syngo.CT Extended Functionality is intended to provide advanced visualization tools to prepare and process medical images for diagnostic purpose. The software package is designed to support technicians and physicians in qualitative and quantitative measurements and in the analysis of clinical data that was acquired and reconstructed by Computed Tomography (CT) scanners, and possibly other medical imaging modalities (e.g. MR scanners).

An interface shall enable the connection between the syngo.CT Extended Functionality software package and the interconnected CT Scanner system.

Resulting images created with the syngo.CT Extended Functionality software package can be used to assist trained technicians or physicians in diagnosis.

Device Description

syngo.CT Extended Functionality is a software bundle that offers tools to support special clinical evaluations. The "tools" are represented by the so-called Extensions. syngo.CT Extended Functionality can be used to create advanced visualizations and measurements on clinical data that was acquired and reconstructed by Computed Tomography (CT) scanners or other medical imaging modalities (e.g. MR scanners) by using the Extensions. Advanced visualizations and measurements are listed as follows. The subject device in the current software version SOMARIS/8 VB51 has been extended by the Extension Pulmonary Density.

This feature provides the possibility to segment opacity regions of CT images of the lungs using an Al algorithm. Pulmonary Density counts image voxels inside opacity regions and calculates the percentages of these voxels relative to the total number of voxels per lobe, lung and in total. Afterwards, each of the five lung lobes is assigned a score ranging from 0 to 4 based on the percentage of opacity as follows: 0 (0%), 1 (1%-25%), 2 (26%-50%), 3 (51%-75%), or 4 (76%-100%). Then a summation of the five lobe scores (range of possible scores, 0–20) are generated in the device outputs.

AI/ML Overview

Here's a breakdown of the acceptance criteria and study information for the syngo.CT Extended Functionality device, specifically focusing on the new "Pulmonary Density" feature.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria provided in the document are somewhat implicit, primarily relying on achieving "equivalent performance in comparison to the secondary predicate device" and demonstrating performance within established statistical limits.

Acceptance Criterion (Implicit)	Reported Device Performance
Lung Lobe Segmentation Algorithm:
High accuracy in computing segmentation masks of the five lung lobes (RUL, RML, RLL, LUL, LLL). Compared against a "secondary predicate device."	Average DICE coefficients ranged from 0.94 to 0.96. This indicates a very high degree of overlap between the algorithm's segmentation and the ground truth. The document states this demonstrates "equivalent performance in comparison to the secondary predicate device."
Identification of Opaque Regions (AI-based) Algorithm:
Agreement with human reads for the percentage of opacity (PO) on a lung lobe level, established through 95%-Limits of Agreement (LoA). Compared against a "secondary predicate device."	93.0% of the PO values were found within the 95%-Limits of Agreement (LoA) established when comparing the algorithm's performance against human reads. This indicates a strong agreement with human expert assessment. The document states this demonstrates "equivalent performance in comparison to the secondary predicate device." Additionally, "consistent performance has been found for both algorithms across all subgroups" when additional analysis was performed for population-specific subgroups and various technical parameters.
Overall equivalent performance to the secondary predicate device for segmentation and lung parenchyma categorization.	The detailed performance metrics (DICE coefficients and % within LoA) are presented as evidence of this equivalence.
Conformance with special controls for medical devices containing software.	Non-clinical tests (integration and functional) were conducted and found acceptable.
Meeting voluntary standards listed in the document.	Siemens certifies the device will meet standards such as DICOM, IEC 62304, ISO 14971, and IEC 62366-1.

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

Lung Lobe Segmentation Test Set Size: 250 datasets
Identification of Opaque Regions Test Set Size: 150 datasets
Data Provenance: "multiple sites across the US and Europe." The document implicitly suggests these are retrospective, as they are referred to as "clinical data."

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

The document states that the ground truth for the "Identification of opaque regions" algorithm's validation was established by "human reads" which were then used to assess "inter-reader variability" and establish "95%-Limits of Agreement (LoA)." However, the number of experts and their specific qualifications (e.g., number of years of experience, specific subspecialty) are not explicitly stated in the provided text. It can be inferred that these were qualified medical professionals, given the context of "human reads" for diagnostic imagery, but specific details are missing.

