(79 days)
Not Found
Yes
The device description explicitly states that the software is "based on machine learning and image processing" and uses "pretrained deep learning neural network models" for image segmentation and prediction of brain structure shape and position.
No
The device is described as an aid in visualization and offers additional, adjunctive information to medical professionals for planning stereotactic surgical procedures, rather than directly providing therapy.
No
The description states the device is an "aid in visualization" and "supplements the information available through standard clinical methods by providing additional, adjunctive information." It does not claim to provide a definitive diagnosis or replace the need for professional interpretation of medical images.
Yes
The device description explicitly states "The SIS System version 5.1.0, a software only device...".
Based on the provided information, this device is not an IVD (In Vitro Diagnostic).
Here's why:
- IVD Definition: In Vitro Diagnostics are tests performed on samples taken from the human body, such as blood, urine, or tissue, to detect diseases, conditions, or infections.
- Device Function: The SIS System is a software-only device that processes medical images (MR and CT) of the brain to aid in visualization and planning for surgical procedures. It does not analyze biological samples.
- Intended Use: The intended use is for viewing, presenting, and processing medical imaging for surgical planning and visualization of brain structures. This is a diagnostic imaging aid, not an in vitro diagnostic test.
Therefore, the SIS System falls under the category of medical imaging software or a surgical planning system, not an In Vitro Diagnostic device.
No
The letter does not state that the FDA has reviewed and approved or cleared a Predetermined Change Control Plan (PCCP) for this specific device. The provided text explicitly states "Not Found" for "Control Plan Authorized (PCCP) and relevant text".
Intended Use / Indications for Use
SIS System is an application intended for use in the viewing, presentation and documentation of medical imaging, including different modules for image processing, image fusion, and intraoperative functional planning where the 3D output can be used with stereotactic image quided surgery or other processing and visualization. The device can be used in conjunction with other clinical methods as an aid in visualization of the subthalamic nuclei (STN) and globus pallidus externa and interna (GPe and GPi, respectively).
Typical users of SIS System are medical professionals, including but not limited to surgeons, neurologists, and radiologists.
Product codes
QIH, LLZ
Device Description
The SIS System version 5.1.0, a software only device based on machine learning and image processing, is designed to enhance standard clinical images for the visualization of structures in the basal ganglia area of the brain, specifically the subthalamic nucleus (STN) and globus pallidus externa and interna (GPe/GPi). The output of the SIS system supplements the information available through standard clinical methods by providing additional, adjunctive information to surgeons, neurologists, and radiologists for use in viewing brain structures for planning stereotactic surgical procedures and planning of lead output.
The SIS System version 5.1.0 provides a patient-specific, 3D anatomical model of specific brain structures based on the patient's own clinical MR image using pretrained deep learning neural network models. This method incorporates ultra-high resolution 7T (7 Tesla) Magnetic Resonance images to determine ground truth for the training data set to train the deep learning models. These pre-trained deep learning neural network models are then applied to a patient's clinical image to predict the shape and position of the patient's specific brain structures of interest. The SIS System is further able to locate and identify implanted leads, where implanted, visible in post-operative CT images and place them in relation to the brain structure of interest from the preoperative processing.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
MR image, CT images
Anatomical Site
Brain, specifically the subthalamic nucleus (STN) and globus pallidus externa and interna (GPe/GPi).
Indicated Patient Age Range
Not Found
Intended User / Care Setting
Medical professionals, including but not limited to surgeons, neurologists, and radiologists.
Description of the training set, sample size, data source, and annotation protocol
This method incorporates ultra-high resolution 7T (7 Tesla) Magnetic Resonance images to determine ground truth for the training data set to train the deep learning models.
Description of the test set, sample size, data source, and annotation protocol
The electrode orientation detection software was validated on 43 CT image series that contained 55 leads.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
To validate the updated algorithm, visualization accuracy testing was conducted for the STN and GPi/GPe structures using the same test methods and acceptance criteria for the previously cleared predicate device. In addition, the company repeated the MRI to CT registration testing to ensure that 3D transformation remains accurate. The company also repeated the testing for image processing of CT images to validate the lead segmentation. Finally, the electrode orientation detection software was validated on 43 CT image series that contained 55 leads. The software was characterized by two probabilities: the probability of a trusted detection being accurate (within ± 30° of the ground truth) and the probability of an untrusted detection being accurate. When the software trusted the lead detection, it was correct in 91% of cases. This testing demonstrated that greater than 90% of orientations presented to the user are accurate within ± 30°. The results of this testing demonstrated that the SIS System version 5.1.0 has been fully verified and validated and the updated device performs as intended and is as safe and effective compared to the predicate.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
When the software trusted the lead detection, it was correct in 91% of cases. This testing demonstrated that greater than 90% of orientations presented to the user are accurate within ± 30°.
