syngo.via RT Image Suite

by Siemens Medical Solutions USA  · Based in United States → — Boosting efficiency in radiation therapy.
Nuclear Medicine Oncology Radiology
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Regulatory Status Disclosed

Overview

syngo.via RT Image Suite is an advanced software solution developed by Siemens Healthineers for radiation oncology professionals. It is designed to simplify and standardize daily tasks in radiation therapy planning, making simulation, image assessment, and contouring easier and more integrated. The tool provides comprehensive 3D and 4D image visualization, manipulation, and contouring capabilities across multiple modalities, including CT, PET, MRI, and CBCT.

Key functionalities include deep learning-based Organs-at-Risk (OAR) contouring, smart contouring tools for parallel contouring on multiple images, and robust multimodality image fusion with deformable registration. It supports the incorporation of Dual Energy CT information and offers features like Direct Laser with Virtual Laser View for precise patient marking. The software aims to improve workflow efficiency and treatment accuracy, enabling clinicians to devise and assess routine and complex treatment strategies and to leverage advanced imaging information, including MR-only workflows.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Deep learning-based Organs-at-Risk (OAR) contouring
  • Smart contouring tools for parallel contouring on multiple images
  • Multimodality image fusion and deformable registration
  • Direct Laser with Virtual Laser View for patient marking
  • Integration of Dual Energy CT information
  • 3D and 4D image visualization and manipulation
  • Semi-automatic and automatic contouring of tumors and organs-at-risk
  • Export of data to Treatment Planning Systems (TPS)
  • Comprehensive respiratory motion management (4D contouring propagation with tumor trajectory)
  • Support for MR-only radiotherapy planning workflows

Use Cases

  • Radiation therapy treatment planning and simulation
  • Image assessment and review in radiation oncology
  • Contouring of tumors and organs-at-risk for treatment
  • Precise patient marking and isocenter placement
  • Treatment monitoring and adaptation based on imaging
  • Leveraging multi-modality imaging (CT, PET, MRI, CBCT) for a comprehensive patient view

What Physicians Need to Know

Key Capabilities
Deep learning-based Organs-at-Risk (OAR) contouring, smart contouring tools for parallel contouring on multiple images, and robust multimodality image fusion with deformable registration across CT, PET, MRI, and CBCT. It includes Direct Laser with Virtual Laser View for precise patient marking and supports MR-only radiotherapy planning workflows with MR-based Synthetic CT. The suite also offers comprehensive respiratory motion management and integrates Dual Energy CT information for enhanced tumor delineation and Stopping Power Ratio (SPR) calculation.
Clinical Utility
Designed to simplify and standardize radiation therapy planning, improving workflow efficiency and treatment accuracy. Deep learning-based autocontouring significantly reduces segmentation time (e.g., 87.6% for breast, 93.5% for thorax, 82.2% for pelvis), reduces interobserver variability, and standardizes OAR delineation. It enables clinicians to devise and assess complex treatment strategies and supports treatment monitoring and adaptation.
Integration Options
Seamlessly exports data to Treatment Planning Systems (TPS) as DICOM RT Structures. It supports automatic DICOM data import from previous scans and operates on a client-server architecture, making cases instantly available from PACS. The system is compatible with LAP laser systems for Direct Laser Steering and adheres to DICOM and HL7 standards.
Compliance Status
FDA 510(k) cleared as a Class II medical device (K232799, K220783). Its AI-based autocontouring feature has been clinically validated on 413 subjects, meeting acceptance criteria for geometric overlap (Dice coefficient) and demonstrating clinical safety and effectiveness. Software verification and validation were performed per FDA guidance, and DICOM Conformance Statements are available.
Pricing Model
Based on the syngo.via platform, which offers a subscription model. This model aims for transparent budget planning, flexible clinical package access, and includes evergreen software updates, service, and education plans, optimizing costs and maximizing system value.
User Experience
Developed as a user-friendly work aid with an intuitive syngo user interface and easy-to-use contouring tools. Its flexible design supports both routine and complex cases, streamlining collaboration among physicians and offering 'zero-click' deep learning-based OAR autocontouring for efficiency.
Support Quality
Siemens Healthineers provides year-round training for onboarding, ramp-ups, and skill refreshers. A dedicated manager offers ongoing support and an annual clinical walkthrough, ensuring customers stay updated with innovations at a predictable cost.
Implementation Complexity
Can be deployed as a server-based solution with multiple clients. It facilitates quick setup through simple import options, pre-fetching from PACS, and patient data reconciliation. It can be integrated directly at the scanner acquisition workstation for efficient patient marking and laser steering. Prerequisites include network connectivity, DICOM compliance, and meeting hardware and data security standards.
Evidence Base
The deep learning-based autocontouring algorithm has been trained and validated with patient images from multiple institutions globally. A published clinical validation study (Adv Radiat Oncol. 2023) confirmed good autocontouring results and significant time savings across various anatomical sites. The AI-based feature was rigorously tested on 413 subjects from an independent dataset, covering diverse clinical scenarios.
Physician Tip

