Al-Rad Companion (Pulmonary) is image processing software that provides quantitative and qualitative analysis from previously acquired Computed Tomography DICOM images to support radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice in the evaluation and assessment of disease of the lungs. It provides the following functionality:

· Segmentation and measurements of complete lung and lung lobes

· Identification of areas with lower Hounsfield values in comparison to a predetined threshold for complete lung and lung lobes

· Providing an interface to external Medical Device syngo.CT Lung CAD

· Segmentation and measurements of found lung lesions and dedication to corresponding lung lobe.

· Identification of areas with elevated Hounsfield values. where areas with elevated versus high opacities are distinguished.

The software has been validated for data from Siemens Healthineers (filtered backprojection and iterative reconstruction), GE Healthcare (filtered backprojection reconstruction), and Philips (filtered backprojection reconstruction).

Only DICOM images of adult patients are considered to be valid input.

Device Description

Al-Rad Companion is a software only medical system that investigates data from imaging systems. Al-Rad Companion receives these data and checks which post-processing algorithms may be applicable. Data that does not meet the Al-Rad Companion requirements are ignored while data that meets the requirements are sent for further processing. Applicable data are processed, and the results are provided to the user via their clinical workplace. The user has the option to accept, review or withdraw single results of Al-Rad Companion.

Al-Rad Companion includes a software operating platform (Al-Rad Companion (Engine)) and optional clinical extensions such as Al-Rad Companion (Pulmonary), Al-Rad Companion (Musculoskeletal) and Al-Rad Companion (Cardiovascular). The clinical extensions are post-processing applications that operate on the Al-Rad Companion (Engine) software platform and process CT datasets in specific regions of the thorax or use datasets from other modalities. The basic post-processing functions are landmark detection, segmentation, and classification. Al-Rad Companion uses Artificial Intelligence (Al)algorithms.

The Al-Rad Companion (Engine) platform is the interface for incoming and outgoing data for the complete Al-Rad Companion system that provides input data and collects results and status information from the extensions. Additionally, it is the interface for incoming and outgoing data for the complete Al-Rad Companion system.

The scope of this submission is the extension Al-Rad Companion (Pulmonary). It is an image postprocessing software that uses CT DICOM data to support clinicians in the evaluation and assessment of lung diseases. It utilizes machine-learning and deep-learning algorithms to provide quantitative and qualitative analysis from previously acquired Computed Tomography DICOM images to support qualified clinicians in the evaluation and assessment of disease of the major functionalities of Al-Rad Companion (Pulmonary) are as follows:

Segmentation and measurements of complete lung, lungs, and lung lobes.
ldentification of areas with lower Hounsfield values in comparison to a predefined threshold for . complete lung and lung lobes.
. Segmentation and measurements of found lung lesions
. Identification of areas with elevated Hounsfield values, where areas with elevated versus high opacities are distinguished

The results will be delivered in different image formats and, depending on the configuration, can be verified in the Results Preview and will be included in the overview with all findings. This will include DICOM Structured Report with measurements results

The software version VA13 of the Al-Rad Companion (Pulmonary) includes the following modifications:

Pulmonary Density: This feature provides the possibility to segment opacity regions inside the lung using an Al algorithm. Al-Rad Companion (Pulmonary) 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, the opacity results are assigned to a certain range as defined by Bernheim et al.
Bi-directional lesion diameter: This feature provides an additional measurement derived from the existing segmentation contour of a lung lesion. The existing list of measurements is extended with the maximum orthogonal diameter in 2D (short axis diameter) which is orthogonal to the lesion's maximum 2D diameter (2D diameter, long axis diameter).
Cloud and Edge Deployment: The system supports the existing cloud deployment as well as a new edge deployment. The system remains hosted in the teamplay digital health platform and remains driven by the Al-Rad Companion (Engine). Now the edge deployment allows the processing of clinical data and the generation of results on-premises within the customer network. The edge system is fully connected to the cloud for monitoring and maintenance of the system from remote.

