(126 days)
Yes
The device description explicitly states that JBS-LVO uses an "artificial intelligence (Al) software algorithm utilizing convolutional neural network (CNN)" for image analysis.
No.
The device is a computer-aided triage and notification software that analyzes CT images for LVOs to notify specialists, not to directly treat or prevent a disease.
No
The device description explicitly states: "Identification of suspected positive findings is not for diagnostic use beyond notification" and "Image viewing through the mobile application interface is for informational purposes only and is not for diagnostic use." It also clarifies that "JBS-LVO is limited to the analysis of imaging data and should not be used in-lieu of full patient evaluation or relied upon to make or confirm a diagnosis."
Yes
The device description explicitly states that JBS-LVO is a "software package" and a "combination of software modules." It analyzes images and sends notifications, with the image analysis algorithm and mobile application being the described components. There is no mention of accompanying hardware that is part of the medical device itself.
Based on the provided information, it is highly likely that this device is an IVD (In Vitro Diagnostic) device, specifically a medical device software. Here's why:
- Intended Use: The device is intended to analyze medical images (CT angiograms of the brain) for findings suggestive of a specific clinical condition (large vessel occlusion). While it explicitly states it's a "notification-only, parallel workflow tool" and "not for diagnostic use beyond notification," the core function is the analysis of biological data (medical images) to provide information related to a disease state.
- Device Description: It is described as a "radiological computer aided triage and notification (CAD) software package." CAD software that analyzes medical images for disease detection or characterization is typically regulated as a medical device.
- Analysis of Biological Data: The device analyzes CT angiogram images, which are representations of the patient's anatomy and blood vessels. This is a form of biological data.
- Relation to a Disease State: The analysis is specifically aimed at identifying "large vessel occlusion," which is a clinical condition.
- Regulatory Context: The description mentions compliance with the DICOM standard and refers to a "Reference device, Rapid LVO (K221248)," which is a predicate device that has gone through the FDA clearance process. This strongly suggests that JBS-LVO is also intended to be a regulated medical device.
- Performance Studies: The inclusion of detailed performance metrics like sensitivity, specificity, and AUC, along with a description of a standalone performance evaluation against ground truth established by medical professionals, is characteristic of the validation required for medical devices, including IVDs.
Why it fits the definition of an IVD (specifically, a medical device software that performs an in vitro diagnostic function):
While the device doesn't directly analyze biological samples like blood or urine in the traditional sense of an IVD, the FDA's definition of an IVD includes devices that examine specimens derived from the human body to provide information for the diagnosis, treatment, or prevention of disease. Medical images are considered specimens derived from the human body. Software that analyzes these images to provide information related to a disease falls under the scope of IVDs, particularly as medical device software.
In summary:
Despite the emphasis on "notification-only" and "not for diagnostic use beyond notification," the fundamental function of JBS-LVO is to analyze medical images (biological data) to identify findings suggestive of a specific disease state (LVO). This places it squarely within the realm of medical devices that perform an in vitro diagnostic function, even if its output is intended for triage and notification rather than definitive diagnosis.
Therefore, based on the provided information, JBS-LVO is very likely considered an IVD device (specifically, a medical device software with an in vitro diagnostic function).
No
The provided text does not contain any explicit statement that the FDA has reviewed, approved, or cleared a Predetermined Change Control Plan (PCCP) for this specific device.
Intended Use / Indications for Use
JBS-LVO is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to identify and communicate images of specific patients to a specialist, independent of standard of care workflow.
JBS-LVO uses an artificial intelligence algorithm to analyze images for findings suggestive of a pre-specified clinical condition and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Identification of suspected positive findings is not for diagnostic use beyond notification. Specifically, the device analyzes CT angiogram images of the brain acquired in the acute setting and sends notifications to a neurovascular specialist that a suspected large vessel occlusion has been identified and recommends a review of those images. Images can be previewed through a mobile application. JBS-LVO is intended to analyze terminal ICA and MCA-M1 vessels for LVOs.
