Viz LVO is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to identify and communicate images of specific patients to a specialist, independent of standard of care workflow.

Viz LVO uses an artificial intelligence algorithm to analyze images for findings suggestive of a pre-specified clinical condition and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Identification of suspected findings is not for diagnostic use beyond notification. Specifically, the device analyzes CT angiogram images of the brain acquired in the acute setting, and sends notifications to a neurovascular specialist that a suspected large vessel occlusion has been identified and recommends review of those images. Images can be previewed through a mobile application. Viz LVO is intended to analyze terminal ICA and MCA-M1 vessels for LVOs.

Images that are previewed through 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. Viz LVO is limited to analysis of imaging data and should not be used in-lieu of full patient evaluation or relied upon to make or confirm diagnosis.

Device Description

Viz LVO is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to analyze images for findings suggestive of a suspected large vessel occlusion and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Viz LVO was previously granted a de-novo as ContaCT (DEN170073); following the granting of the denovo the device name was changed to Viz LVO.

Viz LVO is a combination of software modules that allow for detection and notification of patients with a suspected large vessel occlusion. Viz LVO consists of an algorithm and mobile application software module.

The Viz LVO Image Analysis Algorithm (LVO Detection Algorithm) is a locked, artificial intelligence machine learning (AI/ML) software algorithm that analyzes CTA images of the head for a suspected large vessel occlusion (LVO). The LVO Detection Algorithm is hosted on Viz.ai's Backend Server and analyzes applicable stroke-protocoled CTA images of the head that are acquired on CT scanners and are forwarded to Viz.ai's Backend Server. Upon detection of a suspected LVO, the LVO Detection Algorithm sends a notification of the suspected finding.

The Viz LVO Mobile Notification Software is a software module that enables the end user to receive and toggle notifications for suspected large vessel occlusions identified by the LVO Detection Algorithm. The LVO Mobile Notification Software module is implemented into Viz.ai's generic nondiagnostic DICOM image viewer, Viz VIEW (formerly referred to as the Imaging Viewing Software in the previous submission, DEN170073), which displays CT scans that are sent to Viz.ai's Backend Server. When the Viz LVO Mobile Notification Software module is enabled for a user, the user can receive and toggle the notifications for patients with a suspected LVO, view a unique list of patients with a suspected LVO (as determined by the LVO Detection Algorithm), and view the non-diagnostic CT scan of the patient through the Viz VIEW mobile application. Image viewing through the mobile application interface is for informational purposes only and is not for diagnostic use.

AI/ML Overview

I am sorry, but the provided text does not contain the requested information about acceptance criteria and the study that proves the device meets them. The document is a 510(k) summary for Viz LVO, a medical device, and it primarily focuses on establishing substantial equivalence to a predicate device (ContaCT) for a change in its indications for use.

Here's what the document does state regarding performance data:

"Performance data was not included as part of the premarket notification. Supporting software verification and validation (V&V) testing were provided to demonstrate implementation of the device changes."

This indicates that this specific submission (K223042) did not involve new clinical performance studies to establish acceptance criteria or demonstrate device performance beyond software verification and validation to support the changes to the device. The substantial equivalence is based on the previously cleared predicate device (ContaCT DEN170073).

Therefore, I cannot provide:

A table of acceptance criteria and reported device performance.
Sample size and data provenance for a test set.
Number and qualifications of experts for ground truth.
Adjudication method.
MRMC comparative effectiveness study results.
Details of a standalone performance study.
Type of ground truth used.
Sample size for the training set.
How ground truth for the training set was established.

To find this information, you would typically need to consult the original 510(k) submission or de novo application for the predicate device, ContaCT (DEN170073), which likely contained the initial performance studies and acceptance criteria.

Summary

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Image /page/0/Picture/0 description: The image shows 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, which consists of the letters "FDA" in a blue square, followed by the words "U.S. FOOD & DRUG" in blue, and then the word "ADMINISTRATION" in a smaller font size below that.

Viz.ai, Inc. % Gregory Ramina Director of Regulatory Affairs 201 Mission Street 12th Floor SAN FRANCISCO CA 94105

Re: K223042

October 21, 2022

Trade/Device Name: Viz LVO Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological computer aided triage and notification software Regulatory Class: Class II Product Code: QAS Dated: September 28, 2022 Received: September 29, 2022

Dear Gregory Ramina:

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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510(k) Number (if known)

K223042

Device Name

Viz LVO

Indications for Use (Describe)

lmages that are previewed through the mobile application are compressed and are for informational purposes only and not intended for diagnostic use beyond 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. Viz LVO is limited to analysis of imaging data and should not be used in-lieu of full patient evaluation or relied upon to make or confirm diagnosis.

