Rapid LVO is a radiological computer aided triage and notification software indicated for use in the analysis of CTA head images. The device is intended to assist hospital networks and trained radiologists in workflow triage by flagging and communication of suspected positive Large Vessel Occlusion (LVO) findings in head CTA images. Rapid LVO uses a software algorithm to analyze images and highlight cases with suspected LVO on a server or standalone desktop application in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected LVO findings. Notifications include compressed preview images, that are meant for informational purposes only and not intended for diagnostic use beyond notification. The device does not alter the original medical image and is not intended to be used as a diagnostic device. The results of Rapid LVO are intended to be used in conjunction with other patient information and based on professional judgment, to assist with triage /prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.
Device Story
Rapid LVO 1.0 is a clinical module within the Rapid Platform for triage of Large Vessel Occlusion (LVO). It ingests DICOM-compliant CTA head images from scanners/PACS. The software algorithm analyzes images to detect suspected LVO; it operates in parallel to standard-of-care interpretation. If a suspected LVO is identified, the system sends notifications (including compressed preview images) to clinicians via email and mobile application. The device does not alter original images and is not diagnostic. It is used in hospital networks by radiologists and clinicians to prioritize workflow. By flagging potential LVO cases, it aims to reduce time-to-notification, enabling faster clinical decision-making and potential patient benefit in acute ischemic stroke screening.
Clinical Evidence
Bench testing only. Standalone performance validation demonstrated sensitivity of 0.970 (95% CI: 0.933, 0.987), specificity of 0.956 (95% CI: 0.919, 0.977), and ROC AUC of 0.99 (95% CI: 0.972, 0.995). PPV was 0.95 and NPV was 0.98 at 45% prevalence. Time-to-notification was 2.86 minutes (95% CI: 2.79, 2.92), meeting the <3.5-minute goal.
Technological Characteristics
Software-based triage module running on the Rapid Platform. Operates on standard off-the-shelf server/PC hardware. DICOM-compliant; supports VPN/SSH networking. Integrates with PACS/modalities. Uses traditional software algorithms for image analysis. Conforms to ISO 14971:2019, IEC 62304:2015, IEC 62366:2015, and NEMA PS 3.1-3.20.
Indications for Use
Indicated for use in the analysis of CTA head images to assist hospital networks and trained radiologists in workflow triage by flagging and communicating suspected positive Large Vessel Occlusion (LVO) findings. Not for diagnostic use. Contraindicated for patients where excessive motion artifacts render the scan technically inadequate.
Regulatory Classification
Identification
Radiological computer aided triage and notification software is an image processing prescription device intended to aid in prioritization and triage of radiological medical images. The device notifies a designated list of clinicians of the availability of time sensitive radiological medical images for review based on computer aided image analysis of those images performed by the device. The device does not mark, highlight, or direct users' attention to a specific location in the original image. The device does not remove cases from a reading queue. The device operates in parallel with the standard of care, which remains the default option for all cases.
