K251029 · Vista AI, Inc. · LNH · Aug 21, 2025 · Radiology
Device Facts
Record ID
K251029
Device Name
Vista OS, Vista AI Scan, RTHawk
Applicant
Vista AI, Inc.
Product Code
LNH · Radiology
Decision Date
Aug 21, 2025
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 892.1000
Device Class
Class 2
Attributes
AI/ML, Software as a Medical Device
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
Motion artifact detection
Neural network
Agreement > 80%
80% agreement
—
—
120 sample images collected from prior versions of Vista OS
>1 (cardiologist)
Cardiac waveform suitability
Neural network
Agreement > 80%
80% agreement
—
—
100 sample ECGs
>1 (cardiologist)
Cardiac image denoising
Neural network
Diagnostic quality superior in > 80% of test cases
> 80% of test cases
—
—
209 sample image series
>1 (board-certified radiologists or cardiologists)
Brain localizer prescription
Neural network
Mean angulation error < 3 degrees, mean position error < 5 mm
—
—
—
323 sample image localizations
>1 (board-certified radiologists or cardiologists)
Prostate localizer prescription
Neural network
Mean 3D Intersection-over-Union (IoU) >= 0.65
—
—
—
329 sample image localizations
>1 (board-certified radiologists or cardiologists)
Velocity-encoding (VENC) prediction
Neural network
Average velocity error < 10%
—
—
—
42 sample VENC peak estimates
>1 (board-certified radiologists or cardiologists)
Indications for Use
Vista OS is an accessory to 1.5T and 3.0T whole-body magnetic resonance diagnostic devices (MRDD). It is intended to operate alongside, and in parallel with, the existing MR console to acquire traditional, real-time and accelerated images. Vista OS software controls the MR scanner to acquire, reconstruct and display static and dynamic transverse, coronal, sagittal, and oblique cross-sectional images that display the internal structures and/or functions of the entire body. The images produced reflect the spatial distribution of nuclei exhibiting magnetic resonance. The magnetic resonance properties that determine image appearance are proton density, spin-lattice relaxation time (T1), spin-spin relaxation time (T2) and flow. When interpreted by a trained physician, these images provide information that may assist in the determination of a diagnosis. Vista OS is intended for use as an accessory to the following MRI systems: Manufacturers: GE Healthcare (GEHC), Siemens Healthineers Field Strength: 1.5T and 3.0T GE Software Versions: 12, 15, 16, 23, 24, 25, 26, 30 Siemens Software Versions: N4/VE; NX/VA
Device Story
Vista OS (RTHawk 3.3.0) is a software-based MRI accessory operating in parallel with existing 1.5T/3.0T MR scanner consoles. It requires no permanent hardware modifications; connects via private Ethernet. The system automates MRI setup, parameter selection, and image reconstruction to improve workflow efficiency. Input data includes MR raw signals; output includes static/dynamic cross-sectional images. AI models assist technologists with prescription localization, cardiac segmentation, artifact detection, and motion registration. The technologist retains final control, reviewing AI-suggested settings and images on a workstation. The system benefits patients by reducing exam time and increasing scan reliability through automated parameter adjustments and motion correction. It is used in clinical settings by MRI technologists.
Clinical Evidence
Bench testing and clinical verification studies performed. Clinical verification used independent, blinded board-certified radiologists/cardiologists to assess AI performance on diverse datasets (segregated from training/tuning). Key results: Motion artifact detection (80% agreement); Ungateable waveform detection (80% agreement); Cardiac denoising (superior quality in >80% cases); Brain localizer (mean angulation error <3°, position error <5mm); Prostate localizer (mean IoU ≥0.65); VENC prediction (average velocity error <10%). All metrics met pre-defined acceptance criteria.
Technological Characteristics
Software platform (RTHawk) running on customer-sourced Linux workstation. Connectivity: Private Ethernet to MR scanner. Standards: IEC 60601-2-33 (safety), IEC 60601-1 (PEMS), NEMA PS3.1-3.20 (DICOM), ISO 14971 (risk). AI: Multi-layered neural networks for image analysis/automation. No generative AI. Operates within IEC 60601-2-33 1st Level Operating Mode.
