(176 days)
Not Found
Yes
The document explicitly states that the software uses "deep learning algorithms" and "deep learning techniques" to analyze cases and identify suspected ICH findings. Deep learning is a subset of machine learning.
No
The device aids in prioritizing imaging studies for review but does not provide direct therapy or treatment.
No
The crucial phrase is "Its results are not intended to be used on a stand-alone basis for clinical decision-making nor is it intended to rule out hemorrhage or otherwise preclude clinical assessment of CT studies." This indicates that the device merely aids in prioritization rather than diagnosing.
Yes
The device is described as a "software workflow tool" and a "radiological computer-assisted triage and notification software system." It analyzes existing CT images and provides notifications to a PACS/workstation. There is no mention of any accompanying hardware or hardware components included with the device.
Based on the provided information, this device is not an In Vitro Diagnostic (IVD).
Here's why:
- IVD Definition: In Vitro Diagnostics are medical devices intended to be used in vitro for the examination of specimens, including blood, tissue, and urine, from the human body to provide information for diagnostic, monitoring, or screening purposes.
- Device Function: The EFAI ICHCT is a software tool that analyzes medical images (CT scans). It does not analyze biological specimens from the human body.
- Intended Use: Its intended use is to aid in prioritizing the clinical assessment of non-contrast head CT cases with features suggestive of acute intracranial hemorrhage. This is a function related to image analysis and workflow prioritization, not the analysis of biological samples.
Therefore, the EFAI ICHCT falls under the category of a radiological computer-assisted triage and notification software system, which is a type of medical device, but not an In Vitro Diagnostic.
No
The 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
EFAI ICHCT is a software workflow tool designed to aid in prioritizing the clinical assessment of adult non-contrast head CT cases with features suggestive of acute intracranial hemorrhage (ICH). EFAI ICHCT analyzes cases using deep learning algorithms to identify suspected ICH findings. It makes case-level output available to a PACS/workstation for worklist prioritization or triage.
EFAI ICHCT is not intended to direct attention to specific portions of an image or to anomalies other than acute ICH. Its results are not intended to be used on a stand-alone basis for clinical decision-making nor is it intended to rule out hemorrhage or otherwise preclude clinical assessment of CT studies.
Product codes (comma separated list FDA assigned to the subject device)
QAS
Device Description
EFAI NEUROSUITE CT ICH ASSESSMENT SYSTEM (EFAI ICHCT) is a radiological computer-assisted triage and notification software system. The software uses deep learning techniques to automatically analyze non-contrast head CTs and alerts the PACS/RIS workstation once images with features suggestive of acute ICH are identified.
Through the use of EFAI ICHCT, a radiologist is able to review studies with features suggestive of acute ICH earlier than in standard of care workflow.
The device is intended to provide a passive notification through the PACS/workstation to the radiologists indicating the existence of a case that may potentially benefit from the prioritization. It does not mark, highlight, or direct users' attention to a specific location on the original non-contrast head CT. The device aims to aid in prioritization and triage of radiological medical images only.
Mentions image processing
Not Found
Mentions AI, DNN, or ML
EFAI ICHCT analyzes cases using deep learning algorithms to identify suspected ICH findings.
The software uses deep learning techniques to automatically analyze non-contrast head CTs
AI Used Yes
Input Imaging Modality
Non-contrast Head CT
Anatomical Site
Head
Indicated Patient Age Range
Adult
Intended User / Care Setting
Radiologists/Trained Clinicians
PACS/workstation for worklist prioritization or triage.
Description of the training set, sample size, data source, and annotation protocol
During the process of model development, a total of 5,365 adult cases were retrospectively collected between 2010 and 2018 from Taiwan. These cases were subsequently divided into training, validation, and testing datasets, consisting of 3,776, 1,038, and 551 cases, respectively.
Description of the test set, sample size, data source, and annotation protocol
During the process of model development, a total of 5,365 adult cases were retrospectively collected between 2010 and 2018 from Taiwan. These cases were subsequently divided into training, validation, and testing datasets, consisting of 3,776, 1,038, and 551 cases, respectively.
