Who is the manufacturer of syngo.via RT Image Suite VC10?

Varian Medical Systems, Inc. filed the 510(k) submission for syngo.via RT Image Suite VC10 (K252304).

What is the FDA product code for syngo.via RT Image Suite VC10?

MUJ. It is classified under 21 CFR 892.5050 as a Class 2 device in the Radiology panel.

What is the regulatory pathway for syngo.via RT Image Suite VC10?

510(k) clearance (submission type: Traditional).

Does syngo.via RT Image Suite VC10 use AI or machine learning?

Yes. syngo.via RT Image Suite VC10 (K252304) is flagged as an AI/ML-enabled medical device in the FDA's AI/ML device list.

Who can help prepare an FDA 510(k) submission like syngo.via RT Image Suite VC10?

Innolitics — a medical-device software consultancy — provides regulatory and engineering support for FDA 510(k) submissions. See https://innolitics.com/services/510ks/ or contact https://innolitics.com/contact.

Can an AI/ML device like syngo.via RT Image Suite VC10 get a guaranteed FDA 510(k) clearance?

Yes. Innolitics offers a guaranteed FDA 510(k) clearance engagement for AI/ML Software as a Medical Device — combining engineering and regulatory execution under one agreement with a guaranteed clearance outcome. Eligibility: the device must be an AI/ML Software as a Medical Device (SaMD), and its performance must meet the criteria Innolitics determines during an initial regulatory strategy engagement to be necessary for FDA clearance. See https://innolitics.com/services/end-to-end-samd/ or contact https://innolitics.com/contact.

syngo.via RT Image Suite VC10

K252304 · Varian Medical Systems, Inc. · MUJ · Mar 18, 2026 · Radiology

Device Facts

Record ID	K252304
Device Name	syngo.via RT Image Suite VC10
Applicant	Varian Medical Systems, Inc.
Product Code	MUJ · Radiology
Decision Date	Mar 18, 2026
Decision	SESE
Submission Type	Traditional
Regulation	21 CFR 892.5050
Device Class	Class 2
Attributes	AI/ML, Software as a Medical Device

Intended Use

syngo.via RT Image Suite VC10 is a 3D and 4D image visualization, multimodality manipulation and contouring tool that helps the preparation of treatments such as, but not limited to those performed with radiation (for example, Brachytherapy, Particle Therapy, External Beam Radiation Therapy). It provides tools to view existing contours, create, edit, modify, copy contours of regions of the body, such as but not limited to, skin outline, targets and organs-at-risk. It also provides functionalities to create simple geometric treatment plans. Contours, images and treatment plans can subsequently be exported to a Treatment Planning System. The software combines the following digital image processing and visualization tools (not all of them might be available at each customer): - Multimodality viewing and contouring of anatomical, functional, and multi parametric images such as but not limited to CT, PET, PET/CT, MRI, Linac CBCT images - Multiplanar reconstruction (MPR) thin/thick, minimum intensity projection (MIP), volume rendering technique (VRT) - Freehand and semi-automatic contouring of regions-of-interest on any orientation including oblique - Automated Contouring on CT and MR images, including known (diagnosed) brain metastases - Creation of contours on images supported by the application without prior assignment of a planning CT or planning MR - Manual and semi-automatic registration using rigid and deformable registration - Supports the user in comparing, contouring, and adapting contours based on datasets acquired with different imaging modalities and at different time points - Supports multi-modality image fusion - Visualization and contouring of moving tumors and organs - Management of points of interest including but not limited to the isocenter - Creation of simple geometric treatment plans - Generation of a synthetic CT based on pre-defined MR acquisitions

Device Story

Software tool for radiation therapy preparation; inputs include CT, PET, PET/CT, MRI, and Linac CBCT images. Transforms inputs via multimodality registration, deep-learning-based autocontouring (CT/MR), and synthetic CT generation. Produces contours, isocenter definitions, and geometric treatment plans. Used in reading/control rooms or physician offices by trained medical professionals. Output is exported to a Treatment Planning System to assist in radiation therapy planning (Brachytherapy, Particle Therapy, External Beam). Benefits include streamlined contouring workflows, improved geometric fidelity for synthetic CT, and enhanced interoperability with laser positioning systems.

Clinical Evidence

Bench testing only; no clinical studies. Performance evaluated on 760 independent patient subjects across various models (CT/MR autocontouring, synthetic CT, isocenter estimation). Metrics included DICE coefficient, ASSD, sensitivity, and Hausdorff distance. All models met predefined acceptance criteria based on historical validation thresholds and clinical guidelines. Usability validation confirmed safe operation by intended users.

Technological Characteristics

Software-based image analysis tool. Features deep-learning-based autocontouring (3D UNet/DI2IN architecture) and 3D DL synthetic CT generation. Supports DICOM interoperability. Operates on standard workstation hardware. Complies with IEC 62304, ISO 14971, and cybersecurity standards (UL 2900-1/2-1).

Indications for Use

Indicated for use by trained medical professionals (physicists, RT technologists, physicians, radiologists, oncologists) for 3D/4D image visualization, multimodality manipulation, and contouring to assist in radiation therapy treatment preparation. No specific patient population restrictions; automation tools perform best with adult patients. No known contraindications.

Regulatory Classification

Identification

A medical charged-particle radiation therapy system is a device that produces by acceleration high energy charged particles (e.g., electrons and protons) intended for use in radiation therapy. This generic type of device may include signal analysis and display equipment, patient and equipment supports, treatment planning computer programs, component parts, and accessories.

Predicate Devices

syngo.via RT Image Suite VB80 (K232799)

Reference Devices

VBrain (K203235)
syngo.CT Applications (K220450)

Related Devices

K192065 — Syngo.Via RT Image Suite · Siemens Medical Solutions USA, Inc. · Sep 18, 2019
K211379 — syngo.via RT Image Suite · Siemens Medical Solutions USA, Inc. · Jul 30, 2021
K201444 — Syngo.via RT Image Suite · Siemens Medical Solutions USA, Inc. · Aug 13, 2020
K220783 — syngo.via RT Image Suite · Siemens Medical Solutions USA, Inc. · Sep 7, 2022
K220813 — ART-PLAN · Therapanacea · Jun 17, 2022

Submission Summary (Full Text)