Special Controls
Radiological computer aided triage and notification software must comply with the following special controls: 1. Design verification and validation must include: i. A detailed description of the notification and triage algorithms and all underlying image analysis algorithms including, but not limited to, a detailed description of the algorithm inputs and outputs, each major component or block, how the algorithm affects or relates to clinical practice or patient care, and any algorithm limitations. ii. A detailed description of pre-specified performance testing protocols and dataset(s) used to assess whether the device will provide effective triage (e.g., improved time to review of prioritized images for pre-specified clinicians). iii. Results from performance testing that demonstrate that the device will provide effective triage. The performance assessment must be based on an appropriate measure to estimate the clinical effectiveness. The test dataset must contain sufficient numbers of cases from important cohorts (e.g., subsets defined by clinically relevant confounders, effect modifiers, associated diseases, and subsets defined by image acquisition characteristics) such that the performance estimates and confidence intervals for these individual subsets can be characterized with the device for the intended use population and imaging equipment. iv. Standalone performance testing protocols and results of the device. v. Appropriate software documentation (e.g., device hazard analysis; software requirements specification document; software design specification document; traceability analysis; description of verification and validation activities including system level test protocol, pass/fail criteria, and results). 2. Labeling must include the following: i. A detailed description of the patient population for which the device is indicated for use. ii. A detailed description of the intended user and user training that addresses appropriate use protocols for the device. iii. Discussion of warnings, precautions, and limitations must include situations in which the device may fail or may not operate at its expected performance level (e.g., poor image quality for certain subpopulations), as applicable. iv. A detailed description of compatible imaging hardware, imaging protocols, and requirements for input images. v. Device operating instructions. vi. A detailed summary of the performance testing, including: test methods, dataset characteristics, triage effectiveness (e.g., improved time to review of prioritized images for pre-specified clinicians), diagnostic accuracy of algorithms informing triage decision, and results with associated statistical uncertainty (e.g., confidence intervals), including a summary of subanalyses on case distributions stratified by relevant confounders, such as lesion and organ characteristics, disease stages, and imaging equipment.
*Classification.* Class II (special controls). The special controls for this device are:(1) Design verification and validation must include:
(i) A detailed description of the notification and triage algorithms and all underlying image analysis algorithms including, but not limited to, a detailed description of the algorithm inputs and outputs, each major component or block, how the algorithm affects or relates to clinical practice or patient care, and any algorithm limitations.
(ii) A detailed description of pre-specified performance testing protocols and dataset(s) used to assess whether the device will provide effective triage (
*e.g.,* improved time to review of prioritized images for pre-specified clinicians).(iii) Results from performance testing that demonstrate that the device will provide effective triage. The performance assessment must be based on an appropriate measure to estimate the clinical effectiveness. The test dataset must contain sufficient numbers of cases from important cohorts (
*e.g.,* subsets defined by clinically relevant confounders, effect modifiers, associated diseases, and subsets defined by image acquisition characteristics) such that the performance estimates and confidence intervals for these individual subsets can be characterized with the device for the intended use population and imaging equipment.(iv) Stand-alone performance testing protocols and results of the device.
(v) Appropriate software documentation (
*e.g.,* device hazard analysis; software requirements specification document; software design specification document; traceability analysis; description of verification and validation activities including system level test protocol, pass/fail criteria, and results).(2) Labeling must include the following:
(i) A detailed description of the patient population for which the device is indicated for use;
(ii) A detailed description of the intended user and user training that addresses appropriate use protocols for the device;
(iii) Discussion of warnings, precautions, and limitations must include situations in which the device may fail or may not operate at its expected performance level (
*e.g.,* poor image quality for certain subpopulations), as applicable;(iv) A detailed description of compatible imaging hardware, imaging protocols, and requirements for input images;
(v) Device operating instructions; and
(vi) A detailed summary of the performance testing, including: test methods, dataset characteristics, triage effectiveness (
*e.g.,* improved time to review of prioritized images for pre-specified clinicians), diagnostic accuracy of algorithms informing triage decision, and results with associated statistical uncertainty (*e.g.,* confidence intervals), including a summary of subanalyses on case distributions stratified by relevant confounders, such as lesion and organ characteristics, disease stages, and imaging equipment.
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July 9, 2020
iSchemaView, Inc. % Mr. James Rosa VP Quality and Regulatory 433 Park Point Drive, Suite 220 GOLDEN CO 80401
Re: K200941
Trade/Device Name: Rapid LVO 1.0 Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological computer aided triage and notification software Regulatory Class: Class II Product Code: QAS Dated: June 8, 2020 Received: June 9, 2020
Dear Mr. Rosa:
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 and Part 809); 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
Thalia T. Mills, Ph.D. Director Division of Radiological Health OHT7: Office of In Vitro Diagnostics and Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
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# Indications for Use
510(k) Number (if known) K200941
Device Name Rapid LVO 1.0
#### Indications for Use (Describe)
Rapid LVO is a radiological computer aided triage and notification software indicated for use in the analysis of CTA head images. The device is intended to assist hospital networks and trained radiologists in workflow triage by flagging and communication of suspected positive Large Vessel Occlusion (LVO) findings in head CTA images.
