syngo.via RT Image Suite is a 3D and 4D image visualization, multi-modality 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:

. Multi-modality viewing and contouring of anatomical, 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 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 multiple pre-define MR acquisitions ●

Device Description

The subject device with the current software version SOMARIS/8 VB70 is an image analysis software for viewing, manipulation, 3D and 4D visualization, comparison of medical images from multiple imaging modalities and for the segmentation of tumors and organs-at-risk, prior to dosimetric planning in radiation therapy. syngo.via RT Image Suite combines routine and advanced digital image processing and visualization tools for manual and software assisted contouring of volumes of interest, identification of points of interest, sending isocenter points to an external laser system, registering images and exporting final results. syngo.via RT Image Suite supports the medical professional with tools to use during different steps in radiation therapy case preparation.

For the current software version SOMARIS/8 VB70 the following already cleared features have been modified:

Patient Marking
Contouring
4D Features ●
Basic Features of the subject device ●

AI/ML Overview

The provided text describes the acceptance criteria and a study demonstrating that the lobe-based lung ventilation algorithm within the syngo.via RT Image Suite meets these criteria.

Here's the breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

Feature/Metric	Acceptance Criteria	Reported Device Performance
AI-based Lung Lobe Segmentation	Unchanged geometric overlap with annotated ground truth as measured by DICE compared to the predicate device.	Mean DICE of 0.92 for the lung lobes across the test set (passed acceptance criterion).
Lobe-based Lung Ventilation (4D-CT Normal Breathing)	Median ventilation distribution should be well aligned with ground truth obtained from literature.	Median ventilation of about 20% for the five lung lobes, which is well aligned with literature ground truth.
Lobe-based Lung Ventilation (Breathhold CT)	Significant Pearson correlation between a proxy for vital capacity calculated by the device and vital capacity measured by PFT (spirometry).	Significant Pearson correlation of R = 0.63 (p < 0.001) with spirometry.

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

AI-based Lung Lobe Segmentation:
- Test Set Sample Size: 18 radiotherapy patients (6 female, 12 male).
- Data Provenance: Acquired from external clinical collaborations with radiotherapy departments in Europe and the Americas. The clinics used standard radiotherapy equipment and protocols to acquire the CT images.
Lobe-based Lung Ventilation Algorithm (overall validation):
- Test Set Sample Size: 108 CT datasets from 74 individual lung radiotherapy patients (25 female, 49 male; median age: 66 yrs, range 42-87 yrs).
- Data Provenance: Not explicitly stated beyond being "clinical validation," but implies patient data.

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

The document does not explicitly state the number or qualifications of experts used to establish the ground truth for the test set. It mentions "annotated ground truth" for the AI segmentation component, but doesn't specify how many experts performed the annotation or their specific qualifications (e.g., "radiologist with 10 years of experience").

4. Adjudication Method for the Test Set

The document does not describe a specific adjudication method (e.g., 2+1, 3+1). It simply refers to "annotated ground truth" for the AI segmentation.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

No MRMC comparative effectiveness study was described where human readers improved with AI assistance versus without AI assistance. The study focuses on evaluating the standalone performance of the AI component and the overall algorithm against established ground truth or standard methods.

6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was Done

Yes, a standalone evaluation was done for the AI-based component and the overall lobe-based lung ventilation algorithm.

The AI-based component for lung lobe segmentation was tested on an independent cohort, with its performance (DICE score) being measured directly against annotated ground truth.
The entire lobe-based lung ventilation algorithm's output was compared to literature ground truth (first subgroup) and spirometry (second subgroup), indicating a standalone assessment of the algorithm's output.

7. The Type of Ground Truth Used

AI-based Lung Lobe Segmentation: Expert (or human) annotated ground truth for CT scans.
Lobe-based Lung Ventilation (4D-CT Normal Breathing): Expected values obtained from scientific literature.
Lobe-based Lung Ventilation (Breathhold CT): Vital capacity measurements from spirometry (a clinical standard for pulmonary function assessment, acting as outcomes data).