AI/ML Overview

Here's a breakdown of the acceptance criteria and study details for Al-Rad Companion (Pulmonary) based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

Feature/Metric	Acceptance Criteria (Implied)	Reported Device Performance
Lung Lobe Segmentation	Clinically acceptable segmentation accuracy and equivalence to predicate.	Average DICE coefficients ranged from 0.94 to 0.96 (for 250 datasets from US and Europe). "Demonstrated equivalent performance in comparison to the primary predicate device for segmentation." Consistency across population-specific subgroups and technical parameters.
Opacity Detection (PO values)	Clinically acceptable agreement with human reads during inter-reader variability assessment and equivalence to predicate.	95%-Limits of Agreement (LoA) were established against human reads. 93.0% of the PO (percentage of opacity) values were found within the LoA (for 150 datasets from US and Europe). "Demonstrated equivalent performance in comparison to the primary predicate device for lung parenchyma categorization." Consistency across population-specific subgroups and technical parameters.
Overall Software Performance	Device performs as intended, all software specifications met.	Non-clinical tests (integration and functional) were conducted, and the results "demonstrate that the subject device performs as intended." "The results of all conducted testing was found acceptable to support the claim of substantial equivalence." "The risk analysis was completed, and risk control implemented to mitigate identified hazards. The testing results demonstrate 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."

Note: The document mainly focuses on proving substantial equivalence to a predicate device, thus the "acceptance criteria" are implied to be achieving performance comparable to, or improving upon, the predicate. Specific numerical thresholds for acceptance criteria are not explicitly stated, but are inferred from the reported performance which is deemed acceptable for substantial equivalence.

2. Sample Size for the Test Set and Data Provenance

Lung Lobe Segmentation: 250 datasets
Opacity Detection: 150 datasets
Data Provenance: Multiple sites across the US and Europe. The document states this was a "Clinical Data Based Software Validation." It does not explicitly state if it was retrospective or prospective, but clinical validation of existing images typically suggests a retrospective approach.

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

The document does not specify the number of experts or their qualifications for establishing ground truth for the test set. It mentions "human reads" for comparison in the opacity detection study, implying human experts were involved, but details are not provided.

4. Adjudication Method for the Test Set

The document does not explicitly state the adjudication method (e.g., 2+1, 3+1, none) used for the test set. For opacity detection, "Interreader-variability of the percentage of opacity (PO) was assessed" against "human reads," but the specific process of how those "human reads" were finalized as ground truth is not detailed.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No multi-reader multi-case (MRMC) comparative effectiveness study demonstrating human readers improve with AI vs. without AI assistance is explicitly described. The studies focus on the standalone performance of the AI algorithm against human reads or a "primary predicate device."

6. Standalone (Algorithm Only) Performance Study

Yes, a standalone performance study was done. The "Clinical Evaluation of the AI-based Algorithms" section details the validation of the lung lobe segmentation and opacity detection algorithms. The reported DICE coefficients and the LoA for PO values are measures of the algorithm's performance independent of human-in-the-loop interaction in the context of the reported studies.

7. Type of Ground Truth Used

The ground truth used for the opacity detection algorithm was based on "human reads" during an inter-reader variability assessment. For lung lobe segmentation, while not explicitly stated, it is commonly established through expert annotations. The phrasing "Description of ground truth / annotations generation" indicates that such ground truth was generated, likely by experts.

8. Sample Size for the Training Set

The document mentions "Training cohort: size and properties of data used for training" under the "Clinical Data Based Software Validation" section but does not provide the specific sample size for the training set. It states "Additional training data was added as compared to the primary predicate for the Pulmonary Density Feature."

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

The document states "Description of ground truth / annotations generation" for the training cohort, implying that ground truth was established through annotations, most likely by clinical experts. However, specific details about the process (e.g., number of annotators, their qualifications, adjudication) are not provided for the training set.

Summary

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December 6, 2021

Image /page/0/Picture/1 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' in blue, with 'ADMINISTRATION' written below in a smaller font.

