SyMRI is a post-processing software medical device intended for use in visualization of soft tissue. SyMRI analyzes input data from MR imaging systems. SyMRI utilizes data from supported MR sequences to generate parametric maps of R1, R2 relaxation rates, and proton density (PD).

SyMRI is intended for automatic labeling, visualization and volumetric quantification of segmentable brain tissues from a set of MR images. Brain tissue volumes are determined based on modeling of parametric maps from SyMRI.

SyMRI can also generate multiple image contrasts from the parametric maps. SyMRI enables post-acquisition image contrast adjustment.

SyMRI is indicated for head imaging.

When interpreted by a trained physician, output from SyMRI can provide information useful in determining diagnosis. SyMRI 2D is intended to be used in combination with at least one other, conventional MR acquisition (e.g. T2-FLAIR). T1W and T2W images from SyMRI 3D may replace conventional MR images in a clinical setting when interpreting together with a conventional 3D T2W FLAIR image.

Device Description

SyMRI works by post-processing a multi-delay, multi-echo acquisition into parametric maps. The acquisition is either a multi-slice 2D approach (M2D-MDME), consisting of 4 delays with a short and a long echo time each (8 images per slice), or a 3D approach (3D-QALAS) consisting of 4 delays with a short echo and 1 delay with a long echo time (5 images per slice).

The parametric maps are R1, R2 relaxation rates, and proton density (PD). The inverse relaxation parameters, T1 relaxation time (1/R1), and T2 relaxation time (1/R2) are also provided as parametric maps.

SyMRI also enables the users to obtain volumetric information in the head, including white matter (WM), gray matter (GM), cerebrospinal fluid (CSF), Myelin correlated (MyC) partial volume, brain parenchyma (BP) and intracranial cavity (IC). This is accomplished by using tissue definitions based on the parametric maps. The tissue definitions provide tissue partial volume, or tissue fraction, per voxel. SyMRI also provides image processing tools to extract the values of the parametric maps, and tissue partial volume, per individual voxel, per region of interest, or the entire imaging volume.

The parametric maps can be visualized as contrast weighted MR images, such as T1, T2, PD, and Inversion Recovery (IR) weighted images (including T1-FLAIR, STIR, Double IR, and PSIR weighted images).

The parametric maps can be visualized as contrast weighted MR images from SyMRI 3D may replace conventional MR images in a clinical setting when interpreting together with a conventional 3D T2W FLAIR image.

SyMRI calculates the pixel signal intensity as a function of R1, R2, PD, and desired MR scanner settings, such as echo time (TE), repetition time (TR), and inversion delay time (TI). A number of default settings for TE, TR, and TI are provided, but the user has the ability to change the contrast of the images. SyMRI generates all the different image contrasts from the same parametric maps, derived from the same acquisition. This leads to enhanced image slice registration, owing to the absence of inter-acquisition patient movement. SyMRI provides the user the ability to change the contrast of the images after the acquisition. This is performed by adjusting the TE, TR, and/or TI parameters post-acquisition, to generate the specific contrast desired.

SyMRI is intended to be used on data produced by any of the following acquisition sequences:

. MDME sequence data from GE MAGiC
MDME sequence data from Philips SyntAc
. MDME sequence data from Siemens TSE_MDME
3D-QALAS sequence data from Philips 3DsyntAc

AI/ML Overview

This document describes the acceptance criteria and study proving the device meets them for SyMRI.