Indications for Use
Indicated for use as an accessory to 1.5T and 3.0T whole-body MRI systems (GE Healthcare and Siemens Healthineers) to acquire, reconstruct, and display static and dynamic cross-sectional images of the entire body for diagnostic assistance by a trained physician.
Regulatory Classification
Identification
A magnetic resonance diagnostic device is intended for general diagnostic use to present images which reflect the spatial distribution and/or magnetic resonance spectra which reflect frequency and distribution of nuclei exhibiting nuclear magnetic resonance. Other physical parameters derived from the images and/or spectra may also be produced. The device includes hydrogen-1 (proton) imaging, sodium-23 imaging, hydrogen-1 spectroscopy, phosphorus-31 spectroscopy, and chemical shift imaging (preserving simultaneous frequency and spatial information).
Special Controls
*Classification.* Class II (special controls). A magnetic resonance imaging disposable kit intended for use with a magnetic resonance diagnostic device only is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.
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FDA U.S. FOOD & DRUG ADMINISTRATION
August 21, 2025
Vista AI, Inc.
James Rogers
Regulatory Affairs and Strategic Quality Assurance
431 Florence Street
Suite 100
Palo Alto, California 94301
Re: K251029
Trade/Device Name: Vista OS, Vista AI Scan, RTHawk
Regulation Number: 21 CFR 892.1000
Regulation Name: Magnetic Resonance Diagnostic Device
Regulatory Class: Class II
Product Code: LNH
Dated: April 2, 2025
Received: July 18, 2025
Dear James Rogers:
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/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.
U.S. Food & Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov
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K251029 - James Rogers
Page 2
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).
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 (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-reporting-combination-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.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
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-devices/medical-device-safety/medical-device-reporting-mdr-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/medical-devices/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-devices/device-advice-comprehensive-regulatory-
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K251029 - James Rogers
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assistance/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,

Daniel M. Krainak, Ph.D.
Assistant Director
DHT8C: Division of Radiological
Imaging and Radiation Therapy Devices
OHT8: Office of Radiological Health
Office of Product Evaluation and Quality
Center for Devices and Radiological Health
Enclosure
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FORM FDA 3881 (8/23)
Page 1 of 1
PSC Publishing Services (301) 443-6740
EF
| DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration Indications for Use | Form Approved: OMB No. 0910-0120 Expiration Date: 07/31/2026 See PRA Statement below. |
| --- | --- |
| 510(k) Number (if known) K251029 | |
| Device Name Vista OS, Vista AI Scan, RTHawk | |
| Indications for Use (Describe) Vista OS is an accessory to 1.5T and 3.0T whole-body magnetic resonance diagnostic devices (MRDD). It is intended to operate alongside, and in parallel with, the existing MR console to acquire traditional, real-time and accelerated images. Vista OS software controls the MR scanner to acquire, reconstruct and display static and dynamic transverse, coronal, sagittal, and oblique cross-sectional images that display the internal structures and/or functions of the entire body. The images produced reflect the spatial distribution of nuclei exhibiting magnetic resonance. The magnetic resonance properties that determine image appearance are proton density, spin-lattice relaxation time (T1), spin-spin relaxation time (T2) and flow. When interpreted by a trained physician, these images provide information that may assist in the determination of a diagnosis. Vista OS is intended for use as an accessory to the following MRI systems: Manufacturers: GE Healthcare (GEHC), Siemens Healthineers Field Strength: 1.5T and 3.0T GE Software Versions: 12, 15, 16, 23, 24, 25, 26, 30 Siemens Software Versions: N4/VE; NX/VA | |
| 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) | |
| CONTINUE ON A SEPARATE PAGE IF NEEDED. | |
| This section applies only to requirements of the Paperwork Reduction Act of 1995. *DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.* | |
| The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to: Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff@fda.hhs.gov | |
| "An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number." | |
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vista
Vista AI, Inc.
