(147 days)
The MAGNETOM system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and/or spectra, and that displays the internal structure and/or function of the head, body, or extremities. Other physical parameters derived from the images and/or spectra may also be produced. Depending on the region of interest, contrast agents may be used. These images and/or spectra and the physical parameters derived from the images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.
The MAGNETOM system may also be used for imaging during interventional procedures when performed with MR compatible devices such as in-room displays and MR Safe biopsy needles.
MAGNETOM Amira and MAGNETOM Sempra with syngo MR XA50M include new and modified features comparing to the predicate devices MAGNETOM Amira and MAGNETOM Sempra with syngo MR XA12M (K183221, cleared on February 14, 2019).
The provided document is a 510(k) summary for the Siemens MAGNETOM Amira and Sempra MR systems, detailing their substantial equivalence to predicate devices. It describes new and modified hardware and software features, including AI-powered "Deep Resolve Boost" and "Deep Resolve Sharp."
However, the document does not contain the detailed information necessary to fully answer the specific questions about acceptance criteria and a study proving the device meets those criteria, particularly in the context of AI performance. The provided text is a summary for regulatory clearance, not a clinical study report.
Specifically, it lacks:
- Concrete, quantifiable acceptance criteria for the AI features (e.g., a specific PSNR threshold that defines "acceptance").
- A comparative effectiveness study (MRMC) to show human reader improvement with AI assistance.
- Stand-alone algorithm performance metrics for the AI features (beyond general quality metrics like PSNR/SSIM, which are not explicitly presented as acceptance criteria).
- Details on expert involvement, adjudication, or ground truth establishment for a test set used for regulatory acceptance, as the "test statistics and test results" section refers to quality metrics and visual inspection, and "clinical settings with cooperation partners" rather than a formal test set for regulatory submission.
The "Test statistics and test results" section for Deep Resolve Boost mentions "After successful passing of the quality metrics tests, work-in-progress packages of the network were delivered and evaluated in clinical settings with cooperation partners." It also mentions "seven peer-reviewed publications" covering 427 patients which "concluded that the work-in-progress package and the reconstruction algorithm can be beneficially used for clinical routine imaging." This indicates real-world evaluation but does not provide specific acceptance criteria or detailed study results for the regulatory submission itself.
Based on the provided text, here's what can be extracted and what is missing:
1. Table of acceptance criteria and reported device performance:
The document does not explicitly state quantifiable "acceptance criteria" for the AI features (Deep Resolve Boost and Deep Resolve Sharp) that were used for regulatory submission. Instead, it describes general successful evaluation methods:
| Acceptance Criteria (Inferred/Methods Used) | Reported Device Performance (Summary) |
|---|---|
| For Deep Resolve Boost:- Successful passing of quality metrics tests (PSNR, SSIM)- Visual inspection to detect potential artifacts- Evaluation in clinical settings with cooperation partners- No misinterpretation, alteration, suppression, or introduction of anatomical information reported | Deep Resolve Boost:- Impact characterized by PSNR and SSIM. Visual inspection conducted for artifacts.- Evaluated in clinical settings with cooperation partners.- Seven peer-reviewed publications (427 patients on 1.5T and 3T systems, covering prostate, abdomen, liver, knee, hip, ankle, shoulder, hand and lumbar spine).- Publications concluded beneficial use for clinical routine imaging.- No reported cases of misinterpretation, altered, suppressed, or introduced anatomical information.- Significant time savings reported in most cases by enabling faster image acquisition. |
| For Deep Resolve Sharp:- Successful passing of quality metrics tests (PSNR, SSIM, perceptual loss)- In-house visual rating- Evaluation of image sharpness by intensity profile comparisons of reconstruction with and without Deep Resolve Sharp | Deep Resolve Sharp:- Impact characterized by PSNR, SSIM, and perceptual loss.- Verified and validated by in-house tests, including visual rating and evaluation of image sharpness by intensity profile comparisons.- Both tests showed increased edge sharpness. |
2. Sample sized used for the test set and the data provenance:
The document mixes "training" and "validation" datasets. It doesn't explicitly refer to a separate "test set" for regulatory evaluation with clear sample sizes for that purpose. The "Test statistics and test results" section refers to general evaluations and published studies.