{0} FDA U.S. FOOD & DRUG ADMINISTRATION March 18, 2026 Varian Medical Systems, Inc. Lynn Allman Sr. Director, Regulatory Affairs 3100 Hansen Way Palo Alto, California 94304 Re: K252304 Trade/Device Name: syngo.via RT Image Suite VC10 Regulation Number: 21 CFR 892.5050 Regulation Name: Medical Charged-Particle Radiation Therapy System Regulatory Class: Class II Product Code: MUJ Dated: February 17, 2026 Received: February 17, 2026 Dear Lynn Allman: 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 {1} K252304 - Lynn Allman Page 2 Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download). Your device is also subject to, among other requirements, the Quality Management System Regulation (QMSR) (21 CFR Part 820), which includes, but is not limited to, ISO 13485 clause 7.3 (Design controls), ISO 13485 clause 8.3 (Nonconforming product), ISO 13485 clause 8.5.2 (Corrective action), and ISO 13485 clause 8.5.3 (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 ISO 13485 clause 7.5) and document changes and approvals in the Medical Device File (ISO 13485 clause 4.2.3). 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- {2} K252304 - Lynn Allman Page 3 assistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100). Sincerely, ![img-0.jpeg](img-0.jpeg) 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 {3} 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) K252304 Device Name syngo.via RT Image Suite VC10 Indications for Use (Describe) syngo.via RT Image Suite VC10 is a 3D and 4D image visualization, multimodality manipulation and contouring tool that helps the preparation of treatments such as, but not limited to those performed with radiation (for example, Brachytherapy, Particle Therapy, External Beam Radiation Therapy). It provides tools to view existing contours, create, edit, modify, copy contours of regions of the body, such as but not limited to, skin outline, targets and organs-at-risk. It also provides functionalities to create simple geometric treatment plans. Contours, images and treatment plans can subsequently be exported to a Treatment Planning System. The software combines the following digital image processing and visualization tools (not all of them might be available at each customer): - Multimodality viewing and contouring of anatomical, functional, and multi parametric images such as but not limited to CT, PET, PET/CT, MRI, Linac CBCT images - Multiplanar reconstruction (MPR) thin/thick, minimum intensity projection (MIP), volume rendering technique (VRT) - Freehand and semi-automatic contouring of regions-of-interest on any orientation including oblique - Automated Contouring on CT and MR images, including known (diagnosed) brain metastases - Creation of contours on images supported by the application without prior assignment of a planning CT or planning MR - Manual and semi-automatic registration using rigid and deformable registration - Supports the user in comparing, contouring, and adapting contours based on datasets acquired with different imaging modalities and at different time points - Supports multi-modality image fusion - Visualization and contouring of moving tumors and organs - Management of points of interest including but not limited to the isocenter - Creation of simple geometric treatment plans - Generation of a synthetic CT based on pre-defined MR acquisitions 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) CONTINUE ON A SEPARATE PAGE IF NEEDED. FORM FDA 3881 (8/23) Page 1 of 2 PSC Publishing Services (301) 443-6740 {4} This section applies only to requirements of the Paperwork Reduction Act of 1995. **DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.** The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to: Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff@fda.hhs.gov "An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number." FORM FDA 3881 (8/23) Page 2 of 2 {5} SIEMENS Healthineers \* # Premarket Notification - 510(k) Summary Traditional 510(k) Submission for syngo.via RT Image Suite VC10 ## I. Submitter and Manufacturer Information | Submitter Name and Address | Varian Medical Systems 3100 Hansen Way Palo Alto, CA 94304 | | --- | --- | | Contact Name | Lynn, Allman, PhD., Senior Director Regulatory Affairs | | Email and Phone | submissions.support@varian.com (650) 424-5369 | | Date Prepared | Feb 13th 2026 | | Manufacturer Name and Address | Siemens Healthcare GmbH Henkestr. 127 91052 Erlangen Germany | ## II. Device Information Proprietary Name: syngo.via RT Image Suite VC10 Common/Usual Name: syngo.via RT Image Suite VC10 Classification Name: System, Planning, Radiation Therapy Treatment Regulation: 21 CFR 892.5050 Product Code: MUJ Device Class: Class II ## III. Predicate Device syngo.via RT Image Suite VB80 (K232799) Reference Device: VBrain (K203235) ## IV. Device Description syngo.via RT Image Suite VC10 is an image analysis and radiation therapy preparation software that provides multimodality image viewing, registration, segmentation, synthetic CT generation, and patient-marking workflows. Within the Medical device syngo.via RT Image Suite VC10 the name 'CT Sim&Go' is used. CT Sim&GO is the name used for syngo.via RT Image Suite VC10 when it is deployed in the CT scanner workflow. CT Sim&GO is not a device of its own. CT Sim&GO is a subset of syngo.via RT Image Suite VC10 functionalities that can be accessed from the CT scanner workplace. More precisely it comprises the Patient Marking and Beam Placement modules of syngo.via RT Image Suite VC10. The current submission includes modifications affecting the following functionalities: 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {6} SIEMENS Healthineers ## MR Autocontouring The AI-based MR autocontouring functionality has been introduced to include segmentation of previously diagnosed brain metastases, in addition to MR-based segmentation of brain OARs and male pelvis OARs. The metastasis-specific model is restricted to identification of metastases already diagnosed by a clinician, and the software does not provide diagnostic capability or detect new or unknown lesions. These contours remain fully editable by the user. ## CT Autocontouring syngo.via RT Image Suite VC10 includes 29 new organs and structures for deep-learning-based CT autocontouring. The underlying DL architecture is unchanged; however, additional segmentation guidelines and organ-coverage expansion were incorporated. ## Improvements to Isocenter Definition & Patient Marking The patient-marking workflow includes semi-automated isocenter estimation for breast (originally cleared under K192065) and vertebral regions (originally cleared under K220783). New capability to send the coordinates from a movable laser positioning system to the syngo.via RT Image Suite VC10, enabling a workflow of setting isocenter directly on the skin and transferring it to the planning images. ## Synthetic CT The synthetic CT feature was updated to include a new 3D deep-learning-based algorithm for brain and pelvis, replacing the prior 2D model and improving HU accuracy and geometric fidelity. ## V. Indications for Use syngo.via RT Image Suite VC10 is a 3D and 4D image visualization, multimodality manipulation and contouring tool that helps the preparation of treatments such as, but not limited to those performed with radiation (for example, Brachytherapy, Particle Therapy, External Beam Radiation Therapy). It provides tools to view existing contours, create, edit, modify, copy contours of regions of the body, such as but not limited to, skin outline, targets and organs-at-risk. It also provides functionalities to create simple geometric treatment plans. Contours, images and treatment plans can subsequently be exported to a Treatment Planning System. 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {7} SIEMENS Healthineers The software combines the following digital image processing and visualization tools (not all of them might be available at each customer): - Multimodality viewing and contouring of anatomical, functional, and multi parametric images such as but not limited to CT, PET, PET/CT, MRI, Linac CBCT images - Multiplanar reconstruction (MPR) thin/thick, minimum intensity projection (MIP), volume rendering technique (VRT) - Freehand and semi-automatic contouring of regions-of-interest on any orientation including oblique - Automated Contouring on CT and MR images, including known (diagnosed) brain metastases - Creation of contours on images supported by the application without prior assignment of a planning CT or planning MR - Manual and semi-automatic registration using rigid and deformable registration - Supports the user in comparing, contouring, and adapting contours based on datasets acquired with different imaging modalities and at different time points - Supports multi-modality image fusion - Visualization and contouring of moving tumors and organs - Management of points of interest including but not limited to the isocenter - Creation of simple geometric treatment plans - Generation of a synthetic CT based on pre-defined MR acquisitions ## VI. Comparison of Technological Characteristics with the Predicate Device The modified device, referred to as the "subject device" throughout this summary, is release version VC10 of the syngo.via RT Image Suite with additional software changes incorporated since the release version of the predicate device, version VB80 (K232799). The subject device (VC10) maintains the same fundamental technology and operational principles as the predicate device syngo.via RT Image Suite VB80 (K232799). The following updates have been added to clearly capture changes introduced in VC10 that were not cleared previously: **Metastasis Contouring** The predicate device did not include MR autocontouring **Laser-to-Software and Software-to-Laser Isocenter Transfer** 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {8} SIEMENS Healthineers VC10 adds the ability to receive isocenter coordinates from RTP laser systems in addition to sending them extending interoperability. ## Synthetic CT VC10 replaces the prior 2D synthetic CT algorithm with an enhanced 3D Deep learning model, improving accuracy and robustness for brain and pelvis. The different technical characteristics do not raise different questions about safety and effectiveness. These modifications raise similar questions relating to software performance, software interoperability, and usability. These considerations of safety and effectiveness were also applicable to the predicate device. 