The Viz HDS device is intended for automatic labeling, visualization, and quantification of segmentable brain structures from a set of Non-Contrast CT (NCCT) head scans. The software is intended to automate the current manual process of identifying, labeling, and quantifying the volume of segmentable brain structures identified on NCCT images. Viz HDS provides volumes from NCCT scans acquired at a single time point. The Viz HDS software is indicated for use in the analysis of the following structures: Intracranial Hyperdensities, Lateral Ventricles and Midline Shift. The device output should be reviewed along with patient's original images by a physician.

Device Description

Viz HDS is a software-only device that uses a locked artificial intelligence machine learning (AI/ML) algorithm to processes non-contrast head CT scans to outline intracranial hyperdensity areas, lateral ventricles (right and left), midline shift, and then quantify the volume of intracranial hyperdensity(ies), volume of lateral ventricle asymmetry ratio and distance of midline shift.

Viz HDS analyzes the head NCCT series in DICOM format and produces a summary series and a segmentation series in DICOM format. The summary series is a two-slice output: a single slice from the NCCT series with segmented areas overlaid on it, and a summary table providing the calculated measurements. The segmentation series shows an RGB overlay, on each slice of the input series, of the lateral ventricles and hyperdensity(ies) segmentation masks and a midline shift. For slices including hyperdensities or ventricle/ventricles, its volume would be mentioned in a color legend that is also overlaid on the slice. The colors are only for visual differentiation between the segmented regions, the colors don't have a meaning on their own. The device output is exported in DICOM format, which is sent to a pre-configured PACS destination together with the original NCCT series for review by a physician to aid in the assessment of measuring intracranial hyperdensity(ies), lateral ventricles, and midline shift.

AI/ML Overview

Here's a breakdown of the acceptance criteria and the study details for the Viz HDS device, based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria and Device Performance for Viz HDS

Measurement Trait	Acceptance Criteria (Upper 95% CI Bound)	Reported Device Performance (Upper 95% CI Bound)
Hyperdensities Total Volume (MAE)	≤ 7.5 mL	< 7.5 mL
Right Lateral Ventricle Volume (MAE)	≤ 7.5 mL	< 7.5 mL
Left Lateral Ventricle Volume (MAE)	≤ 7.5 mL	< 7.5 mL
Midline Shift Distance (MAE)	≤ 2 mm	< 2 mm
Hyperdensity(ies) (DICE Score)	> 70% (Lower CI Bound)	> 70% (Lower CI Bound)
Both Lateral Ventricles (DICE Score)	> 70% (Lower CI Bound)	> 70% (Lower CI Bound)

Note: The text explicitly states "less than 7.5 mL" and "greater than 70%", confirming the device met the specified criteria.

2. Sample Size and Data Provenance for Test Set

Sample Size for Test Set: Not explicitly stated in the provided text.
Data Provenance: Not explicitly stated in the provided text. The text mentions "clinical site" for stratification, but not the origin of the data itself (e.g., country, specific hospitals).
Retrospective or Prospective: Not explicitly stated.

3. Number and Qualifications of Experts for Ground Truth (Test Set)

Number of Experts: Not explicitly stated. The text mentions "trained radiologists" was involved in establishing the ground truth.
Qualifications of Experts: The experts were "trained radiologists." No further details on their experience (e.g., "10 years of experience") are provided.

4. Adjudication Method (Test Set)

Adjudication Method: Not explicitly stated. The text only mentions that "ground truth as established by trained radiologists." It does not detail how disagreements among radiologists, if any, were resolved.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

MRMC Study: No, an MRMC comparative effectiveness study was not explicitly mentioned as being performed. The study described compares the device's output to "ground truth as established by trained radiologists" and does not describe a scenario where human readers' performance with and without AI assistance was measured.
Effect Size of Human Readers Improvement: Not applicable, as an MRMC study was not performed.

6. Standalone Performance (Algorithm Only)

Standalone Performance: Yes, a standalone performance study was done. The study compares the Viz HDS's output directly to the established ground truth. This is a measure of the algorithm's performance without direct human intervention in the measurement process itself, although the output is intended for physician review.

7. Type of Ground Truth Used

Type of Ground Truth: The ground truth was established by "expert consensus" from trained radiologists. The text states, "ground truth as established by trained radiologists."

8. Sample Size for Training Set

Sample Size for Training Set: Not explicitly stated in the provided text.

9. How Ground Truth for Training Set Was Established

Ground Truth for Training Set: Not explicitly stated in the provided text.

Summary

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Viz.ai, Inc. Pooja Shah Regulatory Affairs Specialist 5000 Center Green Way Cary, NC 27513

February 5, 2024

Re: K232363 Trade/Device Name: Viz HDS. Viz Volume Plus, Viz ICH+ Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: QIH Dated: January 10, 2024 Received: January 10, 2024

Dear Pooja Shah:

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 (the 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 available at https://www.accessdata.fda.gov/scripts/cdrb/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.

Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).

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Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).

