K220582 · Radformation, Inc. · MUJ · Aug 22, 2022 · Radiology
Device Facts
Record ID
K220582
Device Name
ClearCalc Model RADCA V2
Applicant
Radformation, Inc.
Product Code
MUJ · Radiology
Decision Date
Aug 22, 2022
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.5050
Device Class
Class 2
Attributes
Software as a Medical Device
Indications for Use
ClearCalc is intended to assist radiation treatment planners in determining if their treatment planning calculations are accurate using an independent Monitor Unit (MU) and dose calculation algorithm.
Device Story
ClearCalc Model RADCA V2 is software for radiation oncology quality assurance; assists clinicians in verifying treatment planning system (TPS) accuracy. Inputs include patient CT, structure sets, treatment plans (field parameters), and machine treatment log files via TPS APIs. Operates by performing independent dose/MU calculations using either a Finite-Size Pencil Beam (FSPB) algorithm or a new Monte Carlo-based engine (RadMonteCarlo). Also supports sector integration for electron cutout factors and AAPM TG-43 protocol for brachytherapy. Output is displayed in a GUI, providing per-field MU, dose metrics, and difference comparisons against TPS values. Used by trained radiation oncology personnel to simulate treatments. Helps ensure delivery accuracy by identifying potential calculation errors before treatment delivery, potentially improving patient safety.
Clinical Evidence
Bench testing only. No clinical trials performed. Validation testing compared ClearCalc results against known planning parameters from clinically-utilized TPS. Monte Carlo calculations validated using gamma analysis (passing rate >93% with 3%/3mm criteria). FSPB, TG-71, and TG-43 algorithms maintained consistency with predicate device performance.
Technological Characteristics
Software-only application; runs on Windows OS. Algorithms: Finite-Size Pencil Beam (FSPB), Monte Carlo (RadMonteCarlo), sector integration for electron cutouts, AAPM TG-43 for brachytherapy. Inputs: CT, structure sets, treatment plans, machine log files. Connectivity: TPS/API integration. No energy delivery hardware.
Indications for Use
Indicated for radiation treatment planners to verify accuracy of treatment planning calculations for malignant or benign diseases using independent MU and dose calculation algorithms.
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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Image /page/0/Picture/0 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 words "U.S. FOOD & DRUG" on one line and "ADMINISTRATION" on the line below. The FDA logo is in blue.
Radformation, Inc. % Kurt Sysock Co-founder/CEO 335 Madison Avenue, 4th floor NEW YORK NY 10017
Re: K220582
Trade/Device Name: ClearCalc Model RADCA V2 Regulation Number: 21 CFR 892.5050 Regulation Name: Medical charged-particle radiation therapy system Regulatory Class: Class II Product Code: MUJ Dated: July 18, 2022 Received: July 21, 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/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 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)
#### K220582
Device Name ClearCalc Model RADCA V2
Indications for Use (Describe)
ClearCalc is intended to assist radiation treatment planners in determining if their treatment planning calculations are accurate using an independent Monitor Unit (MU) and dose calculation algorithm.
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)
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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.
| 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 | 8/21/2022 |
# 5.1. Submitter's Information
# 5.2. Device Information
| Table 2 : Device Information | |
|------------------------------|-----------------------------------------------------------------------------------|
| Trade Name: | ClearCalc Model RADCA V2 |
| Common Name: | Secondary Check Quality Assurance Software, Patient<br>Quality Assurance Software |
| Classification Name: | Class II |
| Classification: | Medical charged-particle radiation therapy system |
| Regulation Number: | 892.5050 |
| Product Code: | MUJ |
| Classification Panel: | Radiology |
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# 5.3. Predicate Device and Reference Device Information
### Primary Predicate Device
ClearCalc Model RADCA V2 (Subject Device) makes use of its prior submission - ClearCalc Model RADCA (K193640) - as the primary Predicate Device.
### Reference Devices
With the additions included in the submission, ClearCalc Model RADCA V2 also makes use of RadCalc Version 7.1 (K193381) and myQA iON (K201798) as Reference Devices for the new functionality.
# 5.4. Device Description
The ClearCalc Model RADCA 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 perform a dose and/or monitor unit (MU) calculation on the incoming treatment planning parameters. It is designed to assist radiation treatment planners in determining if their treatment planning calculations are accurate using an independent Monitor Unit (MU) and dose calculation algorithm.
