(27 days)
Not Found
Yes
The device description explicitly states that the SIS System is "based on machine learning and image processing" and uses "pre-trained deep learning neural network models".
No
The device is a software-only system for medical imaging viewing, processing, and surgical planning, primarily for visualization and localization of anatomical structures. It does not directly perform a therapeutic action on a patient.
No
The device aids in visualization and planning for surgical procedures, rather than providing a diagnosis of a patient's condition or disease state. Its purpose is to enhance images for anatomical structure identification and surgical planning.
Yes
The device description explicitly states, "The SIS System is a software only device based on machine learning and image processing."
Based on the provided information, this device is not an IVD (In Vitro Diagnostic).
Here's why:
- IVD Definition: In Vitro Diagnostics are devices intended for use in the collection, preparation, and examination of specimens taken from the human body (such as blood, urine, tissue) to provide information for the diagnosis, treatment, or prevention of disease.
- Device Function: The SIS System is a software-only device that processes medical images (MR and CT) to visualize and enhance anatomical structures within the brain. It aids in surgical planning and visualization, particularly for procedures like Deep Brain Stimulation.
- Lack of Specimen Analysis: The device does not involve the analysis of any biological specimens taken from the patient. Its input is medical imaging data.
Therefore, the SIS System falls under the category of medical imaging software or surgical planning software, not an In Vitro Diagnostic device.
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.
Intended Use / Indications for Use
SIS System is 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 guided surgery or other processing, visualization and localization. The device can be used in coniunction with other cinical methods as an aid in visualization of the subthalamic nuclei (STN) and globus pallidus externa and interna (GPe and GPi, respectively) in neurological procedures. The system is indicated for surgical procedures in which anatomical structure locations are identified in images, including Deep Brain Stimulation Lead Placement.
Typical users of the SIS Software are medical professionals, including but not limited to surgeons, neurologists and radiologists.
Product codes (comma separated list FDA assigned to the subject device)
QIH, LLZ
Device Description
The SIS System is a software only device based on machine learning and image processing. The device is designed to enhance standard clinical images for the visualization of structures in the basal gandlia 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 surqical procedures and planning of lead output.
The SIS System provides a patient-specific, 3D anatomical model of specific brain structures based on the patient's own clinical MR image using pre-trained deep learning neural network models. As discussed in more detail below, the method incorporates ultra-high resolution 7T (7 Tesla) Maqnetic 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. 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 System version 5.6.0 that was cleared under K223032. The primary changes are the addition of two compatible leads, minor modification to image registration algorithm, and a feature to allow users to view post-operative 3D model in a different coordinate system.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
MR, CT
Anatomical Site
Brain, specifically the subthalamic nuclei (STN) and globus pallidus externa and interna (GPe and GPi, respectively) and other structures in the basal ganglia area.
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
The method incorporates ultra-high resolution 7T (7 Tesla) Maqnetic 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
Not Found
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Software verification and validation testing was conducted. Visualization accuracy testing was repeated for STN and GPi/GPe structures. MRI to CT registration testing was repeated. Testing for image processing of CT images was repeated for lead segmentation. Electrode orientation testing was repeated for current and new lead models. Validation of head pose for standardized head position view was extended. The results demonstrated that the SIS System has been fully verified and the updated device performs as intended and is as safe and effective compared to the predicate.
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.
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). The logo consists of two parts: the Department of Health and Human Services logo on the left and the FDA logo on the right. The FDA logo is in blue and includes the letters "FDA" followed by the words "U.S. Food & Drug Administration".
May 2, 2023
Surgical Information Sciences, Inc. % Kelliann Payne Partner Hogan Lovells, US LLP 1735 Market Street, 23rd Floor Philadelphia, Pennsylvania 19103
Re: K230977
Trade/Device Name: SIS System Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: QIH, LLZ Dated: April 5, 2023 Received: April 5, 2023
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.
1
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-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.
Daniel M. Krainak, Ph.D. Assistant Director DHT8C: Division of Radiological Imaging and Radiation Therapy Devices OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
2
510(k) Number (if known)
K230977
Device Name
SIS System
Indications for Use (Describe)
SIS System is 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 guided surgery or other processing, visualization and localization. The device can be used in coniunction with other cinical methods as an aid in visualization of the subthalamic nuclei (STN) and globus pallidus externa and interna (GPe and GPi, respectively) in neurological procedures. The system is indicated for surgical procedures in which anatomical structure locations are identified in images, including Deep Brain Stimulation Lead Placement.
Tvpical users of the SIS Software are medical professionals, including but not limited to surgeons, neurologists and radiologists.
| Type of Use (Select one or both, as applicable) | |
|---|---|
| ------------------------------------------------- | -- |
区 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.gov
"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
Surgical Information Sciences, Inc.'s SIS System
Submitter's Name, Address, Telephone Number, Contact Person and Date Prepared
Surgical Information Sciences, Inc. 5201 Eden Avenue, Suite 300 Edina, Minnesota, 55436 Contact Person: Ann Quinlan-Smith Phone: 612-325-0187 E-mail: ann.quinlan.smith@surqicalis.com
Date Prepared: April 5, 2023
Trade Name of Device: SIS System
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 Devices
Predicate: Surgical Information Sciences SIS Software version 5.6.0 (K223032)
Intended Use / Indications for Use
SIS System is 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, visualization and localization. The device can be used in conjunction with other clinical methods as an aid in visualization and location of the subthalamic nuclei (STN) and globus pallidus externa and interna (GPe and GPi, respectively) in neurological procedures. The system is indicated for surgical procedures in which anatomical structure locations are identified in images, including Deep Brain Stimulation Lead Placement.
Typical users of the SIS Software are medical professionals, including but not limited to surgeons, neurologists and radiologists.
Technological Characteristics
The SIS System is a software only device based on machine learning and image processing. The device is designed to enhance standard clinical images for the visualization of structures in the basal gandlia 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
4
information to surgeons, neurologists, and radiologists for use in viewing brain structures for planning stereotactic surqical procedures and planning of lead output.
The SIS System provides a patient-specific, 3D anatomical model of specific brain structures based on the patient's own clinical MR image using pre-trained deep learning neural network models. As discussed in more detail below, the method incorporates ultra-high resolution 7T (7 Tesla) Maqnetic 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. 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 System version 5.6.0 that was cleared under K223032. The primary changes are the addition of two compatible leads, minor modification to image registration algorithm, and a feature to allow users to view post-operative 3D model in a different coordinate system.
Performance Data
Following the modifications, the software verification and validation testing was conducted to validate that the software functions as specified and performs similarly to the predicate device using the same acceptance criteria and the same test designs as used for the previously cleared predicate device. Visualization accuracy testing was repeated to validation of the STN and GPi/GPe structures. 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 using a similar method representative of actual use, and lastly, repeated electrode orientation testing for current lead models and developed a similar method to validate electrode orientation functionality for the new lead models. The company also extended its validation of the head pose for the standardized head position view. The results of this testing demonstrated that the SIS System has been fully verified and the updated device performs as intended and is as safe and effective compared to the predicate.
Substantial Equivalence
In summary, the company's SIS System has the same intended use as the previously cleared SIS System 5.6.0. In addition, the SIS System has the same indications and similar technological characteristics, and principles of operation as its predicates. Although there are minor differences between the SIS System and its predicate device, those differences do not raise new questions of safety or efficacv. Thus. the SIS System is substantially equivalent.