Ever Fortune.AI conducted a retrospective, blinded, multisite clinical validation study with the proposed device EFAI ICHCT with a pre-determined primary and secondary endpoint and performance goals to evaluate the performance of the EFAI ICHCT in identifying intracranial hemorrhage (ICH) findings from non-contrast head computed tomography (CT) scans on a validation dataset of 288 CT studies (132 ICH positives and 156 ICH negatives) consecutively collected from 23 clinical sites in the United States (U.S.). Each patient included only one CT study. None of the studies was used as part of the EFAI ICHCT model development or analytical validation testing.
The study population contained 49.31% females and 50.69% males; the mean age of cases was 59.43 years. The ethnic and racial distribution includes 52.43% White, 10.42% Asian, 9.38% Black or African American, 7.99% Hispanic, and 19.79% others. The CT scanner manufacturers of images were acquired from Toshiba, Hitachi, Philips, Siemens, GE Medical Systems, and Canon. The CT is taken in a standard brain CT protocol.
The presence of ICH in each case was determined independently by three U.S. board-certified neuroradiologists, and the reference standard (ground truth) was generated by the majority agreement between the three experts. The performance acceptance criteria were set such that the lower bounds of 95% confidence intervals of both sensitivity and specificity should exceed 0.8.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Study Type: Retrospective, blinded, multisite clinical validation study.
Sample Size: 288 CT studies (132 ICH positives and 156 ICH negatives).
Standalone Performance: The observed results of the standalone performance validation study demonstrated that EFAI ICHCT by itself, in the absence of any interaction with a clinician, can provide case-level notifications with features suggestive of ICH with satisfactory results.
Key Results: The EFAI ICHCT was able to demonstrate sensitivity and specificity of 0.947 (95% CI-0.895-0.974) and 0.949 (95% CI=0.902-0.974) respectively, as well as an AUROC of 0.983 (95% Cl=0.969-0.997), which is substantially equivalent to the predicate device (CuraRad-ICH, K192167). The observed system processing time per study is 34.96 seconds (95% CI: 33.89-36.03) on average and was comparable with the predicate device, CuraRad-ICH (CuraCloud, K192167, 43 seconds). In addition, the subgroup analysis results, which encompassed different genders, age groups, CT manufacturer groups, CT slice thickness groups, and types of ICH, revealed that EFAI ICHCT maintained a consistently high performance, indicating the device's reliability and effectiveness across diverse subgroups. No significant statistical difference was observed between EFAI ICHCT and GT. We found the device performs consistently and reliably under these circumstances.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Sensitivity: 0.947 (95% CI: 0.895 - 0.974)
Specificity: 0.949 (95% CI: 0.902 - 0.974)
AUROC: 0.983 (95% CI=0.969-0.997)
Processing time: 34.96 seconds (95% CI: 33.89 - 36.03 seconds)
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.
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Image /page/0/Picture/0 description: The image contains the logos of the Department of Health & Human Services and the Food and Drug Administration (FDA). The Department of Health & Human Services logo is on the left, and the FDA logo is on the right. The FDA logo includes the text "U.S. Food & Drug Administration" in blue.
Ever Fortune.AI Co., Ltd. Ti-Hao Wang Chief Technology Officer 8F., No. 573, Sec. 2, Taiwan Blvd., West Dist. Taichung City, 403020 Taiwan
October 4, 2023
Re: K231025
Trade/Device Name: EFAI NeuroSuite CT ICH Assessment System Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological Computer Aided Triage And Notification Software Regulatory Class: Class II Product Code: QAS Dated: September 4, 2023 Received: September 5, 2023
Dear Ti-Hao Wang:
We have reviewed your section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (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.
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).
1
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 QS 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.
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 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.
Jessica Lamb
Jessica Lamb Assistant Director DHT8B: Division of Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
2
Indications for Use
510(k) Number (if known) K231025
Device Name EFAI NEUROSUITE CT ICH ASSESSMENT SYSTEM
Indications for Use (Describe)
EFAI ICHCT is a software workflow tool designed to aid in prioritizing the clinical assessment of adult non-contrast head CT cases with features suggestive of acute intracranial hemorrhage (ICH). EFAI ICHCT analyzes cases using deep learning algorithms to identify suspected ICH findings. It makes case-level output available to a PACS/workstation for worklist prioritization or triage.
