The TeraRecon Neuro Algorithm is an algorithm for use by trained professionals, including but not limited to physicians, surgeons and medical clinicians. The TeraRecon Neuro Algorithm is a standalone image processing software device that can be deployed as a Microsoft Windows executable on off-the-shelf hardware or as a containerized application (e.g., a Docker container) that runs on off-the-shelf hardware or on a cloud platform. Data and images are acquired via DICOM compliant imaging devices. DICOM results may be exported, combined with, or utilized by other DICOM-compliant systems and results. The TeraRecon Neuro Algorithm provides analysis capabilities for functional, dynamic, and derived imaging datasets acquired with CT or MRI. It can be used for the analysis of dynamic brain perfusion image data, showing properties of changes in contrast over time. This functionality includes calculation of parameters related to brain tissue perfusion, vascular assessment, tissue blood volume, and other parametric maps with or without the ventricles included in the calculation. The algorithm also include volume reformat in various orientation, rotational MIP 3D batch while removing the skull. This "tumble view" allows qualitative review of vascular structure in direct correlation to the perfusion maps for comprehensive review. The results of the TeraRecon Neuro Algorithm can be delivered to the end-user through image viewers such as TeraRecon's Aquarius Intuition system, TeraRecon's Eureka AI Results Explorer, TeraRecon's Eureka Clinical AI Platform, or other image viewing systems like PACS that can support DICOM results generated by the TeraRecon Neuro Algorithm. The TeraRecon Neuro Algorithm results are designed for use by trained healthcare professionals and are intended to assist the physician in diagnosis, who is responsible for making all final patient management decisions.
Device Story
TeraRecon Neuro is a standalone image processing software for brain perfusion analysis. It ingests DICOM-compliant CT or MRI datasets; performs motion correction; calculates perfusion parameters (TTP, TOT, RT, MTT, BV/CBV, BF/CBF, Tmax) and generates mismatch/hypoperfusion maps. It provides 2D/3D visualizations, including skull-stripped rotational MIPs. Deployed as a Windows executable or Docker container on off-the-shelf hardware or cloud platforms. Operated by trained healthcare professionals (physicians/surgeons) in clinical settings. Results are delivered to PACS or TeraRecon viewing platforms (Aquarius Intuition, Eureka AI). Physicians use these outputs to aid diagnosis, treatment planning, and post-treatment monitoring. The device provides analytical support to speed decision-making; however, the physician retains final responsibility for patient management decisions.
Clinical Evidence
Bench testing only. Included software verification/validation per IEC 62304 and ISO 14971. Quantitative phantom testing evaluated Tmax measurements against reference devices (K193289, K182130) using limit of agreement metrics. Qualitative clinical user evaluation by a physician confirmed map equivalence (>=85%) compared to predicate and reference devices.
Technological Characteristics
Standalone software; Windows executable or Docker container. Interoperable with DICOM-compliant CT/MRI scanners and PACS. Uses SVD-based mathematical modeling for perfusion. Features motion correction, ventricle subtraction, and parametric mapping (TTP, TOT, RT, MTT, BV, BF, Tmax, mismatch/hypoperfusion). Software lifecycle follows IEC 62304; risk management per ISO 14971.
Indications for Use
Indicated for use by trained professionals (physicians, surgeons, clinicians) to analyze functional, dynamic, and derived CT or MRI brain perfusion datasets. Assists in diagnosis, treatment planning, and post-treatment evaluation by calculating perfusion parameters and generating parametric maps.
Regulatory Classification
Identification
A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.
Special Controls
*Classification.* Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
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TeraRecon, Inc Michael Sosebee Official Correspondent 4309 Emperor Blvd. Durham, North Carolina 27703
August 12, 2022
Re: K220349
Trade/Device Name: TeraRecon Neuro Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: LLZ Dated: June 28, 2022 Received: June 29, 2022
Dear Michael Sosebee:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for
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devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about 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,
Jessica Lamb, Ph.D.
