(27 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 and image processing.
Here's a summary of the acceptance criteria and the studies that prove the device meets them, based on the provided FDA 510(k) clearance letter for the Swoop® Portable MR Imaging® System:
1. Table of Acceptance Criteria and Reported Device Performance
| Study Component | Acceptance Criteria | Reported Device Performance |
|---|---|---|
| Performance Analysis | NMSE (Normalized Mean Squared Error) should be reduced and SSIM (Structural Similarity Index) should be improved for Advanced Reconstruction test images compared to Linear Reconstruction test images. Advanced Reconstruction must preserve the presentation of motion and zipper artifacts and no unexpected output should be observed. | 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 (CNR) Validation | The mean CNR of Advanced Reconstruction was 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. The study result must demonstrate that Advanced Reconstruction does not unexpectedly modify, remove, or reduce the contrast of pathology features. | 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. |
| Advanced Reconstruction Image Validation | Advanced Reconstruction was required to perform at least as well as Linear Reconstruction in all categories (median score ≥0 on a Likert scale) and perform better (median score ≥1 on a Likert scale) in at least one of the quality-based categories (noise, sharpness, contrast, geometric fidelity, artifact, and overall image quality) when reviewed by external ABR-certified radiologists. | Advanced Reconstruction achieved a median score of 2 (the most positive rating scale value) in all categories. This indicates reviewers found Advanced Reconstruction improved image quality while maintaining diagnostic consistency relative to Linear Reconstruction. |
2. Sample Sizes and Data Provenance
The provided document does not explicitly state the country of origin for the data or whether it was retrospective or prospective for the training or test sets.
| Study Component | Sample Size (Test Set) | Data Provenance (Country, Retrospective/Prospective) |
|---|---|---|
| Performance Analysis | Total Subjects: 118 Total Unique Images: 378 Per Model/Sequence Group: - T1, T2, FLAIR: 44 patients, 92 images - DWI: 34 patients, 65 images | Not specified in the provided document. |
| Contrast-to-Noise Ratio (CNR) Validation | Patients: 43 Images: 95 ROIs (Regions of Interest): 316 | Not specified in the provided document. |
| Advanced Reconstruction Image Validation | Patients: 46 Images: 177 Per Sequence: At least 16 cases per sequence (with at least 4 cases per sequence-available image orientation) | Not specified in the provided document. |
3. Number of Experts and Qualifications for Ground Truth
| Study Component | Number of Experts | Qualifications of Experts |
|---|---|---|
| Performance Analysis | Not applicable for direct expert review; ground truth was generated synthetically or from high-field/synthetic contrast images. | N/A (reference-based metrics comparing reconstructed images to ground truth images). |
| Contrast-to-Noise Ratio (CNR) Validation | 2 | American Board of Radiology (ABR) certified radiologists. |
| Advanced Reconstruction Image Validation | 5 | External, American Board of Radiology (ABR) certified radiologists representing clinical users. |
4. Adjudication Method
| Study Component | Adjudication Method |
|---|---|
| Performance Analysis | Not applicable; objective metrics (NMSE, SSIM) compared reconstructed images to synthetic/derived ground truth. Qualitative assessment for motion and zipper artifacts. |
| Contrast-to-Noise Ratio (CNR) Validation | ROI annotations were reviewed by two ABR-certified radiologists, and inaccurate annotations were excluded. This implies a form of consensus or expert reconciliation for the ROIs. |
| Advanced Reconstruction Image Validation | Reviewers rated images using a five-point Likert scale. Individual ratings were used to derive a median score for each category. No explicit adjudication method (e.g., 2+1) for discrepant reader opinions is described beyond deriving a median. |
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- A form of MRMC study was conducted for the "Advanced Reconstruction Image Validation" where five ABR-certified radiologists reviewed images.
- Effect Size with AI vs. without AI assistance: The study compared Advanced Reconstruction (which utilizes deep learning) to Linear Reconstruction (without advanced AI assistance). 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), indicating "improved image quality" relative to Linear Reconstruction. The Likert scale used was not detailed, but a score of 2 on a 5-point scale (where 0 might be "no difference" and higher values indicate improvement) suggests a significant positive effect.
6. Standalone Performance Study
- Yes, a standalone (algorithm only) performance study was conducted.
- The "Performance Analysis" section describes evaluating Advanced Reconstruction's ability to reproduce ground truth images using objective metrics (NMSE, SSIM) without human reader involvement for the primary comparison. The "Contrast-to-Noise Ratio Validation" also measured objective image characteristics (CNR) of the algorithm's output.
7. Type of Ground Truth Used
| Study Component | Type of Ground Truth |
|---|---|
| Performance Analysis | 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 and compared to this ground truth. This is a form of derived/computed ground truth based on ideal or high-quality reference scans and synthetic generation. |
| Contrast-to-Noise Ratio (CNR) Validation | Pathologies in images were annotated and reviewed by two ABR-certified radiologists. The CNR was measured between these annotated pathologies and healthy white matter. This implicitly uses expert consensus/annotation for identifying and defining the regions of interest for ground truth comparison. However, the "ground truth" for the improvement in CNR is the Linear Reconstruction itself. |
| Advanced Reconstruction Image Validation | The reference standard for comparison was Linear Reconstruction. The "ground truth" here is human expert assessment (radiologists' ratings) of relative image quality and diagnostic consistency between the Advanced and Linear reconstructions, treating Linear Reconstruction as the baseline for comparison. |
8. Sample Size for the Training Set
- The document states that the test dataset was "entirely independent from the dataset used for model training."