1. Table of Acceptance Criteria and Reported Device Performance

Performance Metric	Acceptance Criteria	Reported Device Performance
Quantitative Accuracy & Precision (R1, R2, PD)	Equivalent to predicate device. Correspondence with reference values (gold standard phantoms).	R1, R2, and PD measurements show correspondence with reference values (inversion recovery for R1, CPMG multi-echo for R2, heavy water phantoms for PD, and NIST/ISMRM Model 130 phantom). The subject device met the same predefined acceptance criteria as the predicate device, demonstrating equivalence in accuracy and precision for quantification when compared to gold standards.
Segmentation Accuracy & Precision	Equivalent to predicate device.	The verification results demonstrate that the subject device SyMRI meets the same pre-defined performance criteria as the predicate.
Non-inferiority of Synthetic 3D Images (Diagnostic Performance)	Non-inferiority in sensitivity and specificity for detecting any pathology compared to conventional 3D images. Non-inferiority in diagnostic accuracy of radiological finding class compared to conventional 3D images.	Synthetic 3D images were non-inferior in terms of sensitivity and specificity in detecting any pathology, as well as non-inferior in diagnostic accuracy of radiological finding class, compared to equivalent conventional MR images over a wide range of brain pathologies.
Legibility of Anatomical Structures	High legibility of anatomical structures.	All images (synthetic and conventional) had a very high legibility of anatomical structures.
Artifact Prevalence	Lower prevalence of artifacts in synthetic images compared to conventional images. No novel artifacts.	Synthetic images had lower prevalence of artifacts compared to the conventional MR images. No novel artifacts were reported for synthetic MR images.
Image Quality Score	Higher image quality score for synthetic images compared to conventional images.	Synthetic images had slightly higher image quality scores compared to conventional images for both T1W and T2W images.

2. Sample Size Used for the Test Set and Data Provenance

Sample Size: 189 subjects
Data Provenance:
- Country of Origin: United States (6 institutes in the US)
- Study Type: Prospective, multi-reader clinical investigation.
- Subject characteristics: Patients with a wide range of different pathologies, and healthy controls. Both adults and pediatric patients were included.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications

The document does not explicitly state the number of experts used to establish a ground truth for the test set. However, it mentions that five experienced radiologists assessed the images in the clinical investigation. Their qualifications are described as "experienced radiologists."

4. Adjudication Method for the Test Set

The document does not explicitly state an adjudication method (e.g., 2+1, 3+1). It states that "Five experienced radiologists... assessed the images in two reading sessions with a four-week memory washout period in between." This suggests individual assessments rather than a consensus-based adjudication for primary readings, though further details on how discrepancies (if any) were handled are not provided.

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

Yes, a MRMC comparative effectiveness study was done. The study involved five experienced radiologists assessing images in two reading sessions.
Effect Size of Human Reader Improvement with AI vs. Without AI Assistance: This specific information (effect size of human readers improving with AI assistance vs. without) is not directly provided. The study focused on demonstrating the non-inferiority of synthetic 3D images (generated by the AI device, SyMRI) compared to conventional 3D images in terms of diagnostic performance (sensitivity, specificity, diagnostic accuracy). It also evaluated image quality and artifact prevalence of the synthetic images. It does not describe a scenario where human readers interpreted conventional images and then re-interpreted them with AI assistance to measure improvement. Instead, it compares the diagnostic utility of AI-generated images versus conventional images.

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone performance assessment was conducted for the quantitative aspects of the device:

Accuracy of R1/R2/PD quantification: Evaluated compared to "gold standard inversion recovery (R1), CPMG multi-echo (R2), heavy water phantoms (PD) and standard system Model 130 NIST/ISMRM phantom." This demonstrates an algorithm-only accuracy assessment against established physical standards.
Segmentation Accuracy & Precision: Verified against pre-defined performance criteria similar to the predicate device. While not explicitly stated as "algorithm only," the context of "verification results" for quantification and segmentation usually refers to algorithmic performance.

7. Type of Ground Truth Used

For Quantitative Parameters (R1, R2, PD): Gold standard phantoms (inversion recovery, CPMG multi-echo, heavy water phantoms, NIST/ISMRM Model 130 phantom).
For Diagnostic Performance (Pathology Detection, Diagnostic Accuracy, Image Quality): The consensus or individual expert assessments of the five experienced radiologists after reviewing both synthetic and conventional images served as the reference for comparison, aiming to establish non-inferiority against conventional imaging. Although not explicitly called "ground truth," the conventional images and expert interpretations thereof served as the benchmark. The study compared the device-generated synthetic images to equivalent conventional MR images. It also mentions "radiological finding class," implying expert-derived classifications.

8. Sample Size for the Training Set

The document does not provide information on the sample size used for the training set of the SyMRI algorithm. It focuses on the validation study.

