(114 days)
Yes
The device description explicitly states that "two new algorithms utilizing deep learning technology were introduced." Deep learning is a subset of machine learning.
No
The device is a CT image analysis software package for assessing liver morphology and changes over time, providing visualization and quantitative analysis, but it does not directly treat or cure any medical condition.
Yes
Explanation: The "Intended Use / Indications for Use" section states that Hepatic VCAR is "designed for the purpose of assessing liver morphology, including liver lesion...and its change over time" and "will assist the user by providing initial 3D segmentation, visualization, and quantitative analysis of liver anatomy." This indicates its use in identifying and quantifying medical conditions, which falls under the definition of a diagnostic device.
Yes
The device is described as a "CT image analysis software package" and a "post processing software medical device." While it is deployed on hardware platforms like AW and CT Scanners, the core functionality and the device itself are presented as software for analyzing existing image data.
Based on the provided information, this device is not an IVD (In Vitro Diagnostic).
Here's why:
- IVD devices are used to examine specimens derived from the human body (like blood, urine, tissue) in vitro (outside the body) to provide information for diagnosis, monitoring, or screening.
- This device analyzes in vivo (within the body) imaging data (CT scans) of the liver. It processes and visualizes images obtained directly from the patient.
The device's function is image analysis and visualization of medical images, which falls under the category of medical imaging software, not in vitro diagnostics.
No
The clearance letter does not explicitly state that the FDA has reviewed and approved or cleared a Predetermined Change Control Plan (PCCP) for this specific device. The 'Control Plan Authorized (PCCP) and relevant text' section is marked 'Not Found'.
Intended Use / Indications for Use
Hepatic VCAR is a CT image analysis software package that allows the analysis and visualization of Liver CT data derived from DICOM 3.0 compliant CT scans. Hepatic VCAR is designed for the purpose of assessing liver morphology, including liver lesion, provided the lesion has different CT appearance from surrounding liver tissue; and its change over time through automated tools for liver lobe, liver segments and liver lesion segmentation and measurement. It is intended for use by clinicians to process, review, archive, print and distribute liver CT studies.
This software will assist the user by providing initial 3D segmentation, visualization, and quantitative analysis of liver anatomy. The user has the ability to adjust the contour and confirm the final segmentation.
Product codes (comma separated list FDA assigned to the subject device)
JAK, LLZ
Device Description
Hepatic VCAR is a CT image analysis software package that allows the analysis and visualization of Liver CT data derived from DICOM 3.0 compliant CT scans. Hepatic VCAR was designed for the purpose of assessing liver morphology, including liver lesion, provided the lesion has different CT appearance from surrounding liver tissue; and its change over time through automated tools for liver, liver lobe, liver segments and liver lesion segmentation and measurement.
Hepatic VCAR is a post processing software medical device built on the Volume Viewer (K041521) platform, and can be deployed on the Advantage Workstation (AW) (K110834) and AW Server (K081985) platforms, CT Scanners, and PACS stations or cloud in the future.
This software will assist the user by providing initial 3D segmentation, vessel analysis, visualization, and quantitative analysis of liver anatomy. The user has the ability to adjust the contour and confirm the final segmentation.
In the proposed device, two new algorithms utilizing deep learning technology were introduced. One such algorithm segments the liver producing a liver contour editable by the user; another algorithm segments the hepatic artery based on an initial user input point. The hepatic artery segmentation is also editable by the user.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
CT
Anatomical Site
Liver
Indicated Patient Age Range
Not Found
Intended User / Care Setting
clinicians
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
Not Found
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Bench tests that compare the output of the two new algorithms with ground truth annotated by qualified experts show that the algorithms performed as expected.
A representative set of clinical sample images was assessed by 3 board certified radiologists using 5-point Likert scale. The assessment demonstrated that capability of liver segmentation and hepatic artery segmentation utilizing the deep learning algorithm by Hepatic VCAR.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Not Found
Predicate Device(s): If the device was cleared using the 510(k) pathway, identify the Predicate Device(s) K/DEN number used to claim substantial equivalence and list them here in a comma separated list exactly as they appear in the text. List the primary predicate first in the list.
Reference Device(s): Identify the Reference Device(s) K/DEN number and list them here in a comma separated list exactly as they appear in the text.