Rapid LVO uses a software algorithm to analyze images and highlight cases with suspected LVO on a server or
standalone desktop application in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected LVO findings. Notifications include compressed preview images, that are meant for informational purposes only and not intended for diagnostic use beyond notification. The device does not alter the original medical image and is not intended to be used as a diagnostic device.
The results of Rapid LVO are intended to be used in conjunction with other patient information and based on professional judgment, to assist with triage /prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.
#### Contraindications/Exclusions/Cautions:
· Rapid LVO is one input to physician diagnosis for patients undergoing screening for acute ischemic stroke.
· Excessive patient motion may lead to artifacts that make the scan technically inadequate.
• Identification of suspected findings is not for diagnostic use beyond notification. Images that are previewed through email and the mobile application are compressed and are for informational purposes only and not intended for diagnostic use beyond notification.
· Notified clinicians are responsible for viewing non-compressed images on a diagnostic viewer and engaging in appropriate patient evaluation and relevant discussion with a treating physician before making care-related decisions or requests.
| Type of Use (Select one or both, as applicable) | |
|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| <div> <span> <svg height="15" width="15"> <rect fill="white" height="15" stroke="black" stroke-width="1" width="15"></rect> <line stroke="black" stroke-width="2" x1="0" x2="15" y1="0" y2="15"></line> <line stroke="black" stroke-width="2" x1="0" x2="15" y1="15" y2="0"></line> </svg> </span> Prescription Use (Part 21 CFR 801 Subpart D) </div> | <div> <span> <svg height="15" width="15"> <rect fill="white" height="15" stroke="black" stroke-width="1" width="15"></rect> </svg> </span> Over-The-Counter Use (21 CFR 801 Subpart C) </div> |
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### 510(k) Summary
### iSchemaView, Inc.'s Rapid LVO 1.0
This document contains the 510(k) summary for the iSchemaView Rapid LVO. The content of this summary is based on the requirements of 21 CFR Section 807.92(c).
#### Applicant Name and Address:
| Name: | iSchemaView, Inc. |
|-------------------|------------------------------------------------------------------|
| Address: | 433 Park Point Drive<br>Ste. 220<br>Golden, CO 80401 |
| Official Contact: | Jim Rosa<br>Phone: (303) 704-3374<br>Email: rosa@ischemaview.com |
Summary Preparation Date: June 29, 2020
#### Device Name and Classification:
| Trade Name: | iSchemaView Rapid LVO 1.0 |
|-----------------------|-----------------------------------------------------------------|
| Common Name: | Radiological computer aided triage and<br>notification software |
| Classification: | II |
| Product Code: | QAS |
| Regulation No: | 21 C.F.R. §892.2080 |
| Classification Panel: | Radiology Devices |
#### Predicate Devices:
The iSchemaView Rapid LVO is claimed to be substantially equivalent to the following legally marketed predicate device:
iSchemaView Rapid ICH (K193087)
#### Device Description:
Rapid LVO 1.0 is a clinical module which operates within the integrated Rapid Platform to provide triage and notification of suspected Large Vessel Occlusion (LVO). The Rapid LVO module consists of the core Rapid Platform software which provides the administration and services for the Rapid image processing modules; and the Rapid LVO module which functions as one of many image processing modules hosted by the platform.