Images that are previewed through the mobile application are compressed and for informational purposes only. They are not intended for diagnostic use beyond notification. The JBS-LVO device does not alter the original medical image. Notified clinicians are responsible for viewing non-compressed images on a diagnostic viewer and engaging in appropriate patient evaluation and relevant discussion with a treating physician before making care-related decisions or requests. JBS-LVO is limited to the analysis of imaging data and should not be used in-lieu of full patient evaluation or relied upon to make or confirm a diagnosis.
Product codes
QAS
Device Description
JBS-LVO is a radiological computer aided triage and notification (CAD) software package compliant with the DICOM standard. JBS-LVO is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to analyze computed tomography angiography (CTA) images for findings suggestive of a suspected large vessel occlusion (LVO) and to notify an appropriate medical specialist of these findings in parallel to standard of core image interpretation. Specifically, JBS-LVO is optimized to evaluate occlusions of the intracranial carotid artery (ICA) and proximal middle cerebral artery (MCA-M1 segment). It is important to clarify that this quantification is solely used within the device's Al module to facilitation process. The output provided to healthcare professionals is strictly a flag indicating the presence (positive) of an LVO, in accordance with regulatory guidelines.
JBS-LVO is a combination of software modules that allow for detection and notification of patients with a suspected LVC. JBS-LVO consists of an algorithm and mobile application software module.
The JBS-LVO Image Analysis Algorithm (LVO Detection Algorithm) is a locked, artificial intelligence (Al) software algorithm utilizing convolutional neural network (CNN) that analyzes CTA images of the brain for a suspected LVO. The LVO Detection Algorithm is hosted on the JLK-server and analyzes applicable CTA images of the brain that are acquired on CT scanners and are automatically transmitted to the JLK-server. Upon detection of a suspected LVO, the LVO notification module sends a notification of the suspected finding.
The JBS-LVO notification functionality enable medical professionals and clinicians to preview compressed and informational images through via mobile application notification. Image viewing through the mobile application interface is for informational purposes only and is not for diagnostic use.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
CT angiogram (CTA)
Anatomical Site
Brain (specifically terminal ICA and MCA-M1 vessels)
Indicated Patient Age Range
Not Found
Intended User / Care Setting
Hospital networks and trained clinicians / Neurovascular specialist
Description of the training set, sample size, data source, and annotation protocol
The images used to train the algorithm were sourced from datasets that included equipment from various manufacturers, such as Siemens, Philips, Toshiba, and GE. This dataset, contain imaging studies, was labeled by trained radiologists to identify the presence of LVO.
Description of the test set, sample size, data source, and annotation protocol
The performance of the device's Al algorithms was validated in a standalone performance evaluation, utilizing an independent dataset different from the one used for algorithm training. In this standalone performance evaluation, each case output from the JBS-LVO device was compared with a ground truth was determined by two ground truthers, with a third ground truther intervening in cases of disagreement. All truthers were US board-certified neuroradiologists.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
A retrospective study has been conducted to assess the sensitivity and the image analysis algorithm and notification functionality of Triage LVO. Specifically, the study evaluated the Triage LVO image analysis in terms of sensitivity with respect to ground truth, as established by US board-certified neuro-radiologists, in detecting large vessel occlusion (LVO) in the brain.
The primary endpoints, sensitivity and specificity, both exceeded 80%. Specifically, the sensitivity was 91.8% with a 95% confidence interval (CI) of 85.8% to 95.8%. The specificity was 92.8% with a 95% CI of 87.2% to 96.5%. The area under the curve (AUC) was 95% CI of 93.0% to 98.1 %.
The secondary endpoint involves an analysis of time CTA to notification for LVO-positive cases. The total CTA-to-notification time for the JBS-LVO system ranged from 2.32 to 3.29 minutes (95% CI: 2.89 - 3.02). This performance is comparable to the Reference device, Rapid LVO (K221248), which reported a mean time of 3.18 minutes (95% CI. 3.11 - 3.25). JBS-LVO successfully meets the target time-to-notification of ≤ 3.5 minutes set by the Reference device.