431 Florence Street, Suite 100
Palo Alto, CA 94301
+1 650-800-7937 | info@vista.ai | vista.ai
# 510(k) Summary
# Vista OS; Vista AI Scan; RTHawk
# K251029
Administrative Information
| Submitter Name | Vista AI, Inc. |
| --- | --- |
| Submitter Address | 431 Florence Street
Suite 100
Palo Alto, CA 94301 |
| Establishment Registration # | 3011767965 |
| Primary Contact | James Jochen Rogers
FDA Regulatory Affairs, Quality Assurance, and Clinical Studies
T: 724.713.2298
E: jr@vista.ai |
| Submission Date | April 2, 2025 |
Device Information
| Trade / Proprietary Name | Vista OS, Vista AI Scan, RTHawk |
| --- | --- |
| Common Name | RTHawk |
| Product Version | RTHawk 3.3.0 |
| Regulation Number | 892.1000 |
| Regulation Name | Magnetic resonance diagnostic device (MRDD) |
| Regulatory Class | Class II |
| Device Classification Name | System, Nuclear Magnetic Resonance Imaging |
| Classification Panel | Radiology |
| Classification Product Code | LNH |
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vista
Vista AI, Inc.
431 Florence Street, Suite 100
Palo Alto, CA 94301
+1 650-800-7937 | info@vista.ai | vista.ai
# Predicate Device(s)
| 510(k) # | Device | 510(k) Sponsor | Clearance Date |
| --- | --- | --- | --- |
| K212233 | RTHawk, HeartVista Cardiac Package | HeartVista, Inc. | October 5, 2021 |
# Device Description
The Vista AI "Vista OS" product provides a seamless user experience for performing MRI studies on GE and Siemens scanners. The underlying software platform that we use to accomplish this task is called "RTHawk".
RTHawk is a software platform designed from the ground up to provide efficient MRI data acquisition, data transfer, image reconstruction, and interactive scan control and display of static and dynamic MR imaging data. It can control MR pulse sequences provided by Vista AI and, on scanners that support it, it can equally control MR pulse sequences provided by the scanner vendor. Scan protocols can be created by the user that mix and match among all available sequences.
RTHawk is an accessory to clinical 1.5T and 3.0T MR systems, operating alongside, and in parallel with, the MR scanner console with no permanent physical modifications to the MRI system required.
The software runs on a stand-alone Linux-based computer workstation with color monitor, keyboard and mouse. It is designed to operate alongside, and in parallel with, the existing MR console with no hardware modifications required to be made to the MR system or console. This workstation (the "Vista Workstation") is sourced by the Customer in conformance with specifications provided by Vista AI, and is verified prior to installation.
A private Ethernet network connects the Vista Workstation to the MR scanner computer. When not in use, the Vista Workstation may be detached from the MR scanner with no detrimental, residual impact upon MR scanner function, operation, or throughput.
RTHawk is an easy-to-use, yet fully functional, MR Operating System environment. RTHawk has been designed to provide a platform for the efficient acquisition, control, reconstruction, display, and storage of high-quality static and dynamic MRI images and data.
Data is continuously acquired and displayed. By user interaction or data feedback, fundamental scan parameters can be modified. Real-time and high-resolution image
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vista
Vista AI, Inc.
431 Florence Street, Suite 100
Palo Alto, CA 94301
+1 650-800-7937 | info@vista.ai | vista.ai
acquisition methods are used throughout RTHawk for scan plane localization, for tracking of patient motion, for detection of transient events, for on-the-fly, sub-second latency adjustment of image acquisition parameters (e.g., scan plane, flip angle, field-of-view, etc.) and for image visualization.
RTHawk implements the conventional MRI concept of anatomy- and indication-specific Protocols (e.g., ischemia evaluation, valvular evaluation, routine brain, etc.). Protocols are pre-set by Vista AI, but new protocols can be created and modified by the end user.
