K254016 · Siemens Medical Solutions USA, Inc. · QIH · Feb 10, 2026 · Radiology
Device Facts
Record ID
K254016
Device Name
MI View&GO
Applicant
Siemens Medical Solutions USA, Inc.
Product Code
QIH · Radiology
Decision Date
Feb 10, 2026
Decision
SESE
Submission Type
Special
Regulation
21 CFR 892.2050
Device Class
Class 2
Attributes
AI/ML, Software as a Medical Device, Real-World Evidence
Real-World Evidence
Submission
Device
Sponsor
RWD Sources
RWE Use Summary
Key Tags
K254016 · Feb 10, 2026
MI View&GO
Siemens Medical Solutions USA, Inc.
Retrospective clinical PET/CT image datasets from clinical partners
Retrospective clinical data was used to evaluate the performance of the lung lobe segmentation algorithm and the PERCIST Liver algorithm. The performance was measured using Dice coefficients and compared against predicate device performance and expert reader reference standards.
Predicate device algorithm and semi-automatic expert reader positioning
Dice coefficient, ASSD, and intersection of PERCIST VOIs with suspicious uptake masks
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
Lung Lobe Segmentation
—
Dice coefficient > 0.8 or ASSD < 2 voxel (10 mm)
Dice coefficient higher than predicate for each lobe
—
—
Independent cohort of 20 patients (50% new, 50% from predicate testing cohort)
—
Liver Mask Segmentation
—
Dice coefficient > 0.8 or ASSD < 10 mm
Met both criteria
—
—
20 patients from clinical partners in Europe and USA
—
PERCIST Liver VOI Positioning
—
—
Better agreement with semi-automatic expert reader evaluation than predicate
—
—
129 subjects (foci with suspicious tracer uptake)
>1 (expert readers)
Indications for Use
MI View&GO is a medical diagnostic application for viewing, manipulation, quantification, analysis and comparison of medical images with one or more time-points. MI View&GO supports functional data, such as positron emission tomography (PET) or nuclear medicine (NM), as well as anatomical datasets, such as computed tomography (CT) or magnetic resonance (MR). MI View&GO is intended to be utilized by appropriately trained health care professionals to aid in the management of diseases associated with oncology, cardiology, neurology, and organ function. The images and results produced by MI View&GO can also be used by the physician to aid in radiotherapy treatment planning.
Device Story
Software-only medical device for use at scanner consoles (PET/CT, SPECT/CT) by technologists and physicians; integrates molecular imaging into clinical workflows. Inputs: PET, SPECT, CT, and MR image data. Processing: performs image review, post-processing, and analysis; includes automated lung lobe segmentation and PERCIST liver reference region positioning. Outputs: processed images, quantitative metrics (e.g., SUV, Deauville scores), and subtraction images. Physicians use outputs to assess image quality, manage disease (oncology, cardiology, neurology), and plan radiotherapy. Benefits: enables immediate post-acquisition review, efficient clinical workflow, and standardized quantification for improved diagnostic consistency.
Clinical Evidence
No clinical data. Bench testing only. Performance evaluation of lung lobe segmentation (n=20) used Dice coefficient (DSC) and ASSD; results met acceptance criteria (DSC > 0.8 or ASSD < 10mm). PERCIST Liver algorithm evaluation (n=20) met DSC > 0.8 or ASSD < 10mm criteria. Comparative analysis of 129 subjects showed improved accuracy in avoiding suspicious tracer uptake compared to predicate.
Technological Characteristics
Software-only medical image management and processing system. Architecture: Server/Client. Connectivity: DICOM (PS 3.1-3.20). Standards: ISO 14971 (risk), IEC 62304 (software lifecycle), IEC 62366-1 (usability). Features: PET/SPECT/CT/MR data support, SUV calculation, automated segmentation, and quantification algorithms.
Indications for Use
Indicated for appropriately trained healthcare professionals to view, manipulate, quantify, analyze, and compare PET, NM, CT, and MR images for management of oncology, cardiology, neurology, and organ function diseases, including radiotherapy treatment planning. Patient population: adults > 21 years.
Regulatory Classification
Identification
A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.
Special Controls
*Classification.* Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
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FDA U.S. FOOD & DRUG ADMINISTRATION
February 10, 2026
Siemens Medical Solutions USA, Inc.