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 Part 803) for devices or postmarketing safety reporting (21 CFR Part 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 Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 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 (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely,

Jessica Lamb

Jessica Lamb Assistant Director Imaging Software Team DHT8B: Division of Radiologic Imaging Devices and Electronic Products OHT8: Office of 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) K232363

Device Name

Viz HDS, Viz Volume Plus, Viz ICH+

Indications for Use (Describe)

The Viz HDS device is intended for automatic labeling, visualization of segmentable brain structures from a set of Non-Contrast CT (NCCT) head scans. The software is intended to automate the current manual process of identifying, labeling, and quantifying the volume of segmentable brain structures identified on NCCT images. Viz HDS provides volumes from NCCT scans acquired at a single time point. The Viz HDS software is indicated for use in the analysis of the following structures: Intracranial Hyperdensities, Lateral Ventricles and Midline Shift. The device output should be reviewed along with patient's original images by a physician.

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

☑ Prescription Use (Part 21 CFR 801 Subpart D)	☐ Over-The-Counter Use (21 CFR 801 Subpart C)
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K232363

Image /page/3/Picture/1 description: The image shows a blue logo. The logo is composed of several curved lines that are arranged in a symmetrical pattern. The lines are thicker at the top and bottom and thinner in the middle. The overall shape of the logo is reminiscent of a stylized letter V or a bird in flight.

510(k) SUMMARY

Viz.ai, Inc.'s Viz HDS

Applicant Name: Viz.ai, Inc. 5000 Center Green Way, Cary, NC 27513
Contact Person: Pooja Shah
- Regulatory Affairs Specialist
- 5000 Center Green Way,
- Cary, NC 27513
- Tel. (669)288-4344
- pooja.shah@viz.ai
Date Prepared: January 30, 2024

Device Name and Classification:

Name of Device: Viz HDS, Viz Volume Plus, Viz ICH+
Common or Usual Name: Automated Radiological Image Processing Software
Classification Panel: Radiology
Regulation No: 21 C.F.R. § 892.2050
Regulatory Class: Class II
Product Code: QIH

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Predicate Devices

Manufacturer	Device Name	Application No.
Qure.ai technologies	qER-Quant	K211222

Device Description

Workflow:

Viz HDS is hosted in Viz.ai's cloud server. For customers that have Viz HDS enabled, when they send NCCT head scans to the server, the scans are directed to the HDS processor for analysis. At the end of the processing the results series are created and sent back to the customer's site to a DICOM node (e.g. PACS) defined for that customer.

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Workflow Diagram:

Image /page/5/Figure/2 description: This image shows a diagram of the Viz.ai cloud server system. The diagram shows three healthcare facilities uploading head NCCT scans to the Viz.ai cloud server. The scans are processed on the Viz server using the Viz HDS algorithm. The processed results are sent to the healthcare facilities' PACS.

Figure 1. Workflow diagram of Viz HDS

Segmentation and Summary Series:

Following are two examples for the output series generated by the Viz HDS device. Figure 1 shows a sample image from the Segmentation series and next to it the original slice from the head NCCT series (without the overlay and legend). Figure 2 shows an example of the summary slice and next to it the summary table image that is part of the summary series.

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Image /page/6/Picture/1 description: The image shows two axial CT scans of a brain. The left scan has colored overlays indicating different regions and their volumes: HD1 is 53.58ml, HD2 is 41.92ml, RLV is 11.8ml, and LLV is 7.7ml. The right scan shows the same axial view without the colored overlays, providing a clear view of the brain's anatomical structures.

Figure 2. Left image: A sample image from the Segmentation series showing overlays of the identified hyperdensities and lateral ventricles segmentation provided by the Viz HDS device, legend contains the HDS volume measurements, sorted from high to low volume, and the lateral ventricles volume measurements. Right image: the corresponding image from the original head NCCT series.

Image /page/6/Figure/3 description: This image shows a brain scan with a "Viz Hyperdensity Summary" on the right side. The summary lists HD1 as 53.58ml, HD2 as 41.92ml, and a total of 95.5ml. It also lists RLV Volume as 11.8ml, LLV Volume as 7.7ml, Midline Shift as 2.2mm, and LV Asymmetry Ratio as 1.5.

Figure 3. Left image: An example of a single slice summary image showing as overlays the identified hyperdensity, lateral ventricles and midline shift segmentation provided by the Viz HDS device. The legend contains the hyperdensities volume measurements (mL), sorted from high to low volume, the right and left lateral ventricles volume measurements (mL) and the midline shift value (mm). Right image: An example of the summary table image in the Summary series generated by the Viz HDS device. The table shows all of the

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identified hyperdensities, the right and left lateral ventricles, their asymmetry ratio and midline shift that was measured by the algorithm in the original NCCT series.

Intended Use / Indications for Use

Summary of Technological Characteristics

The subject device, Viz HDS, is substantially equivalent to the predicate device, qER-Quant (K211222). In comparing the technological characteristics, both the subject and predicate devices use an artificial intelligence algorithm to identify, label and quantify clinical findings in NCCT imaging. Where the subject and predicate device differ is that the software algorithm for the subject device provides volumes from NCCT scans acquired at single time point whereas, predicate device provides volumes from NCCT images acquired at a single time point and provides comparative analysis for two or more images that were acquired on the same scanner with the same acquisition protocol for the same individual at multiple time points.