9. How the Ground Truth for the Training Set Was Established

The document does not provide information on how the ground truth for the training set was established, as it does not describe the training process for the algorithm. It primarily details the performance validation of the device.

Summary

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December 6, 2024

SyntheticMR AB (Publ.) % Kelliann Payne Partner Hogan Lovells US LLP 1735 Market Street, Floor 23 Philadelphia, Pennsylvania 19103

Re: K242524

Trade/Device Name: SyMRI Regulation Number: 21 CFR 892.1000 Regulation Name: Magnetic Resonance Diagnostic Device Regulatory Class: Class II Product Code: LNH Dated: August 23, 2024 Received: November 6, 2024

Dear Kelliann Payne:

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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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 of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.

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-device-advicecomprehensive-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-device-safety/medical-device-reportingmdr-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/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatory

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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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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)

K242524

Device Name

SyMRI

Indications for Use (Describe)

SyMRI can also generate multiple image contrasts from the parametric maps. SyMRI enables post-acquisition image contrast adjustment.

SyMRI is indicated for head imaging.

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

X Prescription Use (Part 21 CFR 801 Subpart D) □ Over-The-Counter Use (21 CFR 801 Subpart C)

CONTINUE ON A SEPARATE PAGE IF NEEDED.

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510(K) SUMMARY

K242524

SyntheticMR's SyMRI

Submitter

SyntheticMR AB, (Publ.),

Storgatan 11, 582 23 Linköping, Sweden

Phone: +46 (0)730 69 04 90 Contact Person: Madeleine Enström Date Prepared: 2024-12-06

Name of Device: SyMRI

Common or Usual Name: SyMRI

Classification Name: Magnetic resonance diagnostic device

Regulatory Class: Class II

Product Code: LNH

Predicate Devices

SyntheticMR's SyMRI (K233733)

Device Description

Quantification and segmentation

Supported acquisition sequence: M2D-MDME and 3D-QALAS

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the parametric maps. The tissue definitions provide tissue partial volume, or tissue fraction, per voxel. SyMRI also provides image processing tools to extract the values of the parametric maps, and tissue partial volume, per individual voxel, per region of interest, or the entire imaging volume.

Contrast weighted images

Supported acquisition sequence: M2D-MDME

The parametric maps can be visualized as contrast weighted MR images, such as T1, T2, PD, and Inversion Recovery (IR) weighted images (including T1-FLAIR, STIR, Double IR, and PSIR weighted images).

Supported acquisition sequence: 3D-QALAS

Supported acquisition sequence: M2D-MDME and 3D-QALAS

SyMRI is intended to be used on data produced by any of the following acquisition sequences:

. MDME sequence data from GE MAGiC
MDME sequence data from Philips SyntAc
. MDME sequence data from Siemens TSE_MDME
3D-QALAS sequence data from Philips 3DsyntAc

Intended Use / Indications for Use

SyMRI can also generate multiple image contrasts from the parametric maps. SyMRI enables postacquisition image contrast adjustment.

SyMRI is indicated for head imaging.

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The subject device has similar intended use and indication for use as the predicate device but SyMRI can now also generate contrast weighted images for diagnostic purposes from data based on the 3D-QALAS sequence. Performance data demonstrate that the device is safe and effective.

Summary of Technological Characteristics

The subject device has the same fundamental design characteristics and is based on the same technologies as found in the currently marketed predicate device SyMRI (K23373).

Both the SyMRI and the predicate device use the same fundamental algorithm to calculate parametric maps from acquired images of supported acquisition sequences. Both SyMRI and the predicate device use a segmentation algorithm to calculate volumetric results based on the parametric maps. The segmentation maps and volumes that are provided are the same as in the predicate device, i.e. WM, GM, CSF, NoN, MyC. No new segmentations are provided. Both the subject device and the predicate device have support for both the M2D-MDME sequence and the 3D-QALAS sequence.

Both SyMRI and the predicate device can visualize synthetic contrast weighted images that are generated from the parametric maps, but for the predicate device only images from the M2D-MDME sequence can be used clinically.