Brian Wui
Regulatory Affairs
2501 N. Barrington Rd.
Hoffman Estates, Illinois 60192
Re: K254016
Trade/Device Name: MI View&GO
Regulation Number: 21 CFR 892.2050
Regulation Name: Medical image management and processing system
Regulatory Class: Class II
Product Code: QIH
Dated: February 5, 2026
Received: February 5, 2026
Dear Brian Wui:
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.
U.S. Food & Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993
www.fda.gov
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K254016 - Brian Wui
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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 Management System Regulation (QMSR) (21 CFR Part 820), which includes, but is not limited to, ISO 13485 clause 7.3 (Design controls), ISO 13484 clause 8.3 (Nonconforming product), and ISO 13485 clause 8.5 (Corrective and preventative action). Please note that regardless of whether a change requires premarket review, the QMSR requires device manufacturers to review and approve changes to device design and production (ISO 13485 clause 7.3 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 Management System Regulation (QMSR) (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Rule"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-devices/medical-device-safety/medical-device-reporting-mdr-how-report-medical-device-problems.
For comprehensive regulatory information about medical devices and radiation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-
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K254016 - Brian Wui
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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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| 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. | K254016 | ? |
| Please provide the device trade name(s). | | ? |
| MI View&GO | | |
| Please provide your Indications for Use below. | | ? |
| MI View&GO is a medical diagnostic application for viewing, manipulation, quantification, analysis and comparison of medical images with one or more time-points. MI View&GO supports functional data, such as positron emission tomography (PET) or nuclear medicine (NM), as well as anatomical datasets, such as computed tomography (CT) or magnetic resonance (MR).
MI View&GO is intended to be utilized by appropriately trained health care professionals to aid in the management of diseases associated with oncology, cardiology, neurology, and organ function. The images and results produced by MI View&GO can also be used by the physician to aid in radiotherapy treatment planning. | | |
| Please select the types of uses (select one or both, as applicable). | ☑ Prescription Use (21 CFR 801 Subpart D)
☐ Over-The-Counter Use (21 CFR 801 Subpart C) | ? |
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SIEMENS Healthineers
# 510(k) Summary
K254016
## 1. Identification of the Submitter
**Submitter / Primary Contact Person**
Brian Wui
Regulatory Affairs
hansong.wui@siemens-healthineers.com
+1 (865) 367-4337
**Secondary Contact Person**
Clayton Ginn
Regulatory Affairs
clayton.ginn@siemens-healthineers.com
+1 (865) 898-2692
**Applicant Name and Address**
Siemens Medical Solutions USA, Inc.
2501 North Barrington Road
Hoffman Estates IL, 60192, USA
Establishment Registration Number: 1423253
## 2. Device Name and Classification
Product Trade Name: MI View&GO
Common Name: Medical image management and processing system
Classification Name: Automated Radiological Image Processing Software
Classification Panel: Radiology
CFR Section: 21 CFR §892.2050
Device Class: Class II
Product Code: QIH
## 3. Predicate Devices
**Primary Predicate Device:**
Product Trade Name: MI View&GO
510(k) Number: K242300
Clearance Date: 08/02/2024
Common Name: Medical image management and processing system
Classification Name: Automated Radiological Image Processing Software
Classification Panel: Radiology
CFR Section: 21 CFR §892.2050
Device Class: Class II
Product Code: QIH
Siemens Medical Solutions USA, Inc.
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SIEMENS Healthineers
# Predicate / Reference Device
Trade Name: syngo.via MI Workflows
510(k) Number: K251528
Clearance Date: 05/19/2025
Common Name: Medical image management and processing system
Classification Name: Automated Radiological Image Processing Software
Classification Panel: Radiology
CFR Section: 21 CFR §892.5050
Device Class: Class II
Product Code: QIH
# 4. Device Description
MI View&GO is a software-only medical device which will be delivered in conjunction with Siemens SPECT/CT and PET/CT scanners. MI View&GO software provides additional specific capabilities for handling of PET and SPECT as well as CT and MR data directly at the acquisition console.
The MI View&GO software integrates molecular imaging more efficiently in the clinical environment by providing an interface for its users to review, post-process and read medical images immediately after acquisition. The purpose of the MI View&GO is to allow the technologist and reading physician to:
- Review acquired and reconstructed images at the scanner console
- Determine that the acquired data is of sufficient quality for reading, so the patient can be released.