Predetermined Change Control Plan (PCCP) - All Relevant Information for the subject device only (e.g. presence / absence, what scope was granted / cleared under the PCCP, any restrictions, etc).
Not Found
§ 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
Image /page/0/Picture/10 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left, there is a symbol that appears to be a stylized representation of human figures or faces. To the right of this symbol, there is a blue square with the letters 'FDA' in white. Next to the blue square, the words 'U.S. FOOD & DRUG' are written in a bold, blue font, with the word 'ADMINISTRATION' appearing below in a smaller font size.
GE Medical Systems SCS % Lifeng Wang Regulatory Affairs Manager 283 rue de la Miniere 78530 Buc FRANCE
March 20, 2020
Re: K193281
Trade/Device Name: Hepatic VCAR Regulation Number: 21 CFR 892.1750 Regulation Name: Computed tomography x-ray System Regulatory Class: Class II Product Code: JAK, LLZ Dated: February 19, 2020 Received: February 20, 2020
Dear Lifeng Wang:
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 and Part 809); medical device reporting of medical device-related adverse events) (21 CFR
1
- 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
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
2
Indications for Use
510(k) Number (if known)
Device Name
Hepatic VCAR
Indications for Use (Describe)
Hepatic VCAR is a CT image analysis software package that allows the analysis and visualization of Liver CT data derived from DICOM 3.0 compliant CT scans. Hepatic VCAR is designed for the purpose of assessing liver morphology, including liver lesion, provided the lesion has different CT appearance from surrounding liver tissue; and its change over time through automated tools for liver lobe, liver segments and liver lesion segmentation and measurement. It is intended for use by clinicians to process, review, archive, print and distribute liver CT studies.
This software will assist the user by providing initial 3D segmentation, visualization, and quantitative analysis of liver anatomy. The user has the ability to adjust the contour and confirm the final segmentation.
| Type of Use (Select one or both, as applicable) | |
|---|---|
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510(k) Summary
In accordance with 21 CFR 807.92 the following summary of information is provided:
| Date: | Nov 26, 2019 | ||||
|---|---|---|---|---|---|
| Submitter: | GE Medical Systems SCS (Establishment Registration Number – 9611343) | ||||
| 283 rue de la Miniere | |||||
| 78530 Buc, France | |||||
| Primary Contact | |||||
| Person: | Lifeng Wang | ||||
| Regulatory Affairs Manager | |||||
| GE Healthcare | |||||
| Phone: +86 10 57083145 | |||||
| Email: lifeng.wang@ge.com | |||||
| Secondary Contact | |||||
| Person: | Elizabeth Mathew | ||||
| Senior Regulatory Affairs Manager | |||||
| GE Healthcare | |||||
| Phone: (262) 424-7774 | |||||
| Email: Elizabeth.Mathew@ge.com | |||||
| Proposed Device | > Device Name: Hepatic VCAR | ||||
| > Regulation number/ Product Code: 21 CFR 892.1750 Computed tomography | |||||
| x-ray system / JAK | |||||
| > Secondary Regulation number/ Product Code: 21 CFR 892.2050 Picture | |||||
| archiving and communications system/ LLZ | |||||
| > Classification: Class II | |||||
| Predicate Device: | > Device Name: Hepatic VCAR | ||||
| > 510(k) number: K133649 | |||||
| > Regulation number/ Product Code: 21 CFR 892.1750 Computed tomography | |||||
| x-ray system / JAK | |||||
| > Secondary Regulation number/ Product Code: 21 CFR 892.2050 Picture | |||||
| archiving and communications system/ LLZ | |||||
| > Classification: Class II | |||||
| Device Description | Hepatic VCAR is a CT image analysis software package that allows the analysis | ||||
| and visualization of Liver CT data derived from DICOM 3.0 compliant CT scans. | |||||
| Hepatic VCAR was designed for the purpose of assessing liver morphology, | |||||
| including liver lesion, provided the lesion has different CT appearance from | |||||
| surrounding liver tissue; and its change over time through automated tools for | |||||
| liver, liver lobe, liver segments and liver lesion segmentation and measurement. | |||||
| Hepatic VCAR is a post processing software medical device built on the Volume | |||||
| Viewer (K041521) platform, and can be deployed on the Advantage Workstation |
4
Image /page/4/Picture/1 description: The image shows the General Electric (GE) logo. The logo consists of the letters "GE" in a stylized, cursive font, enclosed within a blue circle. There are three white teardrop shapes surrounding the circle, positioned at the top and on either side.
| | (AW) (K110834) and AW Server (K081985) platforms, CT Scanners, and PACS
stations or cloud in the future.