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {9} SIEMENS Healthineers Comparison of Subject Device to Predicate Device syngo.via RT Image Suite VC10 and syngo.via RT Image Suite VB80 | No. | Specification | Predicate Device (Primary) | Device Under Evaluation | Equivalency | | --- | --- | --- | --- | --- | | | | syngo.via RT Image Suite (VB80) 510(k) Id # K232799 | Syngo.via RT Image Suite VC10 | | | 1.0 | Clinical Characteristics | | | | | 1.1 | Intended Purpose | Image analysis software for evaluating image data sets and preparing them for further use in therapy. | Image analysis software for evaluating image data sets and preparing them for further use in therapy. | Equivalent | | 1.2 | Intended Use | syngo.via RT Image Suite is intended to be used by trained medical professionals including, but not limited to, medical physicists, RT technologists, physicians, radiologists, nuclear medicine physicians, and radiation oncologists. syngo.via RT Image Suite is a medical application for viewing, manipulation, 3D and 4D visualization, and comparison of medical images from multiple imaging modalities. The application enables the registration of images and provides tools to help the user to identify volumes, regions and points of interest inside the patient anatomy. The application also enables the creation of simple geometric plans. The application may assist in the preparation of further radiation therapy treatment planning. The application supports | syngo.via RT Image Suite is intended to be used by trained medical professionals including, but not limited to, medical physicists, RT technologists, physicians, radiologists, nuclear medicine physicians, and radiation oncologists. syngo.via RT Image Suite is a medical application for viewing, manipulation, 3D and 4D visualization, and comparison of medical images from multiple imaging modalities. The application enables the registration of images and provides tools to help the user to identify volumes, regions and points of interest inside the patient anatomy. The application also enables the creation of simple geometric plans. The application may assist in the preparation of further radiation therapy treatment planning. The application supports anatomical datasets from CT, MR, CBCT, as | Equivalent | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {10} SIEMENS Healthineers | | | anatomical datasets from CT, MR, CBCT, as well as functional data, such as 4D CT, 3D/4D PET/CT, and 4D MRI. | well as functional data, such as 4D CT, 3D/4D PET/CT, and 4D MRI. | | | --- | --- | --- | --- | --- | | 1.3 | Indications for Use | syngo.via RT Image Suite is a 3D and 4D image visualization, multimodality manipulation and contouring tool that helps the preparation of treatments such as, but not limited to those performed with radiation (for example, Brachytherapy, Particle Therapy, External Beam Radiation Therapy). It provides tools to view existing contours, create, edit, modify, copy contours of regions of the body, such as but not limited to, skin outline, targets and organs-at-risk. It also provides functionalities to create simple geometric treatment plans. Contours, images and treatment plans can subsequently be exported to a Treatment Planning System. The software combines the following digital | syngo.via RT Image Suite is a 3D and 4D image visualization, multimodality manipulation and contouring tool that helps the preparation of treatments such as, but not limited to those performed with radiation (for example, Brachytherapy, Particle Therapy, External Beam Radiation Therapy). It provides tools to view existing contours, create, edit, modify, copy contours of regions of the body, such as but not limited to, skin outline, targets and organs-at-risk. It also provides functionalities to create simple geometric treatment plans. Contours, images and treatment plans can subsequently be exported to a Treatment Planning System. The software combines the following digital | Substantially Equivalent Updated with the inclusion of MR Images | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 Page 6 of 42 {11} SIEMENS Healthineers | | | The software combines the following digital image processing and visualization tools: • Multimodality viewing and contouring of anatomical, functional, and multi-parametric images such as but not limited to CT, PET, PET/CT, MRI, Linac CBCT images • Multiplanar reconstruction (MPR) thin/thick, minimum intensity projection (MIP), volume rendering technique (VRT) • Freehand and semi-automatic contouring of regions-of-interest on any orientation including oblique • Automated Contouring on CT images • Creation of contours on images supported by the application without prior assignment of a planning CT • Manual and semi-automatic registration using rigid and deformable registration • Supports the user in comparing, contouring, and adapting contours based on datasets acquired with different imaging modalities and at different time points • Supports multimodality image fusion | image processing and visualization tools (not all of them might be available at each customer): • Multimodality viewing and contouring of anatomical, functional, and multi-parametric images such as but not limited to CT, PET, PET/CT, MRI, Linac CBCT images • Multiplanar reconstruction (MPR) thin/thick, minimum intensity projection (MIP), volume rendering technique (VRT) • Freehand and semi-automatic contouring of regions-of-interest on any orientation including oblique • Automated Contouring on CT and MR images, including known (diagnosed) brain metastases • Creation of contours on images supported by the application without prior assignment of a planning CT or planning MR • Manual and semi-automatic registration using rigid and deformable registration • Supports the user in comparing, contouring, and adapting contours based on datasets acquired with different imaging modalities and at different time points • Supports multimodality image fusion | | --- | --- | --- | --- | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 Page 7 of 42 {12} SIEMENS Healthineers | | | • Visualization and contouring of moving tumors and organs • Management of points of interest including but not limited to the isocenter • Creation of simple geometric treatment plans • Generation of a synthetic CT based on multiple pre-define MR acquisitions | • Visualization and contouring of moving tumors and organs • Management of points of interest including but not limited to the isocenter • Creation of simple geometric treatment plans • Generation of a synthetic CT based on pre-define MR acquisitions | | | --- | --- | --- | --- | --- | | 1.4 | Clinical condition intended to diagnose, treat or manage | Not restricted | Not restricted | Equivalent | | 1.5 | Intended patient population | The intended patient population is not subject to any restrictions. However, automation support provided works best with adult patients. | The intended patient population is not subject to any restrictions. However, **functionality like Auto-Contouring and Lung Ventilation work best with adult patients.** | Substantially Equivalent minor deviation in wording | | 1.6 | Contraindications | There are no known specific situations that contraindicate the use of this device. | There are no known specific situations that contraindicate the use of this device. | Equivalent | | 1.7 | Operating Environment | The task is designed to be used embedded in the scanner console or in a workstation next to it to perform patient virtual simulation in the radiation therapy context. It can also be used in the contouring room or in the physicians' office to perform treatment preparation (registration, contouring, | The task is designed to be used embedded in the **Reading/Control Room** on a scanner console or in a workstation next to it to perform patient virtual simulation in the radiation therapy context. It can also be used in the **Reading Room** (contouring room or in the physicians' office) to perform treatment preparation (registration, contouring, | Substantially Equivalent minor deviation in wording | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {13} SIEMENS Healthineers | | | adaption) or treatment assessment (decision on treatment strategy). | adaption) or treatment assessment (decision on treatment strategy). | | | --- | --- | --- | --- | --- | | 1. | Intended Users | Trained medical professionals including, but not limited to, medical physicists, RT technologists, physicians, radiologists, nuclear medicine physicians, and radiation oncologists. | Qualified persons with the necessary knowledge in accordance with country-specific regulations, for example, radiotherapy technologists, medical physicists, clinical administrators, or radiation oncologists | Substantially Equivalent minor deviation in wording | | 2.0 | **Technical Characteristics** | | | | | 2.1 | **Basic Features of the Subject Device** | | | | | | Routine Reading Functionality | VRT, MPR, MIP, thin VRT, thick MPR, Interaction: zoom, pan, rotate | VRT, MPR, MIP, thin VRT, thick MPR, Interaction: zoom, pan, rotate | Equivalent | | | Parallel Display | Parallel Image Display, Image Visualization, Image Fusion, Correlated Cursors | Parallel Image Display, Image Visualization, Image Fusion, Correlated Cursors | Equivalent | | | Routine Annotation Functionality | Distance line, ROI, VOI, pixel lens, angle; findings | Distance line, ROI, VOI, pixel lens, angle; findings | Equivalent | | 2.2 | **Image Registration** | | | | | | Rigid Alignment | Rigid registration of images of the same patient acquired with the same or different modalities within the same or different imaging sessions. The transformation includes only translation and rotation (6 degrees of freedom). | Rigid registration of images of the same patient acquired with the same or different modalities within the same or different imaging sessions. The transformation includes only translation and rotation (6 degrees of freedom). | Equivalent | | | Deformable Alignment | Deformable registration of images of the same patient acquired with the same or different modalities within different imaging | Deformable registration of images of the same patient acquired with the same or different modalities within different imaging sessions. | Equivalent | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 Page 9 of 42 {14} SIEMENS Healthineers | | | sessions. The transformation allows for local deformation to adapt to changing anatomy (many degrees of freedom). The feature includes a tool for visual quality assurance. | The transformation allows for local deformation to adapt to changing anatomy (many degrees of freedom). The feature includes a tool for visual quality assurance. | | | --- | --- | --- | --- | --- | | 2.3 | Contouring | | | | | | Routine Contouring | Routine Contouring tools (e. g. freehand drawing tools, creation of margins, tool to convert isodose lines from a DICOM RT dose file to contours etc.) | Routine Contouring tools (e. g. freehand drawing tools, creation of margins etc.) A tool was added to convert isodose lines from a DICOM RT dose file to contours. | Equivalent | | | Advanced Contouring | Advanced Contouring tools (automatic contouring of structures, nudge 3D tool, etc.). Support of Rapid Results Technology. Streamlined workflow to adapt contours from a prior to a current planning CT (“adaptive contouring”). | Advanced Contouring tools (automatic contouring of structures, nudge 3D tool, etc.). Support of Rapid Results Technology. Streamlined workflow to adapt contours from a prior to a current planning CT (“adaptive contouring”). Additional structures and organs were added for Auto Contouring to extend the organ coverage and included additional segmentation guidelines for CT images and Inclusion of MR Images (MR autocontouring including brain metastasis) (The underlying deep learning technology for this extension is unchanged. It reuses the same technology which was available in prior versions of the auto segmentation feature). | Existing feature enhanced | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {15} SIEMENS Healthineers | | | | Brain metastasis specific contouring model is limited to previously diagnosed metastases, using deep learning segmentation. Note: Brain metastases – only on MR Images) | | | --- | --- | --- | --- | --- | | | Contouring on 4D Image Data | Contouring tools on 4D image data (e. g. display of a cine loop of images acquired through gated CT etc.) | Contouring tools on 4D image data (e. g. display of a cine loop of images acquired through gated CT etc.) | Equivalent | | | Routine Structure Operations | Structure editing tools (e. g. expansion or shrinking of a structure). | Structure editing tools (e. g. expansion or shrinking of a structure). | Equivalent | | | Duplication of Structures and POIs | Duplication of structures and POIs inside the same structure set. | Duplication of structures and POIs inside the same structure set. | Equivalent | | 2.4 | Structure Set Management | | | | | | Structure Set Management | • Loading and storing of DICOM RT structure sets, creating, editing and deletion of structures and POIs. • Creating, editing and deletion of structure templates. • Customize predefined structure database with mapping to international nomenclature schemes. | • Loading and storing of DICOM RT structure sets, creating, editing and deletion of structures and POIs. • Creating, editing and deletion of structure templates. • Customize predefined structure database with mapping to international nomenclature schemes. | Equivalent | | 2.5 | Reference Point Management | | | | | | Reference Point Management | Reference point creation and management | Reference point creation and management | Equivalent | | 2.6 | Patient Marking | | | | | | Patient Marking | Sending of reference points with offset details to a laser system. | Sending and receiving of reference points with offset details and coordinates to and | Minor difference - | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {16} SIEMENS Healthineers | | | • Inclusion of a simplified workflow to place isocenters in the spine • Consistent use of user-configured default names throughout the application | from a movable laser system. • Inclusion of a simplified workflow to place isocenters in the spine • Consistent use of user-configured default names throughout the application | Existing feature enhanced | | --- | --- | --- | --- | --- | | 2.7 | Dose Evaluation | | | | | | Dose Evaluation | Loading of any existing dose files; addition or subtraction of two dose; show Dose Volume Histograms | Loading of any existing dose files; addition or subtraction of two dose; show Dose Volume Histograms | Equivalent | | 2.8 | Beam Placement | | | | | | Beam Placement | Creation of new geometric treatment plans for photon radiotherapy | Creation of new geometric treatment plans for photon radiotherapy | Equivalent | | 2.9 | Synthetic CT | | | | | | Synthetic CT | Generation of CT-density image series (2D model) out of multiple MR-image series for Pelvis and Brain. | New Synthetic CT algorithm (3D model) for Pelvis and Brain was provided | Existing feature enhanced | | 2.10 | Lung Ventilation | | | | | | Lung Ventilation | Calculation of lobe-based lung ventilation from an inspiration and expiration CT scan | Calculation of lobe-based lung ventilation from an inspiration and expiration CT scan | Equivalent | | 2.11 | Software | | | | | | User Interface | syngo.via based GUI | syngo.via based GUI | Equivalent | | | Archiving / Storing | MOD, CD-R, film; DVD | MOD, CD-R, film; DVD | Equivalent | | | Communication | DICOM Compatible | DICOM Compatible | Equivalent | | 2.12 | Model support | | | | | | Model support | CT Scanners, syngo.via platform | CT Scanners, syngo.via platform | Equivalent | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 Page 12 of 42 {17} SIEMENS Healthineers Comparison of Contour Metastases for VBrain and syngo.via RT Image Suite VC10 | Specification | Reference Device VBrain (K203235) | Device Under Evaluation syngo.via RT Image Suite VC10 | Equivalency | | --- | --- | --- | --- | | Intended Use | Assists trained medical professionals in RT planning by providing initial contours for known brain tumors. | Software for multimodality viewing, registration, and autocontouring including brain metastases. | Similar | | Clinical Workflow Role | Provides initial GTV contours requiring clinician review. | Provides editable automated contours; clinician review required. | Similar | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 Page 13 of 42 {18} SIEMENS Healthineers | Specification | Reference Device VBrain (K203235) | Device Under Evaluation syngo.via RT Image Suite VC10 | Equivalency | | --- | --- | --- | --- | | Tumor Types Supported | Brain metastases, meningiomas, acoustic neuromas. | Brain metastases and brain OARs. | Similar | | Imaging Modalities | T1 CE MRI | CT, MRI, CBCT, PET/CT, etc. | Similar | | AI/ML Technology | Deep learning neural networks. | 3D UNet/DI2IN-based DL models. | Similar | | User Control | Fully editable | Fully editable | Similar | | Performance Sensitivity | 90.3% | 92.5% | Similar | | False Positive Rate | 0.681 tumors/case | 1.30 | Similar | | Dice Coefficient | 0.793 | 0.74 | Similar | | Hausdorff Distance | 5.0% in terms of lesion size | 1.41 mm (HD95) | Similar | VII. Summary of Performance Testing (Non-Clinical Testing) The following performance data was provided in support of the substantial equivalence determination. Software Verification and Validation Testing: Software verification and validation was conducted, and documentation was provided as recommended by FDA's Guidance for Industry and FDA Staff, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices." The software for this device was considered as a "major" level of concern. The software development and validation were performed in accordance with recognized standards including IEC 62304, ISO 14971, and applicable FDA-recognized consensus standards. 