(49 days)
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.
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.
Here's a breakdown of the acceptance criteria and study details for the Swoop® Portable MR Imaging® System, based on the provided FDA 510(k) clearance letter:
Acceptance Criteria and Reported Device Performance
| Acceptance Criteria Category | Specific Acceptance Criteria | Reported Device Performance |
|---|---|---|
| Advanced Reconstruction | Performance Analysis: Robustness, stability, and generalizability over a variety of subjects, design parameters, artifacts, and scan conditions using reference-based metrics (NMSE and SSIM). The ability of Advanced Reconstruction to reproduce the ground truth image compared to Linear Reconstruction should be superior or demonstrate expected behavior. | NMSE was reduced and SSIM was improved for Advanced Reconstruction test images compared to Linear Reconstruction test images across all models and test datasets. Reconstruction outputs with motion and zipper artifacts were qualitatively assessed to be acceptable. |
| Contrast-to-Noise Ratio (CNR) Validation | Mean CNR of Advanced Reconstruction required to be greater than the mean CNR of the baseline Linear Reconstruction at a statistical significance level of 0.05 for each sequence type. This demonstrates that pathology features are preserved. | In all cases, CNR of Advanced Reconstruction was greater than or equal to Linear Reconstruction for both hyper- and hypo-intense pathologies. This demonstrates that Advanced Reconstruction does not unexpectedly modify, remove, or reduce the contrast of pathology features. |
| Image Validation (Radiologist Review) | Advanced Reconstruction 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 (noise, sharpness, contrast, geometric fidelity, artifact, and overall image quality). | Advanced Reconstruction achieved a median score of 2 (the most positive rating scale value) in all categories (noise, sharpness, contrast, geometric fidelity, artifact, and overall image quality). This indicates reviewers found Advanced Reconstruction improved image quality while maintaining diagnostic consistency relative to Linear Reconstruction. |
| Software Verification | Software verification testing in accordance with design requirements. | Passed all testing in accordance with internal requirements and applicable standards (IEC 62304:2016, FDA Guidance, "Content of Premarket Submissions for Device Software Functions"). |
| Image Performance | Testing to verify the subject device meets all image quality criteria. | Passed all testing in accordance with internal requirements and applicable standards (NEMA MS 1-2008 (R2020), NEMA MS 3-2008 (R2020), NEMA MS 9-2008 (R2020), NEMA MS 12-2016, American College of Radiology standards for named sequences). |
| Cybersecurity | Testing to verify cybersecurity controls and management. | Passed all testing in accordance with internal requirements and applicable standards (FDA Guidance, "Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions"). |
| Software Validation | Validation to ensure the subject device meets user needs and performs as intended. | Passed all testing in accordance with internal requirements and applicable standards (FDA Guidance, "Content of Premarket Submissions for Device Software Functions"). |
Study Details for Advanced Reconstruction Validation (DWI Sequence - updated in this submission)
This section focuses specifically on the studies conducted to validate the Advanced Reconstruction models for the updated DWI sequence. Performance analysis and validation for T1/T2/FLAIR models were leveraged from predicate devices, so this analysis covers the new data.
1. Performance Analysis
- Sample Size:
- Test Set (DWI): 8 patients, 31 images.
- Data Provenance: Not explicitly stated, but includes data from 6 different sites. Countries of origin are not specified. The study is retrospective, utilizing existing MRI data.
- Ground Truth Establishment (Test Set):
- Number of Experts: Not applicable for quantitative metrics (NMSE, SSIM). Quantitative metrics were reference-based, comparing reconstructed images to ground truth target images (Swoop data, high field images, and synthetic contrast images).
- Qualifications of Experts: N/A.
- Adjudication Method: N/A.
- MRMC Comparative Effectiveness Study: No, this was a standalone performance analysis comparing Advanced Reconstruction to Linear Reconstruction against a reference standard.
- Standalone Performance: Yes. The algorithm's output was compared to ground truth images using quantitative metrics.