4. Adjudication Method for the Test Set

The document mentions "inter-reader variability" was assessed for the opaque region identification, implying that multiple human readers provided assessments. However, the specific adjudication method (e.g., 2+1, 3+1 consensus, averaging, etc.) used to establish the final ground truth from these multiple readers, or how the comparison to "human reads" was performed beyond establishing LoA, is not explicitly detailed.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

The document mentions assessing "inter-reader variability" of the percentage of opacity against "human reads" and comparing the algorithm's performance to these human reads. This suggests an element of comparing AI output to human performance. However, it does not explicitly describe a traditional MRMC comparative effectiveness study designed to measure the effect size of human readers improving with AI vs. without AI assistance. The study focuses on the standalone performance of the AI compared to human consensus/variability, rather than the "human-in-the-loop" improvement.

6. If a Standalone Study Was Done

Yes, a standalone study was done. The performance metrics (DICE coefficients for segmentation, and percentage of PO values within LoA compared to human reads for opacity detection) represent the performance of the algorithm itself without human intervention in the interpretation of the AI's output for diagnosis. The study validates the algorithm's output against a defined ground truth derived from human experts.

7. The Type of Ground Truth Used

Lung Lobe Segmentation: The ground truth for lung lobe segmentation is developed by "segmentation of lung lobes" using an algorithm similar to a previously cleared device but "trained with more data." The DICE coefficient comparison later implies a ground truth mask against which the algorithm's mask is compared. While not explicitly stated, this would typically involve expert-annotated segmentation masks.
Identification of Opaque Regions: The ground truth for opaque region identification was established through "human reads." This suggests expert consensus or expert interpretation as the basis for the ground truth. "Inter-reader variability" was also assessed, further supporting expert-derived ground truth.

8. The Sample Size for the Training Set

The document states that the lung segmentation algorithm has been "trained with more data" than the secondary predicate device and mentions a "Training cohort: size and properties of data used for training." However, the specific sample size for the training set is not provided in the excerpt.

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

The document mentions a section for "Description of ground truth / annotations generation" for the training cohort. However, the specific details of how the ground truth for the training set were established are not provided in this excerpt. It is only generally mentioned that there was a description of its generation. Given the nature of the algorithms, it would typically involve expert manual annotation or labelling of images.

Summary

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April 30, 2021

Image /page/0/Picture/1 description: The image contains the logos of the Department of Health & Human Services and the U.S. Food & Drug Administration (FDA). The Department of Health & Human Services logo is on the left, featuring a stylized emblem. To the right is the FDA logo, with the letters 'FDA' in a blue square, followed by 'U.S. FOOD & DRUG' and 'ADMINISTRATION' in blue text.

Siemens Medical Solutions USA, Inc. % Alaine Medio Regulatory Affairs Professional 810 Innovation Drive KNOXVILLE TN 37932

Re: K203699

Trade/Device Name: syngo.CT Extended Functionality Regulation Number: 21 CFR 892.1750 Regulation Name: Computed tomography x-ray system Regulatory Class: Class II Product Code: JAK Dated: March 29, 2021 Received: March 30, 2021

Dear Alaine Medio:

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/cfpmp/bmn.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 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

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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 medical devices and radiation-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,

Michael D. O'Hara
For

Thalia T. Mills, Ph.D. Director Division of Radiological Health OHT7: Office of In Vitro Diagnostics and 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) K203699

Device Name syngo.CT Extended Functionality

Indications for Use (Describe)

An interface shall enable the connection between the syngo.CT Extended Functionality software package and the interconnected CT Scanner system.

Resulting images created with the syngo.CT Extended Functionality software package can be used to assist trained technicians or physicians in diagnosis.

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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K203699 510(k) Summary FOR syngo.CT Extended Functionality

Identification of the Submitter

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:

Alaine Medio Regulatory Affairs Specialist Siemens Medical Solutions, Inc. USA 810 Innovation Drive Knoxville, TN 37932 Phone: (865) 206-0337 Fax: (865) 218-3019 Email: alaine.medio@siemens-healthineers.com

II. Device Name and Classification

Product Name:	syngo.CT Extended Functionality
Propriety Trade Name:	syngo.CT Extended Functionality
Classification Name:	Computed Tomography X-ray System
Classification Panel:	Radiology
CFR Section:	21 CFR §892.1750
Device Class:	Class II
Product Code:	JAK