- However, the specific sample size or characteristics of the training set are not provided in this document.
9. How the Ground Truth for the Training Set was Established
- The document states: "In all cases, models are trained and validated with MRI data and images as the only inputs and outputs" and "Advanced Reconstruction was performed using a test dataset entirely independent from the dataset used for model training."
- Similar to the training set sample size, the establishment of ground truth for the training set is not detailed in the provided document. It can be inferred that if high-field or synthetically derived images were used for validation, similar methods might have been used for training, but this is not explicitly stated.
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.
Page 2
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-
Page 3
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 |
Page 7
| 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 | <3 minutes | Same |
| Temperature Control | No | Same |
| Humidity Control | No | Same |
| Image Processing: | ||
| Noise Correction | Noise correction and line noise suppression for all sequences | Same |
| T1W • T1-Standard • T1-Gray/White Contrast | Advanced Gridding | Same |
| T2W • T2 • T2-Fast | Advanced Gridding | Same |
| FLAIR | Advanced Gridding | Same |
| DWI | Advanced Gridding, Fast Iterative Shrinkage Thresholding Algorithm (FISTA) | Fast Iterative Shrinkage Thresholding Algorithm (FISTA) |
| Image Post-Processing | • Advanced Denoising • Image orientation transform • Geometric distortion correction • Receive coil intensity correction • Advanced Interpolation • DICOM output | • Advanced Denoising • Image orientation transform • Geometric distortion correction • Receive coil intensity correction • DICOM output |
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 and image processing. 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
Page 8
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 |
| 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 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
Page 9
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. A description of the acceptance criteria and subset of data used for each test is included in the test summaries below.
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:
Page 10
| Model / Sequence Group | #Patients | #Images | Demographics |
|---|---|---|---|
| T1, T2, FLAIR | 44 | 92 | Gender Female: 55%, Male: 30%, Unknown: 15% Age 0-2: 16%, 2-18: 14%, 18-35: 11%, 35-60: 20%, 60+: 23%, 18+*: 9%, Unknown: 7% *partially anonymized Ethnicity data not recorded. Number of sites: 9 Equipment Swoop Mk1.7: 57%, Swoop Mk1.8: 9%, Swoop Mk1.9: 34% Included pathology: Alzheimer's Disease, Hemorrhage, Hydrocephalus, Hypoglycemia, Intracereberal Hemorrhage, Multiple Sclerosis, Subdural Hemorrhage, Seizure, Traumatic Brain Injury, Treacher Collins Syndrome, Tumor, White Matter Hyperintensity |
| DWI | 34 | 65 | Gender: Female: 41%, Male: 47%, Unknown: 12% Age: 0-2: 21%, 2-18: 15%, 18-35: 18%, 35-60: 23%, 60+: 18%, Unknown: 5% Ethnicity data not recorded. Number of sites: 6 Equipment: Swoop Mk1.7: 73%, Swoop Mk1.9: 27% Included pathology: Alzheimer's Disease, Hemorrhage, Hydrocephalus, Hypoglycemia, Subdural Hemorrhage, Seizure, Traumatic Brain Injury, Thrombosis, Treacher Collins Syndrome, White Matter Hyperintensity |
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.
Page 11
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:
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 |
| Demographics and other Variability | Gender: Female: 62%, Male: 17%, Unknown: 21% Age: 0-2: 8%, 2-18: 31%, 18-35: 7%, 35-60: 10%, 60+: 31%, 2+*: 9%, Unknown: 4% *partially anonymized Ethnicity data not recorded. Number of sites: 8 Equipment type: Swoop Mk1.7: 36%, Swoop Mk1.8: 18%, Swoop Mk1.9: 46% Included pathology: stroke, white matter disease, hemorrhage, tumor, hydrocephalus, cerebral edema, hypoxic brain injury, Alzheimer's, Treacher-Collins syndrome, seizures, multiple sclerosis, post-surgical tumor resection, and thrombectomy follow-up |
Page 12
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:
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 |
| Demographics and other Variability | Gender: Female: 31%, Male: 23%, Unknown: 46% Age: 0-2: 6%, 2-18: 11%, 18-35: 6%, 35-60: 17%, 60+: 39%, 2+*: 21% *partially anonymized Ethnicity data not recorded. Number of sites: 11 Equipment type: Swoop Mk1.7: 20%, Swoop Mk1.8: 10%, Swoop Mk1.9: 70% Included pathology: Alzheimer's Disease, Cavernous malformation, Cerebral Amyloid Angiopathy, Cerebral Tuberculosis, Cortical dysplasia, Edema, Empyema Evacuation, Ethmoidectomy, Hemorrhage, Hydrocephalus, Multiple Sclerosis, Subarachnoid Hemorrhage, Subdural Hemorrhage, Seizure, Stroke, Subdural Empyema, Thrombosis, Treacher Collins Syndrome, Tumor, White Matter Hyperintensity |
Page 13
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.
§ 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.