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.
Not Found
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
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
0
Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which is a blue square with the letters "FDA" in white. To the right of the blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.
Surgical Information Sciences, Inc. % Kelliann Payne Partner Hogan Lovells US LLP 1735 Market Street, 23rd Floor PHILADELPHIA, PA 19103
March 31, 2021
Re: K210071
Trade/Device Name: SIS System (Version 5.1.0) Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: QIH, LLZ Dated: January 11, 2021 Received: January 11, 2021
Dear Kelliann Payne:
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
1
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
DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration Indications for Use
510(k) Number (if known)
Device Name
SIS System (version 5.1.0)
Indications for Use (Describe)
SIS System is an application intended for use in the viewing, presentation of medical imaging, including different modules for image processing, image fusion, and intraoperative functional planning where the 3D output can be used with stereotactic image quided surgery or other processing and visualization. The device can be used in conjunction with other clinical methods as an aid in visualization of the subthalamic nuclei (STN) and globus pallidus externa and interna (GPe and GPi, respectively).
Typical users of SIS System are medical professionals, including but not limited to surgeons, neurologists, and radiologists.
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)
CONTINUE ON A SEPARATE PAGE IF NEEDED.
This section applies only to requirements of the Paperwork Reduction Act of 1995.
DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.
The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:
Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff@fda.hhs.qov
"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."
3
510(k) SUMMARY
K210071
Submitter's Name, Address, Telephone Number, Contact Person and Date Prepared
Surgical Information Sciences, Inc. 10405 6th Avenue North, Suite 110 Plymouth, MN 55441 Contact Person: Ann Quinlan-Smith Phone: 612-325-0187 E-mail: ann.quinlan.smith@surqicalis.com
Date Prepared: March 29, 2021
Trade Name of Device: SIS System version 5.1.0
Common or Usual Name/Classification Name:
- Automated Radiological Image Processing Software (Product Code: QIH; 21 Primary: C.F.R 892.2050);
- Secondary: System, Image Processing, Radiological (Product Code: LLZ; 21 C.F.R 892.2050)
Regulatory Class: Class II
Predicate Device: Surgical Information Sciences SIS Software version 3.6.0 (K192304)
Intended Use / Indications for Use
SIS System is an application intended for use in the viewing, presentation and documentation of medical imaging, including different modules for image processing, image fusion, and intraoperative functional planning where the 3D output can be used with stereotactic image guided surgery or other devices for further processing and visualization. The device can be used in conjunction with other clinical methods as an aid in visualization of the subthalamic nuclei (STN) and globus pallidus externa and interna (GPe and GPi, respectively).
Typical users of SIS System are medical professionals, including but not limited to surgeons, neurologists, and radiologists.
4
Technological Characteristics
The SIS System version 5.1.0, a software only device based on machine learning and image processing, is designed to enhance standard clinical images for the visualization of structures in the basal ganglia area of the brain, specifically the subthalamic nucleus (STN) and globus pallidus externa and interna (GPe/GPi). The output of the SIS system supplements the information available through standard clinical methods by providing additional, adjunctive information to surgeons, neurologists, and radiologists for use in viewing brain structures for planning stereotactic surgical procedures and planning of lead output.
The SIS System version 5.1.0 provides a patient-specific, 3D anatomical model of specific brain structures based on the patient's own clinical MR image using pretrained deep learning neural network models. This method incorporates ultra-high resolution 7T (7 Tesla) Magnetic Resonance images to determine ground truth for the training data set to train the deep learning models. These pre-trained deep learning neural network models are then applied to a patient's clinical image to predict the shape and position of the patient's specific brain structures of interest. The SIS System is further able to locate and identify implanted leads, where implanted, visible in post-operative CT images and place them in relation to the brain structure of interest from the preoperative processing.
The proposed device is a modification to the SIS Software version 3.6.0 that was cleared under K192304. The changes made to the SIS System include (1) an updated algorithm that is based on deep learning Convolutional Neural Network models that were architected and optimized for brain image segmentation; (2) the addition of new targets for visualization, specifically the globus pallidus externa and interna (GPe/GPi); and (3) the addition of a functionality to determine the orientation of a directional lead, following its segmentation from the post-operative CT image.
Performance Data
Following the modifications, the software verification and validation testing was repeated to validate that the modified software functions as specified and performs similarly to the predicate device.
