(245 days)
Yes
The summary explicitly mentions "deep learning algorithm" and describes training and test sets, which are characteristic of AI/ML development.
No
The device is described as image processing software that provides analysis to support medical professionals in diagnosis and evaluation, not to directly treat or prevent disease.
Yes
The device is described as software that "supports radiologists and physicians...in the evaluation and assessment of disease of the lungs" and provides "quantitative and qualitative analysis from previously acquired Computed Tomography DICOM images." This indicates its role in assisting in the diagnosis of diseases.
Yes
The device description explicitly states "AI-Rad Companion (Pulmonary) is a software only image processing application". The entire summary focuses on the software's functionality, input data (DICOM images), and performance validation, with no mention of accompanying hardware components being part of the device itself.
Based on the provided information, this device is not an In Vitro Diagnostic (IVD).
Here's why:
- IVDs analyze samples taken from the human body. The definition of an IVD typically involves the examination of specimens such as blood, urine, tissue, or other bodily fluids.
- This device analyzes images of the human body. The input is explicitly stated as "Computed Tomography DICOM images," which are medical images, not biological samples.
- The intended use is image processing and analysis. The software processes pre-acquired CT images to provide quantitative and qualitative analysis of the lungs.
While the device is a medical device that aids in diagnosis and assessment of disease, it does so by analyzing imaging data, not by performing tests on biological specimens. Therefore, it falls under the category of medical imaging software, not an In Vitro Diagnostic.
No
The provided text does not contain any explicit statement that the FDA has reviewed, approved, or cleared a PCCP for this specific device. The term "PCCP" is mentioned only in the context of a section title "Control Plan Authorized (PCCP)" with "Not Found" as its content, which does not indicate authorization.
Intended Use / Indications for Use
AI-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 predefined 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.
The software has been validated for data from Siemens (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.
Product codes
JAK, LLZ
Device Description
AI-Rad Companion (Pulmonary) is a software only image processing application that supports quantitative and qualitative analysis of previously acquired CT DICOM Images to support radiologists and physicians from emergency medicine, specialty care, and general practice in the evaluation of and assessment of disease of the thorax.
As an update to the previously cleared predicate devices, the following modifications have been made:
- Software version VA10A, including the following features:
- Segmentation of the lung (modified)
- Segmentation of lung lobes based on deep learning algorithm (modified)
- Parenchyma evaluation (modified)
- Lesion segmentation (modified)
- Subject device claims list
The subject device AI-Rad Companion (Pulmonary) is an image processing software that provides quantitative and qualitative analysis from previously acquired Tomography DICOM images to support qualified clinicians in the evaluation and assessment of disease of the thorax. The subject device supports the following device specific functionality:
- Segmentation and volume measurements of complete lung and lung lobes
- Identification of areas with lower Hounsfield values in comparison to a predefined threshold for complete lung and lung lobes
- Detection of solid pulmonary nodules with the assistance of LungCAD (K143196, clearance date 05/12/2015) and dedication to lung lobe
- Segmentation and measurements of identified lung lesions
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes (deep learning algorithm)
Input Imaging Modality
Computed Tomography DICOM images
Anatomical Site
lungs, thorax
Indicated Patient Age Range
adult patients
Intended User / Care Setting
radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice
Description of the training set, sample size, data source, and annotation protocol
Not Found
Description of the test set, sample size, data source, and annotation protocol
Performance of lung lobe segmentation of AI-Rad Companion.Pulmonary device has been validated in a retrospective performance study (n>4,500 CT data sets from multiple clinical sites from within and outside United States). In this study DICE coefficients, surface metrics and volume error have been computed by comparing the output of the algorithm to the manually established ground truth.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Study Type: Retrospective performance study for lung lobe segmentation
Sample Size: n>4,500 CT data sets
Key Results: The average DICE coefficients for the individual lung lobes ranged between 0.95 and 0.98 with a standard deviation (SD)
§ 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.