Leverage the deep learning-based autocontouring for organs-at-risk to significantly reduce planning time and standardize contouring, allowing more focus on complex cases. Utilize the multimodality image fusion and deformable registration capabilities to integrate comprehensive patient data (CT, PET, MRI) for more informed treatment decisions, especially for adaptive planning and MR-only workflows. Actively use the 3D/4D visualization and respiratory motion management for precise tumor targeting and to minimize irradiation of healthy tissue. Ensure proper integration with your Treatment Planning System (TPS) to maximize workflow efficiency and data transfer accuracy.

syngo.via RT Image Suite is designed for robust integration within existing radiation oncology ecosystems. It acts as a client-server solution, facilitating seamless data flow from acquisition to planning. Key integration points include DICOM-compliant export of RT Structures to various Treatment Planning Systems (TPS), automatic DICOM data import from imaging modalities, and compatibility with external laser systems for patient marking. Its foundation on the syngo.via platform ensures broad interoperability and centralized access to patient imaging data, including PACS and potentially EMR systems through HL7, streamlining the entire RT workflow.

Details

Category Oncology AI, Radiology & Imaging AI
Pricing Contact for pricing
DeploymentServer-based solution with client installations (e.g., in Radiology, physician's office, dosimetry lab).
Compliance
BAA Available Yes AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status Yes AI-estimated

syngo.via RT Image Suite is a Class II medical device (21 CFR 892.5050) cleared by the FDA under K232799 (latest clearance as of April 26, 2024). It is intended as a 3D and 4D image visualization, multi-modality manipulation, and contouring tool to assist in the preparation of radiation therapy treatments.
Integrations
EHR Not specified
Specialties Nuclear Medicine, Oncology, Radiology

What the Web Says

Siemens Healthineers' syngo.via RT Image Suite is a software solution designed for radiation oncology professionals to streamline and enhance radiation therapy planning. It offers advanced multimodality image viewing, manipulation, and contouring capabilities, leveraging deep learning for automated organ-at-risk (OAR) delineation. The system aims to improve efficiency, precision, and integration of various imaging data into the RT workflow.

Overall: Positive

Strengths

  • Significant time savings in contouring organs at risk, with reported reductions of 82.2% to 93.5% for various body regions.
  • Good autocontouring results with deep learning-based algorithms, achieving high accuracy for a majority of evaluated structures.
  • Supports multimodality imaging (CT, MR, PET/CT) for comprehensive patient understanding and confident contouring.
  • User-friendly interface designed to simplify and standardize daily tasks in simulation, image assessment, and contouring.
  • Enables advanced treatment strategies by visualizing tumor trajectory and capturing mid-ventilation phases for 4D imaging.
  • Facilitates collaboration among physicians and supports evidence sharing for confident therapy decisions.