A table comparing the key features of the subject and predicate devices is provided below.

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Performance Data

Non-Clinical verification tests have been performed with regards to the requirement specifications and the risk management results. The testing was completed with passing results per the pass/fail criteria defined in the test cases.

The accuracy of R1/R2/PD quantification was evaluated compared to gold standard inversion recovery (R1), CPMG multi-echo (R2), heavy water phantoms (PD) and standard system Model 130 NIST/ISMRM phantom. The R1, R2 and PD measurements show correspondence with the reference values, and the subject device met the same predefined acceptance criteria as the predicate device. It can be concluded that the accuracy and precision of SyMRI is equivalent to the predicate.

The verification results demonstrate that the subject device SyMRI meets the same pre-defined performance criteria as the predicate in terms of accuracy and precision for quantification and segmentation.

Furthermore, a prospective, multi-readers clinical investigation was performed to demonstrate that synthetic 3D images are non-inferior to conventional 3D images. 189 subjects were recruited at 6 institutes in the US. The subjects were patients with a wide range of different pathologies, and healthy controls. Both adults and pediatric patients were included. Five experienced radiologists, blinded to the type of images, assessed the images in two reading sessions with a four-week memory washout period in between. The readers assessed artifacts, legibility of anatomical structure, image quality and radiological finding class.

The results showed that synthetic 3D images were non-inferior in terms of sensitivity and specificity in detecting any pathology, as well as non-inferior in diagnostic accuracy of radiological finding class, compared to equivalent conventional MR images over a wide range of brain pathologies.

Furthermore, the result showed that all images had a very high legibility of anatomical structures and that synthetic images had lower prevalence of artifacts compared to the conventional MR images. No

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novel artifacts were reported for synthetic MR images. The synthetic images also had slightly higher image quality score compared to conventional images for both T1W and T2W images.

Based on the clinical performance as documented in the pivotal clinical study, SyMRI has a safety and effectiveness profile that is similar to the predicate device.

Conclusions

The subject device SyMRI is as safe and effective as the predicate device SyMRI. The subject device has the same intended uses and similar indications, technological characteristics, and principles of operation as its predicate device. The minor differences in indications do not alter the intended diagnostic ability of the device and do not affect its safety and effectiveness when used as labeled. In addition, the minor technological differences between the subject device and its predicate devices raise no new issues of safety or effectiveness. Performance data demonstrate that the subject device is as safe and effective as the predicate device. Thus, it is substantially equivalent.

Regulation Number and Section

§ 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.