- "Validation" Datasets (internal validation, not explicitly a regulatory test set):
- Deep Resolve Boost: 1,874 2D slices
- Deep Resolve Sharp: 2,057 2D slices
- Data Provenance (Training/Validation):
- Source: For Deep Resolve Boost: "in-house measurements and collaboration partners." For Deep Resolve Sharp: "in-house measurements."
- Origin: Not specified by country.
- Retrospective/Prospective: "Input data was retrospectively created from the ground truth by data manipulation and augmentation" (for Boost) and "retrospectively created from the ground truth by data manipulation" (for Sharp). This implies the underlying acquired datasets were retrospective.
- "Clinical Settings" / Publications (Implied real-world evaluation, not a regulatory test set):
- Deep Resolve Boost: "a total of seven peer-reviewed publications 427 patients"
- Data Provenance: Not specified by origin or retrospective/prospective for these external evaluations.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
This information is not provided in the document. It mentions "visual inspection" and "visual rating," but does not detail the number or qualifications of experts involved in these processes for the "validation" sets or any dedicated regulatory "test set." For the "seven peer-reviewed publications," the expertise of the authors is implied but not detailed as part of the regulatory submission.
4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
This information is not provided in the document.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:
A formal MRMC comparative effectiveness study demonstrating human reader improvement with AI assistance is not described in this document. The document focuses on the technical performance of the AI features themselves and their general clinical utility as reported in external publications (e.g., faster imaging, no misinterpretation), but not a comparative study of human performance with and without the AI.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
Yes, the sections on "Test statistics and test results" for both Deep Resolve Boost and Deep Resolve Sharp describe evaluation of the algorithm's performance using quality metrics (PSNR, SSIM, perceptual loss) and visual/intensity profile comparisons. This implies standalone algorithm evaluation. No specific quantifiable results for these metrics are provided as acceptance criteria, only that tests were successfully passed and showed increased sharpness for Deep Resolve Sharp.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):
The ground truth for the AI training and validation datasets is described as:
- Deep Resolve Boost: "The acquired datasets represent the ground truth for the training and validation. Input data was retrospectively created from the ground truth by data manipulation and augmentation." This implies that the original, full-quality MR images serve as the ground truth.
- Deep Resolve Sharp: "The acquired datasets represent the ground truth for the training and validation. Input data was retrospectively created from the ground truth by data manipulation." Similarly, the original, high-resolution MR images are the ground truth.
This indicates the ground truth is derived directly from the originally acquired (presumably high-quality/standard) MRI data, rather than an independent clinical assessment like pathology or expert consensus. The AI's purpose is to reconstruct a high-quality image from manipulated or undersampled input, so the "truth" is the original high-quality image.
8. The sample size for the training set:
- Deep Resolve Boost: 24,599 2D slices
- Deep Resolve Sharp: 11,920 2D slices
Note that the document states: "due to reasons of data privacy, we did not record how many individuals the datasets belong to. Gender, age and ethnicity distribution was also not recorded during data collection."
9. How the ground truth for the training set was established:
As described in point 7:
- Deep Resolve Boost: The "acquired datasets" (original, full-quality MR images) served as the ground truth. Input data for the AI model was then "retrospectively created from the ground truth by data manipulation and augmentation," including undersampling, adding noise, and mirroring k-space data.
- Deep Resolve Sharp: The "acquired datasets" (original MR images) served as the ground truth. Input data was "retrospectively created from the ground truth by data manipulation," specifically by cropping k-space data so only the center part was used as low-resolution input, with the original full data as the high-resolution output/ground truth.