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lll. Predicate Device

Primary Predicate Device

Trade Name:	syngo.CT Extended Functionality
510(k) Number:	K192402
Clearance Date:	09/20/2019
Classification Name:	Computed Tomography X-ray System
Classification Panel:	Radiology
CFR Section:	21 CFR §892.1750
Device Class:	Class II
Product Code:	JAK

Secondary Predicate Device

Trade Name:	Al-Rad Companion (Pulmonary)
510(k) Number:	K183271
Clearance Date:	07/26/2019
Classification Name:	Computed Tomography X-ray System
Classification Panel:	Radiology
CFR Section:	21 CFR §892.1750
Device Class:	Class II
Product Code:	JAK

Reference Device

Trade Name:	syngo.CT Pulmo 3D
510(k) Number:	K123540
Clearance Date:	08/29/2013
Classification Name:	Computed Tomography X-ray System
Classification Panel:	Radiology
CFR Section:	21 CFR §892.1750
Device Class:	Class II
Product Code:	JAK

IV. Device Description

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V. Indications for Use

An interface shall enable the connection between the syngo.CT Extended Functionality software package and the interconnected CT Scanner system.

Resulting images created with the syngo.CT Extended Functionality software package can be used to assist trained technicians or physicians in diagnosis.

Comparison of Technological Characteristics with the Predicate Device VI.

The differences and similarities between the above referenced predicate device are listed at a highlevel in the following table:

Feature	Subject Device	Primary Predicate Device	Secondary Predicate Device
	syngo.CT ExtendedFunctionality(SOMARIS/8 VB51)	syngo.CT ExtendedFunctionality(SOMARIS/8 VB40)	Al-Rad Companion(Pulmonary)(VA10)
1. Pulmonary Density
- Segmentation ofLung	Creation of a lungsegmentation mask bycombining thesegmentation masks of 5lung lobes.The same algorithm ascleared with the secondarypredicate device has beentrained with more data.	N/A	The device's algorithmcreates a lung segmentationmask by combining thesegmentation masks of 5lung lobes.
- Segmentation ofLobes	Computation ofsegmentation masks of thefive lung lobes (right upper(RUL), right middle (RML),right lower (RLL), left upper(LUL) and left lower (LLL)lobe) for a given CT data setof the chest.The same algorithm ascleared with the secondarypredicate device has beentrained with more data.	N/A	Computation ofsegmentation masks of thefive lung lobes (right upper(RUL), right middle (RML),right lower (RLL), left upper(LUL) and left lower (LLL)lobe) for a given CT data setof the chest.
- Opacity Detection	Al-based identification ofareas with elevatedHounsfield values.Threshold-basedidentification of highestelevated Hounsfield valuesinside these elevatedregions, by a predefinedthreshold of -200 HU.	N/A	Secondary predicate device(Al-Rad Companion(Pulmonary)):Identification of areas withlower Hounsfield valuesinside both lungs incomparison to a predefinedthreshold of -950 HU.
Feature	Subject Device	Primary Predicate Device	Secondary Predicate Device
	syngo.CT ExtendedFunctionality(SOMARIS/8 VB51)	syngo.CT ExtendedFunctionality(SOMARIS/8 VB40)	Al-Rad Companion(Pulmonary)(VA10)
	Equivalent to the referencedevice syngo.CT Pulmo 3D(K123540): the areas ofelevated Hounsfield valuesare found by the deeplearning approach asdescribed above instead ofthreshold-based.The threshold-basedsegmentation of highopacity regions is same tothe parenchyma analysisalready cleared with thepredicate device Al-RadCompanion Pulmonary(K183271) and syngo.CTPulmo 3D (K123540).		Reference device (syngo.CTPulmo 3D):Pulmo 3D: Identification ofareas with lower or elevatedHounsfield values insideboth lungs in comparison toa predefined threshold.
- Measurement Results	Lung lesion, lungparenchyma, andpulmonary densitymeasurements (output).The Measurement resultsare unchanged with theexception of displaying thePulmonary Densitymeasurements.	N/A	Lung lesion, lungparenchyma measurements(output).
2. Oncology Extension	The oncology extensionoffers tools for localizationand evaluation of nodulessupporting the followingmain functionalities• Orthogonalmeasurementsof maximum length andwidth of anatomicalstructures• Navigation Tool forLungCAD results• Lung LesionSegmentationMinor modifications to the	The oncology extensionoffers tools for localizationand evaluation of nodulessupporting the followingmain functionalities• Diameter and WHO Area• Lung CAD Series• Lung LesionSegmentation	Al-Rad Companion(Pulmonary) offers tools forlocalization and evaluationof nodules supporting thefollowing mainfunctionalities• Lung CAD Series• Lung LesionSegmentation
	Oncology Extension weremade.