RTHawk Apps (Applications) are composed of a pulse sequence, predefined fixed and adjustable parameters, reconstruction pipeline(s), and a tailored graphical user interface containing image visualization and scan control tools. RTHawk Apps may provide real-time interactive scanning, conventional (traditional) batch-mode scanning, accelerated scanning, or calibration functions, in which data acquired may be used to tune or optimize other Apps.
When vendor-supplied pulse sequences are used in Vista OS, parameters and scan planes are prescribed in the Vista interface and images reconstructed by the scanner appear on the Vista Workstation. RTHawk Apps and vendor-supplied sequences can be mixed within a single protocol with a unified user experience for both.
# Machine Learning Use in Vista OS
The AI algorithms within the Vista OS system are designed to assist MRI technologists which are always in control of the scan process. The software automates aspects of MRI setup and parameter selection to help reduce exam time, simplify the workflow, and increase reliability. The AI models are employed to perform specific tasks such as:
- Prescription Localization: The AI provides an initial estimate of image prescriptions, which the technologist can adjust.
- Cardiac Segmentation: The AI provides measurements of the subject's anatomy to aid in optimizing imaging parameters, which the technologist can modify.
- Artifact Detection: The AI alerts the technologist to poor image quality resulting from breathing artifacts or irregular rhythm.
- Cardiac Motion Registration: The AI improves image quality by reducing motion across images when scanned in the cardiac short-axis view.
No clinical decisions are made by the software. The outputs of the AI models are imaging acquisition settings and preliminary analyses useful for assisting the acquisition of images, which are then visually presented to the technologist. The technologist retains the ability to reject or modify the AI's outputs.
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vista
Vista AI, Inc.
431 Florence Street, Suite 100
Palo Alto, CA 94301
+1 650-800-7937 | info@vista.ai | vista.ai
The system uses neural networks for image analysis, with no generative AI employed. These models have a multi-layered architecture that reduces data to the most relevant set for inline image analysis.
RTHawk operates compatible MR scanners within the safety parameters listed below:
| Safety Parameter | Safety Level |
| --- | --- |
| Magnetic Field Strength | 1.5T, 3.0T |
| Operating Modes | IEC 60601-2-33 1st Level Operating Mode |
| Safety Parameter Display | SAR, dB/dt |
| Max SAR | < 4 W/kg whole-body |
| Max dB/dt | 1st Level Operating Mode |
# Indications for Use
Vista OS is an accessory to 1.5T and 3.0T whole-body magnetic resonance diagnostic devices (MRDD). It is intended to operate alongside, and in parallel with, the existing MR console to acquire traditional, real-time and accelerated images.
Vista OS software controls the MR scanner to acquire, reconstruct and display static and dynamic transverse, coronal, sagittal, and oblique cross-sectional images that display the internal structures and/or functions of the entire body. The images produced reflect the spatial distribution of nuclei exhibiting magnetic resonance. The magnetic resonance properties that determine image appearance are proton density, spin-lattice relaxation time (T1), spin-spin relaxation time (T2) and flow. When interpreted by a trained physician, these images provide information that may assist in the determination of a diagnosis.
Vista OS is intended for use as an accessory to the following MRI systems:
Manufacturers:: GE Healthcare (GEHC), Siemens Healthineers
Field Strength:: 1.5T and 3.0T
GE Software Versions:: 12, 15, 16, 23, 24, 25, 26, 30
Siemens Software Versions:: N4/VE; NX/VA
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vista
Vista AI, Inc.