This software will assist the user by providing initial 3D segmentation, vessel
analysis, visualization, and quantitative analysis of liver anatomy. The user has
the ability to adjust the contour and confirm the final segmentation.
In the proposed device, two new algorithms utilizing deep learning technology
were introduced. One such algorithm segments the liver producing a liver contour
editable by the user; another algorithm segments the hepatic artery based on an
initial user input point. The hepatic artery segmentation is also editable by the
user. | | |
|-------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------|
| | This software will assist the user by providing initial 3D segmentation, vessel
analysis, visualization, and quantitative analysis of liver anatomy. The user has
the ability to adjust the contour and confirm the final segmentation. | | |
| Intended Use/
Indication for Use: | Hepatic VCAR is a CT image analysis software package that allows the analysis
and visualization of Liver CT data derived from DICOM 3.0 compliant CT scans.
Hepatic VCAR is designed for the purpose of assessing liver morphology,
including liver lesion, provided the lesion has different CT appearance from
surrounding liver tissue; and its change over time through automated tools for
liver, liver lobe, liver segments and liver lesion segmentation and measurement. It
is intended for use by clinicians to process, review, archive, print and distribute
liver CT studies. | | |
| | This software will assist the user by providing initial 3D segmentation, vessel
analysis, visualization, and quantitative analysis of liver anatomy. The user has
the ability to adjust the contour and confirm the final segmentation. | | |
| Technology: | The modified Hepatic VCAR employs two deep learning convolutional neural
networks to segment the liver contour and the hepatic artery on CT liver exams
while the predicate device uses a traditional deterministic method to segment the
liver and manual tools to segment the vascular structure including the hepatic
artery. These changes do not change the Indications for Use from the predicate,
and represent equivalent technological characteristics, with no impact on control
mechanism, and operating principle.
The table below summarizes the feature/technological comparison between the
predicate device and the proposed device: | | |
| | Specification | Predicate Device:
Hepatic VCAR (K133649) | Proposed Device:
Hepatic VCAR |
| | Liver
segmentation | Atlas algorithm based
segmentation | Deep Learning algorithm
based segmentation |
| | Hepatic artery
segmentation | Manual segmentation tools
("autoselect" and scalpel) | Semi-automatic segmentation
workflow based on deep
learning segmentation of the
hepatic artery and edition |
| | | | tools to correct/refine the
result. |
| Determination of
Substantial
Equivalence: | Verification and validation including risk mitigations have been executed with
results demonstrating Hepatic VCAR met the design inputs and user needs with
no unexpected results or risks. | | |
| | Hepatic VCAR was designed and will be manufactured under the Quality System
Regulations of 21CFR 820 and ISO 13485. The following quality assurance
measures have been applied to the development of the device: | | |
| | Risk Analysis Requirements Reviews Design Reviews Performance testing (Verification, Validation) Safety testing (Verification) | | |
| | Bench tests that compare the output of the two new algorithms with ground truth
annotated by qualified experts show that the algorithms performed as expected. | | |
| | A representative set of clinical sample images was assessed by 3 board certified
radiologists using 5-point Likert scale. The assessment demonstrated that
capability of liver segmentation and hepatic artery segmentation utilizing the deep
learning algorithm by Hepatic VCAR. | | |
| | The substantial equivalence was also based on software documentation for a
"Moderate" level of concern device. | | |
| Conclusion: | GE Healthcare considers proposed device Hepatic VCAR to be as safe, as
effective, and performance is substantially equivalent to the predicate device. | | |
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Image /page/5/Picture/1 description: The image shows the logo for General Electric (GE). The logo consists of the letters "GE" in a stylized, cursive font, enclosed within a blue circle. There are three white, teardrop-shaped elements surrounding the circle, positioned at the top, left, and right sides. The logo is simple and recognizable, representing the company's brand identity.