8. The Sample Size for the Training Set

AI-based Lung Lobe Segmentation:
- Training Set Sample Size: 8721 thoracic CT scans.
- Validation Set Sample Size (for AI training): 969 thoracic CT scans.

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

The document states that the segmentation model was trained and validated on "annotated thoracic CT scans." This implies that human experts (likely radiologists or other medical professionals) manually segmented the lung lobes to create the ground truth for both the training and internal validation datasets. The specific process or number of experts for this annotation is not detailed.

Summary

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Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: the Department of Health & Human Services logo on the left and the FDA logo on the right. The FDA logo features the letters 'FDA' in a blue square, followed by the words 'U.S. FOOD & DRUG ADMINISTRATION' in blue text.

Siemens Medical Solutions USA Inc. % Clayton Ginn Regulatory Affairs Specialist 810 Innovation Drive KNOXVILLE TN 37932

Re: K220783

Trade/Device Name: syngo.via RT Image Suite Regulation Number: 21 CFR 892.5050 Regulation Name: Medical Charged-Particle Radiation Therapy System Regulatory Class: Class II Product Code: MUJ Dated: August 8, 2022 Received: August 8, 2022

Dear Clayton Ginn:

We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.

If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.

Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part

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

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.

For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely,

for Julie Sullivan Assistant Director DHT8C: Division of Radiological Imaging and Radiation Therapy Devices OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

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Indications for Use

510(k) Number (if known)

K220783

Device Name syngo.via RT Image Suite

Indications for Use (Describe)

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 image processing and visualization tools:

· Multi-modality viewing and contouring of anatomical, and multiparametric images such as but not limited to CT, PET, PET/CT, MRI, Linac CBCT images
· Multiplanar reconstruction (MPR) 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, 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 multiple pre-define MR acquisitions

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

X Prescription Use (Part 21 CFR 801 Subpart D)

| Over-The-Counter Use (21 CFR 801 Subpart C)

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510(K) SUMMARY FOR SYNGO.VIA RT IMAGE SUITE

Identification of the Submitter I.

Importer/Distributor

Siemens Medical Solutions USA, Inc. 40 Liberty Boulevard Malvern, PA 19355

Establishment Registration Number 2240869

Manufacturing Site

Siemens Healthcare GmbH Siemensstr 1 D-91301 Forchheim, Germany

Establishment Registration Number

3004977335

Submitter Contact Person:

Clayton Ginn Regulatory Affairs Specialist 2501 North Barrington Road Hoffman Estates, IL 60192-2061 Phone: (865) 898-2692 Email: clayton.ginn@siemens-healthineers.com

II. Device Name and Classification

Product Name: syngo.via RT Image Suite Propriety Trade Name: syngo.via RT Image Suite Classification Name: Medical charged-particle radiation therapy system Classification Panel: Radiology 21 CFR §892.5050 CFR Section: Device Class: Class II Product Code: MUJ

III. Predicate Device

Predicate Device:

Trade Name:	syngo.via RT Image Suite
510(k) Number:	K211379
Clearance Date:	07/30/2021
Classification Name:	Medical charged-particle radiation therapy system
Classification Panel:	Radiology

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CFR Section:	21 CFR §892.5050
Device Class:	Class II
Product Code:	MUJ

Reference Device:

Trade Name:	syngo.CT Bone Reading
510(k) Number:	K123584
Clearance Date:	03/12/2013
Classification Name:	System, X-Ray, Tomography, Computed
Classification Panel:	Radiology
CFR Section:	21 CFR §892.1750
Device Class:	Class II
Product Code:	JAK

IV. Device Description

For the current software version SOMARIS/8 VB70 the following already cleared features have been modified:

Patient Marking
Contouring
4D Features ●
Basic Features of the subject device ●

V. Indications for Use

The software combines the following digital image processing and visualization tools:

. Multi-modality viewing and contouring of anatomical, 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

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. 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 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 multiple pre-define MR acquisitions ●

The Indications for Use is unchanged from that of the predicate device.