Rapid LVO acquires (DICOM compliant) medical image data from CTA scanners through the Rapid Platform interface:
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# Rapid Platform
The Rapid platform is a software package that provides for the visualization and study of changes in tissue using digital images captured by diagnostic imaging systems including CT (Computed Tomography), CTA, XA and MRI (Magnetic Image Resonance), as an aid to physician diagnosis. Rapid can be installed on a customer's Server or it can be accessed online as virtual system. It provides viewing, quantification, analysis and reporting capabilities. The Rapid platform has multiple modules a clinician may elect to run and provide analysis for decision making. The basic architecture supports the general functionality to support the Rapid LVO imaging module such as DICOM interfaces, job management, data base functions and communications. The Rapid Platform and base functions are not under review for this submission.
### Indications for Use:
Rapid LVO is a radiological computer aided triage and notification software indicated for use in the analysis of CTA head images. The device is intended to assist hospital networks and trained radiologists in workflow triage by flagging and communication of suspected positive Large Vessel Occlusion (LVO) findings in head CTA images.
Rapid LVO uses a software algorithm to analyze images and highlight cases with suspected LVO on a server or standalone desktop application in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected LVO findings. Notifications include compressed preview images, that are meant for informational purposes only and not intended for diagnostic use beyond notification. The device does not alter the original medical image and is not intended to be used as a diagnostic device.
The results of Rapid LVO are intended to be used in conjunction with other patient information and based on professional judgment, to assist with triage /prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.
#### Contraindications/Exclusions/Cautions:
- . Rapid LVO is one input to physician diagnosis for patients undergoing screening for acute ischemic stroke.
- Excessive patient motion may lead to artifacts that make the scan technically inadequate.
- . Identification of suspected findings is not for diagnostic use beyond notification. Images that are previewed through email and the mobile application are compressed and are for informational purposes only and not intended for diagnostic use beyond notification.
- Notified clinicians are responsible for viewing non-compressed images on a diagnostic viewer ● and engaging in appropriate patient evaluation and relevant discussion with a treating physician before making care-related decisions or requests.
## Technological Characteristics:
Rapid Platform performs the following functions in support of Rapid LVO:
- processes DICOM images from multiple sources to provide visualization of changes . of tissue perfusion, diffusion and change.
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- . receives DICOM images from external DICOM image providers (modalities (CT/MRI Scanners), PACS and Workstations) and sends DICOM images to external image consumers.
- . processes requests, statuses and results, and references therein, which are stored in a searchable database
- processing status is available through a web browser using HTTP. HTML and PHP. ●
- . can send summary results to the user over email and mobile application. For this, Rapid generally connects to the infrastructure of the medical partner (e.g., the hospital). In particular, Rapid uses a SMTP protocol with security extensions to provide secure emailing.
Rapid is available in the following configurations:
- Standard Rapid, which is installed directly on a customer's Linux-based server and . integrated with medical image processing software such as commercial PACS.
- . Virtual Rapid, wherein the user accesses Rapid online and uses it to process DICOM images otherwise available on his/her computer.
Rapid Platform is a DICOM-compliant PACS software that provides comprehensive functionality to transfer, process, and display modality specific imaging data. Rapid runs on standard "off-the- shelf" computer and networking hardware. Rapid is entirely independent from CT, XA, MRI, or PACS platforms. It supports secure VPN (Virtual Private Network) networking or encapsulated Secure Shell (SSH), and seamlessly integrates into an existing radiological data network.
The primary users of Rapid PACS software are medical imaging professionals who analyze tissue using CT or MRI images.
# Performance Standards:
Rapid has been developed in conformance with the following standards, as applicable:
| ISO 14971:2019 | Application of Risk Management to Medical Devices |
|--------------------|---------------------------------------------------------|
| IEC 62304:2015 | Medical device software – Software lifecycle processes |
| IEC 62366:2015 | Application of Usability Engineering to Medical Devices |
| NEMA PS 3.1 - 3.20 | Digital Imaging and Communications in Medicine (DICOM |
## Performance Data:
Rapid complies with DICOM (Digital Imaging and Communications in Medicine) - Developed by the American College of Radiology and the National Electrical Manufacturers Association. NEMA PS 3.1 - 3.20.
