BriefCase

K221314 · Aidoc Medical , Ltd. · QAS · Jun 3, 2022 · Radiology

Device Facts

• Record ID: K221314
• Device Name: BriefCase
• Applicant: Aidoc Medical , Ltd.
• Product Code: QAS · Radiology
• Decision Date: Jun 3, 2022
• Decision: SESE
• Submission Type: Special
• Regulation: 21 CFR 892.2080
• Device Class: Class 2
• Attributes: AI/ML, Software as a Medical Device

Intended Use

BriefCase is a radiological computer aided triage and notification software indicated for use in the analysis of head CTA images in adults or transitional adolescents aged 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communication of M1 Large Vessel Occlusion (M1-LVO) pathologies. BriefCase uses an artificial intelligence algorithm to analyze images and highlight cases with detected findings on a standalone desktop application in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected 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 BriefCase are intended to be used in conjunction with other patient information and based on their 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

BriefCase is a radiological computer-aided triage and notification software. It receives DICOM head CTA images from hospital PACS; filters and de-identifies data; processes series chronologically via a deep-learning AI algorithm to detect M1-LVO pathologies. The system consists of a hospital server (AHS) for acquisition, a cloud server (ACS) for processing, and a desktop application for user notification. When a suspected finding is detected, the desktop application alerts the clinician and provides a compressed, unannotated, low-quality preview image. The device operates in parallel to standard-of-care workflows; it does not alter original images, remove cases from queues, or provide diagnostic markings. Clinicians use the notification to prioritize their review of the full, original images in the PACS. This preemptive triage aims to reduce turnaround time for time-sensitive critical cases.

Clinical Evidence

Retrospective, blinded, multicenter study (N=383) evaluated performance in identifying M1-LVO in head CTA images. Sensitivity was 88.8% (95% CI: 81.9%, 93.8%) and specificity was 87.2% (95% CI: 82.5%, 91.1%). NPV was 99.5% (95% CI: 99.3%-99.8%) and PPV was 20.1% (95% CI: 13.2%-24.2%). Mean time-to-notification was 3.8 minutes (95% CI: 3.6-4.0).

Technological Characteristics

Software-based system using deep-learning AI algorithms. Components include AHS (image acquisition), ACS (cloud processing), and desktop application. Compatible with DICOM 3.0 compliant CT scanners, PACS, and workstations. Operates on Microsoft Windows Server 2012 64-bit with PostgreSQL. Standalone, networked architecture.

Indications for Use

Indicated for adults and transitional adolescents aged 18 and older undergoing head CTA scans. Intended to assist hospital networks and medical specialists in triage by flagging M1 Large Vessel Occlusion (M1-LVO) pathologies. Not for diagnostic use.

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.

Predicate Devices

• BriefCase LVO triage (K203508)

Reference Devices

• BriefCase ICH (K180647)

Submission Summary (Full Text)

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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 in blue, with the words "U.S. FOOD & DRUG ADMINISTRATION" in blue as well. The FDA is a federal agency responsible for regulating and supervising the safety of food, drugs, and other products.

Aidoc Medical, Ltd. % John J. Smith Partner Hogan Lovells US LLP 555 Thirteenth St. WASHINGTON DC 20004

June 3, 2022

## Re: K221314

Trade/Device Name: BriefCase Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological computer aided triage and notification software Regulatory Class: Class II Product Code: QAS Dated: May 5, 2022 Received: May 5, 2022

Dear John J. Smith:

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 mediation-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 ([e-mail]) or phone [phone] or 301-796-7100).

Sincerely.

Jessica Lamb, Ph.D. Assistant Director Imaging Software Team DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

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DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration

## Indications for Use

510(k) Number (if known)

#### K221314

Device Name

#### BriefCase

Indications for Use (Describe)

BriefCase is a radiological computer aided triage and notification software indicated for use in the analysis of head CTA images in adults or transitional adolescents aged 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communication of M1 Large Vessel Occlusion (M1-LVO) pathologies.