EFAI ICHCT is not intended to direct attention to specific portions of an image or to anomalies other than acute ICH. Its results are not intended to be used on a stand-alone basis for clinical decision-making nor is it intended to rule out hemorrhage or otherwise preclude clinical assessment of CT studies.
| 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)
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Image /page/3/Picture/0 description: The image shows the logo for Ever Fortune AI. The logo consists of a stylized person icon in teal with a green globe with a network pattern on top of the person icon. To the right of the icon is the text "EVER" in teal, with "FORTUNE.AI" in teal below it. The globe icon is also incorporated into the "O" in "FORTUNE".
510(k) Summary
1. General Information
| 510(k) Sponsor | Ever Fortune.AI Co., Ltd. |
|---|---|
| Address | Rm. D, 8F. No. 573, Sec. 2 Taiwan Blvd. |
| West Dist. | |
| Taichung City 403020 | |
| TAIWAN | |
| Applicant | Joseph Chang |
| Contact Information | 886-04-23213838 #216 |
| joseph.chang@everfortune.ai | |
| Correspondence Person | Ti-Hao Wang, MD |
| Contact Information | 886-04-23213838 #168 |
| tihao.wang@everfortune.ai | |
| Date Prepared | April 10, 2023 |
2. Proposed Device
| Proprietary Name | EFAI NEUROSUITE CT ICH ASSESSMENT SYSTEM |
|---|---|
| Common Name | EFAI ICHCT100 |
| Classification Name | Radiological Computer-Assisted Triage And Notification Software |
| Regulation Number | 21 CFR 892.2080 |
| Regulation Name | Radiological Computer Aided Triage and Notification Software |
| Product Code | QAS |
| Regulatory Class | II |
3. Predicate Device
| Proprietary Name | CuraRad-ICH |
|---|---|
| Premarket Notification | K192167 |
| Classification Name | Radiological Computer-Assisted Triage And Notification Software |
| Regulation Number | 21 CFR 892.2080 |
| Regulation Name | Radiological Computer Aided Triage and Notification Software |
| Product Code | QAS |
| Regulatory Class | II |
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Image /page/4/Picture/0 description: The image shows the logo for Ever Fortune AI. The logo consists of a teal-colored abstract figure that resembles a person with a circle above their head. The circle contains a green network of lines and dots. To the right of the figure is the text "EVER FORTUNE.AI" in a teal color.
4. Device Description
EFAI NEUROSUITE CT ICH ASSESSMENT SYSTEM (EFAI ICHCT) is a radiological computer-assisted triage and notification software system. The software uses deep learning techniques to automatically analyze non-contrast head CTs and alerts the PACS/RIS workstation once images with features suggestive of acute ICH are identified.
During the process of model development, a total of 5,365 adult cases were retrospectively collected between 2010 and 2018 from Taiwan. These cases were subsequently divided into training, validation, and testing datasets, consisting of 3,776, 1,038, and 551 cases, respectively.
Through the use of EFAI ICHCT, a radiologist is able to review studies with features suggestive of acute ICH earlier than in standard of care workflow.
The device is intended to provide a passive notification through the PACS/workstation to the radiologists indicating the existence of a case that may potentially benefit from the prioritization. It does not mark, highlight, or direct users' attention to a specific location on the original non-contrast head CT. The device aims to aid in prioritization and triage of radiological medical images only.
5. Intended Use / Indications for Use
EFAI ICHCT is a software workflow tool designed to aid in prioritizing the clinical assessment of adult non-contrast head CT cases with features suggestive of acute intracranial hemorrhage (ICH). EFAI ICHCT analyzes cases using deep learning algorithms to identify suspected ICH findings. It makes case-level output available to a PACS/workstation for worklist prioritization or triage.