Assistant Director Imaging Software Team DHT 8B: Division of Radiological Imaging Devices and Electronic Products OHT 8: 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) K220349
Device Name TeraRecon Neuro
### Indications for Use (Describe)
The TeraRecon Neuro Algorithm is an algorithm for use by trained professionals, including but not limited to physicians, surgeons and medical clinicians.
The TeraRecon Neuro Algorithm is a standalone image processing software device that can be deployed as a Microsoft Windows executable on off-the-shelf hardware or as a containerized application (e.g., a Docker container) that runs on off-the-shelf hardware or on a cloud platform. Data and images are acquired via DICOM compliant imaging devices. DICOM results may be exported, combined with, or utilized by other DICOM-compliant systems and results.
The TeraRecon Neuro Algorithm provides analysis capabilities for functional, dynamic, and derived imaging datasets acquired with CT or MRI. It can be used for the analysis of dynamic brain perfusion image data, showing properties of changes in contrast over time. This functionality includes calculation of parameters related to brain tissue perfusion, vascular assessment, tissue blood volume, and other parametric maps with or without the ventricles included in the calculation. The algorithm also include volume reformat in various orientation, rotational MIP 3D batch while removing the skull. This "tumble view" allows qualitative review of vascular structure in direct correlation to the perfusion maps for comprehensive review.
The results of the TeraRecon Neuro Algorithm can be delivered to the end-user through image viewers such as TeraRecon's Aquarius Intuition system, TeraRecon's Eureka AI Results Explorer, TeraRecon's Eureka Clinical AI Platform, or other image viewing systems like PACS that can support DICOM results generated by the TeraRecon Neuro Algorithm.
The TeraRecon Neuro Algorithm results are designed for use by trained healthcare professionals and are intended to assist the physician in diagnosis, who is responsible for making all final patient management decisions.
| Type of Use (Select one or both, as applicable) | |
|--------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------|
| <div> <span> <span style="font-size: 16px;">☑</span> Prescription Use (Part 21 CFR 801 Subpart D) </span> </div> | <div> <span> <span style="font-size: 16px;">☐</span> Over-The-Counter Use (21 CFR 801 Subpart C) </span> </div> |
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# K220349
#### 510(k) Summary 1
## TeraRecon Neuro version 2.0.0
[in accordance with 21CFR 807.92]
#### Submitter 1.1
| 510(k) Sponsor: | TereRecon, Inc. |
|------------------------|------------------------------------------------------|
| Address: | 4309 Emperor Blvd.,<br>Durham, NC 27703, USA |
| Contact Person: | Michael Sosebee<br>Senior Manager RAQA |
| Contact Information: | Email: msosebee@terarecon.com<br>Phone: 704-651-6828 |
| Date Summary Prepared: | 10Feb2022 |
## 1.2 Subject Device
| Proprietary (Trade) Name of Subject Device | TeraRecon Neuro |
|--------------------------------------------|----------------------------------------|
| Model Number | 2.0.0 |
| Device Class | 2 |
| Common / Classification Name | System, Image Processing, Radiological |
| Product Code | LLZ |
| Regulation Number | 892.2050 |
| 510(k) Number | K220349 |
#### 1.3 Predicate Device
| 1.3 Predicate Device | |
|----------------------------------------------|----------------------------------------|
| Proprietary (Trade) Name of Predicate Device | Neuro.AI Algorithm |
| Model Number | 1.0.0 |
| Device Class | 2 |
| Common / Classification Name | System, Image Processing, Radiological |
| Product Code | LLZ |
| Regulation Number | 892.2050 |
| 510(k) Number | K200750 |
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#### 1.4 Device Description
The TeraRecon Neuro algorithm version 2.0.0 is a modification of the predicate device Neuro.AI Algorithm (K200750), which was a modification of the predicate device, Intuition-TDA, TVA, Parametric Mapping (which was cleared under K131447). The predicate device Intuition -TDA, TVA, Parametric Mapping is an optional module/workflow for the Intuition system (K121916). The TeraRecon Neuro algorithm is an image processing software device that can be deployed as a Microsoft Windows executable on off-the-shelf hardware or as a containerized application (e.g., Docker container) that runs on off-the-shelf hardware or on a cloud platform. The device has limited network connectivity or external medical support.