0
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July 26, 2019
Siemens Medical Solutions USA, Inc. Kimberly Rendon 40 Liberty Blvd. MALVERN, PA 19355
Re: K183271
Trade/Device Name: AI-Rad Companion (Pulmonary) Regulation Number: 21 CFR 892.1750 Regulation Name: Computed Tomography X-Ray System Regulatory Class: Class II Product Code: JAK, LLZ Dated: June 14, 2019 Received: June 17, 2019
Dear Kimberly Rendon:
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 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-reporting
1
combination-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 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
2
Indications for Use
510(k) Number (if known) K183271
Device Name AI-Rad Companion (Pulmonary)
Indications for Use (Describe)
AI-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 predefined 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.
The software has been validated for data from Siemens (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.
| Type of Use (Select one or both, as applicable) | |
|---|---|
| Prescription Use (Part 21 CFR 801 Subpart D) | Over-The-Counter Use (21 CFR 801 Subpart C) |
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Image /page/3/Picture/0 description: The image shows the Siemens Healthineers logo. The word "SIEMENS" is in teal, and the word "Healthineers" is in orange. To the right of the word "Healthineers" is a cluster of orange dots.
510(K) SUMMARY AI-RAD COMPANION (PULMONARY) K183271
Submitted by: Siemens Medical Solutions USA, Inc. 40 Liberty Boulevard Malvern, PA 19355 Date Prepared: July 19, 2019
This summary of 510(k) safety and effectiveness information is being submitted in accordance with the requirements of SMDA 1990 and 21 CFR §807.92.
I. Submitter
Importer/Distributor Siemens Medical Solutions USA, Inc. 40 Liberty Boulevard Malvern, PA 19355 Establishment Registration Number 2240869
Manufacturing Site
Siemens Healthcare GmbH Henkestrasse 127 91052 Erlangen, Germany Establishment Registration Number 3004977335
Contact Person
Kimberly Rendon Sr. Manager Regulatory Affairs (610) 448-6480 kimberly.rendon@siemens-healthineers.com
II. Device Name and Classification
| Product Name: | AI-Rad Companion (Pulmonary) |
|---|---|
| Trade Name: | AI-Rad Companion (Pulmonary) |
| Classification Name: | Computed Tomography X-ray System |
| Secondary Classification Name: | Picture Archiving and Communication System |
| Classification Panel: | Radiology |
| CFR Section: | 21 CFR §892.1750 |
| Device Class: | Class II |
| Product Code: | JAK |
| Secondary Product Code: | LLZ |
| III. Predicate Device | |
| Primary Predicate Device: | |
| Product Name: | syngo.CT Pulmo 3D |
| Propriety Trade Name: | syngo CT Pulmo 3D |
510(k) Number: Clearance Date: Classification Name: Secondary Classification Name: Classification Panel: CFR Section:
K123540 August 29, 2013 Computed Tomography X-Ray System Picture Archiving and Communications System Radiology 21 CFR §892.1750
4
Health
Device Class: Class II Primary Product Code: JAK Secondary Product Code: LLZ Recall Information: There are currently no recalls for this device
Secondary Predicate Device:
| Product Name: | syngo.PET&CT Oncology |
|---|---|
| Propriety Trade Name: | syngo.PET&CT Oncology |
| 510(k) Number: | K093621 |
| Clearance Date: | February 23, 2010 |
| Classification Name: | Picture Archiving and Communications System |
| Classification Panel: | Radiology |
| CFR Section: | 21 CFR §892.2050 |
| Device Class: | Class II |
| Primary Product Code: | LLZ |
| Recall Information: | There are currently no recalls for this device |
IV. Device Description
This section described the technical features and workflow for subject device Al-Rad Companion (Pulmonary). Al-Rad Companion (Pulmonary) is a software only image processing application that supports quantitative and qualitative analysis of previously acquired CT DICOM Images to support radiologists and physicians from emergency medicine, specialty care, and general practice in the evaluation of and assessment of disease of the thorax.