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Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health and Human Services logo. To the right of that is a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.
March 28, 2023
Siemens Medical Solutions USA, Inc. % Alina Goodman Regulatory Affairs Professional 40 Liberty Boulevard MALVERN PA 19355
Re: K223343
Trade/Device Name: MAGNETOM Amira; MAGNETOM Sempra Regulation Number: 21 CFR 892.1000 Regulation Name: Magnetic Resonance Diagnostic Device Regulatory Class: Class II Product Code: LNH, MOS, LNI Dated: March 3, 2023 Received: March 3, 2023
Dear Alina Goodman:
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 (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 located 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.
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
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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 803) for devices or postmarketing safety reporting (21 CFR 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 (OS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 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 mediation-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-regulatoryassistance/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 Magnetic Resonance and Nuclear Medicine Team 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
Submission Number (if known)
K223343
Device Name
MAGNETOM Amira; MAGNETOM Sempra
Indications for Use (Describe)
The MAGNETOM system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and/or spectra, and that displays the internal structure and/or function of the head, body, or extremities. Other physical parameters derived from the images and/or spectra may also be produced. Depending on the region of interest, contrast agents may be used. These images and/or spectra and the physical parameters derived from the images and/or spectra when interpreted by a trained physician vield information that may assist in diagnosis.
The MAGNETOM system may also be used for imaging during interventional procedures when performed with MR compatible devices such as in-room displays and MR Safe biopsy needles.
Type of Use (Select one or both, as applicable)
Prescription Use (Part 21 CFR 801 Subpart D)
Over-The-Counter Use (21 CFR 801 Subpart C)
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510(k) Summary
This summary of 510(k) safety and effectiveness information is being submitted in accordance with the requirements of the Safe Medical Devices Act 1990 and 21 CFR § 807.92.
1. General Information
| Establishment: | Siemens Medical Solutions USA, Inc.40 Liberty BoulevardMalvern, PA 19355, USARegistration Number: 2240869 |
|---|---|
| Date Prepared: | October 31, 2022 |
| Manufacturer: | Siemens Shenzhen Magnetic Resonance Ltd.Siemens MRI Center, Gaoxin C. Ave., 2ndHi-Tech Industrial Park518057 ShenzhenPEOPLE'S REPUBLIC OF CHINARegistration Number: 3004754211Siemens Healthcare GmbH |
Henkestrasse 127 91052 Erlangen Germany Registration Number: 3002808157
2. Contact Information
Alina Goodman Regulatory Affairs Professional Siemens Medical Solutions USA, Inc. 40 Liberty Boulevard Malvern, PA 19355, USA Phone: +1(224)526-1404 E-mail: alina.goodman@siemens-healthineers.com
3. Device Name and Classification
| Device/ Trade name: | MAGNETOM AmiraMAGNETOM Sempra |
|---|---|
| Classification Name: | Magnetic Resonance Diagnostic Device (MRDD) |
| Classification Panel: | Radiology |
| CFR Code: | 21 CFR § 892.1000 |
| Classification: | II |
| Product Code: | Primary: LNHSecondary: LNI, MOS |
| 4.1 Predicate Device | |
| Trade name: | MAGNETOM Amira |
| 510(k) Number: | K183221 |
| Classification Name: | Magnetic Resonance Diagnostic Device (MRDD) |
| Classification Panel: | Radiology |
| CFR Code: | 21 CFR § 892.1000 |
| Classification: | II |
| Product Code: | Primary: LNHSecondary: LNI, MOS |
| Trade name: | MAGNETOM Sempra |
| 510(k) Number: | K183221 |
| Classification Name: | Magnetic Resonance Diagnostic Device (MRDD) |
| Classification Panel: | Radiology |