EFAI ICHCT is not intended to direct attention to specific portions of an image or to anomalies other than acute ICH. Its results are not intended to be used on a stand-alone basis for clinical decision-making nor is it intended to rule out hemorrhage or otherwise preclude clinical assessment of CT studies.
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Image /page/5/Picture/0 description: The image shows a logo for a company called EVER FORTUNE.AI. The logo consists of a stylized human figure with a green globe as its head, and the company name is written in teal next to it. The word "FORTUNE" has a globe in place of the letter "O".
6. Comparison of Technological Characteristics with Predicate Device
Table below provides a comparison of the intended use and key technological features of EFAI ICHCT with that of the Primary Predicate, CuraRad-ICH (K192167).
| Company | Ever Fortune.AI Co., Ltd.
(EFAI) | CuraCloud Corp. |
|------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Device Name | EFAI ICHCT | CuraRad-ICH |
| 510k Number | K231025 | K192167 |
| Regulation No. | 21CFR 892.2080 | 21CFR 892.2080 |
| Classification | II | II |
| Product Code | QAS | QAS |
| Intended
Use/Indication for
Use | EFAI ICHCT is a software
workflow tool designed to aid in
prioritizing the clinical
assessment of adult non-contrast
head CT cases with features
suggestive of acute intracranial
hemorrhage (ICH). EFAI
ICHCT analyzes cases using
deep learning algorithms to
identify suspected ICH findings.
It makes case-level output
available to a PACS/workstation
for worklist prioritization or
triage.
EFAI ICHCT is not intended to
direct attention to specific
portions of an image or to
anomalies other than acute ICH.
Its results are not intended to be
used on a stand-alone basis for
clinical decision-making nor is it
intended to rule out hemorrhage
or otherwise preclude clinical
assessment of CT studies. | CuraRad-ICH is a software
workflow tool designed to aid
in prioritizing the clinical
assessment of adult
non-contrast head CT cases
with features suggestive of
acute intracranial hemorrhage.
CuraRad-ICH analyzes cases
using deep learning algorithms
to identify suspected ICH
findings. It makes case-level
output available to a
PACS/workstation for worklist
prioritization or triage.
CuraRad-ICH is not intended to
direct attention to specific
portions of an image or to
anomalies other than acute ICH.
Its results are not intended to be
used on a stand-alone basis for
clinical decision-making nor is it
intended to rule out
hemorrhage or otherwise
preclude clinical assessment of
CT studies. |
| Population | Adult patients indicated for
non-contrast head CT | Adult patients indicated for
non-contrast head CT |
| Intended Clinical
End User | Radiologists/Trained Clinicians | Radiologists/Trained Clinicians |
| AI Used | Yes | Yes |
| Data Acquisition | Acquires medical image data
from DICOM compliant
imaging devices and modalities. | Acquires medical image data
from DICOM compliant
imaging devices and modalities. |
| Input Image
Modality | Non-contrast Head CT | Non-contrast Head CT |
| Non-Diagnostic
Preview | No | No |
| Clinical condition | Acute Intracranial Hemorrhage | Acute Intracranial Hemorrhage |
| Independent of
standard of care
workflow | Yes; No cases are removed from
worklist | Yes; No cases are removed
from worklist |
| Output | Suspected ICH (Yes or No) | Suspected ICH (Yes or No) |
| Results Receiver | PACS / Workstation | PACS / Workstation |
| Performance
Results | Sensitivity: 0.947
(95% CI: 0.895 - 0.974) | Sensitivity: 0.906
(95% CI: 0.859 - 0.942) |
| | Specificity: 0.949
(95% CI: 0.902 - 0.974) | Specificity: 0.931
(95% CI: 0.883 - 0.964) |
| | Processing time: 34.96 seconds
(95% CI: 33.89 - 36.03 seconds) | Processing time: 43 seconds
(95% CI: 39 - 46 seconds) |
Table - Comparison with the Predicate Device.
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Image /page/6/Picture/0 description: The image shows the logo for Ever Fortune AI. The logo consists of a teal-colored icon that resembles a person with a globe as their head, and the text "EVER FORTUNE.AI" in teal. The globe on the icon and the "O" in "FORTUNE" are both designed with a network of interconnected dots, suggesting a focus on technology and global connectivity.