# 5.5. Indications for Use
ClearCalc is intended to assist radiation treatment planners in determining if their treatment planning calculations are accurate using an independent Monitor Unit (MU) and dose calculation algorithm.
# 5.6. Technological Characteristics
### Predicate Device
ClearCalc Model RADCA V2 (Subject Device) makes use of its prior submission - ClearCalc Model RADCA (K193640) - as the Predicate Device. The functionality and technical components of this prior submission remain unchanged in ClearCalc Model RADCA V2. This submission is intended to build on the functionality and technological components of the 510(k) cleared ClearCalc Model RADCA.
Similar to the Predicate Device software, ClearCalc Model RADCA V2 is designed to run on Windows Operating Systems, performs dose and/or monitor unit (MU) calculations on the incoming supported treatment data, and displays the calculated results to the user. Supported Treatment Planning System and Application Programming Interfaces are used by trained, clinically-qualified radiation oncology personnel to simulate radiation therapy treatments for malignant or benign diseases. The intended user base has not changed from the Predicate Device. ClearCalc may call either its local calculation engine (the same finite-size pencil beam algorithm as with the Predicate Device) or now optionally call a monte carlo dose calculation engine to perform dose and/or MU calculations. Though the monte carlo dose calculation
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engine is new functionality, it serves the same purpose as the currently-implemented Finite-Size Pencil Beam (FSPB) algorithm and is launched from the local User Interface (UI). Additionally, this new algorithm is a monte carlo-based calculation, which is the "gold standard" for radiotherapy treatment planning and can improve the accuracy of the results provided by ClearCalc.
Additionally, new input files are being supported with the Subject Device, namely machine treatment log files and virtual source models. Machine log files record the precise machine parameter setting of linear accelerator deliveries during a set treatment delivery. These files record parameters similar to the treatment plan except they are recorded from a pre-treatment delivery at the machine instead of from a Treatment Planning System. Instead of using the treatment planning parameters, ClearCalc will use the delivered treatment parameters from the machine to re-calculate the dose from the given plan. Since the parameters in machine treatment log files are nearly identical to those captured in a treatment plan, this functionality does not raise any new questions in terms of safety and effectiveness compared to the predicate. The virtual source models are used by the monte carlo dose calculation engine to complete calculations and do not affect the current technological functionality when compared to the Predicate Device. Virtual source models are a different way to store pertinent beam data for dose calculation and originate from the beam data already stored in the Predicate Device. As such, they do not raise any new concerns regarding the safety or effectiveness of the Subject Device compared to the predicate.
Due to the technological characteristic similarities, the Subject Device raises no new concerns regarding safety and effectiveness compared to the predicate.
| Table 3: Substantial Equivalence ClearCalc Model RADCA V2 vs. Predicate Device and<br>Reference Devices | | | | |
|---------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Parameters | Subject Device:<br>ClearCalc Model<br>RADCA V2 | Predicate Device:<br>ClearCalc Model<br>RADCA | Reference Device:<br>RadCalc Version<br>7.1 (K193381) | Reference<br>Device:<br>myQA iON<br>(K201798) |
| Summarized<br>Indications<br>for use | Intended to assist<br>radiation treatment<br>planners in<br>determining if their<br>treatment planning<br>calculations are<br>accurate using an<br>independent Monitor<br>Unit (MU) and dose<br>calculation algorithm.<br>(Equivalent) | Intended to assist<br>radiation treatment<br>planners in<br>determining if their<br>treatment planning<br>calculations are<br>accurate using an<br>independent<br>Monitor Unit (MU)<br>and dose<br>calculation<br>algorithm. | A means of<br>validating the<br>monitors units or<br>radiation dose to<br>points that have<br>been calculated by<br>the primary radiation<br>therapy planning<br>system for external<br>beam radiation<br>therapy and/or<br>brachytherapy<br>treatments. In<br>addition to this, | To perform patient<br>quality assurance<br>activities for<br>radiation therapy<br>treatment delivery<br>systems. myQA<br>iON is a software<br>toolbox allowing<br>the<br>Medical Physicist<br>to perform quality<br>assurance<br>activities before<br>and after the |