Type of Use (Select one or both, as applicable)

区 Prescription Use (Part 21 CFR 801 Subpart D)

□ Over-The-Counter Use (21 CFR 801 Subpart C)

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510(k) SUMMARY

K223042

Viz.ai, Inc.'s Viz LVO

Applicant Name:	Viz.ai, Inc.
	201 Mission St, 12th Floor
	San Francisco, CA 94105

Contact Person: Gregory Ramina Director of Regulatory Affairs 201 Mission Street, 12th Floor San Francisco, CA 94105 Tel. (415) 663-6130 Greg@viz.ai
Date Prepared: September 28, 2022

Device Name and Classification

Name of Device:	Viz LVO
Common or Usual Name:	Radiological Computer-Assisted Triage and Notification Software
Classification Panel:	Radiology
Regulation No:	21 C.F.R. § 892.2080
Regulatory Class:	Class II
Product Code:	QAS

Predicate Device

Manufacturer	Device Name	Application No.
Viz.ai, Inc.	ContaCT	DEN170073

Purpose of Special 510(k)

Viz LVO is a modification to the predicate device, ContaCT. This Special 510(k) was submitted for changes to the Viz LVO indications for use which provide additional information regarding the intended regions analyzed by the Viz LVO device.

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Image /page/4/Picture/0 description: The image shows a blue logo that resembles a stylized letter 'V'. The logo is composed of several horizontal curved lines that create the shape of the 'V'. The top part of the 'V' is formed by two angled lines, and the lower part is formed by curved lines that get progressively shorter towards the bottom.

Intended Use / Indications for Use

Viz LVO uses an artificial intelligence algorithm to analyze images for findings suggestive of a prespecified clinical condition and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Identification of suspected findings is not for diagnostic use beyond notification. Specifically, the device analyzes CT angiogram images of the brain acquired in the acute setting, and sends notifications to a neurovascular specialist that a suspected large vessel occlusion has been identified and recommends review of those images can be previewed through a mobile application. Viz LVO is intended to analyze terminal ICA and MCA-M1 vessels for LVOs.

Device Description

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Image /page/5/Picture/0 description: The image shows a blue logo with a stylized "V" shape. The "V" is formed by several horizontal lines and curved segments. The top part of the "V" is created by two separate, angled shapes, while the lower part consists of three curved lines that get progressively smaller towards the bottom. The overall design is simple and modern.

the previous submission, DEN170073), which displays CT scans that are sent to Viz.ai's Backend Server. When the Viz LVO Mobile Notification Software module is enabled for a user, the user can receive and toggle the notifications for patients with a suspected LVO, view a unique list of patients with a suspected LVO (as determined by the LVO Detection Algorithm), and view the non-diagnostic CT scan of the patient through the Viz VIEW mobile application. Image viewing through the mobile application interface is for informational purposes only and is not for diagnostic use.

Technological Characteristics

Both the subject and predicate device use the same artificial intelligence, machine learning (A//ML) software algorithm to identify suspected large vessel occlusions (LVOs) on stroke-protocoled CTA imaging of head in the same regions of the large vessels. Additionally, the software algorithm for the subject device is hosted on the same architecture, automatically receives imaging in the same DICOM format, and uses the same mechanisms to identify applicable imaging for analysis as the predicate device. The outputs of the subject and predicate device are the same, i.e., both devices identify suspected large vessel occlusions (LVOs) and both devices send notifications for suspected LVO findings from the same server.

Both the subject and predicate device include the same mobile software functions and outputs which are presented through the same mobile application. The user can receive and toggle the notifications for patients with a suspected LVO, view a unique list of patients with a suspected LVO (as determined by the LVO Detection Alqorithm), and view the non-diagnostic CT scan of the patient through the Viz VIEW mobile application. In addition, imaging viewing of CTA scans analyzed by the subject and predicate device are subject to the same limitations, that is they are limited to informational purposes (for prioritization review only) and are not for diagnostic use.

Where the subject and predicate device differ is that the subject device includes additional information which are embedded into the mobile application interface that inform the user of the limitations of the Viz LVO algorithm. These additional mechanisms implemented in the mobile application to communicate limitations of the subject device are not incorporated into the mobile application interface for the predicate device. Providing additional mechanisms through the user interface to inform the device user of the limitations of the subject device through the user interface provide additional means of promoting information for transparency regarding the limitations of the device. Furthermore, these same limitations are applicable to the predicate device. Supportive software testing demonstrated that the additional information is displayed through the mobile application interface as expected. Thus, the additional information provided through the user interface for the user does not raise any new or different questions of safety or efficacy.