The proposed device, EFAI ICHCT, is substantially equivalent to the claimed predicate, CuraRad-ICH (K192167).
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Image /page/7/Picture/0 description: The image shows the logo for Ever Fortune AI. The logo consists of a teal-colored abstract figure with a circle on top, resembling a person. The circle on top has a green network design inside. To the right of the figure is the text "EVER" in teal, with "FORTUNE.AI" below it, also in teal. The "O" in fortune is replaced with a similar green network design.
7. Performance Data
Performance of the EFAI ICHCT has been evaluated and verified in accordance with software specifications and applicable performance standards through software verification and validation testing. Additionally, the software validation activities were performed in accordance with IEC 62304:2006/A1:2016 - Medical device software - Software life cycle processes, in addition to the FDA Guidance documents, "Guidance for the Content of Premarket Submissions for Software in Medical Devices"(2005), and "Content of Premarket Submission for Management of Cybersecurity in Medical Devices."
Ever Fortune.AI conducted a retrospective, blinded, multisite clinical validation study with the proposed device EFAI ICHCT with a pre-determined primary and secondary endpoint and performance goals to evaluate the performance of the EFAI ICHCT in identifying intracranial hemorrhage (ICH) findings from non-contrast head computed tomography (CT) scans on a validation dataset of 288 CT studies (132 ICH positives and 156 ICH negatives) consecutively collected from 23 clinical sites in the United States (U.S.). Each patient included only one CT study. None of the studies was used as part of the EFAI ICHCT model development or analytical validation testing.
The study population contained 49.31% females and 50.69% males; the mean age of cases was 59.43 years. The ethnic and racial distribution includes 52.43% White, 10.42% Asian, 9.38% Black or African American, 7.99% Hispanic, and 19.79% others. The CT scanner manufacturers of images were acquired from Toshiba, Hitachi, Philips, Siemens, GE Medical Systems, and Canon. The CT is taken in a standard brain CT protocol.
The presence of ICH in each case was determined independently by three U.S. board-certified neuroradiologists, and the reference standard (ground truth) was generated by the majority agreement between the three experts. The performance acceptance criteria were set such that the lower bounds of 95% confidence intervals of both sensitivity and specificity should exceed 0.8.
The observed results of the standalone performance validation study demonstrated that EFAI ICHCT by itself, in the absence of any interaction with a clinician, can provide case-level notifications with features suggestive of ICH with satisfactory results. The EFAI ICHCT was able to demonstrate sensitivity and specificity of 0.947 (95% CI-0.895-0.974) and 0.949 (95% CI=0.902-0.974) respectively, as well as an AUROC of 0.983 (95% Cl=0.969-0.997), which is substantially equivalent to the predicate device (CuraRad-ICH, K192167). The observed system processing time per study is 34.96 seconds (95% CI: 33.89-36.03) on average and was comparable with the predicate device, CuraRad-ICH
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Image /page/8/Picture/0 description: The image contains a logo for a company called "EVER FORTUNE.AI". The logo consists of a stylized human figure in teal with a green circle containing a network of interconnected dots above its head. To the right of the figure, the company name is written in teal, with "EVER" stacked above "FORTUNE.AI". The dot in ".AI" is green.
(CuraCloud, K192167, 43 seconds). In addition, the subgroup analysis results, which encompassed different genders, age groups, CT manufacturer groups, CT slice thickness groups, and types of ICH, revealed that EFAI ICHCT maintained a consistently high performance, indicating the device's reliability and effectiveness across diverse subgroups. No significant statistical difference was observed between EFAI ICHCT and GT. We found the device performs consistently and reliably under these circumstances. The results demonstrate that the EFAI ICHCT device is as safe and effective as the predicate device CuraRad-ICH.
8. Conclusion
Based on the information submitted in this premarket notification, and based on the indications for use, technological characteristics, and performance testing, the EFAI ICHCT raises no new questions of safety and effectiveness and is substantially equivalent to the predicate device in terms of safety, effectiveness, and performance.