TeraRecon Neuro allows motion correction and processes, calculates and outputs brain perfusion analysis results for functional, dynamic, and derived imaging datasets acquired with CT or MRI. TeraRecon Neuro results are used for the analysis of dynamic brain perfusion image data, showing properties of changes in contrast over time. This functionality includes calculation of parameters related to brain tissue perfusion, vascular assessment and tissue blood volume.
Outputs include parametric map of measurements including time to peak (TTP), take off time (TOT), recirculation time (RT), mean transit time (MTT), blood volume (BV/CBV), blood flow (BF/CBF), time to maximum (Tmax) and penumbra/umbra maps that are derived from combinations of measurement parameters, such as mismatch maps and hypoperfusion maps with volumes and ratios, as well as 2D and 3D visualization of brain tissues and brain blood vessels (Note: Tmax, mismatch and hypoperfusion maps are only available for images of CT modality).
When TeraRecon Neuro results are used in external viewer devices such as TeraRecon's Intuition or Eureka medical devices, all the standard features offered by Intuition or Eureka are employed such as image manipulation tools like drawing the region of interest, manual or automatic segmentation of structures, tools that support creation of a report, transmitting and storing this report in digital form, and tracking historical information about the studies analyzed by the software.
The TeraRecon Neuro algorithm outputs can be used by physicians to aid in the diagnosis and for clinical decision support including treatment planning and post treatment evaluation. The software is not intended to replace the skill and judgment of a qualified medical practitioner and should only be used by individuals that have been trained in the software's function, capabilities and limitations. The device is intended to provide supporting analytical tools to a physician, to speed decision-making and to improve communication, but the physician's judgment is paramount, and it is normal practice for physicians to validate theories and treatment decisions multiple ways before proceeding with a risky course of patient management.
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#### 1.5 Indications for Use
The TeraRecon Neuro algorithm is an algorithm for use by trained professionals, including but not limited to physicians, surgeons and medical clinicians.
The TeraRecon Neuro algorithm is a standalone image processing software device that can be deployed as a Microsoft Windows executable on off-the-shelf hardware or as a containerized application (e.g., a Docker container) that runs on off-the-shelf hardware or on a cloud platform. Data and images are acquired via DICOM compliant imaging devices. DICOM results may be exported, combined with, or utilized by other DICOM-compliant systems and results.
The TeraRecon Neuro algorithm provides analysis capabilities for functional, dynamic, and derived imaging datasets acquired with CT or MRI. It can be used for the analysis of dynamic brain perfusion image data, showing properties of changes in contrast over time. This functionality includes calculation of parameters related to brain tissue perfusion, vascular assessment, tissue blood volume, and other parametric maps with or without the ventricles included in the calculation. The algorithm also include volume reformat in various orientation, rotational MIP 3D batch while removing the skull. This "tumble view" allows qualitative review of vascular structure in direct correlation to the perfusion maps for comprehensive review.
The results of the TeraRecon Neuro algorithm can be delivered to the end-user through image viewers such as TeraRecon's Aquarius Intuition system, TeraRecon's Eureka AI Results Explorer, TeraRecon's Eureka Clinical AI Platform, or other image viewing systems like PACS that can support DICOM results generated by the TeraRecon Neuro Algorithm.
The TeraRecon Neuro algorithm results are designed for use by trained healthcare professionals and are intended to assist the physician in diagnosis, who is responsible for making all final patient management decisions.
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#### 1.6 Summary of Technological Characteristics
The TeraRecon Neuro algorithm version 2.0.0 (K220349) is substantially equivalent to the predicate device, Neuro.AI Algorithm (K200750). It has the same basic technological characteristics as the predicate device. The main difference between the subject device and the predicate device is the addition of three perfusions maps Tmax, Hypoperfusion and Mismatch along with improvements made to the quality of existing perfusions maps in version 1.0.0 BV, BF, MTT, TOT, TTP and RT. The subject and predicate devices both allow motion correction and process, calculate and output brain perfusion analysis results for functional, dynamic and derived imaging datasets acquired with CT or MRI. The subject and predicate device results are used for visualization and analysis of dynamic brain perfusion image data, showing properties of changes in contrast over time. This functionality includes calculation of parameters related to brain tissue perfusion, vascular assessment and tissue blood volume.
