font-size: large;">☐</span> Over-The-Counter Use (21 CFR 801 Subpart C) | |
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This 510(k) Summary has been created per the requirements of the Safe Medical Device Act (SMDA) of 1990, and the content is provided in conformance with 21 CFR Part 807.92.
# 5.1. Submitter's Information
| Table 1 : Submitter's Information | |
|-----------------------------------|------------------------------------------------------|
| Submitter's Name: | Kurt Sysock |
| Company: | Radformation, Inc. |
| Address: | 335 Madison Avenue, 16th Floor<br>New York, NY 10017 |
| Contact Person: | Alan Nelson<br>Chief Science Officer, Radformation |
| Phone: | 518-888-5727 |
| Fax: | ---------- |
| Email: | anelson@radformation.com |
| Date of Summary Preparation | 08/23/2022 |
# 5.2. Device Information
| Table 2 : Device Information | |
|------------------------------|---------------------------------------------------|
| Trade Name: | ClearCheck |
| Common Name: | Oncology Information System |
| Classification Name: | Class II |
| Classification: | Medical charged-particle radiation therapy system |
| Regulation Number: | 892.5050 |
| Product Code: | IYE |
| Classification Panel: | Radiology |
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## 5.3. Predicate Device Information
#### Primary Predicate Device
ClearCheck Model RADCC V2 (Subject Device) makes use of its prior submission -ClearCheck Model RADCC (K162468) - as the Primary Predicate Device.
### Secondary Predicate Device
With the addition of the Collision Check module included in the submission, ClearCheck Model RADCC V2 also makes use of CollisionCheck Model RADCO (K171350) as a Secondary Predicate Device for the additional functionality.
### 5.4. Device Description
The ClearCheck Model RADCC V2 device is software that uses treatment data, image data, and structure set data obtained from supported Treatment Planning System and Application Programming Interfaces to present radiotherapy treatment plans in a user-friendly way for user approval of the treatment plan. The ClearCheck device (Model RADCC V2) is also intended to assist users to identify where collisions between the treatment machine and the patient or support structures may occur in a treatment plan.
It is designed to run on Windows Operating Systems. ClearCheck Model RADCC V2 performs calculations on the incoming supported treatment data. Supported Treatment Planning Systems are used by trained medical professionals to simulate radiation therapy treatments for malignant or benign diseases.
### 5.5. Indications for Use
ClearCheck is intended to assist radiation therapy professionals in generating and assessing the quality of radiotherapy treatment plans. ClearCheck is also intended to assist radiation treatment planners in predicting when a treatment plan might result in a collision between the treatment machine and the patient or support structures.
### 5.6. Technological Characteristics
### Primary Predicate Device
ClearCheck Model RADCC V2 (Subject Device) makes use of its prior submission -ClearCheck Model RADCC (K162468) - as the Primary Predicate Device.
The functionality and technical components of this prior submission remain unchanged in ClearCheck Model RADCC V2. This submission is intended to build on the functionality and technological components of the 510(k) cleared ClearCheck Model RADCC.
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The main technological characteristics of the subject device and the Primary Predicate device remain the same. Both are computer-based software devices designed to run on Windows Operating Systems. Both use treatment data, image data, and structure set data obtained from supported Treatment Planning System and Application Programming Interfaces to present radiotherapy treatment plans in a user-friendly way for user approval of the treatment plan. Both devices share major functionality such as Dose Constraints, Plan Checks, Plan Reporting and Plan Comparison. Both are used by trained medical professionals to assist in the treatment planning process.
The submission for ClearCheck Model RADCC V2 contains additional functionality to assist in the plan generation process. The significant changes to the previously cleared devices (Primary and Secondary Predicates) are:
- 1. Prescriptions may be entered and managed within the software.
- 2. Radiation dose may be evaluated on different image sets through the use of a deformable registration object provided by Radformation's AutoContour Model RADAC V2 (K220598) software.
- 3. Biologically Equivalent Dose (BED) and Equivalent Dose in 2 Gy fractions (EQD2) may be evaluated for plans and plan sums.