As an update to the previously cleared predicate devices, the following modifications have been made:
-
- Software version VA10A, including the following features: 2)
- Segmentation of the lung (modified) a)
- Segmentation of lung lobes based on deep learning algorithm (modified) b)
- Parenchyma evaluation (modified) c)
- Lesion segmentation (modified) d)
-
- Subject device claims list
The subject device AI-Rad Companion (Pulmonary) is an image processing software that provides quantitative and qualitative analysis from previously acquired Tomography DICOM images to support qualified clinicians in the evaluation and assessment of disease of the thorax. The subject device supports the following device specific functionality:
- Segmentation and volume measurements of complete lung and lung lobes ●
- . Identification of areas with lower Hounsfield values in comparison to a predefined threshold for complete lung and lung lobes
- Detection of solid pulmonary nodules with the assistance of LungCAD (K143196, clearance date 05/12/2015) and dedication to lung lobe
- . Segmentation and measurements of identified lung lesions
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Image /page/5/Picture/0 description: The image shows the logo for Siemens Healthineers. The word "SIEMENS" is written in teal, and the word "Healthineers" is written in orange below it. To the right of the words is a graphic of orange dots arranged in a circular pattern.
V. Indications for Use
AI-Rad Companion (Pulmonary) is image processing software that provides quantitative and qualitative analysis from previously acquired 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 predefined 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.
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.
VI. Comparison of Technological Characteristics with the Predicate Device
In comparison the predicate device, the subject devices provide comparable outputs in terms of lung and lung lobe visualization/segmentation and lung lesion segmentation and labeling. A tabular comparison of the subject device and predicate devices is provided as Table 1 below.
| Feature | Subject Device | Predicate Device | Comparison Results |
|---|---|---|---|
| Siemens | |||
| AI-Rad Companion | |||
| (Pulmonary) | Siemens | ||
| syngo.CT Pulmo 3D | |||
| (K123540, clearance | |||
| date 8/29/2013) | |||
| Segmentation of | |||
| lungs | Segmentation of lungs | Segmentation of left / | |
| right lung | Modified | ||
| subject device: segmentation of | |||
| complete lungs | |||
| predicate device: dedicated | |||
| algorithm for segmentation of | |||
| both lungs | |||
| Segmentation of | |||
| lung lobes | Segmentation of lung | ||
| lobes | Segmentation of lung | ||
| thirds, lung core/peel, | |||
| lung lobes | Modified | ||
| subject device: deep learning- | |||
| based algorithm for long lobes | |||
| segmentation | |||
| predicate device: Model-based | |||
| segmentation algorithm | |||
| Parenchyma | |||
| Evaluation | Calculation and | ||
| visualization of lung | |||
| tissue below -950 HU | Calculation and | ||
| visualization of lung | |||
| tissue below threshold | Modified | ||
| Subject device: fixed threshold | |||
| for segmentation | |||
| Predicate device: Configurable | |||
| threshold for segmentation |
Table 1: Predicate Device Comparable Properties
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Image /page/6/Picture/0 description: The image shows the Siemens Healthineers logo. The word "SIEMENS" is in teal, and the word "Healthineers" is in orange. To the right of the word "Healthineers" is a graphic of orange dots arranged in a circular pattern.
| Feature | Subject Device | Predicate Device | Comparison Results |
|---|---|---|---|
| Visualization of segmentation and parenchyma results | Siemens AI-Rad Companion (Pulmonary) | Siemens syngo.CT Pulmo 3D (K123540, clearance date 8/29/2013) | Same |
| Interface to LungCAD | Siemens AI-Rad Companion (Pulmonary) | Siemens syngo.PET&CT Oncology (K093621, clearance date 02/23/2010) | Same |
| Lesion Segmentation | Segmentation of lung lesions | Segmentation of lesions of the lung, liver, and lymph nodes | Modified |
| subject device: segmentation of lung lesions and localization of found lesion to lung lobe | |||
| predicate device: segmentation of lesions of lung, liver, lymph nodes, and general anatomies | |||
| Visualization of lesion segmentation results | Color overlay of MPR and VRT with evaluation results | Color overlay of MPR and VRT with evaluation results | Same |
The subject device modifications referenced above do not raise different questions of safety or effectiveness in comparison to the predicate devices.