	SyMRI	PREDICATE DEVICE
		SyMRI (K233733)
Product Code	LNH	LNH
Regulation	829.1000	829.1000
Classification	Class II, 510(k)	Class II, 510(k)
Indications for Use	SyMRI is a post-processing software medicaldevice intended for use in visualization of softtissue. SyMRI analyzes input data from MR imagingsystems. SyMRI utilizes data from supported MRsequences to generate parametric maps of R1, R2relaxation rates, and proton density (PD).SyMRI is intended for automatic labeling,visualization and volumetric quantification ofsegmentable brain tissues from a set of MRimages. Brain tissue volumes are determinedbased on modeling of parametric maps fromSyMRI.SyMRI can also generate multiple image contrastsfrom the parametric maps. SyMRI enables post-acquisition image contrast adjustment.	SyMRI is a post-processing software medicaldevice intended for use in visualization of softtissue. SyMRI analyzes input data from MRimaging systems. SyMRI utilizes data fromsupported MR sequences to generate parametricmaps of R1, R2 relaxation rates, and protondensity (PD).SyMRI is intended for automatic labeling,visualization and volumetric quantification ofsegmentable brain tissues from a set of MRimages. Brain tissue volumes are determinedbased on modeling of parametric maps fromSyMRI.When interpreted by a trained physician, theparametric maps, tissue maps, and volumetricsfrom SyMRI can provide information useful in
	SyMRI is indicated for head imaging.When interpreted by a trained physician, outputfrom SyMRI can provide information useful indetermining diagnosis. SyMRI 2D is intended to beused in combination with at least one other,conventional MR acquisition (e.g. T2-FLAIR). T1Wand T2W images from SyMRI 3D may replaceconventional MR images in a clinical setting wheninterpreting together with a conventional 3D T2W FLAIR image.	determining diagnosis. SyMRI is indicated for headimaging.SyMRI can also generate multiple contrastweighted images from the parametric mapsacquired using M2D-MDME sequence. SyMRIenables post-acquisition image contrastsadjustments from acquisition using M2D-MDMEsequence.When M2D-MDME acquisition data is used asinput to SyMRI the synthetic contrast weightedimages can also provide information useful indetermining diagnosis. SyMRI is intended to beused in combination with at least one other,conventional MR acquisition (e.g. T2-FLAIR).
User Population	SyMRI is intended to be used by healthcareprofessionals, e.g. radiologists interpreting theresulting images and quantitative values	SyMRI is intended to be used by healthcareprofessionals, e.g. radiologists interpreting theresulting images and quantitative values
Patient population	All ages	All ages
Intended use environment	SyMRI is intended to be used in a hospital/clinicsetting.	SyMRI is intended to be used in a hospital/clinicsetting.
Design	Automatic segmentation and quantification ofbrain tissues using parametric maps, based on theMR pixel intensity. Automated measurement ofbrain tissue volumes.	Automatic segmentation and quantification ofbrain tissues using parametric maps, based on theMR pixel intensity. Automated measurement ofbrain tissue volumes.
Technology	Generates images and volumes from parametricmaps of PD, R1 and R2.	Generates images and volumes from parametricmaps of PD, R1 and R2.
Processing Architecture	Automated internal pipeline that performs:• Quantification from supported sequencesinput to Parametric maps• Segmentation from Parametric maps toTissue maps• Volume calculation from Tissue maps• Segmentation table summarizes results fromVolume calculations.• Generating adjustable synthetic images fromParametric maps	Automated internal pipeline that performs:• Quantification from supported sequencesinput to Parametric maps• Segmentation from Parametric maps toTissue maps• Volume calculation from Tissue maps• Segmentation table summarizes results fromVolume calculations.• Generating adjustable synthetic images fromParametric maps
Physical Characteristics	Software package. Operates on off-the shelfhardware.	Software package. Operates on off-the shelfhardware.
Operating system	Supports Windows, macOS, and Linux	Supports Windows, macOS, and Linux
Data source 1	GE "MAGIC" sequence	GE "MAGIC" sequence
Data source 2	Philips "SyntAc" sequence	Philips "SyntAc" sequence
Data source 3	Siemens "tse_mdme" sequence	Siemens "tse_mdme" sequence
Data source 4	Philips "3DSyntAc" sequence	Philips "3DSyntAc" sequence
Output	Parametric maps (R1, R2, PD-map) in 2D or 3D	Parametric maps (R1, R2, PD-map) in 2D or 3D
	Tissue segmentation (WM, GM, CSF, MyC, NoN)	Tissue segmentation (WM, GM, CSF, MyC, NoN)
	Visualize segmentations in three planes (Ax, Cor,Sag)	Visualize segmentations in three planes (Ax, Cor,Sag)
	Contrast weighted images (T1w, T2w, FLAIR, PDw,STIR, DIR, PSIR)	Contrast weighted images (T1w, T2w, FLAIR, PDw,STIR, DIR, PSIR)
	Contrast weighted images in 2D or 3D for clinicaluse	Contrast weighted images in 2D
	Supports DICOM format as output of results thatcan be displayed on DICOM workstations and PACS	Supports DICOM format as output of results thatcan be displayed on DICOM workstations and PACS
	Volumes and fractions for multiple previous scans.Calculate difference and % change to previousscan. Reference curve can include multiple time-points.	Volumes and fractions for single scan exported toPACS. Comparison over time done manually.
Safety features	Additional conventional scan. Too many failedpixels check. Sufficient dynamic variation check.Results must be reviewed by a trained physician.	Additional conventional scan. Too many failedpixels check. Sufficient dynamic variation check.Results must be reviewed by a trained physician.