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

Re: K213096

Trade/Device Name: Al-Rad Companion (Pulmonary) Regulation Number: 21 CFR 892.1750 Regulation Name: Computed tomography x-ray system Regulatory Class: Class II Product Code: JAK Dated: September 23, 2021 Received: September 24, 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/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 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for

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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 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,

, 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) K213096

Device Name AI-Rad Companion (Pulmonary)

Indications for Use (Describe)

· Segmentation and measurements of complete lung and lung lobes

· Identification of areas with lower Hounsfield values in comparison to a predetined threshold for complete lung and lung lobes

· Providing an interface to external Medical Device syngo.CT Lung CAD

· Segmentation and measurements of found lung lesions and dedication to corresponding lung lobe.

· Identification of areas with elevated Hounsfield values. where areas with elevated versus high opacities are distinguished.

Only DICOM images of adult patients are considered to be valid input.

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

Prepared December 01, 2021

l. 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

Secondary Contact Person:

Tabitha Estes Regulatory Affairs Specialist Phone: (865) 804-4553 Email: Tabitha.estes@siemens-healthineers.com

II. Device Name and Classification

Product Name:	Al-Rad Companion (Pulmonary)
Propriety Trade Name:	Al-Rad Companion (Pulmonary)
Classification Name:	Computed Tomography X-ray System
Classification Panel:	Radiology

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CFR Section:	21 CFR §892.1750
Device Class:	Class II
Product Code:	JAK

Predicate Device III.

Primary 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, LLZ

Secondary Predicate Device:

Trade Name:	syngo.CT Extended Functionality
510(k) Number:	K203699
Clearance Date:	04/30/2021
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

The Al-Rad Companion (Engine) platform is the interface for incoming and outgoing data for the complete Al-Rad Companion system that provides input data and collects results and status information

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from the extensions. Additionally, it is the interface for incoming and outgoing data for the complete Al-Rad Companion system.

The Al-Rad Companion extensions are optional post-processing applications that operate on the Al-Rad Companion (Engine) software platform. The platform and each of the extensions are distinct software components and thus separate medical devices. A pictorial representation of the interaction between the Al-Rad Companion (Engine) and optional Al-Rad Companion extensions is provided in the figure below.

Image /page/5/Figure/2 description: The image shows a diagram of the AI-Rad Engine platform. The platform has an input and output, and several extensions, including AI-Rad Pulmonary, AI-Rad Cardiovascular, and AI-Rad Musculoskeletal. There is also a confirmation window/result preview box on top of the AI-Rad Engine platform. The AI-Rad Pulmonary extension is highlighted with a red box.

Segmentation and measurements of complete lung, lungs, and lung lobes.
ldentification of areas with lower Hounsfield values in comparison to a predefined threshold for . complete lung and lung lobes.
. Segmentation and measurements of found lung lesions
. Identification of areas with elevated Hounsfield values, where areas with elevated versus high opacities are distinguished

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The software version VA13 of the Al-Rad Companion (Pulmonary) includes the following modifications:

● Pulmonary Density

This feature provides the possibility to segment opacity regions inside the lung using an Al algorithm. Al-Rad Companion (Pulmonary) 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, the opacity results are assigned to a certain range as defined by Bernheim et al.

This feature has been cleared with the secondary predicate device syngo.CT Extended Functionality VB51 (K203699, clearance date 04/30/2021). It is a reuse from the predicate device to this subject device. The feature and its algorithms remain unchanged from this predicate device.

● Bi-directional lesion diameter

This feature provides an additional measurement derived from the existing segmentation contour of a lung lesion. The existing list of measurements is extended with the maximum orthogonal diameter in 2D (short axis diameter) which is orthogonal to the lesion's maximum 2D diameter (2D diameter, long axis diameter).

This feature has been cleared with the secondary predicate device syngo.CT Extended Functionality VB51 (K203699). It is a reuse from the predicate device to this subject device. For this feature, no modifications are required to the detection nor the segmentation of the lung lesions.

