(27 days)
Not Found
Yes.
The device uses "deep learning" for its image reconstruction algorithm to improve image quality. Deep learning is a subset of machine learning, which is a key component of AI models.
No.
The device is used for producing images for diagnostic purposes, not for treating or preventing disease.
Yes
Explanation: The "Intended Use/Indications for Use" states that the device produces images where, "When interpreted by a trained physician, these images provide information that can be useful in determining a diagnosis." This explicitly indicates its role in the diagnostic process.
No
The device is not a software-only medical device because the description explicitly states it is a "portable, ultra-low field magnetic resonance imaging device" and mentions "main interface is a commercial off-the-shelf device that is used for operating the system." This clearly indicates it involves physical hardware components that generate MRI data, not just software for processing. The software components are a part of a larger hardware system.
No.
The device is an MR imaging system used for producing images of the internal structure of the head. It is not designed to perform tests on anatomical samples for diagnostic purposes.
No
The provided text does not contain explicit language stating that the FDA has reviewed and approved or cleared a Predetermined Change Control Plan (PCCP) for this specific device.
Intended Use / Indications for Use
The Swoop Portable MR Imaging System is a portable, ultra-low field magnetic resonance imaging device for producing images that display the internal structure of the head where full diagnostic examination is not clinically practical. When interpreted by a trained physician, these images provide information that can be useful in determining a diagnosis.
Product codes
LNH, MOS
Device Description
The Swoop system is portable, ultra-low field MRI device that enables visualization of the internal structures of the head using standard magnetic resonance imaging contrasts. The main interface is a commercial off-the-shelf device that is used for operating the system, providing access to patient data, exam setup, exam execution, viewing MRI image data for quality control purposes, and cloud storage interactions. The system can generate MRI data sets with a broad range of contrasts. The Swoop system user interface includes touch screen menus, controls, indicators, and navigation icons that allow the operator to control the system and to view imagery. The Swoop System image reconstruction algorithm utilizes deep learning to provide improved image quality for T1W, T2W, FLAIR, and DWI sequences.
The subject Swoop System described in this submission includes software modifications related to the pulse sequences and image processing.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
Magnetic Resonance
Anatomical Site
Head
Indicated Patient Age Range
Adult and pediatric patients (>= 0 years)
Intended User / Care Setting
At the point of care in professional health care facilities such as emergency rooms, intensive/critical care units, hospitals, outpatient, or rehabilitation centers.
Description of the training set, sample size, data source, and annotation protocol
Not Found
Description of the test set, sample size, data source, and annotation protocol
Performance analysis and validation of the subject device Advanced Reconstruction models was performed using a test dataset entirely independent from the dataset used for model training. The test dataset comprised of a total of 118 individual subjects and 378 unique images collected using sequence types available on the subject device. For each subject, a subset of the following sequences were scanned, chosen appropriately for the indication for imaging: T1 Graywhite, T1 Standard, T2, T2 Fast, FLAIR, DWI (DWI b=0, DWI b=900, ADC). Axial, Sagittal, and Coronal orientations were included; for DWI, only Axial was available.
Contrast-to-Noise Ratio Validation: 16 images per sequence type were included for lesion annotation. All annotated images were then reviewed and inaccurate ROI annotations were excluded from the analysis. The data meeting inclusion criteria are described below.
Patients: 43
Images: 95
ROIs: 316
Advanced Reconstruction Image Validation: A sample size of at least 16 was used per sequence. Within the sample dataset at least four cases for each sequence-available image orientation (axial, sagittal, coronal) were used.
Patients: 46
Images: 177
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Advanced Reconstruction Performance Analysis and Validation:
Study Design: Advanced Reconstruction was assessed for robustness, stability, and generalizability over a variety of subjects, design parameters, artifacts, and scan conditions using reference-based metrics. A set of images including Swoop data, high field images, and synthetic contrast images, was used as ground truth target images. Test input data (synthetic k-space generated from the target images) was reconstructed using both Advanced and Linear Reconstruction, and the similarity to the original ground truth image was compared between the two reconstruction methods. Reconstruction outputs with motion and zipper artifacts were qualitatively assessed.
Reference Standard and Metrics: Normalized mean squared error (NMSE) and structural similarity index (SSIM) were used to compare the ability of Advanced Reconstruction to reproduce the ground truth image compared to Linear Reconstruction.