- Type of Ground Truth: Reference images, including Swoop data, high field images, and synthetic contrast images. Test input data (synthetic k-space) was generated from these target images.
- Training Set Sample Size: Not explicitly stated for this particular updated DWI model. The document states "None of these test images were used in model training," implying a separate training set, but its size is not provided.
- Ground Truth Establishment (Training Set): Not explicitly stated, but generally for deep learning reconstruction, the training data would include raw k-space data paired with corresponding reference images (often higher quality, known good reconstructions, or synthetic data).
2. Contrast-to-Noise Ratio (CNR) Validation
- Sample Size:
- Test Set (DWI): 12 patients, 45 images, 145 Regions of Interest (ROIs).
- Data Provenance: Not explicitly stated, but includes data from 5 different sites. Countries of origin are not specified. Retrospective.
- Ground Truth Establishment (Test Set):
- Number of Experts: At least one.
- Qualifications of Experts: An American Board of Radiology (ABR) certified radiologist reviewed the annotations for accuracy.
- Adjudication Method: Not explicitly stated as a formal adjudication method (like 2+1), but radiologists reviewed ROI accuracy.
- MRMC Comparative Effectiveness Study: No, this was a standalone quantitative comparison of CNR between Advanced Reconstruction and Linear Reconstruction.
- Standalone Performance: Yes. The algorithm's output was quantitatively measured and compared to the linear reconstruction, using expert-annotated ROIs for pathology.
- Type of Ground Truth: Expert-annotated regions of interest (ROIs) encompassing pathologies, reviewed for accuracy by an ABR-certified radiologist.
- Training Set Sample Size: Not explicitly stated.
- Ground Truth Establishment (Training Set): Not explicitly stated.
3. Advanced Reconstruction Image Validation (Radiologist Review)
- Sample Size:
- Test Set (DWI): 34 patients, 34 sets of DWI images (102 individual images when considering b=0, trace-weighted/single direction, and ADC).
- Data Provenance: Not explicitly stated, but includes data from 8 different sites. Countries of origin are not specified. Retrospective by nature of rating existing images.
- Ground Truth Establishment (Test Set): Ground truth for rating was established by consensus of the clinical reviewers' assessments on a Likert scale. There wasn't an independent "definitive" ground truth for image quality beyond the expert reviews.
- Number of Experts: Four.
- Qualifications of Experts: External, ABR-certified radiologists representing clinical users.
- Adjudication Method: Not explicitly stated if there was a formal adjudication if reviewers disagreed. Instead, they rated independently, and median scores were used for evaluation.
- MRMC Comparative Effectiveness Study: This study had elements of an MRMC study by using multiple readers (4 radiologists) to rate multiple cases (34 image sets) with and without the AI assistance (Advanced vs. Linear Reconstruction, though not exactly "assisted" as in "human + AI" vs. "human only").
- Effect Size: Advanced Reconstruction achieved a median score of 2 (the most positive rating scale value) in all categories. This indicates a significant improvement in perceived image quality and diagnostic consistency compared to Linear Reconstruction (which would be analogous to "without AI assistance" in this context), as the criteria required only a median score ≥1 in one category for "better performance."
- Standalone Performance: Partially. While radiologists rated the images, their input constituted the performance metric. It's not a purely algorithmic standalone performance against a fixed ground truth.
- Type of Ground Truth: Expert consensus ratings (Likert scale) on image quality attributes and diagnostic consistency.
- Training Set Sample Size: Not explicitly stated.
- Ground Truth Establishment (Training Set): Not explicitly stated.
In summary, for the updated DWI sequence validation:
- Test Set Sample Sizes:
- Performance Analysis: 8 patients, 31 images
- CNR Validation: 12 patients, 45 images, 145 ROIs
- Image Validation: 34 patients, 34 image sets (102 images)
- Data Provenance: Retrospective, multiple sites (6 for performance, 5 for CNR, 8 for image validation via different Swoop System models), countries not specified.