Outputs include parametric map of measurements including time to peak (TTP), take off time (TOT), recirculation time (RT), mean transit time (MTT), blood volume (BV/CBV), blood flow (BF/CBF), time to maximum (Tmax) and penumbra/umbra maps that are derived from combinations of measurement parameters, such as mismatch maps and hypoperfusion maps with volumes and ratios, as well as 2D and 3D visualization of brain tissues and brain blood vessels.
TeraRecon Neuro can be used by physicians to aid in the diagnosis and for clinical decision support including treatment planning and post treatment evaluation.
Both the subject and predicate devices are interoperable or compatible with CT and MR scanners, 3rd party hospital systems such as PACS, and the TeraRecon Intuition platform. Both devices are standalone software packages, the results of which can be consumed by and viewed by TeraRecon's Eureka AI Results Explorer or by other image viewing systems that can support the results generated by the TeraRecon Neuro algorithm.
The differences in technological characteristics do not raise any new or different questions of safety of effectiveness. Software verification and validation testing validates that the TeraRecon Neuro algorithm is as safe and effective as the predicate device in order to support a determination of substantial equivalence.
See the table below for a description of the technological similarities and differences among the subject and predicate device.
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# Table 1: Technological Characteristics Comparison
| | Subject Device | Predicate Device | Reference Device<br>(Used in Qualitative<br>Assessment) | Reference Device<br>(Used in Qualitative<br>Assessment) |
|---------------------|----------------------------------------|-------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------|
| Functionality | TeraRecon Neuro version 2.0.0<br>(TBD) | Neuro.AI Algorithm version<br>1.0.0<br>(K200750) | FastStroke, CT Perfusion 4D<br>(K193289) | iSchemaView RAPID<br>(K182130) |
| Areas of Use | Same as predicate device | Radiology and could also include<br>other clinical specialty areas<br>such as emergency, neurology,<br>surgery and more | Not specified in K193289's<br>510(k) summary. | Hospital LAN, inside the<br>Hospital Firewall<br>To be used by trained<br>professionals.<br>Radiological data network. |
| Modality<br>Support | Same as predicate device | Vendor-neutral - CT, MR and<br>other volumetric imaging<br>modalities. | CT | CT and MRI |
| Body Part | Same as predicate device | Head - entire brain or from<br>lower edge of the base of nucleus<br>to upper edge of the ventricles. | Head and Body | Not specified in K182130's<br>510(k) summary |
| DICOM®<br>formats | Same as predicate device | NEMA PS 3.1 - 3.20 (2016) | DICOM 3.0 image compatibility | NEMA PS 3.1 - 3.20 (2016) |
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| Functionality | Subject Device | Predicate Device | Reference Device<br>(Used in Qualitative Assessment) | Reference Device<br>(Used in Qualitative Assessment) |
|-----------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| | TeraRecon Neuro version 2.0.0<br>(TBD) | Neuro.AI Algorithm version<br>1.0.0<br>(K200750) | FastStroke, CT Perfusion 4D<br>(K193289) | iSchemaView RAPID<br>(K182130) |
| Operating<br>System | Same as predicate device | Microsoft Windows® executable<br>on off the shelf hardware and<br>CentOS (Interoperability) | Not specified in K193289's<br>510(k) summary | The software runs on a standard<br>off-the-shelf computer or a<br>virtual platform, such as<br>VMware,<br>and can be used to perform<br>image viewing, processing and<br>analysis of images. Data and<br>images<br>are acquired through DICOM<br>compliant imaging devices.<br>Linux-based server |
| Functionality | Subject Device<br>TeraRecon Neuro version 2.0.0<br>(TBD) | Predicate Device<br>Neuro.AI Algorithm version<br>1.0.0<br>(K200750) | Reference Device<br>(Used in Qualitative<br>Assessment)<br>FastStroke, CT Perfusion 4D<br>(K193289) | Reference Device<br>(Used in Qualitative<br>Assessment)<br>iSchemaView RAPID<br>(K182130) |