431 Florence Street, Suite 100
Palo Alto, CA 94301
+1 650-800-7937 | info@vista.ai | vista.ai
# Performance Data
Vista OS was designed, developed, and validated to conform with all applicable requirements and standards to establish the device's safety and effectiveness. Quality assurance measures employed during the development of Vista OS include:
- Code reviews
- Design reviews
- Unit and integration level testing
- Verification testing, including System and Manual testing
- Safety testing, including SAR, dB/dt, and acoustic noise
- Performance testing, including SNR and uniformity
- Validation testing
Vista AI has made general use of the FDA Recognized Consensus Standards listed in the table below, as applicable to device features and components:
| Reference # | Title |
| --- | --- |
| IEC 60601-2-33:2022-08 (Ed. 4.0) | Medical electrical equipment - Part 2-33: Particular requirements for the basic safety and essential performance of magnetic resonance equipment for medical diagnosis (radiology) |
| IEC 60601-1:2020 (Ed. 3.2) | Medical electrical equipment - Part 1: General requirements for basic safety and essential performance; Section 14 Programmable Electrical Medical Systems (PEMS) |
| MS1-2008 | Determination of Signal-to-Noise Ratio (SNR) in Diagnostic Magnetic Resonance Imaging |
| MS3-2008 | Determination of Image Uniformity in Diagnostic Magnetic Resonance Images |
| MS4-2010 | Acoustic Noise Measurement Procedure for Diagnostic Magnetic Resonance Imaging Devices |
| MS8-2016 | Characterization of the Specific Absorption Rate (SAR) for Magnetic Resonance Imaging Systems |
| NEMA PS3.1 - 3.20 (2023e) | Digital Imaging And Communications In Medicine (DICOM) Set |
| ISO 14971:2019 | Medical Devices - Application Of Risk Management To Medical Devices |
Tests conducted according to the above-referenced standards demonstrate that Vista OS meets the requirements for its intended use and demonstrates substantial equivalence to the predicate device.
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vista
Vista AI, Inc.
431 Florence Street, Suite 100
Palo Alto, CA 94301
+1 650-800-7937 | info@vista.ai | vista.ai
# Vista OS AI Model Training and Verification
Vista OS neural-network models were developed and trained using industry-standard methods for partitioning and isolating training, tuning, and internal testing datasets. Neural-network parameters and weights were updated on the training data and evaluated on the tuning data at each epoch. Upon full training, the model's generalizability was assessed on the independent internal testing dataset (preceding clinical verification). Model development data was partitioned by unique anonymous patient identifiers to prevent overlap across training, internal testing, and clinical verification datasets.
After training the Vista OS models, clinical verification testing was performed for each new feature to assess clinical performance. Clinical assessments were performed by independent board-certified radiologists or cardiologists who were not involved in any aspect of model development (including providing labels for training, tuning or internal testing). Clinicians involved in clinical assessment were blinded to patient clinical information. Data used in clinical verification were obtained from multiple clinical sites representing diverse ethnic groups, genders, and ages. The clinical verification data was isolated from data used internally for training and tuning.
# Summary of Clinical Verifications
To test the automatic detection of motion artifacts in Cine Cartesian SSFP, 120 sample images collected from prior versions of Vista OS were assessed for the presence of clinically significant artifacts. Among images assessed, 81% were collected from male patients, 50% from 1.5 Tesla scanners, and 84% were scanned using GE scanners. Patient ages ranged from 20 to 80 years. Test data was segregated from training and tuning data and used only once in final clinical verification. The primary acceptance criterion for this test was 80% agreement between neural-network assessment at its default sensitivity level and the cardiologist reader.
To test the automatic detection of ungateable cardiac waveforms, 100 sample ECGs were assessed for suitability for a high-quality gated MR examination. Among waveforms assessed, 64% were collected from 1.5 Tesla scanners and 68% were collected using GE scanners. 37% of test waveform data did not specify a gender. Of the remaining 63%, 75% were collected from male patients. Patient ages ranged from 18 to 100 years. Test data was segregated from training and tuning data and used only once in final clinical verification. The primary acceptance criterion for this test was 80% agreement between neural-network assessment at its default sensitivity level and the cardiologist reader.
To test automatic cardiac image denoising, 209 sample image series collected from prior versions of Vista OS were assessed along with paired image series that were denoised using default parameters. Among image series assessed, 79% were collected from male
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vista
Vista AI, Inc.
