(29 days)
Not Found
Yes
The document explicitly states that the device uses "artificial intelligence algorithms" multiple times to analyze imaging data and detect patterns.
No
The device is a diagnostic tool that identifies suggestive imaging patterns and notifies specialists; it does not directly treat or prevent a disease or condition.
No
Justification: The text explicitly states, "HALO's output should not be used for primary diagnosis or clinical decisions; the final diagnosis is always decided upon by the medical specialist." This indicates it is a clinical support tool for notification, not a device for primary diagnosis.
Yes
The device is explicitly described as "cloud-based image processing software" and a "clinical support tool" that processes images and sends notifications. There is no mention of any accompanying hardware component that is part of the device itself.
Based on the provided information, HALO is NOT an In Vitro Diagnostic (IVD) device.
Here's why:
-
IVD Definition: In Vitro Diagnostics are medical devices intended for use in vitro (outside the body) for the examination of specimens derived from the human body to provide information for diagnostic, monitoring, or compatibility purposes. This typically involves analyzing biological samples like blood, urine, tissue, etc.
-
HALO's Function: HALO analyzes imaging data (CT angiograms of the brain), which are acquired in vivo (from within the body). It processes these images to identify patterns suggestive of a condition. It does not analyze biological specimens.
-
Intended Use: HALO's intended use is to "facilitate the evaluation of the brain vasculature on patients suspected of stroke by processing and analyzing CT angiograms of the brain acquired in an acute setting." This is clearly focused on image analysis, not the analysis of biological samples.
-
Device Description: The description reinforces that HALO "is designed to process CT angiograms of the brain" and "A copy of the original CTA images is sent to HALO cloud servers for automatic image processing."
While HALO is a medical device that provides information to aid in diagnosis, its method of operation (analyzing medical images) places it outside the scope of In Vitro Diagnostics. It falls under the category of medical imaging software or a clinical decision support tool.
No
The letter does not state that the FDA has reviewed and approved or cleared a PCCP for this specific device; it explicitly states "Not Found" under "Control Plan Authorized (PCCP) and relevant text".
Intended Use / Indications for Use
HALO is a notification only cloud-based image processing software artificial intelligence algorithms to analyze patient imaging data in parallel to the standard of care imaging interpretation. Its intended use is to identify suggestive imaging patterns of a pre-specified condition and to directly notify an appropriate medical specialist.
HALO's indication is to facilitate the evaluation of the brain vasculature on patients suspected of stroke by processing and analyzing CT angiograms of the brain acquired in an acute setting. After completion of the data analysis, HALO sends a notification if a pattern suggestive for a suspected intracranial Large Vessel Occlusion (LVO) of the anterior circulation (ICA, M1 or M2) has been identified in an image.
Product codes (comma separated list FDA assigned to the subject device)
QAS
Device Description
HALO is a notification only, cloud-based clinical support tool which identifies image features and communicates the analysis results to a specialist in parallel to the standard of care workflow.
HALO is designed to process CT angiograms of the brain and facilitate evaluation of these images using artificial intelligence to detect patterns suggestive of an intracranial large vessel occlusion (LVO) of the anterior circulation.
A copy of the original CTA images is sent to HALO cloud servers for automatic image processing. After analyzing the images, HALO sends a notification regarding a suspected finding to a specialist, recommending review of these images. The specialist can review the results remotely in a compatible DICOM web viewer.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
CT angiograms of the brain
Anatomical Site
Brain
Indicated Patient Age Range
Not Found
Intended User / Care Setting
The intended users of HALO are defined as medical specialists or a team of specialists that are involved in the diagnosis and care of stroke patients at emergency department where stroke patients are administered. The include physicians such as neurologists, radiologists, and/or other emergency department physicians.
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)
Clinical Study. In a multi-center clinical study, the performance of the HALO clinical decision support algorithm for LVO detection was retrospectively evaluated in a consecutive patient cohort admitted to US comprehensive stroke centers.
434 CTA scans of the brain were collected. After exclusion, 427 patients were included for further analyses. Ground truth was established by an expert panel consisting of 3 neuro radiologists. For the primary endpoint: calculation of the performance of the HALO algorithm showed a sensitivity and specificity for LVO detection of respectively 91.3% (95% CI, 86.6%-94.8%) and 85.9% (95% CI, 80.6%-90.2%). The area under the curve (AUC) is 0.97.
For the secondary endpoints the median notification time for the detected LVO cases was 4 minutes 29 seconds, with a minimum of 3:47 and maximal 7:12.