BriefCase uses an artificial intelligence algorithm to analyze images and highlight cases with detected findings on a standalone desktop application in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected 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 BriefCase are intended to be used in conjunction with other patient information and based on their professional judgment, to assist with triage/prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.

| 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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# K221314

# 510(k) Summary Aidoc Medical, Ltd.'s BriefCase K221314

| Submitter: | Aidoc Medical, Ltd.<br>3 Aminadav St.<br>Tel-Aviv, Israel<br>Phone: [phone] |
|---------------------------|-------------------------------------------------------------------------------------|
| Contact Person: | Amalia Schreier, LLM |
| Date Prepared: | June 02, 2022 |
| Name of Device: | BriefCase |
| Classification Name: | Radiological computer-assisted triage and notification software<br>device |
| Regulatory Class: | Class II |
| Product Code: | QAS (21 C.F.R. 892.2080) |
| Primary Predicate Device: | BriefCase LVO triage (K203508) |

#### Device Description

BriefCase is a radiological computer-assisted triage and notification software system is based on an algorithm programmed component and consists of a standard off-the-shelf operating system, the Microsoft Windows server 2012 64bit, and additional applications, which include PostgreSQL, DICOM module and the BriefCase Image Processing Application. The device consists of the following three modules: (1) Aidoc Hospital Server (AHS/Orchestrator) for image acquisition; (2) Aidoc Cloud Server (ACS) for image processing; and (3) Aidoc Desktop Application for workflow integration.

DICOM images are received, saved, filtered and de-identified before processing. Filtration matches metadata fields with keywords. Series are processed chronologically by running the algorithms on each series to detect suspected cases. The software then flags suspect cases by sending notifications to the desktop application, thereby facilitating triage and prioritization by the user. As the BriefCase software platform harbors several triage algorithms, the user may opt to filter out notifications by pathology, e.g., a chest radiologist may choose to filter out alerts on ICH cases, and a neuro-radiologist would opt to divert PE alerts. Where several medical centers are linked to a shared PACS, a user may read cases for a certain center but not for another, and thus may opt to filter out alerts by center. Activating the filter does not impact the order in which notifications are presented in the Aidoc desktop application.

The desktop application feed displays all incoming suspect cases, each notified case in a line. Hovering over a line in the feed pops up a compressed, low-quality, grayscale, unannotated image that is captioned "not for diagnostic use" and is displayed as a preview function. This compressed preview is meant for informational

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purposes only, does not contain any marking of the findings, and is not intended for primary diagnosis beyond notification.

Presenting the users with worklist prioritization facilitates earlier triage by prompting the user to assess the relevant original images in the PACS. Thus, the suspect case receives attention earlier than would have been the case in the standard of care practice alone.

#### Intended Use / Indications for Use

BriefCase is a radiological computer aided triage and notification software indicated for use in the analysis of head CTA images in adults or transitional adolescents aged 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communication of M1 Large Vessel Occlusion (M1-LVO) pathologies.

BriefCase uses an artificial intelligence algorithm to analyze images and highlight cases with detected findings on a standalone desktop application in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected 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 BriefCase are intended to be used in conjunction with other patient information and based on their professional judgment, to assist with triage/prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.

## Comparison of Technological Characteristics

The subject BriefCase for M1-LVO triage and primary predicate BriefCase for LVO triage (K203508) are identical in most aspects and differ with respect to very specific changes in (1) indications for use, (2) user guide warnings, and (3) minor changes in User Interface. All these changes are added to the subject device with the intent to further clarify its intended use - as analyzing specifically M1 large vessels.

Both the primary predicate and subject devices are radiological computer-aided triage and notification software programs. Both devices are artificial intelligence, deep-learning algorithms incorporated software packages for use with DICOM 3.0 compliant CT scanners, PACS, and radiology workstations.

Both devices are intended to aid in triage and prioritization of radiological images and utilize the same design of deep learning algorithm trained on medical images. Both devices are intended to provide the specialists with notifications and unannotated low-quality preview images of suspect studies for the purpose of preemptive triage.

The subject and predicate BriefCase devices raise the same types of safety and effectiveness questions, namely, accurate detection of findings within the processed study. It is important to note that, like the predicate, the subject device neither removes cases from the standard of care reading queue nor deprioritized cases. 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 the primary predicate devices is provided below.