431 Florence Street, Suite 100
Palo Alto, CA 94301
+1 650-800-7937 | info@vista.ai | vista.ai
patients, 67% from 1.5 Tesla scanners, and 67% were scanned using GE scanners. Patient ages ranged from 25 to 85 years. Test data was segregated from training and tuning data and used only once in final clinical verification. The primary acceptance criterion for this test was that the denoising should not detract from diagnostic accuracy in all cases, and that the diagnostic quality of the denoised data be judged superior to its paired non-denoised series in more than 80% of test cases.
To test automatic brain localizer prescriptions, 323 sample image localizations were assessed across all provided localizer orientations. Among images assessed, 26% were collected from male patients, 95% from 1.5 Tesla scanners, and 86% were scanned using GE scanners. Patient ages ranged from 30 to 88 years. Test data was segregated from training and tuning data and used only once in final clinical verification. Acceptance criteria for this test included mean error in plane angulation of less than 3 degrees with standard deviation less than 5 degrees, and a mean plane position error less than 5 mm with standard deviation less than 15 mm.
To test automatic prostate localizer prescriptions, 329 sample image localizations were assessed across all provided localizer orientations. Among images assessed, 100% were collected from male patients, 25% from 1.5 Tesla scanners, and 5% were scanned using GE scanners. Patient ages ranged from 49 to 76 years. Test data was segregated from training and tuning data and used only once in final clinical verification. Acceptance criteria for this test included mean 3D Intersection-over-Union (IoU) metrics of at least 0.65 for each volumetric scan prescription.
To test automatic prediction of velocity-encoding VENC for cine flow studies, 42 sample VENC peak estimates were assessed. Among images assessed, 86% were collected from male patients, 21% from 1.5 Tesla scanners, and 21% were scanned using GE scanners. Patient ages ranged from 37 to 75 years. Test data was segregated from training and tuning data and used only once in final clinical verification. The primary acceptance criterion for this test was that the average velocity error should be less than 10% individually for all vessels and views.
The results of all above clinical verification studies evaluating the performance of Vista OS models have demonstrated that their performance meets or exceeds the specified acceptance criteria for each of the tasks being assessed. In addition, all automations are provided as an additional aid to the trained operator who has the final decision power to accept or reject any suggestion or image enhancement that is provided. Therefore, the clinical performance of Vista OS has been adequately verified to meet the requirements for its intended use and demonstrates substantial equivalence to the predicate device.
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vista
Vista AI, Inc.
431 Florence Street, Suite 100
Palo Alto, CA 94301
+1 650-800-7937 | info@vista.ai | vista.ai
# Technological Comparison to Predicate Device
Both the subject device and the predicate device software are intended as an accessory to 1.5T and 3.0T MRI systems, and are intended to integrate and interact seamlessly with the operating system software within those MRI systems. Both devices support all coils available on the specific installation's MRI console. Neither device supports software-controlled patient table movements and shifts. Both devices support remote access to and imaging on the specific installation's MRI system.
The submitted Vista OS software is comprised of the following functional modules which are also present in the predicate device:
- Acquisition - responsible for the transfer of MR raw data from the MR scanner to the Vista Workstation
- Analysis - contains the image post-processing tools
- Application - Vista APPs. Each APP is comprised of a pulse sequence, user parameters, a reconstruction pipeline, and a specific user interface
- Information System - the central repository of all relevant MRI system configuration, patient, study, scan, etc., parameters associated with the current patient study
- Reconstruction - responsible for the efficient processing of raw data to generate MR images via a flexible, pipelined topology
- Scan Control - responsible for low-latency network transfer of controlling orders for APPs, APPs parameters modifications, and dynamic information from the MR host in response to user or program requests
- Sequencer - creates and provides a specific set of pulse sequence waveforms to control the MR scanner
- Storage - obtains current patient and scan information, performs non-volatile local storage, exports images and data in DICOM format, and logs events.
- Visualization - implements all aspects of the user interface, including APP selection, controls to modify APP parameters, image display, image analysis, graphical slice prescription, and image review, save, and export.