- Prepare images for reading
- Perform a basic read
# 5. Indications for Use
MI View&GO is a medical diagnostic application for viewing, manipulation, quantification, analysis and comparison of medical images with one or more time-points. MI View&GO supports functional data, such as positron emission tomography (PET) or nuclear medicine (NM), as well as anatomical datasets, such as computed tomography (CT) or magnetic resonance (MR).
MI View&GO is intended to be utilized by appropriately trained health care professionals to aid in the management of diseases associated with oncology, cardiology, neurology, and organ function. The images and results produced by MI View&GO can also be used by the physician to aid in radiotherapy treatment planning.
# 6. Indications for Use Comparison to the Predicate Device
The indications for use are the same between the subject device and the primary predicate device.
Siemens Medical Solutions USA, Inc.
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SIEMENS Healthineers
# 7. Comparison of Technological Characteristics with the Predicate Device
MI View&GO with software version VA40 software provides the same technological characteristics in terms of materials, energy source, and control mechanisms when compared to the legally marketed predicate device since all devices are software only devices.
The software features have been modified in comparison to the predicate device to support enhanced device functionality.
The intended use, indications for use, and fundamental scientific technology for the subject device remains unchanged from the predicate device. No features present from the predicate device have been de-scoped.
At a high level, the subject and predicate devices are based on the following same technological elements:
- Data Supported (PET, SPECT, CT, MR)
- Server/Client architecture
- Workflow Activities (preprocessing, evaluation and reading, reporting and storage)
- Feature Licensing Structure
- SUV values calculated
The following technological differences exist between the subject device and predicate devices.
MI View&GO VA40:
- Features
- General Masking Tool
- VQ Ratio and Subtraction Images for Auto Lung 3D
- Improved Lung Segmentation
- Deauville Score
- Improved PERCIST Liver algorithm
- Improvements to Layout and Usability
- Cardiac Layout Enhancement
- Improvements to Layout Editing and User Presets
Any differences in technological characteristics do not raise different questions of safety and effectiveness. Testing and validation are completed. Test results show that the subject devices are comparable to the predicate devices in terms of technological characteristics and safety and effectiveness and therefore are substantially equivalent to the predicate devices.
# 8. Non-Clinical and/or Clinical Test Summary & Conclusions
The following performance data were provided in support of the substantial equivalence determination.
Siemens Medical Solutions USA, Inc.
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SIEMENS Healthineers
# Software Verification and Validation
'Enhanced' software documentation per FDA's guidance document "Content of Premarket Submissions for Device Software Functions" issued on June, 2023 is also included as part of this submission. The performance data demonstrates continued conformance with special controls for medical devices containing software. The testing supports that all software specifications have met the predetermined acceptance criteria. Verification and validation testing substantiates all requirement and functional specifications, including specifications related to device hazards, and supports the claim of substantial equivalence.
# Performance Testing
The device under application, MI View&GO (K254061), deploys the same improved Lung Segmentation and improved PERCIST Liver algorithm as cleared in the predicate / reference device syngo.via VC10 (K251528).
# Improved Lung Segmentation
In addition to verification and validation testing, performance evaluation was conducted in order to ensure the safety and effectiveness of the lung lobe segmentation algorithm compared to the predicate device. The lung lobe segmentation algorithm was re-trained with additional data and is utilized within Auto Lung 3D.
Quantitative evaluation of the segmentation results was performed using the commonly used overlap measure Dice coefficient (DSC). The algorithm was tested retrospectively on an independent cohort of 20 patients that were not part of training or tuning cohort. The test cohort was augmented compared to the predicate to include new subjects. Half of the patients in the test cohort were new and the other 50% were randomly selected from the predicate testing cohort.
Performance was compared between the predicate and updated algorithms.
In summary:
I. No overlap of patients between training, tuning, and test cohorts.
II. Relevant test cohort parameters are as follows:
- ~50% male patients
- Slice thickness <=5 mm
- 50% of patients were from the US
- All patients from Siemens Scanner
- Adults, age > 21
Acceptance Criteria for organ segmentation:
- For new organs, the average Dice coefficient per organ shall be greater than 0.8 or the average symmetric surface distance (ASSD) per organ less than 2 voxel of worst slice thickness, i.e. 10 mm.
- For unchanged organs, the average Dice coefficient per organ shall be within +/-0.03 of the average Dice coefficient per organ of the predicate algorithm.
Siemens Medical Solutions USA, Inc.
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SIEMENS Healthineers
- For improved organs, the average Dice coefficient per organ shall be greater or equal than the average Dice coefficient per organ of the predicate algorithm.