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| Table 1. Key Feature Comparison | | |
|----------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| | Predicate Device<br>Aidoc BriefCase for LVO triage (K203508) | Subject Device<br>Aidoc BriefCase for M1-LVO triage (K221314) |
| Intended Use /<br>Indications for<br>Use | BriefCase is a radiological computer aided<br>triage and notification software indicated<br>for use in the analysis of head CTA images.<br>The device is intended to assist hospital<br>networks and appropriately trained<br>medical specialists in workflow triage<br>by flagging and communication and<br>suspected positive findings of Large Vessel<br>Occlusion (LVO) pathologies.<br><br>BriefCase uses an artificial intelligence<br>algorithm to analyze images and highlight<br>cases with detected findings on a<br>standalone desktop application in parallel<br>to the ongoing standard of care image<br>interpretation. The user is presented<br>with notifications for cases with suspected<br>findings. Notifications include compressed<br>preview images that are<br>meant for informational purposes only<br>and not intended for diagnostic use<br>beyond notification. The device does not<br>alter the original medical image and is not<br>intended to be used as a diagnostic device. | BriefCase is a radiological computer aided<br>triage and notification software indicated for<br>use in the analysis of head CTA images in<br>adults or transitional adolescents aged 18 and<br>older. The device is intended to assist hospital<br>networks and appropriately trained medical<br>specialists in workflow triage by flagging and<br>communication of M1 Large Vessel Occlusion<br>(M1-LVO) pathologies.<br><br>BriefCase uses an artificial intelligence<br>algorithm to analyze images and highlight<br>cases with detected findings on a standalone<br>desktop application in parallel to the ongoing<br>standard of care image interpretation. The<br>user is presented with notifications for cases<br>with suspected findings. Notifications include<br>compressed preview images that are meant<br>for informational purposes only and not<br>intended for diagnostic use beyond<br>notification. The device does not alter the<br>original medical image and is not intended to<br>be used as a diagnostic device. |
| | The results of BriefCase are intended to be<br>used in conjunction with other<br>patient information and based on their<br>professional judgment, to assist with<br>triage/prioritization of medical images.<br>Notified clinicians are responsible for<br>viewing full images per the standard of<br>care. | The results of BriefCase are intended to be<br>used in conjunction with other patient<br>information and based on their<br>professional judgment, to assist with<br>triage/prioritization of medical images.<br>Notified clinicians are responsible for<br>viewing full images per the standard of care. |
| User population | Hospital networks and appropriately<br>trained medical specialists | Hospital networks and appropriately trained<br>medical specialists |
| Anatomical<br>region of interest | Head | Head |
| Data acquisition<br>protocol | Head CTA scans | Head CTA scans |
| | Predicate Device<br>Aidoc BriefCase for LVO triage (K203508) | Subject Device<br>Aidoc BriefCase for M1-LVO triage (K221314) |
| Notification-only<br>(/notification<br>alerts), parallel<br>workflow tool | Yes | Yes |
| Images<br>format | DICOM | DICOM |
| Interference<br>with standard<br>workflow | No. No cases are removed from<br>Worklist or deprioritized. | No. No cases are removed from<br>desktop app or deprioritized |
| Inclusion/<br>Exclusion criteria<br>for clinical<br>performance<br>testing | Inclusion criteria<br>- Head CTA protocol with a 64-slice<br>scanner or higher;<br>- Scans performed on<br>adults/transitional adults ≥ 18 years of<br>age;<br>- Slice thickness 0.5 mm - 1.0 mm.<br><br>Exclusion Criteria<br>- All studies that are technically<br>inadequate, including studies with<br>motion artifacts, severe metal<br>artifacts, sub or an inadequate field of<br>view. | Inclusion criteria<br>- Head CTA protocol with a 64-slice scanner<br>or higher;<br>- Scans performed on adults/transitional<br>adults ≥ 18 years of age;<br>- Slice thickness 0.5 mm – 1.0 mm.<br><br>Exclusion Criteria<br>- All studies that are technically<br>inadequate, including studies with motion<br>artifacts, severe metal artifacts, sub or an<br>inadequate field of view. |
| Algorithm | Artificial intelligence algorithm with<br>database of images. | Artificial intelligence algorithm with database<br>of images. |
| Structure | - AHS module (image acquisition);<br>- ACS module (image processing));<br>- Aidoc Worklist application for<br>workflow integration (worklist and<br>non-diagnostic Image Viewer) | - AHS module ( image acquisition);<br>- ACS module (image processing));<br>Aidoc Desktop application for workflow<br>integration (non-diagnostic Image<br>Viewer) |

## Table 1. Key Feature Comparison

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## Performance Data

The performance data was previously provided in K192383. A retrospective, blinded, multicenter study with the BriefCase software was conducted to evaluate the software's performance in identifying head CTA images containing M1 Large Vessel Occlusion (M1-LVO). The cases were collected from medical centers in the US and are distinct datasets from the ones used to train the algorithm.