| CFR Code: | 21 CFR § 892.1000 |
| Classification: | II |
| Product Code: | Primary: LNHSecondary: LNI, MOS |
| 4.2 Reference Device | |
| Trade name: | MAGNETOM Sola |
| 510(k) Number: | K221733 |
| Classification Name: | Magnetic Resonance Diagnostic Device (MRDD) |
| Classification Panel: | Radiology |
| CFR Code: | 21 CFR § 892.1000 |
| Classification: | II |
| Product Code: | Primary: LNHSecondary: LNI, MOS |
| Trade name: | MAGNETOM Free.Max |
| 510(k) Number: | K220575 |
| Classification Name: | Magnetic Resonance Diagnostic Device (MRDD) |
| Classification Panel: | Radiology |
| CFR Code: | 21 CFR § 892.1000 |
| Classification: | II |
| Product Code: | Primary: LNHSecondary: MOS |
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4. Legally Marketed Predicate Device
5. Intended Use
The indications for use for the subject devices are the same as that of the predicate device:
The MAGNETOM system is indicated for use as a magnetic resonance diagnostic device (MRDD) that produces transverse, sagittal, coronal and oblique cross sectional images, spectroscopic images and/or spectra, and that displays the internal structure and/or function of the head, body, or extremities. Other physical parameters derived from the images and/or spectra may also be produced. Depending on the region of interest, contrast agents may be used. These images and/or spectra and the physical parameters derived from the
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images and/or spectra when interpreted by a trained physician yield information that may assist in diagnosis.
The MAGNETOM system may also be used for imaging during interventional procedures when performed with MR compatible devices such as in-room displays and MR Safe biopsy needles.
6. Device Description
MAGNETOM Amira and MAGNETOM Sempra with syngo MR XA50M include new and modified features comparing to the predicate devices MAGNETOM Amira and MAGNETOM Sempra with syngo MR XA12M (K183221, cleared on February 14, 2019).
Below is a high-level summary of the new and modified hardware and software features comparing to the predicate devices MAGNETOM Amira and MAGNETOM Sempra with syngo MR XA12M:
Hardware
Dedicated coils only for MAGNETOM Sempra with syngo MR XA50M:
- -Flex Large 8 Coil
- Flex Small 8 Coil -
- Flex 8 Coil Interface -
Software
New Features and Applications:
- SMS TSE DIXON -
- SE EPI MRE (EP2D_SE_MRE) -
- ZOOMit PRO -
- High bandwidth inversion recovery -
- WAVE-CAIPI SWI (GRE) WAVE) -
- Deep Resolve Sharp -
- Deep Resolve Gain -
- -Deep Resolve Boost
- -Table positioning mode
- Coil independent pulse sequences -
- BLADE Diffusion -
- -TSE MoCo
- MR protocols module (new name for "MR Protocol Manager") -
- Automatic fiducial detection -
- Access-i -
- myExam Brain Autopilot
- SMS Averaging -
Modified Features and Applications:
- 3D ASL (TGSE_ASL) -
- myExam LiverLab Assist
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Below Table 1 shows an executive summary of training and validation dataset of Al features (Deep Resolve Boost and Deep Resolve Sharp) in subject devices:
| Deep Resolve Boost | Deep Resolve Sharp | |
|---|---|---|
| Sample size | 26,473 2D slices | 13,977 2D slices |
| Note: due to reasons of data privacy, we did not record how manyindividuals the datasets belong to. Gender, age and ethnicity distributionwas also not recorded during data collection. Due to the networkarchitecture, attributes like gender, age and ethnicity are not relevant tothe training data. | ||
| Sample source | in-house measurementsand collaboration partners | in-house measurements |
| Dataset slipt | Training: 24,599 slicesValidation: 1,874 slices | Training: 11,920 slicesValidation: 2,057 slices |
| Note: Data split maintained similar data distribution (e.g. contrast,orientation, field strength, ...) in both training and validation datasets. | ||
| Equipments | 1.5T and 3T MRI scanners | |
| Protocols | Representative protocols (T1, T2 and PD with and withoutfat saturation) which have been altered (e.g. to increaseSNR, increase resolution or reduced acceleration). | |