| | | | RadCalc Software<br>can also be used as<br>the primary means of<br>calculating monitor<br>units for external<br>beam radiation<br>treatments in<br>situations where the<br>physician does not<br>order the use of a<br>radiation therapy<br>plan. Users may also<br>send/receive results<br>from an eternal dose<br>calculation engine,<br>whereby the results<br>are displayed in<br>RadCalc for<br>evaluation. | patient treatment<br>fractions for all<br>patients<br>undergoing<br>radiation therapy. |
| Energy<br>Used and/or<br>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.<br>(Substantially<br>equivalent) | None -<br>software-only<br>application. The<br>software<br>application does<br>not deliver or<br>depend on energy<br>delivered to or<br>from patients. | 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 - software<br>only application.<br>The software<br>application does<br>not deliver or<br>depend on energy<br>delivered to or<br>from patients |
| Intended<br>users | Trained radiation<br>oncology personnel<br>(Substantially<br>equivalent) | Trained radiation<br>oncology<br>personnel | Trained radiation<br>oncology personnel | Trained radiation<br>oncology health<br>professionals |
| OTC/Rx | Rx (Substantially<br>equivalent) | Rx | Rx | Rx |
| Design:<br>Graphical<br>User<br>Interface | Contains a Data<br>Visualization /<br>Graphical User<br>Interface<br>(Substantially<br>Equivalent) | 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 |
| Design:<br>Supported<br>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)<br>data as well as | Files/Treatment<br>Planning System<br>API-provided data<br>containing CT,<br>Structure Set, and<br>Treatment Plan<br>(including<br>treatment field<br>parameters) data | Files containing<br>Structure Set, and<br>Treatment Plan<br>(including treatment<br>field parameters)<br>data | Files containing<br>Structure Set, and<br>Treatment Plan<br>(including<br>treatment field<br>parameters) data<br>as well as machine<br>treatment log files |
| | machine treatment<br>log files<br>(Substantially<br>equivalent) | | | |
| Design:<br>Reporting<br>and data<br>routing | Reporting built-in<br>and user has ability<br>to customize<br>(Substantially<br>equivalent) | Reporting built-in<br>and user has<br>ability to customize | Reporting built-in<br>and user has ability<br>to customize | Reporting built-in<br>and user has<br>ability to customize |
| Input | 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)<br>data (Substantially<br>equivalent) | Files/Treatment<br>Planning System<br>API-provided data<br>containing CT,<br>Structure Set, and<br>Treatment Plan<br>(including<br>treatment field<br>parameters) data | Files containing<br>Structure Set, and<br>Treatment Plan<br>(including treatment<br>field parameters)<br>data | N/A |
| Functionality | Utilizes a Finite-Size<br>Pencil Beam (FSPB)<br>algorithm to calculate<br>MU/Dose on a<br>per-field<br>basis.ClearCalc<br>utilizes the full 3D<br>geometry of the<br>patient for<br>heterogeneity<br>corrections and<br>simulating the scatter<br>conditions of the<br>actual patient. Users<br>may also<br>send/receive data<br>from its monte carlo<br>dose calculation<br>engine (branded as<br>RadMonteCarlo),<br>whereby the results<br>are displayed in<br>ClearCalc for<br>evaluation.<br>(Substantially<br>equivalent) | Utilizes a<br>Finite-Size Pencil<br>Beam (FSPB)<br>algorithm to<br>calculate MU/Dose<br>on a per-field<br>basis.ClearCalc<br>utilizes the full 3D<br>geometry of the<br>patient for<br>heterogeneity<br>corrections and<br>simulating the<br>scatter conditions<br>of the actual<br>patient. | Utilizes a Clarkson<br>summation algorithm<br>to calculate<br>MU/Dose on a<br>per-field basis.<br>RadCalc utilizes a<br>consistent flat<br>phantom geometry<br>using radiological<br>equivalent depth for<br>heterogeneity<br>corrections and<br>includes modules<br>that allow the user to<br>indicate changes in<br>scatter conditions<br>(e.g. for breast<br>treatments). Users<br>may also<br>send/receive results<br>from an eternal dose<br>calculation engine,<br>whereby the results<br>are displayed in<br>RadCalc for<br>evaluation. | N/A |