Additionally, the time from CTA to notification using the JBS-LVO system successfully met the target goal.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Sensitivity: 91.8% with a 95% confidence interval (Cl) of 85.8% to 95.8%
Specificity: 92.8% with a 95% Cl of 87.2% to 96.5%
AUC: 95% Cl of 93.0% to 98.1 %
Total CTA-to-notification time: 2.32 to 3.29 minutes (95% Cl: 2.89 - 3.02)
Predicate Device(s)
Reference Device(s)
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 892.2080 Radiological computer aided triage and notification software.
(a)
Identification. Radiological computer aided triage and notification software is an image processing prescription device intended to aid in prioritization and triage of radiological medical images. The device notifies a designated list of clinicians of the availability of time sensitive radiological medical images for review based on computer aided image analysis of those images performed by the device. The device does not mark, highlight, or direct users' attention to a specific location in the original image. The device does not remove cases from a reading queue. The device operates in parallel with the standard of care, which remains the default option for all cases.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Design verification and validation must include:
(i) A detailed description of the notification and triage algorithms and all underlying image analysis algorithms including, but not limited to, a detailed description of the algorithm inputs and outputs, each major component or block, how the algorithm affects or relates to clinical practice or patient care, and any algorithm limitations.
(ii) A detailed description of pre-specified performance testing protocols and dataset(s) used to assess whether the device will provide effective triage (
e.g., improved time to review of prioritized images for pre-specified clinicians).(iii) Results from performance testing that demonstrate that the device will provide effective triage. The performance assessment must be based on an appropriate measure to estimate the clinical effectiveness. The test dataset must contain sufficient numbers of cases from important cohorts (
e.g., subsets defined by clinically relevant confounders, effect modifiers, associated diseases, and subsets defined by image acquisition characteristics) such that the performance estimates and confidence intervals for these individual subsets can be characterized with the device for the intended use population and imaging equipment.(iv) Stand-alone performance testing protocols and results of the device.
(v) Appropriate software documentation (
e.g., device hazard analysis; software requirements specification document; software design specification document; traceability analysis; description of verification and validation activities including system level test protocol, pass/fail criteria, and results).(2) Labeling must include the following:
(i) A detailed description of the patient population for which the device is indicated for use;
(ii) A detailed description of the intended user and user training that addresses appropriate use protocols for the device;
(iii) Discussion of warnings, precautions, and limitations must include situations in which the device may fail or may not operate at its expected performance level (
e.g., poor image quality for certain subpopulations), as applicable;(iv) A detailed description of compatible imaging hardware, imaging protocols, and requirements for input images;
(v) Device operating instructions; and
(vi) A detailed summary of the performance testing, including: test methods, dataset characteristics, triage effectiveness (
e.g., improved time to review of prioritized images for pre-specified clinicians), diagnostic accuracy of algorithms informing triage decision, and results with associated statistical uncertainty (e.g., confidence intervals), including a summary of subanalyses on case distributions stratified by relevant confounders, such as lesion and organ characteristics, disease stages, and imaging equipment.
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JLK, Inc. % John Smith M.D, J.D. - Global Regulatory Partner Hogan Lovells Columbia Square 555 Thirteenth Street NW Washington, District of Columbia 20004
September 27, 2024
Re: K241480
Trade/Device Name: JBS-LVO Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological Computer Aided Triage And Notification Software Regulatory Class: Class II Product Code: QAS Dated: August 30, 2024 Received: August 30, 2024
Dear John Smith:
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 (the 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 available 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
Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).
Your device is also subject to, among other requirements, the Quality System (QS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review. the OS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).
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 Part 803) for devices or postmarketing safety reporting (21 CFR Part 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 Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.