| Body regions | a broad range of different body regions | |
| Clinicalsubgroups | No clinical subgroups have been defined for the datasets. | |
| Counfouders | The input and output variables of the network have beenderived from the same dataset so that no confounders existfor the training methodology. | |
| Test statisticsand testresults | The impact of the network hasbeen characterized by severalquality metrics such as peaksignal-to-noise ratio (PSNR)and structural similarity index(SSIM). Additionally, imageswere inspected visually toensure that potential artefactsare detected that are not wellcaptured by the metrics listedabove.After successful passing of thequality metrics tests, work-in-progress packages of thenetwork were delivered andevaluated in clinical settingswith cooperation partners. In atotal of seven peer-reviewedpublications 427 patients weresuccessfully scanned on 1.5Tand 3T. The investigationscovered following bodyregions: prostate, abdomen, | The impact of the network hasbeen characterized by severalquality metrics such as peaksignal-to-noise ratio (PSNR),structural similarity index(SSIM), and perceptual loss. Inaddition, the feature has beenverified and validated byinhouse tests. These testsinclude visual rating and anevaluation of image sharpnessby intensity profile comparisonsof reconstruction with andwithout Deep Resolve Sharp.Both tests show increased edgesharpness. |
| liver, knee, hip, ankle,shoulder, hand and lumbarspine. All publications haveconcluded that the work-in-progress package and thereconstruction algorithm canbe beneficially used for clinicalroutine imaging. No caseshave been reported where thenetwork led to amisinterpretation of the imagesor where anatomicalinformation has been altered,suppressed, or introduced. Inmost cases the new algorithmhas been used to acquireimages faster and significanttime savings are reported. | ||
| Referencestandard | The acquired datasetsrepresent the ground truth forthe training and validation.Input data was retrospectivelycreated from the ground truthby data manipulation andaugmentation. This processincludes further under-sampling of the data bydiscarding k-space lines,lowering of the SNR level byaddition of noise and mirroringof k-space data. | The acquired datasets representthe ground truth for the trainingand validation. Input data wasretrospectively created from theground truth by datamanipulation. k-space data hasbeen cropped such that only thecenter part of the data was usedas input. With this methodcorresponding low-resolutiondata as input and high-resolutiondata as output / ground truthwere created for training andvalidation. |
Table 1. Training and validation dataset of Al features
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7. Substantial Equivalence
MAGNETOM Amira and MAGNETOM Sempra with software syngo MR XA50M are substantially equivalent to the predicate devices list in Table 2:
| Predicate Device | FDA Clearance Number and Date | ProductCode | Manufacturer |
|---|---|---|---|
| MAGNETOM Amira withsyngo MR XA12M | K183221, cleared on February 14, 2019 | LNH,LNI,MOS | Siemens ShenzhenMagnetic ResonanceLtd. |
| MAGNETOM Sempra withsyngo MR XA12M | K183221, cleared on February 14, 2019 | LNH,LNI,MOS | Siemens ShenzhenMagnetic ResonanceLtd. |
| Reference Device | FDA Clearance Number and Date | ProductCode | Manufacturer |
| MAGNETOM Sola withsyngo MR XA51A | K221733, cleared on September 13, 2022 | LNH,LNI,MOS | Siemens HealthcareGmbH |
| MAGNETOM Free.Max withsyngo MR XA50A | K220575, cleared on June 24, 2022 | LNH,MOS | Siemens ShenzhenMagnetic ResonanceLtd. |
Table 2. Predicate devices and reference devices.
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8. Technological Characteristics
The subject devices, MAGNETOM Amira and MAGNETOM Sempra with software syngo MR XA50M, are substantially equivalent to the predicate devices with regard to the operational environment, programming language, operating system and performance.
The subject devices conform to the standard for medical device software (IEC 62304) and other relevant IEC and NEMA standards.