As with the predicate device, RTHawk Apps (Applications) are composed of a pulse sequence, predefined fixed and adjustable parameters, reconstruction pipeline(s), and a tailored graphical user interface containing image visualization and scan control tools. RTHawk Apps provide real-time interactive, batch-mode, and accelerated scanning, as well as calibration functions, in which data acquired may be used to tune or optimize other Apps. Orthogonal, oblique, and double oblique imaging planes are fully supported. Vista OS consists of a collection of default protocols containing a combination of RTHawk Apps and vendor-provided pulse sequences, and functions and features of those Apps are unchanged from the predicate device.
In this submission, notable changes include:
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vista
Vista AI, Inc.
431 Florence Street, Suite 100
Palo Alto, CA 94301
+1 650-800-7937 | info@vista.ai | vista.ai
- Automatic detection of motion artifacts in Cine Cartesian SSFP
- Automatic detection of ungateable cardiac waveforms
- New AI-based image denoising applicable to cardiac image acquisitions
- A new Brain Localizer App is provided to automatically localize several standard views in the brain
- A new Prostate Localizer App is provided to automatically localize several standard views in the prostate
- Extended the Cardiac Localizer App to provide automatic localization of additional views
- A new Frequency Scout App is provided to automatically determine the frequency offset that minimizes SSFP banding artifacts in the four-chamber view
- A new Cine Flow Calibration App option performs a high-VENC Cine Flow scan and then automatically determines the optimal VENC setting for subsequent scans
- A new inversion pulse is used in the Cardiac T1 Map App to improve inversion efficiency
- Support for new GE software versions HD16, SV25, and MR30.1
- Compatibility with the newer Ubuntu 24.04 operating system version
- Product name change to "Vista AI Scan" / "Vista OS"
Instructions for use are included within the device labeling, and the information provided enables the user to operate the device in a safe and effective manner.
The following compares the modified device to the predicate device K212233:
| Attribute | RTHawk 3.0.0, K212233 | RTHawk 3.3.0: Subject Device |
| --- | --- | --- |
| Device Name | RTHawk, HeartVista Cardiac Package | Vista OS, Vista AI Scan, RTHawk |
| Indications for Use | RTHawk is an accessory to 1.5T and 3.0T whole-body magnetic resonance diagnostic devices (MRDD or MR). It is intended to operate alongside, and in parallel with, the existing MR console to acquire traditional, real-time and accelerated images. The HeartVista Cardiac Package is a collection of RTHawk Apps designed to acquire, reconstruct and display cardiovascular MR (CMR) images. RTHawk produces static and dynamic transverse, coronal, sagittal, and oblique cross-sectional images that display the internal structures and/or functions of the entire body. The images produced reflect the spatial distribution of nuclei exhibiting magnetic resonance. The magnetic resonance properties that determine image appearance are proton density, spin-lattice relaxation time (T1), spin-spin relaxation time (T2) and flow. When interpreted by a trained physician, these | Vista OS is an accessory to 1.5T and 3.0T whole-body magnetic resonance diagnostic devices (MRDD). It is intended to operate alongside, and in parallel with, the existing MR console to acquire traditional, real-time and accelerated images. Vista OS software controls the MR scanner to acquire, reconstruct and display static and dynamic transverse, coronal, sagittal, and oblique cross-sectional images that display the internal structures and/or functions of the entire body. The images produced reflect the spatial distribution of nuclei exhibiting magnetic resonance. The magnetic resonance properties that determine image appearance are proton density, spin-lattice relaxation time (T1), spin-spin relaxation time (T2) and flow. When interpreted by a trained physician, these |
{13}
vista
Vista AI, Inc.