Performance Data and Software Testing

Performance data was not included as part of the premarket notification. Supporting software verification and validation (V&V) testing were provided to demonstrate implementation of the device changes.

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Image /page/6/Picture/0 description: The image shows a stylized blue logo. The logo is composed of several curved and straight lines that form a V-like shape. The lines are arranged in a way that suggests a sense of movement or flight. The logo is simple, modern, and visually appealing.

Substantial Equivalence

The Viz LVO device has the same intended use, and has very similar indications, technological characteristics, and principles of operation as its predicate. Although there are minor differences between Viz LVO and the predicate device indications and the presentation of device limitations and device information available through the mobile application interface, those differences do not raise new questions of safety or efficacy. Thus, the Viz LVO device is substantially equivalent.

	Subject Device	Predicate Device
	Viz LVO	ContaCT
Application No.	KXXXXXX	DEN170073
Product Code	QAS	QAS
Regulation No.	21 C.F.R. § 892.2080	21 C.F.R. § 892.2080
Intended Use /Indications for Use	Viz LVO is a notification-only, parallel workflowtool for use by hospital networks and trainedclinicians to identify and communicate images ofspecific patients to a specialist, independent ofstandard of care workflow.Viz LVO uses an artificial intelligence algorithm toanalyze images for findings suggestive of a pre-specified clinical condition and to notify anappropriate medical specialist of these findings inparallel to standard of care image interpretation.Identification of suspected findings is not fordiagnostic use beyond notification. Specifically,the device analyzes CT angiogram images of thebrain acquired in the acute setting, and sendsnotifications to a neurovascular specialist that asuspected large vessel occlusion has beenidentified and recommends review of thoseimages. Images can be previewed through amobile application. Viz LVO is intended to analyzeterminal ICA and MCA-M1 vessels for LVOs.Images that are previewed through the mobileapplication are compressed and are forinformational purposes only and not intended fordiagnostic use beyond notification. Notifiedclinicians are responsible for viewing non-compressed images on a diagnostic viewer andengaging in appropriate patient evaluation andrelevant discussion with a treating physicianbefore making care-related decisions or requests.Viz LVO is limited to analysis of imaging data andshould not be used in-lieu of full patient evaluationor relied upon to make or confirm diagnosis.	ContaCT is a notification-only, parallel workflowtool for use by hospital networks and trainedclinicians to identify and communicate images ofspecific patients to a specialist, independent ofstandard of care workflow.ContaCT uses an artificial intelligence algorithmto analyze images for findings suggestive of apre-specified clinical condition and to notify anappropriate medical specialist of these findings inparallel to standard of care image interpretation.Identification of suspected findings is not fordiagnostic use beyond notification. Specifically,the device analyzes CT angiogram images of thebrain acquired in the acute setting, and sendsnotifications to a neurovascular specialist that asuspected large vessel occlusion has beenidentified and recommends review of thoseimages. Images can be previewed through amobile application.Images that are previewed through the mobileapplication are compressed and are forinformational purposes only and not intended fordiagnostic use beyond notification. Notifiedclinicians are responsible for viewing non-compressed images on a diagnostic viewer andengaging in appropriate patient evaluation andrelevant discussion with a treating physicianbefore making care-related decisions orrequests. ContaCT is limited to analysis ofimaging data and should not be used in-lieu offull patient evaluation or relied upon to make orconfirm diagnosis.
AnatomicalRegion	Head	Head

Table 1: Substantial Equivalence Table Comparing Subject and Predicate Devices

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	Subject Device	Predicate Device
DiagnosticApplication	Notification-only	Notification-only
Notification/Prioritization	Yes	Yes
Intended User	Neurovascular Specialist	Neurovascular Specialist
DICOMCompatible	Yes	Yes
Data Acquisition	Acquires medical image data from DICOMcompliant imaging devices and modalities.	Acquires medical image data from DICOMcompliant imaging devices and modalities.
SupportedImaging Modality	Computed Tomography Angiography (CTA)	Computed Tomography Angiography (CTA)
Alteration ofOriginal Image	No	No
Results of ImageAnalysis	Internal, no image marking	Internal, no image marking
Preview Images	Initial assessment; non-diagnostic purposes	Initial assessment; non-diagnostic purposes
View DICOM Data	DICOM Information about the patient, study andcurrent image.	DICOM Information about the patient, study andcurrent image.

Regulation Number and Section

§ 892.2080 Radiological computer aided triage and notification software.

(a)
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.(b)
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.