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VI. Comparison of Technological Characteristics with the Predicate Device

As with the predicate device syngo.via RT Image Suite SOMARIS/8 VB70, the subject device supports viewing, manipulation, 3D and 4D visualization, comparison of medical images from multiple imaging modalities and the segmentation of tumors and organs-at-risk, prior to dosimetric planning and response assessment in radiation therapy.

At a high-level a tabular summary of the subject and predicate device's technological differences is provided as Table 4 below for the software version SOMARIS/8 VB70:

Feature	Description and Comparison of the Subject Device to the Predicate Device
Patient Marking	General Description:Transmission of reference points with the offset details to a movable laser system for patient marking.Modification:• Simplified workflow to place isocenters in the spine• Consistent user-configured default names for POIs throughout the application
Contouring	General Description:With Contouring, the user can create, delete, and edit Volumes of Interest (VOIs).Modification:• Tool to convert isodose lines from a DICOM RT dose file to contours• Minor usability improvement in the structure display in the image segment
4D Features	General Description:The subject device provides features to handle 4D image data, such as the display of a cine loop of images acquired through gated CT.Modification:• Contouring on 4D Image Data improved• Lobe-based Lung Ventilation implemented
Basic Feature ofsyngo.via RTImage Suite	General Description:The set provides basic feature of the subject device.Modification:A software interface was added to provide additional advanced visualization and measurement tools to extend the subject device

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VII. Performance Data

The following performance data were provided in support of the substantial equivalence determination.

Software Verification and Validation

Software Documentation for a Major Level of Concern software per FDA's Guidance Document "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" issued on May 11, 2005 is also included as part of this submission. The performance data demonstrates continued conformance with special controls for medical devices containing software. The Risk Analysis was completed, and risk control implemented to mitigate identified hazards. The testing supports that all software specifications have met the acceptance criteria. Testing for verification and validation support the claim of substantial equivalence.

Summary of the Clinical Validation

The subject device employs an algorithm to calculate lobe-based lung ventilation based on two input CT images representing an inspiration and expiration breathing state of the patient. The algorithm contains an AI-based component, namely deep-learning based autosegmentation of lung lobes. The AIbased component is combined with the analytic calculation of a ventilation metric that is well established in scientific literature. The output is segmented lung lobes with an associated ventilation value.

The AI-based component of the algorithm is reused in unmodified form the previously cleared software version VB40A. The segmentation model was trained and validated on annotated thoracic CT scans from 8721 and 969 patients, respectively. It was tested on an independent cohort of 18 radiotherapy patients (6 female, 12 male). Test data was acquired from external clinical collaborations with radiotherapy departments in Europe and the Americas. The clinics used standard radiotherapy equipment and protocols to acquire the CT images. The test set was not made available to the model development team, thus guaranteeing its independence from the training set. Acceptance criterion for the test was unchanged geometric overlap with the annotated ground truth as measured by DICE compared to the predicate device. The test passed the acceptance criterion for all lung lobes. A mean DICE of 0.92 was achieved for the lung lobes across the test set.

In addition to the validation of the AI-based segmentation component, a clinical validation of the entire lobe-based lung ventilation algorithm was performed on 108 CT datasets from 74 individual lung radiotherapy patients (25 female, 49 male; median age: 66 yrs, range 42-87 yrs). Two subgroups were formed based on the CT acquisition technique and respective breathing mode of the patient.

In the first subgroup (4D-CT with normal breathing), the distribution of lung ventilation as produced by the predicate device was evaluated. The five lung lobes showed a similar distribution of lung ventilation with median of about 20%. The investigation demonstrated that the median ventilation is well aligned with the ground truth obtained from literature, confirming the validity of the results returned by the evaluated lung ventilation algorithm.