| Output | ClearCalc calculates<br>the dose from fields | ClearCalc<br>calculates the | RadCalc calculates<br>the dose from fields | N/A |
| | in a plan and<br>displays results for<br>per-field MU and<br>provides a difference<br>metric for evaluation<br>in tabular format.<br>Users can also<br>evaluate global point<br>doses, as well as<br>per-field doses and,<br>when applicable, a<br>generated dose<br>volume histogram..<br>(Substantially<br>equivalent) | dose from fields in<br>a plan and<br>displays results for<br>per-field MU and<br>provides a<br>difference metric<br>for evaluation in<br>tabular format.<br>Users can also<br>evaluate global<br>point doses, as<br>well as per-field<br>doses. | in a plan and<br>displays results for<br>per-field MU and<br>provides a difference<br>metric for evaluation<br>in tabular format.<br>Users can also<br>evaluate global point<br>doses, as well as<br>per-field doses. | |
| | ClearCalc vs. Predicate Devices Electron MU and Dose Calculation | | | |
| Input | 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)<br>data (Substantially<br>equivalent) | Files/Treatment<br>Planning System<br>API-provided data<br>containing CT,<br>Structure Set, and<br>Treatment Plan<br>(including<br>treatment field<br>parameters) data | Files containing<br>Treatment Plan<br>(including treatment<br>field parameters)<br>data | N/A |
| Functionality | Utilize a library of<br>custom cutouts and<br>computes cutout<br>factors using a<br>sector integration<br>method. Cutout<br>factors may also be<br>user-entered. Users<br>may also<br>send/receive results<br>from its monte carlo<br>dose calculation<br>engine (branded as<br>RadMonteCarlo),<br>whereby the results<br>are displayed in<br>ClearCalc for<br>evaluation.<br>(Substantially<br>equivalent) | Utilize a library of<br>custom cutouts<br>and computes<br>cutout factors<br>using a sector<br>integration<br>method. Cutout<br>factors may also<br>be user-entered. | Utilize a library of<br>custom cutouts and<br>computes cutout<br>factors using a<br>sector integration or<br>square root method.<br>Cutout factors may<br>also be user-entered.<br>Users may also<br>send/receive results<br>from an eternal dose<br>calculation engine,<br>whereby the results<br>are displayed in<br>RadCalc for<br>evaluation. | N/A |
| Output | ClearCalc calculates<br>dose based on<br>electron field | ClearCalc<br>calculates dose<br>based on electron | RadCalc calculates<br>dose based on<br>electron field | N/A |
| | parameters and<br>cutout geometry, and<br>displays results for<br>per-field MU and/or<br>dose and provides a<br>difference metric for<br>evaluation in tabular<br>format and, when<br>applicable, a<br>generated dose<br>volume histogram.<br>(Substantially<br>equivalent) | field parameters<br>and cutout<br>geometry, and<br>displays results for<br>per-field MU<br>and/or dose and<br>provides a<br>difference metric<br>for evaluation in<br>tabular format. | parameters and<br>cutout geometry, and<br>displays results for<br>per-field MU and/or<br>dose and provides a<br>difference metric for<br>evaluation in tabular<br>format. | |
| | ClearCalc vs. RadCalc Brachytherapy Dose Calculation | | | |
| Input | Files or Treatment<br>Planning System<br>API-provided data<br>containing Treatment<br>Plan (including<br>source positions and<br>dwell times) data<br>(Substantially<br>equivalent) | Files or Treatment<br>Planning System<br>API-provided data<br>containing<br>Treatment Plan<br>(including source<br>positions and dwell<br>times) data | Files containing<br>Treatment Plan<br>(including source<br>positions and dwell<br>times) data | N/A |
| Functionality | Utilizes the AAPM<br>TG-43 protocol for its<br>brachytherapy dose<br>calculations<br>(Substantially<br>equivalent) | Utilizes the AAPM<br>TG-43 protocol for<br>its brachytherapy<br>dose calculations | Utilizes the AAPM<br>TG-43 protocol for its<br>brachytherapy dose<br>calculations | N/A |
| Output | ClearCalc calculates<br>dose to arbitrary<br>calculation point<br>locations and<br>presents difference<br>metrics comparing<br>the TPS dose vs.<br>ClearCalc dose in a<br>tabular format.<br>(Substantially<br>equivalent) | ClearCalc<br>calculates dose to<br>arbitrary<br>calculation point<br>locations and<br>presents difference<br>metrics comparing<br>the TPS dose vs.<br>ClearCalc dose in<br>a tabular format. | RadCalc calculates<br>dose to arbitrary<br>calculation point<br>locations and<br>presents difference<br>metrics comparing<br>the TPS dose vs.<br>RadCalc dose in a<br>tabular format. | N/A |