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {19} SIEMENS Healthineers Cybersecurity and Interoperability requirements were assessed per FDA guidance’s “Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions”, “Postmarket Management of Cybersecurity in Medical Devices”, “Design Considerations and Premarket Submission Recommendations for Interoperable Medical Devices”. Verification and validation testing demonstrated that the software met all specified requirements. All test cases passed predefined acceptance criteria. The testing supports the safety, effectiveness, and substantial equivalence of the device. Test results demonstrate conformance to applicable requirements and specifications. No animal studies or clinical tests have been included in this pre-market submission. However, usability validation was successfully performed and demonstrated that intended users can safely and effectively operate the modified features without patterns of use error. This is consistent with the nonclinical validation showing equivalent or improved performance relative to the predicate. ## Scope and Goals of Testing and Criteria Each algorithm was evaluated using quantitative metrics appropriate for its output: - CT auto-contouring: DICE coefficient and ASSD vs. expert ground truth. - MR Brain Metastasis: DICE, Hausdorff Distance, false-positive rate per case, sensitivity. - MR OAR Models (Brain, Pelvis): DICE and ASSD. - Synthetic CT: HU accuracy and geometric fidelity. - Semi-automated isocenter estimates or defining isocenters via RTP lasers: Isocenter placed within defined anatomical structure (breast, vertebrae) All models met predefined acceptance criteria based on historical SYNGO.VIA RT IMAGE SUITE VC10 validation thresholds and clinical guideline requirements. 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {20} SIEMENS Healthineers # Clinical Data Summary Algorithm performance was evaluated using independent test datasets comprising a total of 760 patients subjects, distributed across the following models and features: | Model / Feature | Number of Subjects | | --- | --- | | CT auto-contouring | 469 | | MR brain metastasis model | 30 | | MR brain organs-at-risk (OAR) model | 46 | | MR pelvis OAR model | 154 | | Synthetic CT model | 51 | | Semi-automated isocenter estimation / laser-based isocenter definition (breast) | 10 | | Semi-automated isocenter estimation / laser-based isocenter definition (vertebra) | 10 | All test datasets were independent of training datasets. # Demographics and Subgroup Representation Each dataset included adult patients with distributions across gender and age ranges relevant to the intended use. Subgroup analyses were performed to assess potential confounding factors. For CT auto-contouring, subgroups included scanner manufacturer, slice thickness, and gender. For MR-based models, subgroups included scanner manufacturer, magnetic field strength (1.5T and 3T), and gender. No clinically relevant confounders were identified. # Imaging Equipment and Protocols 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {21} SIEMENS Healthineers Image data were collected across multiple scanner vendors (Siemens, GE, and Philips) and included variation in relevant acquisition parameters such as slice thickness, magnetic field strength, and MR sequence type, as applicable to each model. ## Reference Standard and Data Independence Ground truth contours were generated by expert clinicians using well-established international contouring guidelines and underwent independent quality assurance reviews. All algorithms were evaluated using test datasets that were not used during model training, with test data drawn from separate patient cohorts, clinical sites, or imaging systems where applicable. ## Training Data Overview Training datasets consisted of curated, multicenter CT and MR image collections with expert-annotated reference standards and standardized preprocessing. The training data included a range of manufacturers, acquisition settings, and clinical conditions relevant to the intended use. ## Performance Evaluation of the Algorithm: ### CT auto-contouring The AI-based auto-contouring feature of syngo.via RT Image Suite VC10 was tested on 469 subjects. The test data was generated from an independent set that was not seen by the model during training stage to cover a wide range of CT scanners and typical CT acquisition and reconstruction parameters. The general guideline was to reserve 20% of the available data for validation. The test data covers: - Regional distribution (Europe: IT, PT, CH, UK, NL, DE; North America: US, CA; South America: BR; Australia, Asia: JP, IN) - Demographic distribution: Male/female - Distribution by manufacturer of the scanner: GE, Siemens, Philips - Distribution in protocols of different slice thicknesses: between 1 mm till 5 mm Subgroup analysis regarding manufacturer, slice thickness and gender did not show any confounder. 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {22} SIEMENS Healthineers Distribution of test data across subgroups for CT auto-contouring | Subgroup | # Test data sets | | --- | --- | | Data Source | Europe: 110, US: 149, Canada: 56, South America: 83, Australia: 29, Asia: 33, unknown: 13 | | Body Region | Head&Neck: 114, Thorax&Abdomen: 266, Pelvis: 93 | | Gender | Male: 199, female: 216, Unknown: 58 | | Age | <=30: 1, [30-50]: 6, [50;70]: 46, >70: 22, unknown: 398 | | Slice thickness (in mm) | <=1:20, (1,2]: 220, (2,3]: 213, >3: 20 | | Manufacturer | Siemens: 148, GE: 100, Philips: 149, unknown/others: 76 | Manual ground-truth segmentations were annotated by an expert team based on well accepted international contouring guidelines, followed by a rigorous independent quality assessment. The testing ensures the quantitative performance of the resulting segmentations by comparing them to the manually annotated ground truth. Analysis was performed on DICE (Dice Similarity Coefficient) and ASSD (Average symmetric surface distance) DICE: measures the volumetric overlap between algorithm result and manual ground truth annotation; value range between 0 (no overlap) and 1 (full overlap). ASSD: measures the average surface-to-surface distance in mm between algorithm result and manual ground truth annotation. While the DICE coefficient is very commonly used for the purpose of comparing segmentations, its meaningfulness is limited for small structures. For small organs, the ASSD is the more suitable metric. The performances from predicate device (for organs available in predicate and subject device) and FDA cleared /scientific literature (for new organs) were used as reference standards. ## Quantitative evaluation of organs available in predicate and subject device The acceptance criterion was defined in the following way: - Statistical non-inferiority of the Dice score compared with the reference predicate. 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {23} SIEMENS Healthineers Non-inferiority is defined such that the lower 95th percentile confidence bound of the subject device is greater than the mean reference performance subtracted by a 10% margin. Test results: passed for all organs. Table below shows the performance results. | Structure | # Test Cases | DICE | | | | --- | --- | --- | --- | --- | | | | Mean | Std.Dev | Lower 95th % Confidence Interval | | Body | 46 | 0.99 | 0.003 | 0.99 | | Spinal Canal | 27 | 0.85 | 0.073 | 0.82 | | Spinal Cord | 39 | 0.67 | 0.102 | 0.64 | | Brain | 20 | 0.98 | 0.005 | 0.98 | | Brainstem Brouwer et al. | 20 | 0.89 | 0.024 | 0.88 | | Brainstem DAHANCA¹ | 30 | 0.88 | 0.025 | 0.88 | | Cochlea Left | 25 | 0.75 | 0.164 | 0.68 | | Cochlea Right | 25 | 0.8 | 0.049 | 0.78 | | Eye Globe Left | 20 | 0.89 | 0.038 | 0.88 | | Eye Globe Right | 20 | 0.89 | 0.027 | 0.88 | | Glottis Brouwer et al. | 20 | 0.7 | 0.103 | 0.65 | | Glottis DAHANCA¹ | 30 | 0.68 | 0.087 | 0.65 | | Lens Left | 20 | 0.68 | 0.192 | 0.59 | | Lens Right | 20 | 0.67 | 0.121 | 0.61 | | Lips | 20 | 0.79 | 0.072 | 0.76 | | LN Level Ia Submental Triangle | 59 | 0.64 | 0.157 | 0.6 | | LN Level Ib Submandibular Triangle Left | 59 | 0.8 | 0.063 | 0.79 | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {24} SIEMENS Healthineers | Structure | # Test Cases | DICE | | | | --- | --- | --- | --- | --- | | | | Mean | Std.Dev | Lower 95th % Confidence Interval | | LN Level Ib Submandibular Triangle Right | 58 | 0.77 | 0.086 | 0.75 | | LN Level II Upper Jugular Nodes Left | 59 | 0.82 | 0.051 | 0.81 | | LN Level II Upper Jugular Nodes Right | 59 | 0.8 | 0.063 | 0.78 | | LN Level III Middle Jugular Nodes Left | 59 | 0.79 | 0.067 | 0.77 | | LN Level III Middle Jugular Nodes Right | 59 | 0.77 | 0.085 | 0.75 | | LN Level IVa Lower Jugular Group Left | 59 | 0.71 | 0.109 | 0.68 | | LN Level IVa Lower Jugular Group Right | 59 | 0.73 | 0.084 | 0.71 | | LN Level IVb Medial Supraclavicular Group Left | 59 | 0.66 | 0.159 | 0.62 | | LN Level IVb Medial Supraclavicular Group Right | 59 | 0.7 | 0.11 | 0.67 | | LN Level IX Bucco-facial Group Left | 59 | 0.64 | 0.08 | 0.62 | | LN Level IX Bucco-facial Group Right | 59 | 0.62 | 0.096 | 0.59 | | LN Level V Posterior Triangle Group Left | 59 | 0.71 | 0.117 | 0.68 | | LN Level V Posterior Triangle Group Right | 59 | 0.69 | 0.122 | 0.66 | | LN Level Vc Lateral Supraclavicular Group Left | 59 | 0.56 | 0.156 | 0.52 | | LN Level Vc Lateral Supraclavicular Group Right | 59 | 0.61 | 0.123 | 0.57 | | LN Level Vla Anterior Jugular Nodes | 59 | 0.7 | 0.066 | 0.69 | | LN Level Vlb Prelaryngeal, Pretracheal, & Paratracheal Nodes | 59 | 0.66 | 0.109 | 0.64 | | LN Level Vlla Retropharyngeal Nodes Left | 59 | 0.53 | 0.1 | 0.5 | | LN Level Vlla Retropharyngeal Nodes Right | 59 | 0.49 | 0.149 | 0.45 | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 Page 20 of 42 {25} SIEMENS Healthineers | Structure | # Test Cases | DICE | | | | --- | --- | --- | --- | --- | | | | Mean | Std.Dev | Lower 95th % Confidence Interval | | LN Level VIIb Retro-styloid Nodes Left | 59 | 0.73 | 0.079 | 0.71 | | LN Level VIIb Retro-styloid Nodes Right | 59 | 0.74 | 0.095 | 0.71 | | LN Level VIII Parotid Group Left | 59 | 0.85 | 0.037 | 0.84 | | LN Level VIII Parotid Group Right | 59 | 0.84 | 0.042 | 0.83 | | LN Level Xa Retroauricular & Subauricular Nodes Left | 59 | 0.69 | 0.099 | 0.66 | | LN Level Xa Retroauricular & Subauricular Nodes Right | 59 | 0.73 | 0.075 | 0.71 | | LN Level Xb Occipital Nodes Left | 59 | 0.57 | 0.111 | 0.54 | | LN Level Xb Occipital Nodes Right | 59 | 0.56 | 0.136 | 0.52 | | Mandible | 20 | 0.88 | 0.028 | 0.87 | | Optic Chiasm | 20 | 0.37 | 0.183 | 0.29 | | Optic Nerve Left | 20 | 0.63 | 0.121 | 0.57 | | Optic Nerve Right | 20 | 0.63 | 0.103 | 0.58 | | Oral Cavity | 20 | 0.89 | 0.049 | 0.87 | | Parotid Gland Left | 20 | 0.85 | 0.081 | 0.82 | | Parotid Gland Right | 20 | 0.85 | 0.072 | 0.81 | | Pharyngeal Constrictor Muscle Inferior | 30 | 0.78 | 0.049 | 0.76 | | Pharyngeal Constrictor Muscle Middle | 30 | 0.67 | 0.076 | 0.64 | | Pharyngeal Constrictor Muscle Superior | 30 | 0.66 | 0.056 | 0.64 | | Submandibular Gland Left | 19 | 0.87 | 0.045 | 0.84 | | Submandibular Gland Right | 15 | 0.85 | 0.066 | 0.82 | | Supraglottic Larynx Brouwer et al. | 20 | 0.77 | 0.091 | 0.73 | | Supraglottic Larynx DAHANCA¹ | 30 | 0.8 | 0.059 | 0.78 | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {26} SIEMENS Healthineers | Structure | # Test Cases | DICE | | | | --- | --- | --- | --- | --- | | | | Mean | Std.Dev | Lower 95th % Confidence Interval | | Thyroid | 30 | 0.84 | 0.034 | 0.83 | | Aorta | 35 | 0.87 | 0.032 | 0.86 | | Brachial Plexus Right | 20 | 0.66 | 0.051 | 0.63 | | Brachial Plexus Left | 20 | 0.63 | 0.089 | 0.59 | | Chest Wall Left | 28 | 0.92 | 0.016 | 0.92 | | Chest Wall Right | 28 | 0.93 | 0.013 | 0.92 | | Esophagus RTOG | 34 | 0.81 | 0.059 | 0.79 | | Esophagus DAHANCA¹ | 30 | 0.86 | 0.042 | 0.84 | | Female Breast Left RTOG | 8 | 0.89 | 0.049 | 0.85 | | Female Breast Left ESTRO¹ | 28 | 0.91 | 0.034 | 0.89 | | Female Breast Right RTOG | 7 | 0.85 | 0.066 | 0.79 | | Female Breast Right ESTRO¹ | 28 | 0.91 | 0.035 | 0.89 | | LN Axilla Level I Left | 24 | 0.81 | 0.055 | 0.79 | | LN Axilla Level I Right | 24 | 0.8 | 0.072 | 0.77 | | LN Axilla Level II Left | 24 | 0.79 | 0.068 | 0.76 | | LN Axilla Level II Right | 24 | 0.78 | 0.07 | 0.75 | | LN Axilla Level III Left | 24 | 0.75 | 0.042 | 0.74 | | LN Axilla Level III Right | 24 | 0.76 | 0.078 | 0.73 | | LN Internal Mammary Left | 24 | 0.59 | 0.081 | 0.55 | | LN Internal Mammary Right | 24 | 0.63 | 0.096 | 0.59 | | LN Supraclavicular Left | 24 | 0.79 | 0.085 | 0.76 | | LN Supraclavicular Right | 24 | 0.8 | 0.068 | 0.77 | | Lung Lobe Left Lower | 18 | 0.9 | 0.125 | 0.84 | | Lung Lobe Left Upper | 18 | 0.94 | 0.073 | 0.91 | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 Page 22 of 42 {27} SIEMENS Healthineers | Structure | # Test Cases | DICE | | | | --- | --- | --- | --- | --- | | | | Mean | Std.Dev | Lower 95th % Confidence Interval | | Lung Lobe Right Lower | 17 | 0.93 | 0.045 | 0.9 | | Lung Lobe Right Middle | 18 | 0.89 | 0.079 | 0.85 | | Lung Lobe Right Upper | 18 | 0.93 | 0.053 | 0.91 | | Proximal Bronchial Tree | 27 | 0.84 | 0.051 | 0.82 | | Pulmonary Artery | 27 | 0.8 | 0.058 | 0.78 | | Rib Left 1 | 19 | 0.84 | 0.043 | 0.82 | | Rib Left 10 | 19 | 0.77 | 0.189 | 0.68 | | Rib Left 11 | 19 | 0.77 | 0.191 | 0.68 | | Rib Left 12 | 18 | 0.8 | 0.073 | 0.76 | | Rib Left 2 | 19 | 0.83 | 0.075 | 0.8 | | Rib Left 3 | 19 | 0.82 | 0.038 | 0.8 | | Rib Left 4 | 19 | 0.83 | 0.033 | 0.81 | | Rib Left 5 | 19 | 0.83 | 0.032 | 0.82 | | Rib Left 6 | 19 | 0.84 | 0.024 | 0.83 | | Rib Left 7 | 19 | 0.83 | 0.031 | 0.82 | | Rib Left 8 | 19 | 0.82 | 0.036 | 0.8 | | Rib Left 9 | 19 | 0.82 | 0.023 | 0.81 | | Rib Right 1 | 19 | 0.84 | 0.051 | 0.81 | | Rib Right 10 | 19 | 0.79 | 0.194 | 0.69 | | Rib Right 11 | 19 | 0.78 | 0.193 | 0.68 | | Rib Right 12 | 18 | 0.82 | 0.044 | 0.8 | | Rib Right 2 | 19 | 0.87 | 0.027 | 0.85 | | Rib Right 3 | 19 | 0.85 | 0.039 | 0.83 | | Rib Right 4 | 19 | 0.86 | 0.027 | 0.85 | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {28} SIEMENS Healthineers | Structure | # Test Cases | DICE | | | | --- | --- | --- | --- | --- | | | | Mean | Std.Dev | Lower 95th % Confidence Interval | | Rib Right 5 | 19 | 0.86 | 0.026 | 0.85 | | Rib Right 6 | 19 | 0.86 | 0.026 | 0.85 | | Rib Right 7 | 19 | 0.85 | 0.031 | 0.84 | | Rib Right 8 | 19 | 0.81 | 0.109 | 0.76 | | Rib Right 9 | 19 | 0.79 | 0.2 | 0.69 | | Ribs | 19 | 0.88 | 0.025 | 0.87 | | Sternum | 34 | 0.88 | 0.032 | 0.87 | | Trachea | 27 | 0.89 | 0.046 | 0.87 | | Vena Cava Inferior | 27 | 0.76 | 0.128 | 0.71 | | Vena Cava Superior | 27 | 0.79 | 0.069 | 0.76 | | Atrium Left | 57 | 0.86 | 0.048 | 0.85 | | Atrium Right | 57 | 0.79 | 0.089 | 0.77 | | Heart | 57 | 0.93 | 0.02 | 0.93 | | CA Left Anterior Descending Artery (LAD) | 55 | 0.42 | 0.097 | 0.39 | | Ventricle Left Endocardium | 57 | 0.84 | 0.054 | 0.82 | | Ventricle Left | 57 | 0.86 | 0.041 | 0.85 | | Ventricle Right | 57 | 0.83 | 0.034 | 0.83 | | Abdominopelvic Cavity | 21 | 0.96 | 0.032 | 0.94 | | Bowel Large | 102 | 0.9 | 0.045 | 0.89 | | Bowel Small | 76 | 0.89 | 0.042 | 0.88 | | Duodenum | 76 | 0.77 | 0.104 | 0.75 | | Kidney Left | 16 | 0.93 | 0.019 | 0.92 | | Kidney Right | 16 | 0.91 | 0.07 | 0.87 | | Liver | 23 | 0.96 | 0.013 | 0.95 | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 Page 24 of 42 {29} SIEMENS Healthineers | Structure | # Test Cases | DICE | | | | --- | --- | --- | --- | --- | | | | Mean | Std.Dev | Lower 95th % Confidence Interval | | Pancreas | 31 | 0.68 | 0.138 | 0.63 | | Stomach | 31 | 0.91 | 0.043 | 0.89 | | Spleen | 21 | 0.93 | 0.022 | 0.92 | | Bladder | 20 | 0.95 | 0.052 | 0.93 | | LN Common Iliac Left | 19 | 0.85 | 0.053 | 0.82 | | LN Common Iliac Right | 19 | 0.82 | 0.048 | 0.8 | | LN External Iliac Left | 19 | 0.89 | 0.036 | 0.87 | | LN External Iliac Right | 19 | 0.88 | 0.031 | 0.87 | | LN Internal Iliac Left | 19 | 0.83 | 0.072 | 0.79 | | LN Internal Iliac Right | 19 | 0.84 | 0.063 | 0.81 | | LN Obturator Left | 19 | 0.83 | 0.026 | 0.82 | | LN Obturator Right | 19 | 0.83 | 0.041 | 0.81 | | LN Presacral | 19 | 0.68 | 0.144 | 0.61 | | Penile Bulb | 30 | 0.74 | 0.092 | 0.71 | | Prostate | 12 | 0.87 | 0.057 | 0.83 | | Proximal Femur Left | 20 | 0.93 | 0.028 | 0.92 | | Proximal Femur Right | 20 | 0.92 | 0.027 | 0.91 | | Rectum | 74 | 0.82 | 0.088 | 0.8 | | Seminal Vesicles | 18 | 0.77 | 0.1 | 0.72 | | Sigmoid | 74 | 0.8 | 0.107 | 0.77 | | Uterus | 25 | 0.88 | 0.043 | 0.86 | ¹ structures with secondary guideline support added in subject device. 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {30} SIEMENS Healthineers # Quantitative evaluation of new organs in the subject device Two quantitative metrics (DICE & ASSD) and a qualitative clinical user evaluation were employed. Clinical user evaluation included a four-point scale to evaluate each contour in the context of time savings compared to contouring from scratch. Our acceptance criteria combine the statistical tests and the user evaluation - only structures that pass two or more tests could be included in the final models: 1. Statistical non-inferiority of the Dice score compared with the reference device. 2. Statistical non-inferiority of the ASSD score compared with the reference device. 3. Average user evaluation of 3 or higher. Non-inferiority is defined for: DICE: such that the lower 95th percentile confidence bound of the subject device is greater than the mean reference performance subtracted by a 10% margin. ASSD: such that the upper 95th percentile confidence bound of the subject device is smaller than the mean reference performance added by the standard deviation. Test result: Passed for all new organs. The quantitative performance is shown in the table below. | Structure | # Test Cases | DICE | | | ASSD (mm) | | | | --- | --- | --- | --- | --- | --- | --- | --- | | | | Mean | Std.Dev | Lower 95th % Confidence Interval | Mean | Std.Dev | Upper 95th % Confidence Interval | | Lacrimal Gland Left | 66 | 0.7 | 0.069 | 0.69 | 0.85 | 0.255 | 0.92 | | Lacrimal Gland Right | 66 | 0.68 | 0.112 | 0.66 | 1 | 0.612 | 1.15 | | Pituitary Gland | 66 | 0.73 | 0.095 | 0.71 | 0.76 | 0.39 | 0.85 | | Humeral Head Left | 70 | 0.94 | 0.019 | 0.94 | 0.7 | 0.319 | 0.78 | | Humeral Head Right | 70 | 0.94 | 0.025 | 0.94 | 0.74 | 0.418 | 0.84 | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {31} SIEMENS Healthineers | Structure | # Test Cases | DICE | | | ASSD (mm) | | | | --- | --- | --- | --- | --- | --- | --- | --- | | | | Mean | Std.Dev | Lower 95th % Confidence Interval | Mean | Std.Dev | Upper 95th % Confidence Interval | | N2 Station 1: Highest Mediastinal Nodes Left | 59 | 0.7 | 0.1 | 0.67 | 2.34 | 1.013 | 2.6 | | N2 Station 1: Highest Mediastinal Nodes Right | 59 | 0.67 | 0.108 | 0.64 | 2.36 | 0.784 | 2.56 | | N2 Station 2: Upper Paratracheal Nodes Left | 59 | 0.67 | 0.072 | 0.65 | 1.43 | 0.445 | 1.54 | | N2 Station 2: Upper Paratracheal Nodes Right | 59 | 0.51 | 0.146 | 0.47 | 2.58 | 1.541 | 2.98 | | N2 Station 3A: Prevascular Nodes | 59 | 0.75 | 0.072 | 0.73 | 1.58 | 0.393 | 1.68 | | N2 Station 3P: Retrotracheal Nodes | 59 | 0.66 | 0.057 | 0.65 | 1.53 | 0.575 | 1.68 | | N2 Station 4: Lower Paratracheal Nodes Left | 59 | 0.6 | 0.114 | 0.58 | 1.8 | 0.998 | 2.06 | | N2 Station 4: Lower Paratracheal Nodes Right | 59 | 0.71 | 0.086 | 0.69 | 1.72 | 0.724 | 1.91 | | N2 Station 5: Subaortic Nodes | 59 | 0.59 | 0.146 | 0.55 | 1.84 | 0.921 | 2.08 | | N2 Station 6: Para-aortic Nodes | 59 | 0.58 | 0.143 | 0.54 | 1.98 | 1.089 | 2.26 | | N2 Station 7: SubCarinal Nodes | 59 | 0.6 | 0.064 | 0.58 | 1.78 | 0.719 | 1.97 | | N2 Station 8: Paraesophageal Nodes | 59 | 0.67 | 0.071 | 0.65 | 1.83 | 0.766 | 2.03 | | N2 Station 9: Pulmonary Ligament Nodes Left | 59 | 0.39 | 0.169 | 0.35 | 4.28 | 3.417 | 5.17 | | N2 Station 9: Pulmonary Ligament Nodes Right | 57 | 0.4 | 0.147 | 0.36 | 3.3 | 1.758 | 3.76 | | N1 Station 10: Hilar Nodes Left | 59 | 0.55 | 0.095 | 0.52 | 1.19 | 0.666 | 1.37 | | N1 Station 10: Hilar Nodes Right | 59 | 0.52 | 0.09 | 0.49 | 1.27 | 0.584 | 1.42 | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {32} SIEMENS Healthineers | Structure | # Test Cases | DICE | | | ASSD (mm) | | | | --- | --- | --- | --- | --- | --- | --- | --- | | | | Mean | Std.Dev | Lower 95th % Confidence Interval | Mean | Std.Dev | Upper 95th % Confidence Interval | | CA Left Circumflex (LCX) | 63 | 0.28 | 0.125 | 0.25 | 3.81 | 1.427 | 4.17 | | CA Right Coronary Artery (RCA) | 60 | 0.27 | 0.119 | 0.24 | 4.58 | 2.215 | 5.15 | | Bowel Bag | 51 | 0.95 | 0.033 | 0.94 | 2.31 | 2.153 | 2.92 | | Femoral Head Left | 59 | 0.95 | 0.011 | 0.95 | 0.55 | 0.144 | 0.59 | | Femoral Head Right | 59 | 0.95 | 0.03 | 0.94 | 0.64 | 0.484 | 0.77 | | Hip Bone Left | 65 | 0.94 | 0.017 | 0.94 | 0.46 | 0.164 | 0.5 | | Hip Bone Right | 65 | 0.95 | 0.016 | 0.95 | 0.4 | 0.151 | 0.44 | | Sacrum | 65 | 0.92 | 0.032 | 0.92 | 0.58 | 0.417 | 0.69 | ## Subgroup analysis for photon-counting CT Subgroup analysis was performed to evaluate the performance in terms of various CT image contrasts (achieved by varying the energy of virtual monoenergetic images derived from photon-counting CT in the energy range of conventional CT with 80 kVp to 140 kVp) and image resolutions (achieved by varying the sharpness of reconstruction kernels) with respect to reference settings using the following subgroups: - Image contrast: Six different virtual monoenergetic images (VMIs) from 50 keV to 100 keV in 10 keV steps with smooth image impression (Qr40) - Image resolution: Four different sharpness levels of reconstruction kernels from soft (Qr32) to sharp (Qr76) Evaluation cohort: - 199 oncological patient cases with and without metal implants 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {33} SIEMENS Healthineers - 326 CT acquisitions in total covering various body regions in different phases after iodine contrast injection (early arterial, late aterial, venous, late venous, delayed) or without contrast injection Robustness assessment: - Reference image contrast and resolution for generating the reference organ contour with the subject device: 70 keV VMI with Qr40 (similar image impression as conventional CT with 120 kVp [1-4]) - Robustness assessment with respect to possible conventional image contrasts [1-5] - 80 kVp (equal to 58 keV VMI) - 120 kVp (equal to 70/71 keV VMI) - 140 kVp (equal to 79 keV VMI) simulated by VMIs with 50 keV, 60 keV, 70 keV, 80 keV, 90 keV, 100 keV derived from photon-counting CT. - Robustness assessment with respect to possible image sharpness levels from soft to sharp: Qr32, Qr40, Qr60, Qr76. The mean and standard deviation of Dice coefficients (between reference and variable image impression), along with the lower 95th percentile confidence bound, were calculated for structures obtained by the subject device. The acceptance criterion for segmentation robustness is fulfilled when the mean Dice is greater or equal to the reference mean Dice. Test Result: All organs evaluated passed the acceptance criterion. Robustness assessment of structures for different image contrasts and image resolutions, grouped by body region are shown in the tables below. | Body Region | Robustness assessment of structures/OAR for different image contrasts | | | --- | --- | --- | | | #Images | DICE | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {34} SIEMENS Healthineers | | | Mean | Std. Dev | Lower 95th % Confidence Interval | | --- | --- | --- | --- | --- | | Abdomen | 16572 | 0.97 | 0.076 | 0.89 | | Body | 8390 | 0.97 | 0.032 | 0.93 | | Cardiac | 6692 | 0.95 | 0.074 | 0.78 | | Head and Neck | 21019 | 0.90 | 0.143 | 0.67 | | Pelvis | 19960 | 0.93 | 0.123 | 0.76 | | Thorax | 74624 | 0.95 | 0.080 | 0.86 | | Body Region | Robustness assessment of structures for different image resolutions | | | | | --- | --- | --- | --- | --- | | | #Images | DICE | | | | | | Mean | Std. Dev | Lower 95th % Confidence Interval | | Abdomen | 9975 | 0.99 | 0.039 | 0.96 | | Body | 5034 | 0.99 | 0.012 | 0.97 | | Cardiac | 4017 | 0.98 | 0.038 | 0.93 | | Head and Neck | 12770 | 0.93 | 0.117 | 0.80 | | Pelvis | 12114 | 0.98 | 0.066 | 0.92 | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 Page 30 of 42 {35} SIEMENS Healthineers | Thorax | 44819 | 0.98 | 0.039 | 0.94 | # MR auto-contouring of brain metastasis The AI-based auto-contouring feature of syngo.via RT Image Suite was tested on 30 subjects. The test data was generated from an independent set that was not seen by the model during training stage to cover a wide range of MR scanners and typical magnetic field strengths. The test data covers: - Regional distribution - Demographic distribution: Male/female - Distribution by manufacturer of the scanner: GE, Siemens Subgroup analysis regarding manufacturer and gender did not show any confounder. Distribution of test data across subgroups for MR auto-contouring of brain metastasis | Subgroup | # Test data sets | | --- | --- | | Data Source | USA: 11 EU:30 Unknown: 19 | | Body Region | Intraparenchymal brain: 60 | | Sequence | MR T1W Post-contrast | | Gender | Male: 24 female: 17, Unknown: 19 | | Age | [<30Y]: 3 [30Y – 50Y]: 16 [50Y – 60Y]: 10 [60Y – 70Y]: 17 [>70Y]: 14 | | Field strength | 1.5T: 48 3.0 T: 12 | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {36} SIEMENS Healthineers | Subgroup | # Test data sets | | --- | --- | | Manufacturer | Siemens: 33, GE: 27 | Manual ground-truth segmentations were annotated by an expert team based on well accepted international contouring guidelines, followed by a rigorous independent quality assessment. The testing ensures the quantitative performance of the resulting segmentations by comparing them to the manually annotated ground truth. Analysis was performed on Hausdorff Distance, DICE (Dice Similarity Coefficient), false-positive rate/case and sensitivity. Performances from an FDA cleared device were used as reference standard. ## Quantitative evaluation of MR auto-contouring for Brain Metastases Our acceptance criteria involve the following statistical tests - only structures that pass both the quantitative metrics are included in the final models: 1. Statistical non-inferiority of the Lesionwise DICE compared with the reference device. 2. Statistical non-inferiority of the Lesionwise Sensitivity compared with the reference device. Non-inferiority is defined for. Lesionwise DICE: such that the lower 95th percentile confidence bound of the subject device is greater than the mean reference dice coefficient subtracted by a 10% margin. Lesionwise Sensitivity: such that the lower 95th percentile confidence bound of the subject device is greater than the mean reference sensitivity subtracted by a 10% margin. Test result: Passed. Performance results are shown in the table below. | | DICE | Sensitivity (%) | | --- | --- | --- | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {37} SIEMENS Healthineers | Structure | # Test Cases | Mean | Std.Dev | Lower 95th % Confidence Interval | Mean | Std.Dev | Lower 95th % Confidence Interval | | --- | --- | --- | --- | --- | --- | --- | --- | | Brain metastases (parenchymal) | 60 | 0.74 | 0.17 | 0.72 | 92.5 | 3.4 | 85.8 | ## MR auto-contouring of brain OAR The AI-based auto-contouring feature of syngo.via RT Image Suite was tested on 81 subjects. The test data was generated from an independent set that was not seen by the model during training stage to cover a wide range of MR scanners and typical magnetic field strengths. The test data covers: - Regional distribution (North America: US;) - Demographic distribution: Male/female - Distribution by manufacturer of the scanner: GE, Siemens - Distribution of different field strengths: 1.5 and 3T Subgroup analysis regarding manufacturer, field strength and gender did not show any confounder. Distribution of test data across subgroups for MR auto-contouring of brain OAR 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {38} SIEMENS Healthineers | Subgroup | # Test data sets | | --- | --- | | Data Source | USA: 26, EU: 35, Unknown: 20 | | Body Region | brain: 81 | | Sequence | MR T1W Post-contrast | | Gender | Male: 30, female: 31, Unknown: 20 | | Age | [<30Y]: 1 [30Y – 50Y]: 17 [50Y – 60Y]: 15 [60Y – 70Y]: 18 [>70Y]: 20 Unknown: 10 | | Field strength | 1.5T: 61, 3T: 20 | | Manufacturer | Siemens: 50, GE: 31 | Manual ground-truth segmentations were annotated by an expert team based on well accepted international contouring guidelines, followed by a rigorous independent quality assessment. The testing ensures the quantitative performance of the resulting segmentations by comparing them to the manually annotated ground truth. Analysis was performed on DICE (Dice Similarity Coefficient) and ASSD (Average symmetric surface distance). Performances from the FDA cleared devices were used as the reference standard ## MR auto-contouring of pelvis OAR The AI-based auto-contouring feature of syngo.via RT Image Suite was tested on 153 subjects. The test data was generated from an independent set that was not seen by the model during training stage to cover a wide range of MR scanners and typical magnetic field strength. The test data covers: 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {39} SIEMENS Healthineers - Regional distribution (North America: US; Europe: Germany, Romania, France, Switzerland, Spain; Australia) - Distribution by manufacturer of the scanner: GE, Siemens, Philips - Distribution of different field strengths: 1.5 and 3T Subgroup analysis regarding manufacturer, field strength did not show any confounder. Distribution of test data across subgroups for MR auto-contouring of pelvis OAR | Subgroup | # Test data sets | | --- | --- | | Data Source | US (4 sites): 78; Europe (7 sites): 75; Australia (1 site): 1 | | Body Region | Male pelvis: 153 | | Sequence | T2 W TSE, T1 VIBEDixon W | | Gender | Male: 154 | | Age | [40Y – 50Y]: 11 [50Y – 60Y]: 8 [60Y – 70Y]: 35 [70Y – 80Y]: 31 > 80Y: 2 Unknown: 66 | | Field strength | 1.5T: 51, 3T: 102 | | Manufacturer | Siemens: 66, GE: 18, Philips: 69 | Manual ground-truth segmentations were annotated by an expert team based on well accepted international contouring guidelines, followed by a rigorous independent quality assessment. The testing ensures the quantitative performance of the resulting segmentations by comparing them to the manually annotated ground truth. Analysis was performed on DICE (Dice Similarity Coefficient) and ASSD (Average symmetric surface distance). Performances from the FDA cleared devices were used as the reference standard. # Quantitative evaluation of MR auto-contouring for Brain and Pelvis OARs 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {40} SIEMENS Healthineers The acceptance criteria combine the statistical tests and a qualitative clinical user evaluation. (Clinical user evaluation included a four-point scale to evaluate each contour in the context of time savings compared to contouring from scratch) - only structures that pass two or more tests could be included in the final models: 1. Statistical non-inferiority of the DICE score compared with the reference device. 