All medical devices, including Class I and unclassified devices and combination product device constituent parts are required to be in compliance with the final Unique Device Identification System rule ("UDI Re"). The UDI Rule requires, among other things, that a device bear a unique device identifier (UDI) on its label and package (21 CFR 801.20(a)) unless an exception or alternative applies (21 CFR 801.20(b)) and that the dates on the device label be formatted in accordance with 21 CFR 801.18. The UDI Rule (21 CFR 830.300(a) and 830.320(b)) also requires that certain information be submitted to the Global Unique Device Identification Database (GUDID) (21 CFR Part 830 Subpart E). For additional information on these requirements, please see the UDI System webpage at https://www.fda.gov/medical-devices/device-advicecomprehensive-regulatory-assistance/unique-device-identification-system-udi-system.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 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
2
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,
Jessica Lamb
Jessica Lamb, Ph.D. Assistant Director DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
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Indications for Use
510(k) Number (if known) K241480
Device Name JBS-LVO
Indications for Use (Describe)
JBS-LVO is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to identify and communicate images of specific patients to a specialist, independent of standard of care workflow.
JBS-LVO uses an artificial intelligence algorithm to analyze images for findings suggestive of a pre-specified clinical condition and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Identification of suspected positive findings is not for diagnostic use beyond notification. Specifically, the device analyzes CT angiogram images of the brain acquired in the acute sottfications to a neurovascular specialist that a suspected large vessel occlusion has been identified and recommends a review of those images. Images can be previewed through a mobile application. JBS-LVO is intended to analyze terminal ICA and MCA-M1 vessels for LVOs.
Images that are previewed through the mobile application are compressed and for informational purposes only. They are not intended for diagnostic use beyond notification. The JBS-LVO device does not alter the original medical image. Notified clinicians are responsible for viewing non-compressed images on a diagnostic viewer and engaging in appropriate patient evaluation and relevant discussion with a treating physician before making care-related decisions or requests. JBS-LVO is limited to the analysis of imaging data and should not be used in-lieu of full patient evaluation or relied upon to make or confirm a diagnosis.
Limitations:
The device does not process scans containing metallic artifacts.
| Type of Use (Select one or both, as applicable) | |
|---|---|
| X Prescription Use (Part 21 CFR 801 Subpart D) | ̄ Over-The-Counter Use (21 CFR 801 Subpart C) |
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| 510(k)# | K241480 | 510(k) Summary | Prepared on: 2024-09-26 |
|---|---|---|---|
| --------- | --------- | ---------------- | ------------------------- |
| Contact Details | 21 CFR 807.92(a)(1) | ||
|---|---|---|---|
| Applicant Name | JLK, Inc. | ||
| Applicant Address | JLK Tower, 5, Teheran-ro 33-gil Gangnam-gu Seoul n/a 06141 Korea, | ||
| South | |||
| Applicant Contact Telephone | (+82)1038507933 | ||
| Applicant Contact | Dr. Kim Dongmin | ||
| Applicant Contact Email | dmkim@jlkgroup.com | ||
| Correspondent Name | Hogan Lovells | ||
| Correspondent Address | Columbia Square 555 Thirteenth Street NW Washington D/C 20004 | ||
| United States | |||
| Correspondent Contact Telephone | (+1)2026373638 | ||
| Correspondent Contact | Mr. Smith John | ||
| Correspondent Contact Email | john.smith@hoganlovells.com |
| Device Name | 21 CFR 807.92(a)(2) | ||
|---|---|---|---|
| Device Trade Name | JBS-LVO | ||
| Common Name | Radiological computer aided triage and notification software | ||
| Classification Name | Radiological Computer-Assisted Triage And Notification Software | ||
| Regulation Number | 892.2080 | ||
| Product Code(s) | QAS |
| Legally Marketed Predicate Devices | 21 CFR 807.92(a)(3) | ||
|---|---|---|---|
| Predicate # | Predicate Trade Name (Primary Predicate is listed first) | Product Code | |
| K223042 | Viz LVO | QAS | |
| K221248 | Rapid LVO | QAS |
Device Description Summary
JBS-LVO is a radiological computer aided triage and notification (CAD) software package compliant with the DICOM standard. IBS-VV is a notification-only, parallel workflow tool for use by hospital networks and trained clinicians to analyze computed tomography angiography (CTA) images for findings suggestive of a suspected large vessel occlusion (LVO) and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Specifically, JBS-LVO is optimized to evaluate occlusions of the intracranial carotid artery (ICA) and proximal middle cerebral artery (MCA-M1 segment). It is important to clarify that this quantification is solely used within the device's Al module to facilitation process. The output provided to heathcare professionals is stiritly a flag indicating the presence (positive) of an LVO, in accordance with regulatory guidelines.