## Primary Endpoint

Sensitivity and specificity exceeded the 80% performance goal. Sensitivity was 88.8% (95% Cl: 81.9%, 93.8%) and specificity was 87.2% (95% CI: 82.5%, 91.1%).

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#### Secondary Endpoint

In addition, the time-to-notification metric observed for the BriefCase software in the three medical centers was compared to the equivalent metric of the predicate devices.

- -The BriefCase time-to-notification includes the time to get the DICOM exam, de-identify it, upload it to the cloud, analyze and send a notification on a positive suspect case back to the worklist application.
The BriefCase time-to-notification was measured for all True Positive cases (i.e., identified as positive both by the reviewers as well as the BriefCase device) and is given in Table 2 below. The table also displays the same metric reported for the BriefCase ICH.

The time-to-notification results obtained for the subject BriefCase device show comparability with the primary predicate with regard to time savings to the standard of care review. The BriefCase mean time-to-notification for M1-LVO was 3.8 minutes (95% C: 3.6-4.0). The time-to-notification for the BriefCase for ICH triage was 4.46 minutes (95% CL: 4.10-4.83).

| Parameter | N | Mean<br>estimate | Lower<br>Confidence<br>Limit | Upper<br>Confidence<br>Limit | Median |
|-----------------------------------------------------|-----|------------------|------------------------------|------------------------------|--------|
| Time-to-notification<br>of BriefCase M1-LVO | 111 | 3.8 | 3.6 | 4.0 | 3.8 |
| Time-to-notification<br>of BriefCase ICH<br>K180647 | 59 | 4.46 | 4.10 | 4.83 | - |

Table 2. Time-to-Notification Comparison for BriefCase Devices

NPV was 99.5% (95% Cl: 99.3%-99.8%) and PPV was 20.1% (95% Cl: 13.2%-24.2%).

Thus, the reported similar time-to-notification data demonstrates that when using the subject BriefCase for M1-LVO triage the radiologists may have the same benefit in time saving as with the BriefCase for ICH triage.

As can be seen in Table 3 the mean age of patients whose scans were reviewed for M1-LVO was 65.1 years, with a standard deviation of 17.5 years. Gender distribution was 39.9% female (Table 4). Scanner distribution can also be found in Table 5 below.

| | Mean | Std | Min | Median | Max | N |
|---------|------|------|------|--------|------|-----|
| Age (Y) | 65.1 | 17.5 | 18.0 | 67.0 | 90.0 | 383 |

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| Gender | N | % |
|---------|-----|-------|
| Male | 153 | 39.9% |
| Female | 227 | 59.3% |
| Unknown | 3 | 0.8% |
| All | 383 | 100.0 |

Table 4. Frequency Distribution of Gender

#### Table 5. Frequency Distribution of Manufacturer

| Manufacturer | N | % |
|--------------|-----|------|
| Siemens | 32 | 8% |
| GE | 212 | 55% |
| Canon | 73 | 19% |
| Philips | 66 | 17% |
| Total | 383 | 100% |

In summary, performance validation data, combined with a comparison of the time-to-notification metric with the predicate device establishes the achievement by the subject BriefCase of preemptive triage in the range of several minutes.

## Conclusions

The subject BriefCase for M1-LVO triage is as safe and effective as the predicate BriefCase. Both devices are software packages with the same technological characteristics and principles of operating deep learning AI algorithms that process images, and software to send notifications and display unannotated compressed low-quality preview images. In both devices, the labeling clearly states that the devices are not for diagnostic use and instructs the user to further evaluate and diagnose based only on the original images in the local PACS.

Both devices operate in parallel to the standard of care workflow in the sense that they do not change the original image, do not provide any marking on the output preview, do not remove images from the standard of care FIFO queue and do not de-prioritize cases, thus not disturbing standard interpretation of the images. Both devices notify the radiologist of time-sensitive critical cases within the range of several minutes, and thus contribute similarly to the standard of care workflow turnaround time reduction through preemptive triage.

The subject BriefCase device for M1-LVO triage is thus substantially equivalent to the primary predicate BriefCase for LVO.