Dataset and Sample Size:
T1, T2, FLAIR: 44 Patients, 92 Images
DWI: 34 Patients, 65 Images
Study Results: For all models and all test datasets NMSE was reduced and SSIM was improved for Advanced Reconstruction test images compared to Linear Reconstruction test images. Advanced Reconstruction preserved the presentation of motion and zipper artifacts and no unexpected output was observed.
Contrast-to-Noise Ratio Validation:
Study Design: Regions of interest (ROI) encompassing pathologies were annotated and reviewed by two American Board of Radiology (ABR) certified radiologists. The contrast-to-noise of hyper- and hypo-intense pathologies were measured with respect to healthy white matter tissue from the same image. The inclusion criterion for images used for this study was at least one visible pathology.
Reference Standard and Metrics: Linear Reconstruction was used as the reference standard for the comparison. Contrast-to-Noise Ratio (CNR) between pathology and healthy tissues was measured to quantify how accurately pathology features are preserved by Advanced Reconstruction. The mean CNR of Advanced Reconstruction was required to be greater than the mean CNR of the baseline Linear Reconstruction at statistical significance level of 0.05 for each sequence type.
Dataset and Sample Size: 43 Patients, 95 Images, 316 ROIs
Study Results: In all cases, CNR of Advanced Reconstruction was greater than or equal to Linear Reconstruction for both hyper- and hypo-intense pathologies. The study result demonstrates that Advanced Reconstruction does not unexpectedly modify, remove, or reduce the contrast of pathology features.
Advanced Reconstruction Image Validation:
Study Design: Five external, ABR-certified radiologists representing clinical users were asked to review side-by-side clinical image sets taken with the subject Swoop System, reconstructed with both Advanced and Linear Reconstruction. The reviewers rated the images using a five-point scale for image quality and the consistency of diagnosis using both methods in the categories of noise, sharpness, contrast, geometric fidelity, artifact, and overall image quality.
Reference Standard and Metrics: Linear Reconstruction was used as the reference standard for the comparison. Advanced Reconstruction was required to perform at least as well as Linear Reconstruction in all categories (median score >=0 on Likert scale) and perform better (>=1 on Likert scale) in at least one of the quality-based categories.
Dataset and Sample Size: 46 Patients, 177 Images
Test Results: Advanced Reconstruction achieved a median score of 2 (the most positive rating scale value) in all categories. This scoring indicates reviewers found Advanced Reconstruction improved image quality while maintaining diagnostic consistency relative to Linear Reconstruction.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Normalized mean squared error (NMSE), structural similarity index (SSIM), Contrast-to-Noise Ratio (CNR), Likert scale scores.
Predicate Device(s)
Reference Device(s)
Not Found
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 892.1000 Magnetic resonance diagnostic device.
(a)
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).(b)
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.
FDA 510(k) Clearance Letter - Swoop® Portable MR Imaging® System
Page 1
U.S. Food & Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov
Doc ID # 04017.07.05
May 21, 2025
Hyperfine, Inc.
Kristen Evenson
Staff Regulatory Affairs Specialist
351 New Whitfield St
Guilford, CT 06437
Re: K251276
Trade/Device Name: Swoop® Portable MR Imaging® System
Regulation Number: 21 CFR 892.1000
Regulation Name: Magnetic Resonance Diagnostic Device
Regulatory Class: Class II
Product Code: LNH, MOS
Dated: April 24, 2025
Received: April 24, 2025
Dear Kristen Evenson:
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.
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K251276 - Kristen Evenson 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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K251276 - Kristen Evenson Page 3
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
Page 4
Indications for Use
Please type in the marketing application/submission number, if it is known. This textbox will be left blank for original applications/submissions.
K251276
Please provide the device trade name(s).
Swoop® Portable MR Imaging® System
Please provide your Indications for Use below.
The Swoop Portable MR Imaging System is a portable, ultra-low field magnetic resonance imaging device for producing images that display the internal structure of the head where full diagnostic examination is not clinically practical. When interpreted by a trained physician, these images provide information that can be useful in determining a diagnosis.
Please select the types of uses (select one or both, as applicable).