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The remaining functions in Syngo.CT Extended Functionality remain unchanged compared to the predicate version.

Interactive Spectral Imaging Display different representations of Dual Energy data. •
Vascular Extensions - The user can perform a vascular evaluation supporting the following main functionalities: Measuring vessels, Creating DICOM snapshots or result series for

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documenting findings and Working on images that are acquired with CT or MR scanner systems constituting one or more volumes of vascular structures

. Osteo Extension - Evaluation of Bone Mineral Density (BMD) values (mg CA-HA/ml).
Neuro DSA Extension - Selective bone removal from a CT angiography dataset
. ROI HU Threshold Extension – Evaluation of HU Value distributions
. Dual Energy Extension – Simultaneous evaluation for low and high kV dual energy images
Endoscopic Viewing Extension – Interactive fly through tubular structures that are filled by either low-intensity or high-intensity material
. General (Extension Independent features) — Multiphase support for merged 4D series and editing tool for pre-generated results.

The core modification of the subject device as compared to its predicate device (syngo.CT Extended Functionality (SOMARIS/8 VB40)) is the new feature Pulmonary Density.

VII. Performance Data

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

Non-Clinical Testing

This submission contains performance tests (Non-clinical test reports) to demonstrate continued conformance with special controls for medical devices containing software. Non-clinical tests (integration and functional) were conducted for syngo.CT Extended Functionality 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.

Clinical Evaluation of the Al-based Algorithms

Clinical Data Based Software Validation

To validate the syngo.CT Extended Functionality clinical workflow, the following algorithms underwent a scientific evaluation:

. Segmentation of lung lobes
The lung lobe segmentation algorithm computes segmentation masks of the five lung lobes (right upper (RUL), right middle (RML), right lower (RLL), left upper (LUL) and left lower (LLL) lobe) for a given CT data set of the chest.
. Identification of opaque regions (Al-based) The algorithm computes masks of opaque regions in the lung for a given CT data set of the chest. The opaque regions include ground glass opacities, consolidations, and crazy-paving patterns. The calculation is done for each lobe as well as for the complete lung.
For each algorithm of syngo.CT Extended Functionality the analysis is structured as follows:
. Algorithm Description: purpose, functionality, technical description
. Data
- Training cohort: size and properties of data used for training O
- O Description of ground truth / annotations generation

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Validation cohort: size and properties of data used for testing/validation
. Performance
- Choice of performance metric
- Actual performance results
- o Assessment of clinical relevance of achieved performance
. Related clinical research, e.g. publications (if applicable)

The results of clinical data-based software validation for the subject device syngo.CT Extended Functionality demonstrated equivalent performance in comparison to the secondary predicate device for segmentation and lung parenchyma categorization. A complete scientific evaluation report is provided in support of the device modifications.

Performance of lung lobe segmentation of syngo.CT Extended Functionality device has been validated using 250 datasets from multiple sites across the US and Europe. Average DICE coefficients ranged from 0.94 to 0.96.

Performance of the segmentation of opaque regions of syngo.CT Extended Functionality device has been validated using 150 datasets from multiple sites across the US and Europe. Inter-readervariability of the percentage of opacity (PO) was assessed on a lung lobe level and 95%-Limits of Agreement (LoA) were established. The algorithm performance was compared against the human reads and 93.0% of the PO values were found within the LoA.

Additional analysis was performed for both population-specific subgroups and various technical parameters and consistent performance has been found for both algorithms across all subgroups.

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.CT Extended Functionality 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; 62304:2006 (1st Edition)/A1:2016	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.CT Extended Functionality has the same intended use and same indication for use as the primary predicate device. The technological characteristics such as image visualization, operating platform, and image measurement are the same as the predicate devices.

For the subject device, syngo.CT Extended Functionality, Siemens used the same testing with the same workflows as used to clear the primary predicate device. Siemens considers syngo.CT Extended Functionality to be as safe, as effective, and with performance substantially equivalent to the commercially available predicate devices.

Regulation Number and Section

§ 892.1750 Computed tomography x-ray system.

(a)
Identification. A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.