Both the subject device and the predicate device provide findings through back to PACS to hospital's server that allow user to preview images and patients identified, labeled and quantified with segmentable brain structure to automate the manual process of measurement. Both the devices have DICOM annotated series image and summary report as an output. Where the subject and predicate device differ is that the subject device have RGB overlay as the output for abnormal hyperdensities whereas the predicate device represent hyperdensities is a singular color. This difference does not raise any safety or efficacy question as the colors are only for visual differentiation between the segmented regions, the colors don't have a meaning on their own.

Both the subject and predicate device use a deep-learning algorithm that analyzes NCCT images for identifying, labeling and quantifying volume of segmentable brain structures. Both the devices are intended to be used as aid to physicians for identifying, labeling and quantifying segmentable brain structures on NCCT images. Because of the similarities regarding the type of algorithms, the type of imaging data processed by the devices, the intended use of the devices, and the outputs of the image analysis, the difference in the output visual does not raise new or different questions regarding safety or efficacy.

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	Predicate Device	Subject Device
	qER-Quant	Viz HDS
Application No.	K211222	K232363
Product Code	QIH	QIH
Regulation No.	21 C.F.R. § 892.2050	21 C.F.R. § 892.2050
Intended Use /Indications for Use	The qER-Quant device is intended forautomatic labeling, visualization andquantification of segmentable brainstructures from a set of Non-Contrast headCT (NCCT) images. The software is intendedto automate the current manual process ofidentifying, labeling and quantifying thevolume of segmentable brain structuresidentified on NCCT images.qER-Quant provides volumes from NCCTimages acquired at a single time point andprovides a table with comparative analysis fortwo or more images that were acquired on thesame scanner with the same imageacquisition protocol for the same individual atmultiple time points.The qER-Quant software is indicated for usein the analysis of the following structures:Abnormal Intracranial Hyperdensities, LateralVentricles and Midline Shift.	The Viz HDS device is intended for automaticlabeling, visualization, and quantification ofsegmentable brain structures from a set ofNon-Contrast CT (NCCT) head scans. Thesoftware is intended to automate the currentmanual process of identifying, labeling, andquantifying the volume of segmentable brainstructures identified on NCCT images. VizHDS provides volumes from NCCT scansacquired at a single time point. The Viz HDSsoftware is indicated for use in the analysis ofthe following structures: IntracranialHyperdensities, Lateral Ventricles andMidline Shift. The device output should bereviewed along with patient's original imagesby a physician.
Anatomical Region	Head	Head
IndependentStandard of CareWorkflow	Yes	Yes
Input images	Non-contrast CT from a single or multipletime points	Non-contrast CT from a single time point
Clinical Condition	Intracranial hyperdensities, lateral ventriclesand midline shift	Intracranial hyperdensities, lateral ventriclesand midline shift
Data Acquisition	Acquires medical image data from DICOMcompliant imaging devices and modalities.	Acquires medical image data from DICOMcompliant imaging devices and modalities.
Supported ImagingModality	Non-contrast CT (NCCT)	Non-contrast CT (NCCT)
Alteration ofOriginal Image	No	No
Artificial IntelligenceAlgorithm	Yes	Yes
Output	Multiple electronic reports with volumetricinformation of brain structures and midlineshift AND Annotated DICOM Images	Multiple electronic reports with volumetricinformation of brain structures and midlineshift AND Annotated DICOM Images

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Performance Data

Clinical testing was performed as a study comparing the Viz HDS's output to the ground truth as established by trained radiologists. The study demonstrated that the MAE (Mean absolute error) for hyperdensities total volume, right lateral ventricle volume, left lateral ventricle volume, and midline shift distance upper 95% Cl bounds were less than 7.5 mL, 3 mL, and 2 mm, respectively between the algorithm and the established ground truth, which was aligned with the performance goal.

Additionally, DICE score was calculated to describe the degree of agreement between the measurements by the Viz HDS algorithm in comparison to the measurements that were obtained manually. The study demonstrated that the DICE score for hyperdenity(ies) and both lateral ventricles lower CI bound was greater than 70%, which was aligned with the performance goal.

Stratification of device performance was divided by clinical site, gender, age, slice thickness, scanner manufacturer,model, scanning parameters and size of estimated quantity.

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Conclusions

Viz HDS is as safe and effective as the predicate device. The subject device and the predicate have the same intended use and similar indications, technological characteristics, and principles of operation. The subject device differs in that it provides a report acquired at a single time point whereas, predicate device provides a report acquired at a single time point and provides comparative analysis. Both subject and predicate provide findings through back to PACS destination of hospital. These differences do not present new or different questions of safety or effectiveness with respect to the predicate device. Viz.ai has provided supportive clinical data and software testing which demonstrates that the subject device can perform effective labeling, visualization of intracranial hyperdensities, lateral ventricles and midline shift. Thus, Viz HDS is substantially equivalent to the predicate.

Regulation Number and Section

§ 892.2050 Medical image management and processing system.

(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).