VII. Performance Data
Non-Clinical Testing Summary
Performance tests were conducted to test the functionality of AI-Rad Companion (Pulmonary). Software validations, bench testing, and clinical data-based software validations have been conducted to the performance claims as well as the claim of substantial equivalence to the predicate devices. Al-Rad Companion has been tested to meet the requirements of conformity to multiple industry standards. Nonclinical performance testing demonstrated that AI-Rad Companion complies with the following voluntary FDA recognized Consensus Standards listed in Table 2 on the next page:
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Image /page/7/Picture/0 description: The image shows the logo for Siemens Healthineers. The word "SIEMENS" is written in teal, and the word "Healthineers" is written in orange below it. To the right of the word "Healthineers" is a cluster of orange dots.
| Recognition
Number | Product
Area | Title of Standard | Publication
Date | Standards
Development
Organization |
|-----------------------|--------------------------|------------------------------------------------------------------------------------------------------------|---------------------|------------------------------------------|
| 12-300 | Radiology | Digital Imaging and Communications in
Medicine (DICOM) Set; PS 3.1 – 3.20 | 06/27/2016 | NEMA |
| 13-32 | Software | Medical Device Software -Software Life
Cycle Processes; 62304:2006 (1st Edition) | 08/20/2012 | AAMI, ANSI,
IEC |
| 5-40 | Software/
Informatics | Medical devices – Application of risk
management to medical devices: 14971
Second Edition 2007-03-01 | 08/20/2012 | ISO |
| 5-95 | General I
(QS/RM) | Medical devices - Part 1: Application of
usability engineering to medical devices
IEC 62366-1:2015 | 06/27/2016 | IEC |
Table 2: Voluntary Conformance Standards
Verification and Validation
Software Documentation for a Moderate 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, and "Off-The-Shelf Software Use in Medical Devices" is also included as part of this submission. The performance data demonstrates continued conformance with special controls for medical devices containing software. Non-clinical tests were conducted on the Subject Device AI-Rad Companion (Pulmonary) software version VA10 during product development.
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 for the device was found acceptable to support the claims of substantial equivalence.
Bench testing in the form of Unit, Subsystem and System Integration testing were performed to evaluate the performance and functionality of the new features and software updates. All testable requirements in the Engineering Requirements Specifications keys, Subsystem Requirements Specifications keys, and the Risk Management Hazard keys have been successfully verified and traced in accordance with the Siemens product development (lifecycle) process. The software verification and regression testing have been performed successfully to meet their previously determined acceptance criteria as stated in the test plans. Electrical safety and EMC testing requirements are addressed as part of the host system (CT device or PACS system) to ensure compliance with the application IEC standards.
Siemens conforms to the cybersecurity requirementing a process of preventing unauthorized access, modifications, misuse or denial of use, or the unauthorized use of information that is stored, accessed or transferred from a medical device to an external recipient. Provided in this submission is a cybersecurity statement that considers IEC 80001-1:2010. The responsibility for compliance with IEC 80001-1-2010 is the hospital.
Clinical Data Based Software Validation
To validate the AI-Rad Companion (Pulmonary) 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 lobe (LLL) for a given CT data set of the chest.
- . Evaluation of the lung parenchyma
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Image /page/8/Picture/0 description: The image shows the Siemens Healthineers logo. The word "SIEMENS" is in teal, and the word "Healthineers" is in orange. To the right of the word "Healthineers" is a cluster of orange dots.
The algorithm receives a 3D CT data set and binary masks of the segmented lung lobes. It computes, the ratio of voxels below -950 HU (%LAV950) each lobe as well as for the complete lung.
For each algorithm of AI-Rad Companion the analysis is structured as follows:
- Algorithm Description: purpose, functionality, technical description ●
- . Data
- Training cohort: size and properties of data used for training O
- Description of ground truth / annotations generation O
- Validation cohort: size and properties of data used for testing/validation o
- Performance ●
- Choice of performance metric O
- Actual performance results O
- Assessment of clinical relevance of achieved performance O
- Related clinical research, e.g. publications (if applicable) .
The results of clinical data-based software validation for the subject device Al-Rad Companion (Pulmonary) demonstrated superior performance in comparison to the primary predicate device for segmentation. A complete scientific evaluation report is provided in support of the device modifications.
Performance of lung lobe segmentation of AI-Rad Companion.Pulmonary device has been validated in a retrospective performance study (n>4,500 CT data sets from multiple clinical sites from within and outside United States). In this study DICE coefficients, surface metrics and volume error have been computed by comparing the output of the algorithm to the manually established ground truth. The average DICE coefficients for the individual lung lobes ranged between 0.95 and 0.98 with a standard deviation (SD)