- Expert Reviewers: An ABR-certified radiologist for ROI accuracy in CNR validation, and four external ABR-certified radiologists for the image quality review.
- Ground Truth: Varied from reference images, to expert-annotated ROIs, to expert consensus ratings.
- Training Set Details: Minimal information provided regarding the training set's size or ground truth establishment in this document. The focus here is on the validation of the updated DWI model.
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 # 04017.08.02
December 12, 2025
Hyperfine, Inc.
Kristen Evenson
Sr. Manager, Regulatory Affairs
351 New Whitfield St
Guilford, Connecticut 06437
Re: K253489
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: October 23, 2025
Received: October 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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K253489 - 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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K253489 - 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
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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. | K253489 |
|---|---|
| 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 (21 CFR 801 Subpart D)☐ Over-The-Counter Use (21 CFR 801 Subpart C) |
|---|
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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: December 5, 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 primary predicate Swoop System (K250236), and the secondary predicate Swoop System (K251276).
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
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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.
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 | SubjectSwoop Portable MR Imaging System | Primary PredicateSwoop Portable MR Imaging System Model 2(K250236) | Secondary PredicateSwoop Portable MR Imaging System Model 1(K251276) |
|---|---|---|---|
| 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 | Same |
| Patient Population: | Adult and pediatric patients (≥ 0 years) | Same | Same |
| Anatomical Sites: | Head | Same | 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 | Same |
| Energy Used and/or delivered: | Magnetic Resonance | Same | Same |
| Magnet: |
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| Specification | SubjectSwoop Portable MR Imaging System | Primary PredicateSwoop Portable MR Imaging System Model 2(K250236) | Secondary PredicateSwoop Portable MR Imaging System Model 1(K251276) |
|---|---|---|---|
| Field Strength | Model 1 Swoop System63.3 ± 2.0 mTModel 2 Swoop System64.9 mT (nominal) | Same as Model 2 of subject device | Same as Model 1 of subject device |
| Type | Permanent magnet | Same | Same |
| Patient accessible bore size | Model 1 Swoop System24.0 in. width, 12.4 in. heightModel 2 Swoop System36.0 in. width, 13.4 in. height | Same as Model 2 of subject device | Same as Model 1 of subject device |
| Magnet weight | Model 1 Swoop System705 lbsModel 2 Swoop System712 lbs | Same as Model 2 of subject device | Same as Model 1 of subject device |
| Gradient System: | |||
| Maximum gradient amplitude | Model 1 Swoop SystemX: 24 mT/m, Y: 23 mT/m, Z: 39 mT/mModel 2 Swoop SystemX: 33.9 mT/m, Y: 33.2 mT/m, Z: 66.2 mT/m | Same as Model 2 of subject device | Same as Model 1 of subject device |
| Rise Time | Model 1 Swoop SystemX: 2.1 ms, Y: 2.0 ms, Z: 3.8 msModel 2 Swoop SystemX: 1.8 ms, Y: 1.8 ms, Z: 5.1 ms | Same as Model 2 of subject device | Same as Model 1 of subject device |
| Slew Rate | Model 1 Swoop SystemX: 24 T/m/s, Y: 22 T/m/s, Z: 21 T/m/sModel 2 Swoop SystemX: 18.8 T/m/s, Y: 18.4 T/m/s, Z: 13.0 T/m/s | Same as Model 2 of subject device | Same as Model 1 of subject device |
| RF Coils: | |||
| Coil Type | Transmit/receive | Same | Same |
| Coil Design | Linear | Same | Same |
| Other: | |||
| Patient Weight Capacity | 1.6kg-200 kg | Same | Same |
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| Specification | SubjectSwoop Portable MR Imaging System | Primary PredicateSwoop Portable MR Imaging System Model 2(K250236) | Secondary PredicateSwoop Portable MR Imaging System Model 1(K251276) |
|---|---|---|---|
| Operation Temperature | 15-30 C | Same | Same |
| Warm Up Time | <3 minutes | Same | Same |
| Temperature Control | No | Same | Same |
| Humidity Control | No | Same | Same |
| Sequences: | |||
| T1W sequences | • T1 (Standard), T1 (Gray/White)• Advanced Gridding reconstruction | Same | Same |
| T2W sequences | • T2, T2 (Fast)• Advanced Gridding reconstruction | Same | Same |