☑ Prescription Use (Part 21 CFR 801 Subpart D)
☐ Over-The-Counter Use (21 CFR 801 Subpart C)
Page 5
510(k) Summary
Swoop® Portable MR Imaging® System
510(K) SUBMITTER
Company Name: Hyperfine, Inc.
Company Address: 351 New Whitfield St
Guilford, CT 06437
CONTACT
Name: Kristen Evenson
Telephone: (612) 251-3030
Email: kevenson@hyperfine.io
Date Prepared: May 20, 2025
DEVICE IDENTIFICATION
Trade Name: Swoop® Portable MR Imaging® System
Common Name: Magnetic Resonance Imaging
Regulation Number: 21 CFR 892.1000
Classification Name: System, Nuclear Magnetic Resonance Imaging Coil, Magnetic Resonance, Specialty
Product Code: LNH; MOS
Regulatory Class: Class II
PREDICATE DEVICE INFORMATION
The subject Swoop Portable MR Imaging System is substantially equivalent to the predicate Swoop System (K240944).
DEVICE DESCRIPTION
The Swoop system is portable, ultra-low field MRI device that enables visualization of the internal structures of the head using standard magnetic resonance imaging contrasts. The main interface is a commercial off-the-shelf device that is used for operating the system, providing access to patient data, exam setup, exam execution, viewing MRI image data for quality control purposes, and cloud storage interactions. The system can generate MRI data sets with a broad range of contrasts. The Swoop system user interface includes touch screen menus, controls, indicators, and navigation icons that allow the
Page 6
operator to control the system and to view imagery. The Swoop System image reconstruction algorithm utilizes deep learning to provide improved image quality for T1W, T2W, FLAIR, and DWI sequences.
The subject Swoop System described in this submission includes software modifications related to the pulse sequences and image processing.
INDICATIONS FOR USE
The Swoop Portable MR Imaging System is a portable, ultra-low field magnetic resonance imaging device for producing images that display the internal structure of the head where full diagnostic examination is not clinically practical. When interpreted by a trained physician, these images provide information that can be useful in determining a diagnosis.
SUBSTANTIAL EQUIVALENCE DISCUSSION
The table below compares the subject device to the predicate.
| Specification | Subject Swoop Portable MR Imaging System | Predicate Swoop Portable MR Imaging System (K240944) |
|---|---|---|
| Intended Use/ Indications for Use: | The Swoop Portable MR Imaging System is a portable, ultra-low field magnetic resonance imaging device for producing images that display the internal structure of the head where full diagnostic examination is not clinically practical. When interpreted by a trained physician, these images provide information that can be useful in determining a diagnosis. | Same |
| Patient Population: | Adult and pediatric patients (≥ 0 years) | Same |
| Anatomical Sites: | Head | Same |
| Environment of Use: | At the point of care in professional health care facilities such as emergency rooms, intensive/critical care units, hospitals, outpatient, or rehabilitation centers. | Same |
| Energy Used and/or delivered: | Magnetic Resonance | Same |
| Magnet: | ||
| Physical Dimensions | 835 mm x 630 mm x 652 mm | Same |
| Bore Opening | 610 mm x 315 mm | Same |
| Weight | 320 kg | Same |
| Field Strength | 63.3 mT permanent magnet | Same |
| Gradient: | ||
| Strength | X: 24 mT/m, Y: 23 mT/m, Z: 39 mT/m | Same |
| Rise Time | X: 2.1 ms, Y: 2.0 ms, Z: 3.8 ms | Same |
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| Specification | Subject Swoop Portable MR Imaging System | Predicate Swoop Portable MR Imaging System (K240944) |
|---|---|---|
| Slew Rate | X: 24 T/m/s, Y: 22 T/m/s, Z: 21 T/m/s | Same |
| Computer Display | Hyperfine-supplied tablet | Same |
| RF Coils: | ||
| Number of Coils | 1 head coil | Same |
| Coil Type | TX/RX | Same |
| Coil Geometry | Form-fitting | Same |
| Inner Dimensions (mm) | 205 mm x 240 mm | Same |
| Coil Design | Linear Volume | Same |
| Patient Weight Capacity | 1.6kg-200 kg | Same |
| Operation Temperature | 15-30 C | Same |
| Warm Up Time |