2. Statistical non-inferiority of the ASSD score compared with the reference device. 3. Average user evaluation of 3 or higher. Non-inferiority is defined for DICE: such that the lower 95th percentile confidence bound of the subject device is greater than the mean reference performance subtracted by a 10% margin. ASSD: such that the upper 95th percentile confidence bound of the subject device is smaller than the mean reference performance added by the standard deviation. Test result: Passed for all organs. Quantitative performance results for both Brain and Pelvis OARs are shown in the tables below. | Structure (Brain OAR) | # Test Cases | DICE | | | ASSD (mm) | | | | --- | --- | --- | --- | --- | --- | --- | --- | | | | Mean | Std.Dev | Lower 95th % Confidence Interval | Mean | Std.Dev | Upper 95th % Confidence Interval | | Brainstem | 81 | 0.93 | 0.02 | 0.92 | 0.54 | 0.15 | 0.57 | | Cochlea Left | 80 | 0.5 | 0.18 | 0.46 | 1.11 | 0.84 | 1.3 | | Cochlea Right | 81 | 0.49 | 0.19 | 0.45 | 1.07 | 0.76 | 1.23 | | Cornea Left | 81 | 0.52 | 0.16 | 0.48 | 0.59 | 0.35 | 0.66 | | Cornea Right | 81 | 0.53 | 0.15 | 0.5 | 0.66 | 0.8 | 0.83 | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {41} SIEMENS Healthineers | Eye Left | 79 | 0.92 | 0.05 | 0.9 | 0.4 | 0.24 | 0.45 | | --- | --- | --- | --- | --- | --- | --- | --- | | Eye Right | 79 | 0.92 | 0.03 | 0.92 | 0.36 | 0.15 | 0.4 | | Hippocampus Left | 81 | 0.77 | 0.07 | 0.75 | 0.72 | 0.36 | 0.79 | | Hippocampus Right | 81 | 0.76 | 0.08 | 0.75 | 0.71 | 0.31 | 0.77 | | Lacrimal Gland Left | 80 | 0.56 | 0.2 | 0.51 | 1.6 | 1.58 | 1.95 | | Lacrimal Gland Right | 81 | 0.57 | 0.2 | 0.52 | 1.48 | 1.3 | 1.77 | | Lens Left | 77 | 0.75 | 0.14 | 0.71 | 0.43 | 0.3 | 0.5 | | Lens Right | 76 | 0.77 | 0.15 | 0.73 | 0.42 | 0.36 | 0.5 | | Optic Chiasm | 81 | 0.66 | 0.11 | 0.63 | 0.69 | 0.66 | 0.84 | | Optic Nerve Left | 81 | 0.54 | 0.15 | 0.51 | 1.21 | 2.7 | 1.8 | | Optic Nerve Right | 81 | 0.57 | 0.14 | 0.54 | 0.85 | 0.86 | 1.04 | | Pituitary Gland | 79 | 0.65 | 0.17 | 0.61 | 0.76 | 0.47 | 0.86 | | Retina Left | 81 | 0.62 | 0.15 | 0.59 | 0.43 | 0.5 | 0.54 | | Retina Right | 81 | 0.63 | 0.11 | 0.6 | 0.38 | 0.14 | 0.4 | | Spinal cord | 80 | 0.86 | 0.09 | 0.84 | 0.51 | 0.47 | 0.61 | | Structure (Pelvis OAR) | # Test Cases | DICE | | | ASSD (mm) | | | | --- | --- | --- | --- | --- | --- | --- | --- | | | | Mean | Std.Dev | Lower 95th % Confidence Interval | Mean | Std.Dev | Upper 95th % Confidence Interval | | T1 Pelvis | | | | | | | | | Body | 55 | 0.98 | 0.01 | 0.98 | 1.4 | 1.56 | 1.82 | | Femur head Left | 55 | 0.93 | 0.03 | 0.92 | 1.1 | 0.59 | 1.26 | | Femur head Right | 55 | 0.94 | 0.02 | 0.93 | 0.96 | 0.48 | 1.09 | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {42} SIEMENS Healthineers | T2 Pelvis | | | | | | | | | --- | --- | --- | --- | --- | --- | --- | --- | | Anus | 98 | 0.73 | 0.1 | 0.71 | 2.24 | 1.16 | 2.47 | | Bladder | 98 | 0.9 | 0.08 | 0.88 | 1.36 | 0.85 | 1.53 | | Penile Bulb | 95 | 0.81 | 0.09 | 0.79 | 0.91 | 0.76 | 1.07 | | Prostate | 90 | 0.86 | 0.07 | 0.84 | 1.66 | 2.01 | 2.08 | | Rectum | 98 | 0.86 | 0.06 | 0.85 | 1.92 | 2.01 | 2.32 | | Seminal Vesicles | 89 | 0.72 | 0.14 | 0.69 | 1.78 | 1.25 | 2.05 | ## Synthetic CT for pelvis and brain The AI-based synthetic CT feature of syngo.via RT Image Suite was tested on 51 subjects. The test data was generated from an independent set that was not seen by the model during training stage to cover a range of MR scanners and typical magnetic field strengths. The test data covers: - Regional distribution (North America, Europe) - Distribution of different field strengths: 1.5 and 3T - Distribution of different Siemens scanners Distribution of test data across subgroups for synthetic CT | Subgroup | # Test data sets | | --- | --- | | Data Source | US: 17; Europe: 18; Unknown: 16 | | Body Region | pelvis: 29, brain: 22 | | Sequence | T1 VIBE Dixon | | Gender | Male: 24, female: 21, unknown: 6 | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {43} SIEMENS Healthineers | Subgroup | # Test data sets | | --- | --- | | Age | [21Y-40Y]:6 [41Y-60Y]:11 [61Y-80Y]:18 Unknown:16 | | Field strength | 1.5T: 33, 3T: 18 | | Siemens scanners | MAGNETOM Aera: 24, MAGNETOM Skyra: 5, MAGNETOM Vida: 13, MAGNETOM Sola: 1, MAGNETOM Sola Fit: 1 | The testing ensures the quantitative performance of the resulting synthetic CT. Analysis was performed on geometric fidelity and HU accuracy. # Semi-automated isocenter estimates of vertebrae (cleared in K220450) The AI-based algorithm is cleared within the medical device syngo.CT Applications (K220450, clearance date 03/7/2022). It was tested on 426 subjects. The test data was generated from an independent set that was not seen by the model during training stage to cover a wide range of CT scanners and typical CT acquisition and reconstruction parameters. The test data covers: - Regional distribution (North America: US; Asia: CN, IN, CO; Europe: BE, CH, F, UK, DE) - Demographic distribution: Male/female - Distribution by manufacturer of the scanner: GE, Siemens, Philips, Toshiba, NeuroLogica Distribution of test data across subgroups for Semi-automated isocenter estimates or defining isocenters via RTP lasers | Subgroup | # Test data sets | | --- | --- | | Data Source | Europe: 142, US: 126, Asia: 131, unknown: 27 | | Body Region | Head&Neck: 113, Thorax&Abdomen: 264, Pelvis: 92 | | Gender | Male: 187, female: 74, Unknown: 165 | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {44} SIEMENS Healthineers | Age | [0-2]:5, [3-12]: 25, [13-19]: 64, [20-29]:38 [30-39]:21 [40-49]:71 [50-59]:46 [60-69]:80 [70-79]:49 [80-89]:12 unknown: 15 | | --- | --- | | Slice thickness (in mm) | <=1:20, (1,2]: 220, (2,3]: 209, >3: 20 | | Manufacturer | Siemens: 369, GE: 10, Philips: 28, Toshiba: 2; NeuoLogica: 14 unknown/others: 3 | Manual ground-truth of spine landmarks were annotated by an expert team, followed by a rigorous independent quality assessment. The testing ensures the quantitative performance of the resulting landmarks by comparing them to the manually annotated ground truth. Analysis was performed on percentage of cases which need corrections. ## VIII. Use of Consensus Standards: The following list of FDA-recognized, voluntary consensus standards were utilized in the design and evaluation of the subject device's safety and efficacy. | Standard Organization | Title | | --- | --- | | ISO 14971:2019 | Medical devices - Application of risk management to medical devices | | ISO 15223-1:2021 | Medical devices - Symbols to be used with medical device labels, labelling and information to be supplied - Part 1: General requirements | | ISO 20417:2021 | Information supplied by the manufacturer of medical devices | | IEC 62304:2006 + A1:2016 | Medical Device Software - Software Lifecycle processes | 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {45} SIEMENS Healthineers | IEC 62366-1:2015+A1:2020 | Application of Usability Engineering to Medical Devices | | --- | --- | | IEC 82304-1:2016 | Health software Part 1: General requirements for product safety | | IEC 61217:2011 | Radiotherapy Equipment, Coordinates, Movements and Scales | | IEC 62083:2009 | Medical electrical equipment – Requirements for the safety of radiotherapy treatment planning systems | | UL ANSI 2900-1:2017 | Standard for Software Cybersecurity for Network-Connectable Products, Part 1: General Requirements | | UL ANSI 2900-2-1:2017 | Software Cybersecurity for Network-Connectable Products, Part 2-1: Particular Requirements for Network Connectable Components of Healthcare and Wellness Systems | | IEC 81001-5-1:2021 | Health Software and Health IT Systems Safety, Effectiveness and Security - Part 5-1: Security - Activities In The Product Life Cycle | IX. Determination of Substantial Equivalence to the Predicate A subset of software features and characteristics of the subject device are different from the predicate device. However, Siemens Healthineers considers these differences to be enhancements of the predicate. The principle of operation of the subject device is the same as that of the existing predicate device. Verification and validation demonstrate that the subject device is as safe, as effective as the predicate. VBrain serves as a reference device within this submission. syngo.via RT Image Suite VC10 is comparable to VBrain (K203235) and has similar performance 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 {46} SIEMENS Healthineers metrics with respect to the ability to contour metastases in MR images. Siemens Healthineers therefore believes that the subject device is substantially equivalent to the predicate device. 510(k) Summary Traditional 510(k) Application syngo.via RT Image Suite VC10 Page 42 of 42