| FLAIR sequences | Model 1 Swoop System• FLAIR• Advanced Gridding reconstructionModel 2 Swoop System• FLAIR, FLAIR (Fast)• Advanced Gridding reconstruction | Same as Model 2 of subject device | Same as Model 1 of subject device |
| DWI sequences | Model 1 Swoop System• Single Direction DWI/ADC• Multi-direction DWI/ADC• Advanced Gridding + FISTAModel 2 Swoop System• Single Direction DWI/ADC,• Multi-direction DWI/ADC• Advanced Gridding + FISTA | • Single Direction DWI/ADC, Single Direction DWI/ADC (Fast)• Advanced Gridding + FISTA | • Single Direction DWI/ADC• Advanced Gridding + FISTA |
| Image Post-Processing (All sequences) | • Advanced Denoising• Image orientation transform• Geometric distortion correction• Receive coil intensity correction• Advanced Interpolation• ADC/Trace output (DWI)• DICOM output | • Advanced Denoising• Image orientation transform• Geometric distortion correction• Receive coil intensity correction• Advanced Interpolation• ADC output (DWI)• DICOM output | • Advanced Denoising• Image orientation transform• Geometric distortion correction• Receive coil intensity correction• Advanced Interpolation• ADC output (DWI)• DICOM output |
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The subject device and the predicate device have the same intended use, operating principles, and similar technological characteristics. There are minor differences between the subject device and the predicate in pulse sequences. These differences do not raise new questions of safety and efficacy as compared to the predicate.
NON-CLINICAL PERFORMANCE
As part of demonstrating substantial equivalence to the predicate, a risk-based assessment was completed to identify the risks associated with the modifications. Based on the risk assessment, the following testing was performed. The subject device passed all the testing in accordance with internal requirements and applicable standards to support substantial equivalence.
| Test | Test Description | Applicable Standard(s) |
|---|---|---|
| Software Verification | Software verification testing in accordance with the design requirements to ensure that the software requirements were met. | • IEC 62304:2016• FDA Guidance, "Content of Premarket Submissions for Device Software Functions" |
| Image Performance | Testing to verify the subject device meets all image quality criteria. | • NEMA MS 1-2008 (R2020)• NEMA MS 3-2008 (R2020)• NEMA MS 9-2008 (R2020)• NEMA MS 12-2016• American College of Radiology standards for named sequences |
| Cybersecurity | Testing to verify cybersecurity controls and management. | • FDA Guidance, "Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions" |
| Software Validation | Validation to ensure the subject device meets user needs and performs as intended. | • FDA Guidance, "Content of Premarket Submissions for Device Software Functions" |
The following testing was leveraged from the predicate device. Test results from the predicate were used to support the subject device because the conditions were identical or the subject device modifications did not introduce a new worst-case configuration or scenario for testing.
| Test | Test Description | Applicable Standard(s) |
|---|---|---|
| Biocompatibility | Biocompatibility testing of patient-contacting materials. | • ISO 10993-1:2018• ISO 10993-5:2009• ISO 10993-10:2010 |
| Cleaning/ Disinfection | Cleaning and disinfection validation of patient-contacting materials. | • FDA Guidance, "Reprocessing Medical Devices in Health Care Settings: Validation Methods and Labeling"• ISO 17664:2017• ASTM F3208-17 |
| Safety | Electrical Safety, EMC, and Essential Performance testing. | • ANSI/AAMI ES 60601-1:2005/(R)2012• IEC 60601-1-2:2014• IEC 60601-1-6:2013 |
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| Performance | Characterization of the Specific Absorption Rate for Magnetic Resonance Imaging Systems. | • NEMA MS 8-2016 |
|---|
ADVANCED RECONSTRUCTION PERFORMANCE ANALYSIS AND VALIDATION
Performance analysis and validation of the subject device Advanced Reconstruction models was performed for the updated DWI sequence. No images from the test dataset were used for model training. Only the DWI test dataset was updated as no changes were made to T1, T2, or FLAIR sequences, and no changes were made to any of the advanced reconstruction models. Performance analysis and validation of the T1/T2/FLAIR models were leveraged from the predicate device. The test summaries below describe the updated DWI test datasets. The test datasets for the T1, T2, and FLAIR are described in the previous clearances.