| Key<br>Functionality/<br>Feature and<br>Region-of-<br>Interest (ROI)<br>Markers | Same as predicate device | • Automatic arterial and venous<br>input function selection<br>• Ventricle subtraction | CT perfusion 4D is an image<br>analysis software package, which<br>allows the user to produce<br>dynamic image<br>data and to generate information<br>with regards to changes in image<br>intensity over time. It supports<br>the<br>analysis of CT Perfusion images<br>(in the head and body) after the<br>intravenous injection of contrast,<br>and<br>calculation of the various<br>perfusion-related parameters (i.e.<br>regional blood flow, regional<br>blood volume,<br>mean transit time and capillary<br>permeability). | The iSchemaView RAPID<br>provides both viewing and<br>analysis capabilities for<br>functional and<br>dynamic imaging datasets<br>acquired with CT Perfusion (CT-<br>P), CT Angiography (CTA), and<br>MRI including a Diffusion<br>Weighted MRI (DWI) Module<br>and a Dynamic Analysis Module<br>(dynamic contrast-enhanced<br>imaging data for MRI and CT).<br>The DWI Module is used to<br>visualize local water diffusion<br>properties from the analysis of<br>diffusion - weighted MRI data.<br>The Dynamic Analysis Module<br>is used for visualization and<br>analysis of dynamic imaging<br>data, showing properties of<br>changes in contrast over time.<br>This functionality includes<br>calculation of parameters related<br>to tissue flow (perfusion) and<br>tissue blood volume. |
| Functionality | Subject Device<br>TeraRecon Neuro version 2.0.0<br>(TBD) | Predicate Device<br>Neuro.AI Algorithm version<br>1.0.0<br>(K200750) | Reference Device<br>(Used in Qualitative<br>Assessment)<br>FastStroke, CT Perfusion 4D<br>(K193289) | Reference Device<br>(Used in Qualitative<br>Assessment)<br>iSchemaView RAPID<br>(K182130) |
| Perfusion<br>measurements<br>and color maps | • Same as predicate device and<br>• Time to Maximum (Tmax)<br>• Hypoperfusion maps and<br>volumes<br>• Mismatch maps<br>(penumbra/umbra maps that<br>are derived from combinations<br>of measurement parameters)<br>and related volumes and ratios | • Time to peak (or Time to<br>Minimum)<br>• Take off time (or Maximum<br>Slope of Increase)<br>• Recirculation time (RT)<br>• Mean transit time (MTT)<br>• Blood volume (BV/CBV)<br>• Blood flow (BF/CBF)<br>• User configurable settings | • Blood Flow<br>• Blood Volume<br>• Mean Transit Time<br>• Capillary Permeability<br>• Time to Maximum | • Blood Flow<br>• Blood Volume<br>• Mean Transit Time<br>• Time to Maximum |
| Graph Displays | Same as predicate device | Artery and Vein Fitted and Raw<br>curves - time/activity | Not specified in K193289's<br>510(k) summary | Not specified in K182130's<br>510(k) summary |
| Export<br>Capability | • Same as predicate device and<br>• Artery Intensity Profile | DICOM files | Not specified in K193289's<br>510(k) summary | Not specified in K182130's<br>510(k) summary |
| Methods for<br>Mathematical<br>Modeling | Same as predicate device | SVD | Not specified in K193289's<br>510(k) summary | Not specified in K182130's<br>510(k) summary |
| Arterial and<br>Venous Input<br>Function<br>Selection | Same as predicate device | Automatic | Not specified in K193289's<br>510(k) summary | Arterial input function (AIF) and<br>Venous output function (VOF) |
| Functionality | Subject Device<br>TeraRecon Neuro version 2.0.0<br>(TBD) | Predicate Device<br>Neuro.AI Algorithm version<br>1.0.0<br>(K200750) | Reference Device<br>(Used in Qualitative<br>Assessment)<br>FastStroke, CT Perfusion 4D<br>(K193289) | Reference Device<br>(Used in Qualitative<br>Assessment)<br>iSchemaView RAPID<br>(K182130) |