. Cloud and Edge Deployment

The system supports the existing cloud deployment as well as a new edge deployment. The system remains hosted in the teamplay digital health platform and remains driven by the Al-Rad Companion (Engine). Now the edge deployment allows the processing of clinical data and the generation of results on-premises within the customer network. The edge system is fully connected to the cloud for monitoring and maintenance of the system from remote.

V. Indications for Use

lt provides the following functionality:

Segmentation and measurements of complete lung and lung lobes
ldentification of areas with lower Hounsfield values in comparison to a predefined threshold for complete lung and lung lobes
. Providing an interface to external Medical Device syngo.CT Lung CAD

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Segmentation and measurements of found lung lesions and dedication to corresponding lung lobe
Identification of areas with elevated Hounsfield values, where areas with elevated versus high opacities are distinguished

Only DICOM images of adult patients are considered to be valid input.

Comparison of Technological Characteristics with the Predicate Device VI.

The comparison between the above referenced predicate devices is listed in the following table. It compares each feature of the subject device either with the primary predicate device or the secondary predicate device.

Subject Device	Primary Predicate Device	Secondary Predicate Device	Comparison
Al-Rad Companion(Pulmonary) VA13A(K213096)	Al-Rad Companion(Pulmonary) VA10A(K183271)	syngo.CT ExtendedFunctionality VB51(K203699)
Segmentation of Lung
Creation of a lungsegmentation mask bycombining the segmentationmasks of 5 lung lobes.	Creation of a lungsegmentation mask bycombining the segmentationmasks of 5 lung lobes.	Creation of a lungsegmentation mask bycombining the segmentationmasks of 5 lung lobes.	The same algorithm as cleared withthe predicate devices is used.Additional training data was addedas compared to the primary predicatefor the Pulmonary Density Feature.This same data and method wereused with the secondary predicatedevice (K203699).
Segmentation of Lobes
Computation of segmentationmasks of the five lung lobes(right upper (RUL), rightmiddle (RML), right lower(RLL), left upper (LUL) and leftlower (LLL) lobe) for a givenCT data set of the chest.	Computation of segmentationmasks of the five lung lobes(right upper (RUL), rightmiddle (RML), right lower(RLL), left upper (LUL) and leftlower (LLL) lobe) for a givenCT data set of the chest.	Computation of segmentationmasks of the five lung lobes(right upper (RUL), rightmiddle (RML), right lower(RLL), left upper (LUL) and leftlower (LLL) lobe) for a givenCT data set of the chest.	This same data and method wereused with the secondary predicatedevice (K203699).
Opacity Detection
Al-based identification ofareas with elevatedHounsfield values. Threshold-based identification ofhighest elevated Hounsfieldvalues inside these elevatedregions, by a predefinedthreshold of -200 HU.	N/A	Al-based identification ofareas with elevatedHounsfield values. Threshold-based identification ofhighest elevated Hounsfieldvalues inside these elevatedregions, by a predefinedthreshold of -200 HU.	The Opacity Detection is the same asthe secondary predicate devicessyngo.CT Extended Functionality(K203699).
Measurement Results
Lung lesion, lungparenchyma, and pulmonarydensity measurements.	Lung lesion, and lungparenchyma measurements.	Pulmonary densitymeasurements.	Extended with Pulmonary Densityresults, as cleared in the secondarypredicate device (syngo.CT ExtendedFunctionality (K203699).
Parenchyma Evaluation
Subject Device	Primary Predicate Device	Secondary Predicate Device	Comparison
Al-Rad Companion(Pulmonary) VA13A(K213096)	Al-Rad Companion(Pulmonary) VA10A(K183271)	syngo.CT ExtendedFunctionality VB51(K203699)
The parenchyma evaluationuses the lobe mask, counts allvoxels per lobe, counts imagevoxels below -950 HU, andcalculates the percentages ofthese voxels relative to thetotal number of voxels.Additionally, it sums theindividual lobe results andcalculates the percentage forthe complete lung.	The parenchyma evaluationuses the lobe mask, counts allvoxels per lobe, counts imagevoxels below -950 HU, andcalculates the percentages ofthese voxels relative to thetotal number of voxels.Additionally, it sums theindividual lobe results andcalculates the percentage forthe complete lung.	N/A	Same as the primary predicate deviceAl-Rad Companion (Pulmonary)VA10A (K183271).
Parenchyma Ranges
The percentages are likewisededicated to the 4 ranges.Name of ranges and theirranges are configurable bythe user.	The percentages are likewisededicated to the 4 ranges.Name of ranges and theirranges are configurable bythe user.	N/A
Visualization of Segmentation and Parenchyma Results
Color overlay of MPR and VRTwith evaluation results.	Color overlay of MPR and VRTwith evaluation results.	N/A
LungCAD Interface
The external device syngo.CTLungCAD is connected.	The external device syngo.CTLungCAD is connected.	The external device syngo.CTLungCAD is connected.	Same as both predicate devices.
Based on the positionsprovided via the LungCADInterface, a segmentation ofsuspicious lung areas isstarted. Within the derivedcontours the maximumdiameter within one slice, the3-dimensional diameter, andthe volume are determined.The lesion is dedicated to alung lobe.Additionally, the maximumorthogonal 2D diameter ismeasured and the mean frommaximum 2D diameter andmaximum orthogonal 2Ddiameter.	Based on the positionsprovided via the LungCADInterface, a segmentation ofsuspicious lung areas isstarted. Within the derivedcontours the maximumdiameter within one slice, the3-dimensional diameter, andthe volume are determined.The lesion is dedicated to alung lobe.	Based on positions providedby the user, a segmentationof suspicious lung areas isstarted. Within the derivedcontours the maximumdiameter within one slice, the3-dimensional diameter, andthe volume are determined.The lesion is dedicated to alung lobe.Additionally, the maximumorthogonal 2D diameter ismeasured and the mean frommaximum 2D diameter andmaximum orthogonal 2Ddiameter is shown.	The Bi-directional lesion diameter isthe same as the secondary predicatedevice syngo.CT ExtendedFunctionality VB51 (K203699).