To validate the updated algorithm, visualization accuracy testing was conducted for the STN and GPi/GPe structures using the same test methods and acceptance criteria for the previously cleared predicate device. In addition, the company repeated the MRI to CT registration testing to ensure that 3D transformation remains accurate. The company also repeated the testing for image processing
5
of CT images to validate the lead segmentation. Finally, the electrode orientation detection software was validated on 43 CT image series that contained 55 leads. The software was characterized by two probabilities: the probability of a trusted detection being accurate (within ± 30° of the ground truth) and the probability of an untrusted detection being accurate. When the software trusted the lead detection, it was correct in 91% of cases. This testing demonstrated that greater than 90% of orientations presented to the user are accurate within ± 30°. The results of this testing demonstrated that the SIS System version 5.1.0 has been fully verified and validated and the updated device performs as intended and is as safe and effective compared to the predicate.
Substantial Equivalence
Both the subject and predicate devices are applications intended for use in the viewing, presentation and documentation of medical imaging, including different modules for image processing, image fusion, and intraoperative functional planning where the 3D output can be used with stereotactic image guided surgery or other devices for further processing and visualization. Both devices can be used in conjunction with other clinical methods as an aid in visualization of the target brain structures. In addition, typical users of both devices are medical professionals, including, but not limited to surgeons, neurologists and radiologists.
The subject device, like the predicate, operates on other computer platforms and uses a proprietary algorithm to generate 3D segmented anatomical models from patients' MRI scans. The subject device employs an updated version of the algorithm based on deep learning Convolutional Network Models, which were trained to identify the region of interest and individually predict the location and size of the anatomical structures of interest. Furthermore, the addition of the globus pallidus externa and interna (GPe/GPi) structures as well as the functionality to detect the orientation of the implanted directional lead, further facilitate the fundamental clinical purpose for which the predicate was cleared, namely assistance with visualization, surgical planning, image review and analysis. Validation testing demonstrated that the subject device is as safe and effective as the predicate device. The table below provides a summary comparison between the subject and predicate devices.
6
| | SIS System version 5.1.0
(subject device) | SIS Software version 3.6.0
(predicate device) |
|-------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Intended Use /
Indications for Use | SIS System is an application intended for use in the
viewing, presentation and
documentation of medical
imaging, including different
modules for image
processing, image fusion,
and intraoperative functional
planning where the 3D
output can be used with
stereotactic image guided
surgery or other devices for
further processing and
visualization. The device
can be used in conjunction
with other clinical methods
as an aid in visualization of
the subthalamic nuclei
(STN) and globus pallidus
externa and interna (GPe
and GPi, respectively).
Typical users of the SIS
System are medical
professionals, including but
not limited to surgeons,
neurologists and
radiologists. | SIS Software is an application intended for use in the
viewing, presentation and
documentation of medical
imaging, including different
modules for image
processing, image fusion, and
intraoperative functional
planning where the 3D output
can be used with stereotactic
image guided surgery or
other devices for further
processing and visualization.
The device can be used in
conjunction with other clinical
methods as an aid in
visualization of the
subthalamic nuclei (STN).
Typical users of SIS Software
are medical professionals,
including but not limited to
surgeons, neurologists, and
radiologists. |
| User Population | Medical professionals,
including but not limited to
surgeons, neurologists and
radiologists. | Medical professionals,
including but not limited to
surgeons, neurologists, and
radiologists. |
| Allows for importing of
digital imaging sets | Yes | Yes |
| Uses proprietary
software algorithm to
generate 3D segmented
anatomical models from
patient's MR scans | Yes | Yes |
| | SIS System version 5.1.0
(subject device) | SIS Software version 3.6.0
(predicate device) |
| Allows for review and
analysis of data in 2D
and 3D formats | Yes | Yes |
| Performs image fusion
of datasets using
automated or manual
image matching
technique | Yes | Yes |
| Segments structures in
images with manual and
automated tools and
converts them into 3D
objects for display | Yes | Yes |
| Creates hybrid datasets
by filing in segmented
regions slice-by-slice
on anatomical datasets | Yes | Yes |
| Can be downloaded to
planning system | Yes | Yes |
| Segmentation of CT
scan to identify
structures in relation to
those visualized on MR | Yes | Yes |
| Feature to Account for
CT images with gantry
tilt | Yes | Yes |
| Cross-registers images
and creates 3D (fused)
model | Yes | Yes |
| Uses registration
methods (linear and
non-linear) by multiple
registration tools (ANTS
and ELASTIX) | Yes | Yes |
7
8
Conclusion
The updated SIS System version 5.1.0 is as safe and effective as the predicate version previously cleared in K192304. The subject device has the same intended use and similar technological characteristics and principles of operation, with minor differences supported by performance validation testing demonstrating that the subject device is as safe and effective as the predicate device. Thus, the minor technological differences between SIS System version 5.1.0 and its predicate device raise no new issues of safety or effectiveness, and the updated SIS System version 5.1.0 is substantially equivalent.