There are some differences in technological characteristics between the subject devices and predicate devices, including new and modified hardware and software features. Please see below Table 3 and Table 4 for the comparison between subject devices and predicate/ reference devices.
| Subject Device | Predicate Device | Subject Device | Predicate Device | |
|---|---|---|---|---|
| Feature | MAGNETOMAmira withsoftware syngoMR XA50M | MAGNETOMAmira withsoftware syngoMR XA12M(K183221) | MAGNETOMSempra withsoftware syngoMR XA50M | MAGNETOMSempra withsoftware syngoMR XA12M(K183221) |
| MagnetSystem | same | same | same | same |
| RF System | same | same | same | same |
| TransmissionTechnique | same | same | same | same |
| GradientSystem | same | same | same | same |
| Patient Table | same | same | same | same |
| Computer | same | same | same | same |
| Coils | same | same | New coils:-Flex Large 8,-Flex Small 8,-Flex 8 CoilInterface | - |
| Other HWcomponents | same | same | same | same |
Table 3. Hardware Comparison
Comparison results: new local coils are introduced to MAGNETOM Sempra with syngo MR XA50M comparing to the predicate device. These differences have been tested and non-clinical data concluded no impact on safety and effectiveness of the device.
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| Table 4. Software Features Comparison | |
|---|---|
| Subject Device | Subject Device | ReferenceDevice | PredicateDevice | PredicateDevice | |
|---|---|---|---|---|---|
| Feature | MAGNETOMAmira withsyngo MRXA50M | MAGNETOMSempra withsyngo MRXA50M | MAGNETOMSola withsyngo MRXA51A(K221733) | MAGNETOMAmira withsyngo MRXA12M(K183221) | MAGNETOMSempra withsyngo MRXA12M(K183221) |
| SMS for TSEDIXON | same | No | No | ||
| SE EPI MRE | same | No | No | ||
| ZOOMit PRO | same | No | No | ||
| High bandwidthinversionrecovery | same | No | No | ||
| WAVE-CAIPI SWI | same | No | No | ||
| Deep ResolveSharp | same | No | No | ||
| Deep ResolveGain | same | No | No | ||
| Deep ResolveBoost | same | No | No | ||
| Table positioningmode | same | No | No | ||
| Coil independentpulse sequences | same | No | No | ||
| BLADE Diffusion | same | No | No | ||
| TSE MoCo | same | No | No | ||
| MR ProtocolsModule | same | No | No | ||
| Automatic fiducialdetection | same | No | No | ||
| Access-i | same | No | No | ||
| myExam BrainAutopilot | same | No | No | ||
| SMS Averaging [1] | same | No | No | No | |
| 3D ASL | same, modified comparing to predicate device | Yes | Yes | ||
| myExam LiverLabAssist | same, modified comparing to predicate device | Yes | Yes |
[1] SMS Averaging for TSE was cleared in reference device MAGNETOM Free.Max with syngo MR XA50A (K220575). SMS Averaging is made available for both TSE and TSE DIXON pulse sequence in subject devices.
Comparison results: new and modified software features are introduced to subject devices comparing to the predicate devices. These differences have been tested and non-clinical data concluded no impact on safety and effectiveness of the devices.
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9. Nonclinical Tests
| Performance Test | Tested Hardware or Software | Source/Rationale for test |
|---|---|---|
| Sample clinical images | New local coils, new andmodified software features,pulse sequence types | Guidance for Submission ofPremarket Notifications forMagnetic ResonanceDiagnostic Devices |
| Software verification andvalidation | mainly new and modifiedsoftware features | Guidance for the Content ofPremarket Submissions forSoftware Contained in MedicalDevices |
The following performance testing was conducted on the subject devices:
The following performance testing for local coils was conducted on the predicate devices and can be reused for the subject devices:
| Performance Test | Tested Hardware or Software | Source/Rationale for test |
|---|---|---|
| Performance bench test | - SNR and image uniformitymeasurements for coils- Heating measurements forcoils | Guidance for Submission ofPremarket Notifications forMagnetic ResonanceDiagnostic Devices |
The results from each set of tests demonstrate that the devices perform as intended and are thus substantially equivalent to the predicate device to which it has been compared.