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Performance Data VII.

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

Non-Clinical Testing

Non-clinical tests (integration and functional) were conducted for Al-Rad Companion (Pulmonary) 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.

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Clinical Evaluation of the Al-based Algorithms

The following activities have been conducted for the syngo.CT Extended Functionality VB51 software application, to evaluate the feature Pulmonary Density which has been introduced with this application. The K-number is K203699 and it has been considered as the secondary predicate device for this submission K213096:

Clinical Data Based Software Validation

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 Pulmonary Density 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
- Validation cohort: size and properties of data used for testing/validation O
Performance
- O Choice of performance metric
- O 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 feature Pulmonary Density demonstrated equivalent performance in comparison to the primary predicate device for segmentation and lung parenchyma categorization.

Performance of lung lobe segmentation of Al-Rad Companion (Pulmonary) 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 Al-Rad Companion Pulmonary device has been validated using 150 datasets from multiple sites across the US and Europe. Interreader-variability 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.

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Risk Analysis

The risk analysis was completed, and risk control implemented to mitigate identified hazards. The testing results demonstrate 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 Al-Rad Companion (Pulmonary) meets the following voluntary standards covering electrical and mechanical safety listed below:

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)	01/14/2019	AAMI, ANSI, IEC
5-125	Software/Informatics	Medical devices – Application of riskmanagement to medical devices; 14971 ThirdEdition 2019-12	12/23/2019	ISO
5-114	General I(QS/RM)	Medical devices - Part 1: Application ofusability engineering to medical devicesIEC 62366-1:2015	12/23/2016	IEC

VIII. Conclusion

Al-Rad Companion (Pulmonary) has the same intended use and similar indication for use 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 as the predicate device that is currently marketed for the same intended use.

For the subject device, Al-Rad Companion (Pulmonary) VA13, Siemens used the same testing with the same workflows as used to clear the predicate device in addition to the clinical evaluation. Siemens considers Al-Rad Companion (Pulmonary) version VA13 to be as safe, as effective and with performance substantially equivalent to the commercially available predicate device.

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.