Limitations

  • Some studies indicate that while deep learning-based sCT reconstruction shows improvements, it is not flawless, with noticeable CT number differences near anatomical anomalies.
  • In specific cases, like synthetic materials having similar MR signals to bone, the software might incorrectly reconstruct them as bone, leading to dose discrepancies.
  • Interobserver variability in target definition can still be significant, even with automated tools, as shown in studies comparing delineated GTVs.
  • The quality scores of some systematic reviews evaluating deep learning auto-segmentation software, including syngo.via RT Image Suite, were moderate (44.0u201365.0%).
  • The software's full capabilities and availability may vary by country due to regulatory reasons.
  • Requires appropriate system configuration by the user to fully leverage automated functions.

Based on reviews from: Clinical Validation of Siemens' Syngo.via Automatic Contouring System - PMC - NIH, syngo.via RT Image Suite - Siemens Healthineers, Clinical Validation of Siemens' Syngo.via Automatic Contouring System - ResearchGate, syngo.via, Simulation and data analysis in RT - with syngo.via, syngo.via RT Image Suite Boosting efficiency - Siemens Healthineers, accessdata.fda.gov, syngo.via RT Image Suite: Empower Radiation Therapy with MRI Information, syngo.via RT Image Suite - Siemens Healthineers Canada, Siemens Medical Solutions USA, Inc. April 26, 2024 Monsuru Bello Official Correspondent 810 Innovation Drive KNOXVILLE, TN - accessdata.fda.gov, Siemens Introduces New Radiation Therapy Systems, Software | Imaging Technology News, Siemens Healthineers Introduces New Radiotherapy Imaging Solutions at ASTRO 2016, syngo.via VB40A Datasheet, Performance of Commercial Deep Learning-Based Auto-Segmentation Software for Breast Cancer Radiation Therapy Planning: A Systematic Review - MDPI, Patient positioning: why lasers point the way to optimized workflows in radiation therapy, Impact of FAPI-PET/CT on Target Volume Definition in Radiation Therapy of Locally Recurrent Pancreatic Cancer - PMC, A systematic review of clinical trials comparing radiation therapy vs. radical prostatectomy in prostate cancer | Request PDF - ResearchGate, Does dose calculation algorithm affect the dosimetric accuracy of synthetic CT for MRu2010only radiotherapy planning in brain tumors? - Lui - 2025 - DOI, Artificial intelligence in surgery | Request PDF - ResearchGate, Predicting Drug Response and Synergy Using a Deep Learning Model of Human Cancer Cells | Request PDF - ResearchGate, Ryuji Murakami's research while affiliated with Kumamoto University and other places - ResearchGate, unsupervised detection and localization of MRI artefacts and clinical anomalies using deep learning - MRinRT 2026