The HALO performance with regard to sensitivity and specificity, and the notification time are both equivalent to that of the selected predicate device. Therefore, the HALO algorithm fulfils the requirement of a suitable screening tool to support diagnosis of LVOs by flagging these scans as requiring urgent radiologist review.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Sensitivity: 91.3% (95% CI, 86.6%-94.8%)
Specificity: 85.9% (95% CI, 80.6%-90.2%)
AUC: 0.97
Median notification time: 4 minutes 29 seconds (min 3:47, max 7:12)
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
§ 892.2080 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.
0
July 8, 2021
Image /page/0/Picture/1 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: on the left, there is a seal with an eagle emblem, and on the right, there is the text "FDA U.S. FOOD & DRUG ADMINISTRATION" in blue. The text is arranged in three lines, with "FDA" in a larger font size and a blue square behind it.
Nico.Lab B.V. % Ruojuan Zhang RA Consultant MD Squared B.V. High Tech Campus 29 Eindhoven. Noord Brabant 5656 AE THE NETHERLANDS
Re: K211788
Trade/Device Name: HALO Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological computer aided triage and notification software Regulatory Class: Class II Product Code: QAS Dated: June 5, 2021 Received: June 9, 2021
Dear Ruojuan Zhang:
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
1
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 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 HALO
Indications for Use (Describe)
HALO is a notification only cloud-based image processing software artificial intelligence algorithms to analyze patient imaging data in parallel to the standard of care imaging interpretation. Its intended use is to identify suggestive imaging patterns of a pre-specified condition and to directly notify an appropriate medical specialist.
HALO's indication is to facilitate the evaluation of the brain vasculature on patients suspected of stroke by processing and analyzing CT angiograms of the brain acquired in an acute setting. After completion of the data analysis, HALO sends a notification if a pattern suggestive for a suspected intracranial Large Vessel Occlusion (LVO) of the anterior circulation (ICA, M1 or M2) has been identified in an image.
The intended users of HALO are defined as medical specialists or a team of specialists that are involved in the diagnosis and care of stroke patients at emergency department where stroke patients are administered. The include physicians such as neurologists, radiologists, and/or other emergency department physicians.
HALO's output should not be used for primary diagnosis or clinical decisions; the final diagnosis is always decided upon by the medical specialist. HALO is indicated for CT scanners from GE Healthcare and Philips.
| 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.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
This 510(k) summary of safety and effectiveness information is prepared in accordance with 21 CFR §807.92.
| Submission Number: | K211788 | |
|---|---|---|
| Date Prepared: | June 4, 2021 | |
| Manufacturer: | NICO.LAB B.V. | |
| Paasheuvelweg 25, 1105 BP Amsterdam | ||
| The Netherlands | ||
| Primary Contact | ||
| Person: | Merel Boers | |
| CEO | ||
| Phone: +31 6 22177913 | ||
| E-mail: mboers@nico-lab.com | ||
| Device: | ||
| Trade Name: | HALO | |
| Classification Name: | Radiological Computer-Assissted Triage and | |
| Notification Software | ||
| Classification Regulation: | 21CFR §892.2080 | |
| Classification Panel: | Radiology | |
| Device Class: | Class II | |
| Primary Product Code: | QAS | |
| Primary Predicate | ||
| Device: | ||
| Trade Name: | HALO | |
| Manufacturer: | NICO.LAB B.V. | |
| 510(k) Clearance: | K200873 (November 20, 2020) | |
| Classification Name: | Radiological Computer-Assissted Triage and | |
| Notification Software | ||
| Classification Regulation: | 21CFR §892.2080 | |
| Classification Panel: | Radiology | |
| Device Class: | Class II | |
| Product Code: | QAS | |
| Device description: | HALO is a notification only, cloud-based clinical support tool which | |
| identifies image features and communicates the analysis results to a | ||
| specialist in parallel to the standard of care workflow. |
HALO is designed to process CT angiograms of the brain and facilitate
evaluation of these images using artificial intelligence to detect patterns
suggestive of an intracranial large vessel occlusion (LVO) of the anterior
circulation.
A copy of the original CTA images is sent to HALO cloud servers for
automatic image processing. After analyzing the images, HALO sends a
notification regarding a suspected finding to a specialist, recommending
review of these images. The specialist can review the results remotely in
a compatible DICOM web viewer. | |
| Indications for Use: | HALO is a notification only cloud-based image processing software
application using artificial intelligence algorithms to analyze patient
imaging data in parallel to the standard of care imaging interpretation. Its
intended use is to identify suggestive imaging patterns of a pre-specified
clinical condition and to directly notify an appropriate medical specialist.