21 CFR 807.92(a)(4)
The images used to train the algorithm were sourced from datasets that included equipment from various manufacturers, such as Siemens,
5
Philips, Toshiba, and GE. This dataset, contain imaging studies, was labeled by trained radiologists to identify the presence of LVO. The performance of the device's Al algorithms was validated in a standalone performance evaluation, utilizing an independent dataset different from the one used for algorithm training. In this standalone performance evaluation, each case output from the JBS-LVO device was compared with a ground truth was determined by two ground truthers, with a third ground truther intervening in cases of disagreement. All truthers were US board-certified neuroradiologists.
JBS-LVO is a combination of software modules that allow for detection and notification of patients with a suspected LVC. JBS-LVO consists of an algorithm and mobile application software module.
The JBS-LVO Image Analysis Algorithm (LVO Detection Algorithm) is a locked, artificial intelligence (Al) software algorithm utilizing convolutional neural network (CNN) that analyzes CTA images of the brain for a suspected LVO. The LVO Detection Algorithm is hosted on the ILK-server and analyzes applicable CTA images of the brain that are acquired on CT scanners and are automatically transmitted to the ILKserver. Upon detection of a suspected LVO, the LVO notification module sends a notification of the suspected finding.
The JBS-LVO notification functionality enable medical professionals and clinicians to preview compressed and informational images through via mobile application notification. Image viewing through the mobile application interface is for informational purposes only and is not for diagnostic use.
Intended Use/Indications for Use
21 CFR 807.92(a)(5)
JBS-LVO is a notification-only, parallel workflow tool for use by hospital networks and trained cinicians to identify and communicate images of specific patients to a specialist, independent of standard of care workflow.
JBS-LVO uses an artificial intelligence algorithm to analyze images for findings suggestive of a pre-specified clinical condition and to notify an appropriate medical specialist of these findings in parallel to standard of care image interpretation. Identification of suspected positive findings is not for diagnostic use beyond notification. the device analyzes CT angiogram images of the brain acquired in the acute setting and sends notifications to a neurovascular that a suspected large vessel occlusion has been identified and recommends a review of those images. Images can be previewed through a mobile application. JBS-LVO is intended to analyze terminal ICA and MCA-M1 vessels for LVOs.
lmages that are previewed through the mobile application are compressed and for informational purposes only. They are not intended for diagnostic use beyond notification. The JBS-LVO device does not alter the original medical image. Notified clinicians are responsible for viewing non-compressed images on a diagnostic viewer and engaging in appropriate patient evaluation and relevant discussion with a treating physician before making care-related decisions or requests. JBS-LVO is limited to the and should not be used in-lieu of full patient evaluation or relied upon to make or confirm a diagnosis. Limitations: The device does not process scans containing metallic artifacts.
Indications for Use Comparison
Viz LVO and JBS-LVO are both designed to analyze images for findings suggestive of a pre-specified clinical condition and to notify an appropriate medical specialist of these findings in care interpretation. Since both devices are equally intended for use as a tool for assisting study triage within existing pathways and they do not replace any part of the current standard of care, there is no question about the effectiveness and safety of JBS-LVO compared to Viz LVO.
Technological Comparison
Both the subject and predicate devices utilize intelligence and machine learning (A/ML) algorithms to detect suspected large vessel occlusions (LVOs) on CTA imaging of the brain in the large vessels. Moreover, the software algorithm for the subject device is hosted on the similar architecture, automatically receives imaging in the same DICOM format, and uses similar mechanisms as the predicate device to identify applicable imaging for analysis. The subject and predicate devices are the same; both devices identify suspected LVOs and send notifications of suspected LVO findings from the same server.