Last updated: 2026-07-19

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Press & Coverage

Imaging Technology News
Siemens Introduces New Radiation Therapy Systems, Software
Siemens introduced the syngo.via RT Image Suite software solution, designed to help radiation oncologists understand patients comprehensively by supporting various image types and efficiently contouring tumors and organs-at-risk. The software can display up to eight fused image series simultaneously, aiding in complex treatment planning.
2015-10
Imaging Technology News
Siemens Healthineers Introduces New Radiotherapy Imaging Solutions at ASTRO 2016
Siemens Healthineers debuted new hardware and software for radiation therapy imaging at ASTRO 2016, including an updated version of syngo.via RT Image Suite. This version aims to increase efficiency with integrated image assessment, contouring, and patient marking, and streamlines workflow by integrating 4-D data tools.
2016-09
Imaging Technology News
Dedicated Radiation Therapy CT System Receives FDA Clearance
The Somatom Confidence RT Pro CT scanner received FDA 510(k) clearance, complemented by the new syngo.via RT Image Suite software. This combination helps radiation oncology professionals increase efficiency with integrated image assessment, contouring, and patient marking features.
2016-12
Siemens Healthineers Press Release
Siemens Healthineers debuts RT Pro Edition for Magnetom Sola for aid in MRI radiation therapy planning
Siemens Healthineers unveiled the Magnetom RT Pro edition for Magnetom Sola, a 1.5T MRI scanner designed for radiation therapy treatment planning. The new syngo.via RT Image Suite post-planning software, also part of this edition, allows for the calculation of synthetic CT images from MR images, potentially eliminating the need for separate CT scans.
2018-10
accessdata.fda.gov
510(K) SUMMARY FOR SYNGO.VIA RT IMAGE SUITE
This FDA 510(k) summary details the syngo.via RT Image Suite (software version SOMARIS/8 VB40) as a 3D and 4D image visualization, multi-modality manipulation, and contouring tool for radiation therapy treatment preparation and response assessment. It highlights improved performance compared to the predicate device, particularly in organ-at-risk segmentation using a Deep Image-to-Image Network.
2019-09
accessdata.fda.gov
510(K) SUMMARY FOR SYNGO.VIA RT IMAGE SUITE
This FDA 510(k) summary describes syngo.via RT Image Suite (software version SOMARIS/8 VB50) as an image analysis software for viewing, manipulating, and visualizing medical images from multiple modalities for tumor and organ-at-risk segmentation in radiation therapy. It outlines modifications to contouring and deformable alignment features, maintaining substantial equivalence to the predicate device.
2020-08
PMC - NIH
Clinical Validation of Siemens' Syngo.via Automatic Contouring System
This peer-reviewed article validates Siemens Healthineers' syngo.via RT Image Suite for automatic contouring of organs-at-risk in radiation therapy. The study concludes that the system offers good autocontouring results, potentially saving significant time in the delineation of critical organs and overall treatment preparation.
2022-07
accessdata.fda.gov
510(K) SUMMARY FOR SYNGO.VIA RT IMAGE SUITE VC10
This FDA 510(k) summary for syngo.via RT Image Suite VC10 details its capabilities as a 3D and 4D image visualization, multimodality manipulation, and contouring tool for radiation therapy. Key modifications include the introduction of AI-based MR autocontouring for brain metastases and male pelvis OARs, and the CT Sim&GO subset for CT scanner workflows.
2026-03

Videos

Product demos, reviews, and walkthroughs for syngo.via RT Image Suite.

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Frequently Asked Questions

The AI in syngo.via RT Image Suite primarily utilizes deep learning for automated contouring of organs-at-risk (OARs), significantly reducing the time required for segmentation. This AI-based autocontouring has been clinically validated, demonstrating high accuracy with a large percentage of structures receiving maximum scores and achieving substantial time savings in delineation.
syngo.via RT Image Suite is an FDA-cleared medical device, having received 510(k) clearance. Its AI-based autocontouring feature underwent rigorous software verification and validation in accordance with FDA guidance, including evaluation on a diverse set of patient data.
The suite integrates by providing tools for 3D and 4D image visualization, multi-modality manipulation, and contouring, which can be exported to treatment planning systems. Key AI-driven features include deep learning-based OAR autocontouring directly triggered at the CT simulator, smart contouring tools for parallel contouring on multiple images, and support for an MR-only workflow with MR-based Synthetic CT.
While the AI autocontouring offers significant efficiency gains, it is designed to assist clinicians, meaning physician review and potential manual adjustments remain crucial for optimal patient care. The effectiveness of the AI can also be influenced by factors such as the diversity of imaging protocols and patient anatomies, necessitating expert oversight.
syngo.via RT Image Suite is designed to enhance existing radiation therapy workflows by addressing the challenges of managing diverse imaging data, rather than replacing entire treatment planning systems. It supports multi-modality image fusion and can export results to various treatment planning systems via DICOM RT Structures, indicating a degree of interoperability.
Siemens Healthineers offers syngo.via through a subscription model, which aims to optimize costs with transparent budget planning and flexible access to clinical packages. Specific pricing for AI functionalities is generally part of these packages, and interested parties are typically advised to contact a local sales representative for detailed quotations.
Yes, syngo.via RT Image Suite supports an MR-only workflow, particularly for brain and pelvic cancer patients, through its MR-based Synthetic CT feature. This functionality can potentially eliminate the need for a separate CT scan, streamlining the planning process and reducing patient inconvenience.

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Suggest an Edit → | Last Verified: 2026-04-19 | First Added: 2026-04-19
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