HALO's indication is to facilitate the evaluation of the brain vasculature
on patients suspected of stroke by processing and analyzing CT
angiograms of the brain acquired in an acute setting. After completion of
the data analysis, HALO sends a notification if a pattern suggestive for a
suspected intracranial Large Vessel Occlusion (LVO) of the anterior
circulation (ICA, M1 or M2) has been identified in an image.
The intended users of HALO are defined as medical specialists or a team
of specialists that are involved in the diagnosis and care of stroke patients
at emergency departments or other departments where stroke patients are
administered. They include physicians such as neurologists, radiologists,
and/or other emergency department physicians.
HALO's output should not be used for primary diagnosis or clinical
decisions; the final diagnosis is always decided upon by the medical
specialist. HALO is indicated for CT scanners from GE Healthcare and
Philips. | |
| Technological
characteristics: | The subject device, HALO, is substantially equivalent to the predicate
device, the previously cleared version of the HALO (K200873). In
comparing the technological characteristics, both the subject and
predicate devices process CT angiograms of the brain and facilitate
evaluation of these images using artificial intelligence to detect patterns
suggestive of an intracranial large vessel occlusion (LVO) of the anterior | |
4
5
circulation. After analyzing the images, the device sends a notification regarding a suspected finding to a specialist, recommending review of these images. Where the subject and predicate only differ is that the subject device not only process images from GE Healthcare, but also Philips scanners.
The technological characteristic of HALO and how it is comparable to the predicate device are summarized below.
| | Predicate
HALO | Subject
HALO |
|------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Clinical condition | Large vessel
occlusion | Large vessel
occlusion |
| Anatomical region
of interest | Head | Head |
| Data acquisition
protocol | CT angiogram images
of the brain | CT angiogram images
of the brain |
| Segmentation of
region of interest | No; device does not
mark, highlight, or
direct users' attention
to a specific location
in the original image. | No; device does not
mark, highlight, or
direct users' attention
to a specific location
in the original image. |
| Core Algorithm | Artificial intelligence
algorithm with
database of images | Artificial intelligence
algorithm with
database of images |
| Device Output/
Notification | The software sends a
notification email to
the specialist
identifying the study
of interest.
Additionally, the
device provides user
with a link to DICOM
Web viewer allowing
users review the
images. | The software sends a
notification email to
the specialist
identifying the study
of interest.
Additionally, the
device provides user
with a link to DICOM
Web viewer allowing
users review the
images. |
| Triage effectiveness | Notification time is
defined as the time
between upload of
CTA (CTA images
are received in the
cloud) to the
availability of AI
results (user receives
a notification to view | Notification time is
defined as the time
between upload of
CTA (CTA images
are received in the
cloud) to the
availability of AI
results (user receives
a notification to view |
| | the suspected
finding). | the suspected
finding). |
| Independent of
standard of care
workflow | No cases are removed
from worklist | No cases are removed
from worklist |
6
Performance Data:
Summary of Clinical In a multi-center clinical study, the performance of the HALO clinical decision support algorithm for LVO detection was retrospectively evaluated in a consecutive patient cohort admitted to US comprehensive stroke centers.
434 CTA scans of the brain were collected. After exclusion, 427 patients were included for further analyses. Ground truth was established by an expert panel consisting of 3 neuro radiologists. For the primary endpoint: calculation of the performance of the HALO algorithm showed a sensitivity and specificity for LVO detection of respectively 91.3% (95% CI, 86.6%-94.8%) and 85.9% (95% CI, 80.6%-90.2%). The area under the curve (AUC) is 0.97.
For the secondary endpoints the median notification time for the detected LVO cases was 4 minutes 29 seconds, with a minimum of 3:47 and maximal 7:12.
The HALO performance with regard to sensitivity and specificity, and the notification time are both equivalent to that of the selected predicate device. Therefore, the HALO algorithm fulfils the requirement of a suitable screening tool to support diagnosis of LVOs by flagging these scans as requiring urgent radiologist review.
Substantial The clinical performance tests provided in this 510(k) premarket Equivalence notification demonstrate HALO is substantial equivalence to its predicate Conclusion: device, the previously cleared HALO (K200873). HALO has the same intended use and similar indications, technological characteristics, and principles of operation as its predicate device. The minor differences in indications do not alter the triage use of the device and do not affect its safety and effectiveness.