The subject and predicate devices integrate the same mobile software functions and outputs, presented through the same mobile application. Users can conveniently receive notifications for patients with suspected LVOs, view a unique list of patients with a suspected LVO (as determined by the LVO Detection Algorithm), and examine the non-diagnostic CT scan of the patient through the JBS-LVO mobile application. The imaging viewing of CTA scans analyzed by the subject and predicate devices are subject to the same limitations, which means they are solely for informational purposes (for prioritization) and are not intention) and are not intended for diagnostic use.
Where the subject and predicate device device incorporates an advanced "Critical Pathway" (CP) feature within the IBS-LVO software system that enhances the management of clinical pathways for patient treatment. This feature is integrated into the mobile application interface, providing users with real-time patient care steps and facilitating effective communication among medical staff. Unlike the predicate device includes functionalities such as real-time updates, activity logs, and push notifications that are not present in the predicate device's in the subject device ensure that all parties
21 CFR 807.92(a)(6)
21 CFR 807.92(a)(5)
6
involved in patient care are consistently informed and cordinated, enhancing patient outcomes. Moreover, the inclusion of these advanced features does not introduce new safety or efficacy concerns, as confirmed by software testing which verified that the CP functionalities operateas expected. This integration of care management tools into the user interface thus represents a significant advancement over the predicate device, promoting greater transparency and efficiency in patient care management. These differences do not raise any new or different questions of safety and efficacy. As such, the JBS-LVO is considered substantially equivalent to Viz LVC.
In conclusion, JBS-LVO does not raise any new or different questions of safety or effectiveness compared to the predicate device Viz LVO (K223042). Both devices are radiological computer-aided triage and notifications for use with CTA input. Hence, it is substantially equivalent to the predicate device.
Non-Clinical and/or Clinical Tests Summary & Conclusions 21 CFR 807.92(b)
ILK, Inc. conducted extensive performance validation testing and software verification of the JBS-LVO system. This performance validation testing demonstrated that the JBS-LVO system accurately represents key processing parameters under a range of clinically relevant parameters and perturbations associated with the intended use of the software. The documentation was provided as recommended by FDA's Guidance for Industry and FDA staff, "Content of Premarket Submissions for Device Software Functions," June 14, 2023.
ILK, Inc. performed a standalone performance with the §892.2080 special controls to show acceptance of the clinical performance of the JBS-LVO module. The test dataset used during the standalone performance evaluation was newly acquired, and appropriate steps were taken to ensure it was independent of the training dataset used in model development. Performance testing is intended to inform users about the algorithm's accuracy. As a result, we achieved the desired performance results, demonstrating that IBS-LVO is as safe and effective as a predicate device.
A retrospective study has been conducted to assess the sensitivity and the image analysis algorithm and notification functionality of Triage LVO. Specifically, the study evaluated the Triage LVO image analysis in terms of sensificity with respect to ground truth, as established by US board-certified neuro-radiologists, in detecting large vessel occusion (LVQ) in the brain.
The primary endpoints, sensitivity and specificily, both exceded 80%. Specifically, the sensitivity was 91.8% with a 95% confidence interval (CJ of 85.8% to 95.8%. The specificity was 92.8% with a 95% Cl of 87.2% to 96.5%. The area under the curve (AUC) was 95% Cl of 93.0% to 98.1 %.
The secondary endpoint involves an analysis of time CTA to notification for LVO-positive cases. The total CTA-tonotification time for the JBS-LVO system ranged from 2.32 to 3.29 minutes (95% Cl: 2.89 - 3.02). This performance is comparable to the Reference device, Rapid LVO (K221248), which reported a mean time of 3.18 minutes (95% Cl. 3.11 - 3.25). JBS-LVO successfully meets the target time-to-notification of ≤ 3.5 minutes set by the Reference device.
Additionally, the time from CTA to notification using the JBS-LVO system successfully met the target goal.
In conclusion, JBS-LVO, which has the same intentially equivalent technological, safety, and performance characteristics, is comparable to the legally marketed predicate device, Viz LVO (K223042). Therefore, JBS-LVO is substant to the selected predicate device and raises no questions regarding safety or effectiveness.