Additionally, iSchemaView conducted extensive performance validation testing and software verification and validation testing of the Rapid system. This performance validation testing demonstrated that the Rapid system provides accurate representation of key processing parameters under a range of clinically relevant parameters and perturbations associated with the intended use of the software. Software performance, validation and verification testing demonstrated that the Rapid system met all design requirements and specifications.
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iSchemaView performed standalone performance in accordance with the 892.2080 special controls to show acceptance of the clinical performance of the Rapid LVO module. The Standalone Performance exceeded the 80% Goal using the lower bound of the 95% Confidence Interval for Sensitivity (Se) and Specificity (Sp). The observed results are Se: Sensitivity (Se) of 0.970 (95% CI: 0.933.0.987) and Specificity (Sp) 0.956 (95% CI: 0.919, 0.977) with a ROC AUC of 0.99 (95% CI:0.972, 0.995). Additionally, at a prevalence of 45%, PPV = 0.95 (95% CI: 0.90, 0.97) and NPV = 0.98 (95% CI 0.94, 0.99)
In addition, an analysis on time to notification using Rapid LVO to notify of suspicion/nonsuspicion as 2.86 min (95% CI: 2.79. 2.92) was achieved meeting the goal of < 3.5min established by the predicate. The Rapid LVO time-to-notification includes the time to get the DICOM exam, de-identify it (if required), analyze and send a notification to the attending physician(s) email and mobile. The time to notification consists primarily of the processing time, as the notification time via electronic transmission is considered in seconds via email and mobile.
## Prescriptive Statement:
Caution: Federal law restricts this device to sale by or on the order of a physician.
## Safety & Effectiveness:
Rapid has been designed, verified and validated in compliance with 21 CFR, Part 820.30 requirements. The device has been designed to meet the requirements associated with ISO 14971:2019 (risk management). The Rapid System performance has been validated through the use of phantoms (Rapid core indications) and clinical data (Rapid LVO).
## Substantial Equivalence:
Rapid LVO is as safe and effective as the previously cleared Rapid ICH (K193087). The subject and predicate devices are radiological computer-assisted triage and notification software programs. Both devices are implemented in software algorithms, LVO using traditional and ICH using machine learning software implementations for use with CTA scanners, PACS, and workstations. Both devices process images intended to aid in prioritization and triage of radiological medical images. The subject and predicate differ in imaging input, the subject device process CTA images and the predicate NCCT images for indication. Both devices are intended to provide notifications and preview head images of potential findings to radiologists and other clinicians for the purpose of treatment planning and follow up.
Both software devices notify a designated list of clinicians of the availability of time sensitive radiological medical images for review based on computer aided image analysis performed by the device's algorithm. The subject and predicate device sends notifications and compressed previews to the workstations' desktop. Additionally, the subject device sends an email (normal processing within Rapid Platform and previously cleared and mobile notification (similar to the predicate's predicate device. Those notifications work in parallel to the standard of care. They prompt the clinician to start preemptive triage of a flagged case, upon which they may decide after observing the preview, to turn to the local PACS/Workstation to perform the evaluation. If a notification is found to be non-suspicious of LVO, the case still remains in the queue to be handled per the standard of care.
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As a system, the Rapid LVO raises the same types of safety and effectiveness questions as the predicate; namely, accurate detection of findings within the reviewed and processed study on which a clinician can base a clinically useful triage/prioritization assessment considering all available clinical information.
It is important to note that, like the predicate, the device does not remove cases from a reading queue. Again, both devices operate in parallel with the standard of care, which remains the default option for all cases.
A table comparing the key features of the subject and predicate devices is provided below.