- 4. Additional Dose Constraints and Plan Checks added.
- 5. Addition of a Collision Check module that alerts the user to a potential collision between the treatment machine and the patient or support structures. The Secondary Predicate Device is now included in the Subject device with additional features as stated below.
- 6. Additional reporting features.
### Secondary Predicate Device
ClearCheck Model RADCC V2 (Subject Device) also makes use of CollisionCheck Model RADCO (K171350) as a Secondary Predicate Device for the additional functionality of the Collision Check module.
The Collision Check module within ClearCheck Model RADCC V2 is an updated version of the previously cleared CollisionCheck Model RADCO device. The core functionality of the Collision Check module is the same as in the Secondary Predicate Device, however additional features have been added. Treatment device components such as gantry head, SRS cones and Electron cones are modeled in the same way as they are in the Secondary Predicate Device. Similarly, SUPPORT, BOLUS and patient EXTERNAL structures are modeled in the same way as in the Secondary Predicate device. Collision calculations between the two classes of structures remain the same as in the Secondary Predicate Device, where a collision occurs if any part of a Treatment device component is found within a SUPPORT, BOLUS, or patient EXTERNAL structure for the particular
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plan geometry. HU collisions are calculated in the same way as in the Secondary Predicate Device as well.
The added features to the Collision Check module in the Subject Device are as follows:
- 1. The ability to assess collisions with kV On Board Imaging arms (OBI)
- 2. The ability to detect collision warnings, i.e. situations where there is no collision detected but two objects are within a user defined warning distance of each other.
- 3. Sticky settings
- 4. Printing capabilities
| Table 3: Substantial Equivalence ClearCheck Model RADCC V2 vs.<br>Primary Predicate: ClearCheck Model RADCC (K162468)<br>and Secondary Predicate: CollisionCheck Model RADCO (K171350) | | | | |
|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------|
| Parameters | Subject Device:<br>ClearCheck Model<br>RADCC V2 | Primary<br>Predicate:<br>ClearCheck<br>Model RADCC<br>(K162468) | Secondary<br>Predicate:<br>CollisionCheck<br>Model RADCO<br>(K171350) | Equivalence |
| Indications for<br>Use | ClearCheck is<br>intended to assist<br>radiation therapy<br>professionals in<br>generating and<br>assessing the quality<br>of radiotherapy<br>treatment plans.<br>ClearCheck is also<br>intended to assist<br>radiation treatment<br>planners in predicting<br>when a treatment<br>plan might result in a<br>collision between the<br>treatment machine<br>and the patient or<br>support structures. | ClearCheck is<br>intended for<br>quality<br>assessment of<br>radiotherapy<br>treatment plans | CollisionCheck is<br>intended to assist<br>radiation treatment<br>planners in predicting<br>when a treatment<br>plan might result in a<br>collision between the<br>treatment machine<br>and the patient or<br>support structures. | Equivalent to<br>Primary and<br>Secondary<br>Predicates |
| Energy Used<br>and/or Delivered | None - software-only<br>application. The<br>software application<br>does not deliver or<br>depend on energy<br>delivered to or from<br>patients. | None -<br>software-only<br>application. The<br>software<br>application does<br>not deliver or<br>depend on<br>energy delivered<br>to or from | None - software-only<br>application. The<br>software application<br>does not deliver or<br>depend on energy<br>delivered to or from<br>patients. | Equivalent to<br>both Primary<br>and Secondary<br>Predicates |
| | | patients. | | |
| Intended users | Trained clinically<br>qualified radiation<br>oncology personnel | Trained clinically<br>qualified<br>radiation<br>oncology<br>personnel | Trained clinically<br>qualified radiation<br>oncology personnel | Equivalent to<br>both Primary<br>and Secondary<br>Predicates |
| OTC/Rx | Rx | Rx | Rx | Equivalent to<br>both Primary<br>and Secondary<br>Predicates |
| Functionality | Performs dosimetric<br>and plan evaluation<br>for Radiation<br>Treatment Plans. Also<br>simulates the plan<br>and predicts whether<br>that no gantry<br>collisions occur with<br>patient or support<br>structures | Performs<br>dosimetric and<br>plan evaluation<br>for Radiation<br>Treatment Plans. | Simulates the plan<br>and predicts<br>whether any gantry<br>collisions occur with<br>patient or support<br>structures. | Equivalent to<br>both Primary<br>and Secondary<br>Predicates |