| Parameters | Subject Device:<br>ClearCalc Model<br>RADCA V2 | Predicate Device:<br>ClearCalc Model<br>RADCA | Predicate Device:<br>RadCalc Version<br>7.1 (K193381) | Predicate Device:<br>myQA iON<br>(K201798) |
| ClearCalc vs. myQA iON Proton MU and Dose Calculation | | | | |
| Input | Files/Treatment<br>Planning System | N/A | N/A | Files containing<br>Structure Set, and |
| | API-provided data<br>containing CT,<br>Structure Set, and<br>Treatment Plan<br>(including treatment<br>field parameters)<br>data (Minor<br>differences) | | | Treatment Plan<br>(including<br>treatment field<br>parameters) data |
| Functionality | Sends/receives data<br>from its monte carlo<br>dose calculation<br>engine (branded as<br>RadMonteCarlo) to<br>calculate proton<br>plans from the<br>necessary files and<br>displays the results<br>to the user.<br>(Substantially<br>equivalent) | N/A | N/A | Sends/receives<br>data from an<br>external dose<br>calculation engine<br>to calculate proton<br>plans from the<br>necessary files<br>and displays the<br>results to the user. |
| Output | ClearCalc displays<br>the dose results<br>received from the<br>RadMonteCarlo dose<br>calculation engine<br>and allows the user<br>to analyze the results<br>in the UI.<br>(Substantially<br>equivalent) | N/A | N/A | myQA iON<br>displays the dose<br>results received<br>from the external<br>dose calculation<br>engine and allows<br>the user to analyze<br>the results in the<br>UI. |
| ClearCalc vs. myQA iON Machine Treatment Log File Analysis | | | | |
| Input | Files or Treatment<br>Planning System<br>API-provided data<br>containing Treatment<br>Plan data as well as<br>machine log files<br>from a pre-treatment<br>or treatment session<br>(Substantially<br>equivalent) | N/A | N/A | Files containing<br>Treatment Plan<br>data as well as<br>machine log files<br>from a<br>pre-treatment or<br>treatment session |
| Functionality | Utilizes the machine<br>logs files to<br>reconstruct the<br>delivered dose<br>utilizing a dose<br>calculation from the<br>set machine<br>parameters. | N/A | N/A | Utilizes the<br>machine logs files<br>to reconstruct the<br>delivered dose<br>utilizing a dose<br>calculation from the<br>set machine<br>parameters. |
| | (Substantially<br>equivalent) | | | |
| Output | ClearCalc displays<br>the log file<br>calculation result to<br>the user via<br>displayed dose<br>information and<br>provides a difference<br>metric for evaluation.<br>(Substantially<br>equivalent) | N/A | N/A | myQA iON<br>displays the log file<br>calculation result<br>to the user via<br>displayed dose<br>information and<br>provides a<br>difference metric<br>for evaluation. |
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# 5.7. Performance Data
As with the Predicate Device and Reference Devices, no clinical trials were performed for ClearCalc. Verification tests were performed to ensure that the software works as intended and passffail criteria were used to verify requirements. Validation testing was performed to ensure that the software was behaving as intended, and results from ClearCalc were validated against accepted results for known planning parameters from clinically-utilized treatment planning systems. All passing criteria for ClearCalc's primary dose calculation algorithms (FSPB for photon plans, TG-71 for electron plans, and TG-43 for brachytherapy plans) remain consistent with the Predicate Device. Passing criteria for monte carlo calculations was a gamma analysis passing rate of >93% with +/-3% relative dose agreement and 3mm distance to agreement (DTA). The verification and validation testing passed in all test cases.
### 5.8. Conclusion
ClearCalc Model RADCA V2 is deemed substantially equivalent to the scope of Predicate Device, ClearCalc Model RADCA (K193640). Additional functionality for monte carlo calculations was supported with Reference Device RadCalc Version 7.1 (K1933981) and proton and machine treatment log file analysis for photons functionality was demonstrated with Reference Device myQA iON (K201798). Verification and Validation testing and the Risk Management Report demonstrate that ClearCalc is as safe and effective as the Predicate Device and Reference Devices. The minor technological differences between ClearCalc and the Predicate Device and Reference Devices do not raise any questions on the safety and effectiveness of the Subject Device.
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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.