The average Dice coefficient for the 20 subjects was higher for each lobe in the subject device than in the predicate device, although not greater than a +0.03 difference for all lobes.
The anatomy segmentation feature supports segmentation for a wide variety of organs. Since each organ utilizes a different model, the Dice-score on other organs (other than lungs and lung lobes) that were not retrained remained unchanged and this was verified by recalculating the Dice score with the new algorithm.
# Improved PERCIST Liver algorithm
Additionally, performance evaluation was conducted for the improved PERCIST Liver algorithm. The algorithm takes as input the PET/CT image together with a binary liver mask and returns the coordinates of the reference region center.
The performance specifications for the binary liver mask used as input to the algorithm are detailed below.
The test data consisted of 20 patients. The patients were obtained from clinical partners in Europe and USA. The data was randomly selected using the following stratification:
- No overlap of patients between training, tuning, and test cohorts
- Adults, Age > 21
- ~50% male patients
- Slice thickness <= 5 mm
- All subject from Siemens Scanner
The acceptance criteria for the liver is an average Dice coefficient greater than 0.8 or an average symmetric surface distance (ASSD) less than 10 mm. The liver met both criteria.
The performance evaluation for the updated PERCIST Liver algorithm is detailed below.
In the first analysis conducted, the reference standard used to evaluate the subject device method performance consisted of liver VOI positioning obtained semi-automatically by two expert readers. The subject device algorithm was then compared to the reference standard and shown to yield results in better agreement with semi-automatic evaluation by expert readers compared with the method of placement used in the predicate device.
The second analysis conducted focused on PET/CT scans presenting foci with suspicious tracer uptake either in the liver or with spill over to the liver, evaluating the subject and predicate devices based on how often the PERCIST VOIs intersected the suspicious uptake masks identified by an expert reader. Out of 129 subjects included in the analysis, the subject device had fewer intersections (4 cases) compared
Siemens Medical Solutions USA, Inc.
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SIEMENS Healthineers
to the predicate device (13 cases). As with the predicate device, the user can manually reposition the PERCIST liver reference region at any time.
## Clinical Testing
Clinical testing was not conducted for this submission.
## Risk Analysis
The risk analysis was completed, and risk control implemented to mitigate identified hazards. The testing results support that all the software specifications have met the predetermined acceptance criteria. Testing for verification and validation of the device was found acceptable to support the claims of substantial equivalence.
## Standards
Siemens hereby certifies that MI View&GO meets the following FDA Recognized Consensus standards listed below:
| Designation Number and Edition/Date | Title | Standards Development Organization | Recognition Number |
| --- | --- | --- | --- |
| PS 3.1 - 3.20 2023e | Digital Imaging and Communications in Medicine (DICOM) Set | NEMA | 12-352 |
| 62304 Edition 1.1 2015-06 CONSOLIDATED VERSION | Medical Device Software –Software Life Cycle Processes | AAMI, ANSI, IEC | 13-79 |
| 14971 Third Edition 2019-12 | Medical devices – Application of risk management to medical devices | ISO | 5-125 |
| 62366-1 Edition 1.1 2020-06 CONSOLIDATED VERSION | Medical devices - Part 1: Application of usability engineering to medical devices | AAMI, ANSI, IEC | 5-129 |
| 15223-1 Fourth edition 2021-07 | Medical devices - Symbols to be used with medical device labels, labelling, and information to be supplied - Part 1: General requirements | ISO | 5-134 |
Siemens Medical Solutions USA, Inc.
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| 20417 First edition
2021-04
Corrected version
2021-12 | Medical devices – Information to be supplied by the manufacturer | ISO | 5-135 |
| --- | --- | --- | --- |
# Conclusion
There are no differences in the Indications for Use, Intended Use, or Fundamental Technological Characteristics of the MI View&GO VA40 software as compared to the currently commercially available MI View&GO VA30 software (K242300).
Both the current and predicate devices are used for viewing, manipulation, quantification, analysis, and comparison of medical images from single or multiple imaging modalities with one or more time-points.
Additionally, the new features implemented within this release do not raise any new issues of safety and effectiveness as compared to the predicate device. Based on this information, as well as the documentation in support of the modifications, it is Siemens’ opinion that the MI View&GO software—with the modifications outlined in this application—is substantially equivalent to the predicate device.
Siemens Medical Solutions USA, Inc.
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1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
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Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
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Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
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Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
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A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
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The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.