| Containerization<br>/ dockerization<br>of algorithm that<br>enables<br>interoperability<br>with 3rd party<br>results including<br>viewing such<br>results | Same as predicate device | • Neuro.AI Algorithm is hosted<br>on the Eureka platform within<br>its own docker. The algorithm<br>is triggered based on input<br>data and generates result<br>which will be delivered to<br>third party system.<br>• CT and MR Scanners<br>• 3rd party hospital systems<br>such as a PACS server, EMR<br>or other<br>• TeraRecon Intuition<br>• Visualization system<br>• Other image viewing<br>systems that can support<br>results generated by the<br>Neuro.AI Algorithm<br>• Notification systems | The configuration of<br>NeuroPackage enables the user<br>to open a single application,<br>FastStroke, which provides them<br>access to both the updated CT<br>Perfusion 4D<br>and FastStroke applications.<br>The capabilities in CT Perfusion<br>4D<br>and FastStroke can be offered<br>independently. | RAPID is available in the<br>following configurations:<br>• Standard RAPID, which is<br>installed directly on a customer's<br>Linux-based server and<br>integrated with medical image<br>processing software such as<br>commercial PACS.<br>• Virtual RAPID, wherein the<br>user accesses RAPID online and<br>uses it to process DICOM<br>images otherwise available on<br>his/her computer. |
| Ventricle<br>Subtraction | Same as predicate device | Setting allows software to<br>calculate maps with or without<br>ventricle included. | Ventricle Segmentation | Not specified in K182130's<br>510(k) summary |
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#### 1.7 Performance Data
Safety and performance of the TeraRecon Neuro algorithm have been verified and validated through software testing, quantitative phantom testing and qualitative clinical user evaluation. Software development and testing were performed in accordance with IEC 62304:2006/AI:2015, Medical Device Software - Software life cycle processes, utilizing a risk-based testing methodology. Risk has been evaluated in accordance with ISO 14971:2007, Medical Devices – Application of Risk Management to Medical Devices. During software testing, all pre-defined acceptance criteria for the Neuro.AI Algorithm were met and all software test cases passed. The same verification and validation methodology, risk assessment and acceptance criterion were used for predicate device.
To execute our clinical user evaluation TeraRecon worked with our evaluator Dr. Robert Falk, MD whom was presented with comparison maps generated by the subject device, the predicate device and two additional reference devices GE Medical Systems FastStroke CT Perfusion 4D (K193289) and ISchemaView RAPID (K182130). The evaluator was asked to confirm through qualitative assessment that the generated maps of TeraRecon Neuro are at least 85% substantially equivalent or better than the predicate and reference devices.
Additionally, we performed a quantitative evaluation of Tmax measurements in comparison to the two reference devices. Considering the ground truth as the average Tmax measurement of the two reference devices for a given ROI, we calculated absolute error and absolute percent error for the subject device compared to ground truth. Acceptance criteria was defined as subject device limit of agreement for both metrics less than or equal than the limit of agreement of each predicate device compared to the ground truth.
The results of the software testing and clinical user evaluation validate that the TeraRecon Neuro device meets its qualified requirements, performs as intended, and is as safe and effective as the predicate device. No new or different questions of safety or efficacy have been raised as a result of the verification and validation process.
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#### 1.8 Conclusion
The TeraRecon Neuro algorithm is as safe and effective as the predicate device, Neuro.AI Algorithm. The indications for use of the subject device falls within the scope of that for the predicate device. Many of the technological characteristics are the same for the subject and predicate devices. Differences in the technological characteristics between the subject and predicate devices have been addressed through software verification and validation testing and do not raise any new of different questions of safety and effectiveness.
All risk were analyzed, and there are no new risks or modified risks that could result in significant harm which are not effectively mitigated in the predicate device. The analysis above supports a determination of Substantial Equivalence of the TeraRecon Neuro algorithm to the predicate device in terms of safety, efficacy, and performance.
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.