In the second subgroup (breathhold CT with forced breathing), a proxy for the vital capacity was calculated from the ventilation results as returned from the subject device; and correlated with vital capacity as measured by PFT (spirometry) for the same patient within one week of the CT scan. A significant Pearson correlation of R = 0.63 was observed (p < 0.001). In conclusion, the lung ventilation algorithm, based on a CT acquisition, was successfully validated by spirometry, a widely used standard method for assessment of pulmonary function.

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Limitations of the clinical evaluation

In the first subgroup, the ground truth was taken from an expected value obtained from literature, rather than establishing ground truth from each patient undergoing standard diagnostic evaluation for ventilation.
In the second subgroup, the two clinical exams (spirometry and CT) were taken at two different time points (within one week) and under varying conditions for the patient (upright vs. supine pose, forced maximal expiration vs. instructed controlled breath hold, breathing with nose clamped vs. breathing with nose and mouth, etc)."

Because of these limitations, which may have positive or negatives effects on the results of the clinical study, the physician should be aware of these limitations and also be aware that the calculation is based on the volume and mean HU values of the lobes in the inspiration series, rather than a measurement of the air flow through each lung using an inhaled radiopharmaceutical as normally performed in nuclear medicine procedures. Thus, the ventilation results produced by RT Image Suite should not be used as the sole diagnostic tool. Clinical diagnostic evaluation of the lung ventilation is normally performed by a ventilation perfusion nuclear medicine study.

Non-Clinical Testing

This submission contains performance tests (Non-clincal test reports) to demonstrate continued conformance with special controls for medical devices containing software. Non-clinical tests (integration and functional) were conducted for syngo.via RT Image Suite during product development. These tests have been performed to test the ability of the included features of the subject device. The results of these tests demonstrate that the subject device performs as intended. The result of all conducted testing was found acceptable to support the claim of substantial equivalence.

Risk Analysis

The risk analysis was completed, and risk control implemented to mitigate identified hazards. The testing results support that all the software specifications have met the acceptance criteria. Testing for verification and validation of the device was found acceptable to support the claims of substantial equivalence.

Siemens hereby certifies that syngo.via RT Image Suite will meet the following voluntary standards covering electrical and mechanical safety listed below, prior to introduction into interstate commerce:

RecognitionNumber	ProductArea	Title of Standard	Date ofRecognition	StandardsDevelopmentOrganization
12-300	Radiology	Digital Imaging and Communications inMedicine (DICOM) Set: PS 3.1 - 3.20	06/27/2016	NEMA
13-79	Software	Medical Device Software -Software Life CycleProcesses; 62304:2015-06 (Edition 1.1)	01/14/2019	AAMI, ANSI,IEC
5-40	Software/Informatics	Medical devices – Application of riskmanagement to medical devices; 14971 SecondEdition 2007-03-01	06/27/2016	ISO
5-114	General I(QS/RM)	Medical devices - Part 1: Application ofusability engineering to medical devicesIEC 62366-1:2015	12/23/2016	IEC

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VIII. Conclusion

syngo.via RT Image Suite (software version SOMARIS/8 VB70) has the same intended use and same indication for use as the predicate device (software version SOMARIS/8 VB60). The fundamental technological characteristics are the same as the predicate device. The result of all testing conducted was found acceptable to support the claim of substantial equivalence. The comparison of technological characteristics, non-clinical performance data, and software validation demonstrates that the subject device is as safe and effective when compared to the predicate device that is currently marketed for the same intended use. For the subject device, syngo.via RT Image Suite, Siemens used the same testing with the same workflows as used to clear the predicate device. Siemens considers syngo.via RT Image Suite to be as safe, as effective and with performance substantially equivalent to the commercially available predicate devices.

Regulation Number and Section

§ 892.5050 Medical charged-particle radiation therapy system.

(a)
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.(b)
Classification. Class II. When intended for use as a quality control system, the film dosimetry system (film scanning system) included as an accessory to the device described in paragraph (a) of this section, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 892.9.