10.Clinical Tests / Publications
No clinical tests were conducted to support substantial equivalence for the subject device; however, as stated above, sample clinical images were provided.
11.Safety and Effectiveness
The device labeling contains instructions for use and any necessary cautions and warnings to ensure safe and effective use of the device.
Risk Management is ensured via a risk analysis in compliance with ISO 14971, to identify and provide mitigation of potential hazards early in the design cycle and continuously throughout the development of the product. Siemens adheres to recognized and established industry standards, such as the IEC 60601-1 series, to minimize electrical and mechanical hazards. Furthermore, the devices are intended for healthcare professionals familiar with and responsible for the acquisition and post processing of magnetic resonance images.
MAGNETOM Amira and MAGNETOM Sempra with software syngo MR XA50M conform to the following FDA recognized and international IEC, ISO and NEMA standards:
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| RecognitionNumber | ProductArea | Title of Standard | ReferenceNumber and date | StandardsDevelopmentOrganization |
|---|---|---|---|---|
| 19-4 | General | Medical electrical equipment - part1: general requirements for basicsafety and essential performance | ES60601-1:2005/(R) 2012and A1:2012 | AAMI / ANSI |
| 19-8 | General | Medical electrical equipment - Part1-2: General requirements for basicsafety and essential performance -Collateral Standard:Electromagnetic disturbances -Requirements and tests | 60601-1-2 Edition4.0:2014-02 | IEC |
| 12-295 | Radiology | Medical electrical equipment - Part2-33: Particular requirements for thebasic safety and essentialperformance of magnetic resonanceequipment for medical diagnosis | 60601-2-33 Ed.3.2:2015 | IEC |
| 5-40 | General | Medical devices - Application of riskmanagement to medical devices | 14971:2019 | ISO |
| 5-96 | General | Medical devices - Application ofusability engineering to medicaldevices | 62366 Edition 1.02015 | AAMI ANSIIEC |
| 13-32 | Software | Medical device software - Softwarelife cycle processes | 62304 Edition 1.12015-06 | AAMIANSIIEC |
| 12-195 | Radiology | NEMA MS 6-2008 (R2014)Determination of Signal-to-NoiseRatio and Image Uniformity forSingle-Channel Non-Volume Coilsin Diagnostic MR Imaging | MS 6-2008(R2014) | NEMA |
| 12-300 | Radiology | Digital Imaging andCommunications in Medicine(DICOM) Set 03/16/2012 Radiology | PS 3.1 - 3.20(2016) | NEMA |
| 2-156 | Biocompatibility | Biological evaluation of medicaldevices - part 1: evaluation andtesting within a risk managementprocess. (Biocompatibility) | 10993-1:2018/(R)2013 | AAMIANSIISO |
12.Conclusion as to Substantial Equivalence
MAGNETOM Amira and MAGNETOM Sempra with software syngo MR XA50M have the same intended use and same basic technological characteristics as the predicate devices system, MAGNETOM Amira and MAGNETOM Sempra with syngo MR XA12M (K183221, cleared on February 14, 2019), with respect to the magnetic resonance features and functionalities. While there are some differences in technical features compared to the predicate devices, the differences have been tested and the conclusions from all verification and
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validation data suggest that the features bear an equivalent safety and performance profile to that of the predicate device and reference device.
Siemens believes that MAGNETOM Amira and MAGNETOM Sempra with software syngo MR XA50M are substantially equivalent to the currently marketed devices MAGNETOM Amira and MAGNETOM Sempra with syngo MR XA12M.
§ 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.