| Design:<br>Graphical User<br>Interface | Contains a Data<br>Visualization /<br>Graphical User<br>Interface | Contains a Data<br>Visualization /<br>Graphical User<br>Interface | Contains a Data<br>Visualization /<br>Graphical User<br>Interface | Equivalent to<br>both Primary<br>and Secondary<br>Predicates |
| Design:<br>Supported Files | Files/Treatment<br>Planning System<br>API-provided data<br>containing CT,<br>Structure Set, and<br>Treatment Plan<br>(including treatment<br>field parameters) data | Files/Treatment<br>Planning System<br>API-provided<br>data containing<br>CT, Structure<br>Set, and<br>Treatment Plan<br>(including<br>treatment field<br>parameters) data | Files/Treatment<br>Planning System<br>API-provided data<br>containing CT,<br>Structure Set, and<br>Treatment Plan<br>(including treatment<br>field parameters) data | Equivalent to<br>both Primary<br>and Secondary<br>Predicates |
| Design:<br>Calculation<br>Requirements | Uses local hardware | Uses local<br>hardware | Uses local hardware | Equivalent to<br>both Primary<br>and Secondary<br>Predicates |
| Design:<br>Reporting | Reporting built-in and<br>user has ability to<br>customize | Reporting built-in<br>and user has<br>ability to<br>customize | No reporting<br>capabilities | Equivalent to<br>Primary<br>Predicate |
| Pure software | Yes | Yes | Yes | Equivalent to<br>both Primary |
| | | | | and Secondary<br>Predicates |
| Operating<br>System | Windows Operating<br>System | Windows<br>Operating<br>System | Windows Operating<br>System | Equivalent to<br>both Primary<br>and Secondary<br>Predicates |
| Input | Treatment data,<br>image data, and<br>structure set data<br>obtained from<br>supported Treatment<br>Planning System and<br>Application<br>Programming<br>interfaces | Treatment data,<br>image data, and<br>structure set data<br>obtained from<br>supported<br>Treatment<br>Planning System<br>and Application<br>Programming<br>interfaces | Treatment data,<br>image data, and<br>structure set data<br>obtained from<br>supported Treatment<br>Planning System and<br>Application<br>Programming<br>interfaces | Equivalent to<br>both Primary<br>and Secondary<br>Predicates |
| ClearCheck Model RADCC V2 vs. ClearCheck Model RADCC (K162468) Functionality Comparison | | | | |
| Dose<br>Constraints | Additional dose<br>constraints added | Initial set of dose<br>constraints | N/A | Minor<br>differences<br>with Primary<br>Predicate |
| Plan Checks | Additional plan<br>checks added | Initial set of plan<br>checks | N/A | Minor<br>differences<br>with Primary<br>Predicate |
| Create Users<br>and Edit User<br>Rights | Addition of option to<br>authenticate with<br>Active Directory<br>credentials | User rights<br>managed by<br>Administration<br>Application | N/A | Minor<br>differences<br>with Primary<br>Predicate |
| Global and<br>Patient Specific<br>Templates | Addition of<br>Prescription<br>templates and overall<br>improvements to<br>template usability | Initial set of dose<br>constraint and<br>plan check<br>templates | N/A | New Feature /<br>Minor<br>differences<br>with Primary<br>Predicate |
| Reporting | Improvements to<br>report usability | Initial reporting<br>functionality | N/A | Minor<br>differences<br>with Primary<br>Predicate |
| Compare<br>Treatment Plans | Improvements to plan<br>comparison usability | Initial plan<br>comparison<br>functionality | N/A | Minor<br>differences<br>with Primary<br>Predicate |
| Prescription | Physician prescriptions may be entered and managed in the ClearCheck software. | N/A | N/A | New Feature |
| Deformed Dose Evaluation | Radiation dose may be evaluated on different image sets through the use of a deformable registration object. | N/A | N/A | New Feature |
| BED/EQD2 dose | Ability to evaluate BED/EQD2 for plans and plan sums | N/A | N/A | New Feature |
| ClearCheck Model RADCC V2 vs. CollisionCheck Model RADCO (K171350) Functionality Comparison | | | | |
| Parameters | Subject Device:<br>ClearCheck Model<br>RADCC V2 | N/A | Secondary Predicate:<br>CollisionCheck<br>(K171350) | Equivalence |