431 Florence Street, Suite 100
Palo Alto, CA 94301
+1 650-800-7937 | info@vista.ai | vista.ai
| | spin-spin relaxation time (T2) and flow. When interpreted by a trained physician, these images provide information that may assist in the determination of a diagnosis. RTHawk is intended for use as an accessory to the following MRI systems: Manufacturers: GE Healthcare (GEHC), Siemens Healthineers Field Strengths: 1.5T and 3.0T GE Software Versions: 12, 15, 16, 23, 24, 25, 26 Siemens Software Versions: N4/VE; NX/VA | images provide information that may assist in the determination of a diagnosis. Vista OS is intended for use as an accessory to the following MRI systems: Manufacturers:: GE Healthcare (GEHC), Siemens Healthineers Field Strength:: 1.5T and 3.0T GE Software Versions:: 12, 15, 16, 23, 24, 25, 26, 30 Siemens Software Versions:: N4/VE; NX/VA |
| --- | --- | --- |
| Scanner Compatibility | GE Healthcare, Siemens Healthineers | GE Healthcare, Siemens Healthineers |
| Magnetic Field Strengths | 1.5T, 3.0T | 1.5T, 3.0T |
| Shift/Advance Table | No | No |
| Imaging Planes | Transverse, Coronal, Sagittal, Oblique, Double Oblique | Transverse, Coronal, Sagittal, Oblique, Double Oblique |
| Pulse Sequences | | |
| | B0 Mapping | B0 Mapping |
| | | Brain Localizer |
| | Cardiac Localizer | Cardiac Localizer |
| | Cardiac T1 Map | Cardiac T1 Map |
| | Cardiac T2 Map | Cardiac T2 Map |
| | Cardiac T2* Map Spiral | Cardiac T2* Map Spiral |
| | Cardiac T2* Map Cartesian | Cardiac T2* Map Cartesian |
| | Cartesian Shimming | Cartesian Shimming |
| | Cine Cartesian SSFP | Cine Cartesian SSFP |
| | Cine DE Cal | Cine DE Cal |
| | | Cine Flow Calibration |
| | Cine Spiral SSFP | Cine Spiral SSFP |
| | FB DE GRE Cal | FB DE GRE Cal |
| | FB DE GRE | FB DE GRE |
{14}
vista
Vista AI, Inc.
431 Florence Street, Suite 100
Palo Alto, CA 94301
+1 650-800-7937 | info@vista.ai | vista.ai
| | FB DE SSFP | FB DE SSFP |
| --- | --- | --- |
| | FB MS Tagging GRE | FB MS Tagging GRE |
| | FB Multi-Slice GRE | FB Multi-Slice GRE |
| | FB Multi-Slice SSFP | FB Multi-Slice SSFP |
| | | Frequency Scout |
| | Gated 3D MRA GRE | Gated 3D MRA GRE |
| | Gated High-Res GRE | Gated High-Res GRE |
| | Gated Double-IR FSE | Gated Double-IR FSE |
| | HART GRE | HART GRE |
| | HART SSFP | HART SSFP |
| | Multi-Slice Cine Flow | Multi-Slice Cine Flow |
| | Multi-Slice DE GRE | Multi-Slice DE GRE |
| | Multi-Slice DE SSFP | Multi-Slice DE SSFP |
| | Nav 3D DE GRE | Nav 3D DE GRE |
| | Noise Measurement | Noise Measurement |
| | | Prostate Localizer |
| | Real-Time Loc GRE | Real-Time Loc GRE |
| | Real-Time Loc SSFP | Real-Time Loc SSFP |
| | Real-Time Color PC | Real-Time Color PC |
| | Single-BH 3D DE GRE | Single-BH 3D DE GRE |
| | Stack of Spiral Cine Flow | Stack of Spiral Cine Flow |
| | Time-Course GRE | Time-Course GRE |
| | Wait | Wait |
| Remote Imaging and Support | Yes | Yes |
| Automated Scan Planning | Yes | Yes |
{15}
vista
Vista AI, Inc.
431 Florence Street, Suite 100
Palo Alto, CA 94301
+1 650-800-7937 | info@vista.ai | vista.ai
# Conclusion
Based upon verification testing and compliance with voluntary standards, the Company believes that Vista OS and RTHawk are substantially equivalent to the predicate device, and do not raise any new questions of safety or effectiveness.
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Learn the FDA Browser
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.