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Substantial Equivalence Discussion:
| Parameter | Rapid ICH (K193087) | Rapid LVO (K200941) |
|--------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Product Code | QAS | QAS |
| Regulation | 21 CFR §892.2080 | 21 CFR §892.2080 |
| Intended Use/ Indications<br>for Use | Rapid ICH is a radiological computer aided<br>triage and notification software indicated for use<br>in the analysis of non-enhanced head CT images.<br>The device is intended to assist hospital networks<br>and trained radiologists in workflow triage by<br>flagging and communication of suspected<br>positive Intracranial Hemorrhage (ICH) findings<br>in head CT images, namely Intracranial<br>Hemorrhage (ICH).<br>Rapid ICH uses an artificial intelligence<br>algorithm to analyze images and highlight cases<br>with suspected ICH on a server or standalone<br>desktop application in parallel to the ongoing<br>standard of care image interpretation. The user is<br>presented with notifications for cases with<br>suspected ICH findings. Notifications include<br>compressed preview images, that are meant for<br>informational purposes only and not intended for<br>diagnostic use beyond notification. The device<br>does not alter the original medical image and is<br>not intended to be used as a diagnostic device.<br>The results of Rapid ICH are intended to be used<br>in conjunction with other patient information and<br>based on professional judgment, to assist with<br>triage/prioritization of medical images. Notified<br>clinicians are responsible for viewing full images<br>per the standard of care. | Rapid LVO is a radiological computer aided triage<br>and notification software indicated for use in the<br>analysis of CTA head images. The device is<br>intended to assist hospital networks and trained<br>radiologists in workflow triage by flagging and<br>communication of suspected positive Large Vessel<br>Occlusion (LVO) findings in head CTA images.<br>Rapid LVO uses a software algorithm to analyze<br>images and highlight cases with suspected LVO on<br>a server or standalone desktop application in<br>parallel to the ongoing standard of care image<br>interpretation. The user is presented with<br>notifications for cases with suspected LVO<br>findings. Notifications include compressed preview<br>images, that are meant for informational purposes<br>only and not intended for diagnostic use beyond<br>notification. The device does not alter the original<br>medical image and is not intended to be used as a<br>diagnostic device. The results of Rapid LVO are<br>intended to be used in conjunction with other<br>patient information and based on professional<br>judgment, to assist with triage /prioritization of<br>medical images. Notified clinicians are responsible<br>for viewing full images per the standard of care. |
| PACS Functionality | | |
| Stroke/Head | Hemorrhagic Stroke/Head | Intracranial Stroke/Head |
| Parameter | Rapid ICH (K193087) | Rapid LVO (K200941) |
| Product Code | QAS | QAS |
| Regulation | 21 CFR §892.2080 | 21 CFR §892.2080 |
| Computer Platform | Standard off-the-shelf PC workstation/server<br>Virtual platform such as VMware | Same<br>Same |
| DICOM Compliance | Yes | Yes |
| Imaging Type | Non-Contrast CT | CT Angiography |
| Data Acquisition | Acquires medical image data from DICOM<br>compliant imaging devices and modalities | Same |
| Technical Implementation | | |
| SaMD | Yes - Machine Learning | Yes – Traditional Algorithms |
| Notification/Workflow | | |
| Pathways | PACS, email, mobile | PACS, email, mobile |
| Preview/Prioritization | Notification Message of Suspected Hemorrhage.<br>Presentation of a preview of the study for initial<br>assessment not meant for diagnostic purposes.<br>The device operates in parallel with the standard<br>of care, which remains. | Notification Message of Suspected LVO.<br>Presentation of a preview of the study for<br>initial assessment not meant for diagnostic<br>purposes.<br>The device operates in parallel with the<br>standard of care, which remains. |
| SoC Workflow | In parallel to the SoC | In parallel to the SoC |
| Original Image | No Alteration | No Alteration |
| Primary Users | Clinician | Clinician |
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# Conclusion:
In conclusion, the iSchemaView Rapid LVO is substantially equivalent in intended use, technological characteristics, safety, and performance characteristics to the legally marketed predicate device, Rapid ICH (K193087) with a focus on LVO analysis only.
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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.