| Simulation Details | Simulates the plan and predicts whether any gantry collisions occur with patient or support structures. Calculates gantry clearance by modeling the linac as a cylinder with a user-configured value for distance between isocenter and the face of the gantry. Collision Check also supports additional applicators: Stereotactic radiosurgery cones (also modeled as a cylinder) and Electron Applicators (modeled as a rectangular prism). ClearCheck also simulates the on-board imaging (OBI) arms as a rectangular prism. User can define a | N/A | Simulates the plan and predicts whether any gantry collisions occur with patient or support structures. Calculates gantry clearance by modeling the linac as a cylinder with a user-configured value for distance between isocenter and the face of the gantry. CollisionCheck also supports additional applicators: Stereotactic radiosurgery cones (also modeled as a cylinder) and Electron Applicators (modeled as a rectangular prism). | Minor differences with Secondary Predicate |
| | warning distance that<br>adds a margin to the<br>shapes in the<br>simulation. | | | |
| Collision Check<br>Output | Collision Check tests<br>thousands of sample<br>points against CT<br>data and patient and<br>couch structures and<br>reports the number of<br>sample points that<br>resulted in a collision.<br>Collision Check also<br>displays these<br>sample point test<br>results with a 3D<br>display and an axial<br>2D image plane<br>viewer for the user to<br>inspect the results.<br>If the user has<br>defined warning<br>distances, then<br>collisions within the<br>warning margin are<br>presented to the user<br>with a different color<br>and label. | N/A | Collision Check tests<br>thousands of sample<br>points against CT<br>data and patient and<br>couch structures and<br>reports the number of<br>sample points that<br>resulted in a collision.<br>Collision Check also<br>displays these<br>sample point test<br>results with a 3D<br>display and an axial<br>2D image plane<br>viewer for the user to<br>inspect the results. | Minor<br>differences<br>with Secondary<br>Predicate |
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### 5.7. Performance Data
As with the Primary and Secondary Predicates, no clinical trials were performed for ClearCheck Model RADCC V2. Verification tests were performed to ensure that the software works as intended and pass/fail criteria were used to verify requirements.
Validation testing for the added BED / EQD2 functionality compared ClearCheck's results on a plan and plan sum against values calculated by hand using the well-known BED / EQD2 formulas. A passing criteria of 0.5% difference for dose type constraints and 3% for Volume type constraints was used. Validation testing for the added Deformed
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Dose functionality compared known dose deformations to the deformed dose results from ClearCheck. Qualitative dose-volume histogram (DVH) analysis showed good agreement for all cases and evaluation of Dman and Dmax differences used a quantitative +/-3% difference to achieve a passing result. The verification and validation testing passed in all test cases.
## 5.8. Conclusion
ClearCheck Model RADCC V2 is substantially equivalent to the Primary Predicate Device, ClearCheck Model RADCC (K162468). Additionally, the Collision Check module found within ClearCheck Model RADCC V2 is substantially equivalent to the Secondary Predicate Device, CollisionCheck Model RADCO (K171350). The minor technological differences between ClearCheck and the Primary and Secondary Predicate Devices do not raise any questions on the safety and effectiveness of the Subject Device. Verification and Validation testing and the Risk Management Report demonstrate that the ClearCheck is as safe and effective as the Primary and Secondary Predicates.
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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?
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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).
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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.
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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.
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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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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?
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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.
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Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
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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.