In all cases, models are trained and validated with MRI data and images as the only inputs and outputs; there are no confounding factors and clinical subgroups are not defined or considered. While gender and age are available for most subjects, age, gender, ethnic background, and pathology are not expected to influence model architecture.
Performance Analysis:
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 per Model:
The Swoop DWI dataset was updated to include multi-direction DWI images. None of these test images were used in model training. The demographics of the DWI subset are shown below.
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| Model / Sequence Group | #Patients | #Images | Demographics |
|---|---|---|---|
| DWI | 8 | 31 | Gender:Female: 13%, Male: 87%, Unknown: 0%Age:0-2: 0%, 2-18: 0%, 18-35: 25%, 35-60: 0%, 60+: 75%, Unknown: 0%Ethnicity data not recorded.Number of sites: 6Equipment:Model 1 Swoop System (V1.9): 13%Model 2 Swoop System: 87%Included pathology: Post-resection Tumor, ICH, Stroke, TBI, Post-Craniotomy. |
Study Results:
NMSE and SSIM with the included multi-direction DWI dataset were similar to previous 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.
Contrast-to-Noise Ratio Validation
Study Design: Regions of interest (ROI) encompassing pathologies were annotated, and the annotations were reviewed for accuracy by an American Board of Radiology (ABR) certified radiologist. 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.
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Dataset and Sample Size:
45 DWI images (41 multi-direction, 4 single-direction) were included for lesion annotation. Inclusion criteria were that the images had at least one visible pathology. The demographics of the DWI dataset are shown below.
| Patients | 12 |
|---|---|
| Images | 45 |
| ROIs | 145 |
| Demographics and other Variability | Gender:Female: 25%, Male: 42%, Unknown: 33%Age:0-2: 0%, 2-18: 0%, 18-35: 8%, 35-60: 42%, 60+: 33%, Unknown: 17%Ethnicity data not recorded.Number of sites: 5Equipment type:Model 1 Swoop System (V1.8): 22%Model 1 Swoop System (V1.9): 22%Model 2 Swoop System: 56%Included pathology: Acute/Subacute Stroke Stroke, Tumor, Post-operative Tumor, Cerebellar metastatic disease, white matter disease, Acute/Subacute Infarct |
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: Four 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.
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Dataset and Sample size:
34 sets of DWI images (30 multi-direction, 4 single-direction) were rated. A set consisted of DWI b=0, DWI (trace-weighted or single direction), and ADC.
| Patients | 34 |
|---|---|
| Images | 102 |
| Demographics and other Variability | Gender:Female: 41%, Male: 35%, Unknown: 24%Age:0-2: 0%, 2-18: 0%, 18-35: 15%, 35-60: 26%, 60+: 32%, unknown*: 26%*anonymizedEthnicity data not recorded.Number of sites: 8Equipment type:Model 1 Swoop System (V1.8): 20%Model 1 Swoop System (V1.9): 10%Model 2 Swoop System: 70%Included pathology: Acute Stroke, Subacute Stroke, Multiple Sclerosis, White matter disease, Metastatic disease, Post-operative glioma, Tumor, Hydrocephalus, ICH, IVH |
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.
CONCLUSION
Based on the intended use, technological characteristics, performance results, and comparison to the predicate, the subject Swoop Portable MR Imaging System has been shown to be substantially equivalent to the predicate device identified in this submission and does not present any new issues of safety or effectiveness.
N/A