(53 days)
Not Found
Yes
The device description explicitly states that the algorithm uses "artificial intelligence CNN (convolutional neural networks)".
No.
therapeutic devices are devices that treat a disease or condition, and this device is intended for diagnosis (detection of disease).
No
The device is described as "radiological computer-assisted triage and notification software" intended to "assist hospital networks and trained radiologists in workflow triage by flagging and prioritizing studies with suspected positive findings of Intracranial Hemorrhage (ICH)." It explicitly states that the DICOM image preview is "devoid of diagnostic markers, and is not to be used for definitive diagnosis," indicating it is for triage and notification, not diagnosis.
Yes
The device description explicitly states it is "radiological computer-assisted triage and notification software" and a "component of the uAI Easy Triage platform". It processes DICOM files and communicates findings in DICOM format, indicating it operates solely on digital data without requiring or including dedicated hardware for its primary function.
Based on the provided information, this device is not an IVD (In Vitro Diagnostic).
Here's why:
- IVD Definition: In Vitro Diagnostics are medical devices used to perform tests on samples taken from the human body (like blood, urine, tissue) to provide information about a person's health.
- Device Function: The uAI Easy Triage ICH analyzes medical images (non-enhanced head CT scans) to assist in workflow triage. It does not perform tests on biological samples.
- Intended Use: The intended use is to flag and prioritize studies with suspected findings based on image analysis, not to diagnose or provide information about a patient's health through laboratory testing.
Therefore, while it is a medical device, it falls under the category of radiological computer-assisted triage and notification software, not an In Vitro Diagnostic.
No
The letter does not explicitly state that the FDA has reviewed and approved or cleared a PCCP for this specific device.
Intended Use / Indications for Use
uAI Easy Triage ICH is a radiological computer-assisted triage and notification software device indicated for analysis of non-enhanced head CT images. The device is intended to assist hospital networks and trained radiologists in workflow triage by flagging and prioritizing studies with suspected positive findings of Intracranial Hemorrhage (ICH).
Product codes
QAS
Device Description
uAI Easy Triage ICH is a radiological computer-assisted triage and notification software intended to assist radiologists by flagging potential intracranial hemorrhage (ICH) in non-contrast head CT images. The Triage Software is a component of the uAI Easy Triage platform, a comprehensive medical imaging communication system designed to integrate and deploy specialized image processing applications.
The uAI Easy Triage ICH algorithm uses artificial intelligence CNN (convolutional neural networks) and advanced image processing to triage the non-contrast CT images for suspicious intracranial hemorrhage.
The uAI Easy Triage ICH alerts users to new studies with suspicious ICH findings via pop-up notifications. The software provides both active and passive notification mechanisms. Active notifications are presented as an alert icon with a count of pending cases, and an alert status bar displaying patient details, suspected findings, and the time of examination. Passive notifications are represented by an icon beside the patient's name in the list for cases with detected ICH findings. Additionally, the application offers a DICOM image preview feature for radiologists to review. This preview is strictly informational, devoid of diagnostic markers, and is not to be used for definitive diagnosis.
The uAI Easy Triage ICH embodies the core algorithmic technology that identifies image characteristics consistent with intracranial hemorrhage. The application reads DICOM files, verifies their compatibility with the prescribed acquisition protocols, executes the triage algorithm, and communicates findings in DICOM format, compatible with the uAI Easy Triage Platform.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
non-enhanced head CT images.
Anatomical Site
Head
Indicated Patient Age Range
Not Found
Intended User / Care Setting
hospital networks and trained radiologists
Description of the training set, sample size, data source, and annotation protocol
To train and internally test this ICH CADt device, a total of 9791 data points were collected from multiple sites as well as cases in China. Only cases that met the inclusion criteria were used. The reference standard (ground truth) was established in the form of ICH positive/negative by radiologists.
9791 cases were only used for training and internal testing and final validation data was from USA and independent from those used for training and internal testing.
Algorithm training of uAI Portal software has been conducted on images collected from China as training dataset. The dataset ensures a variety of data for different gender, age, equipment and CT protocol.
Description of the test set, sample size, data source, and annotation protocol
Algorithm validation has been conducted on data from the USA.
A total of 295 non-contrast CT scans (studies) were obtained from different zip codes across four U.S. states.
There were approximately equal numbers of positive and negative cases (147 of images with ICH and 148 without ICH, respectively) included in the analysis.
Regarding the validation of the algorithm, the test data was used independently from that used for training, tuning and internal testing dataset.
Validation data demographic information:
Gender: Male (49%), Female (51%)
Age Ranges (Years): 18-45 (17%), 45-65 (36%), 65+ (47%)
Race Group: White (63%), Black (18%), others (19%)
Equipment: GE (17%), Philips (21%), Siemens (62%)
ICH Subtypes: Intraparenchymal Hemorrhage (IPH) (30%), Intraventricular Hemorrhage (IVH) (17%), Subarachnoid Hemorrhage (SAH) (24%), Subdural Hemorrhage (SDH) (22%), Extradural Hemorrhage (EDH) (0.3%)
Sensitivity and specificity of uAI Easy Triage ICH in processing of non-contrast head CT have been analyzed by comparison to a ground truth established by majority read of 3 U.S .- board-certified neuroradiologists.
Summary of Performance Studies
Study Type: Retrospective study
Sample Size: 295 non-contrast CT scans (studies)
Key Metrics:
Sensitivity: 92% (95% CI: 86%-96%)
Specificity: 95% (95% CI: 90%-98%)
Average Time to Notification: 41.1 seconds (95% CI: 40.1, 42.1)
Key Results: The performance levels (sensitivity and specificity) met the predefined acceptance criteria of 80% and the time to notification of the device is similar to the predicate device's time.
Key Metrics
Sensitivity: 92% (95% CI: 86%-96%)
Specificity: 95% (95% CI: 90%-98%)
Predicate Device(s)
Reference Device(s)
Not Found
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.
0
September 24, 2024
Image /page/0/Picture/1 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, with the letters FDA in a blue box. To the right of the blue box is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.
Shanghai United Imaging Intelligence Co., Ltd. % Nima Akhlaghi Director, Digital Health, AI & Imaging Center Lead MCRA Digital Health 803 7th Street NW, 3rd Floor WASHINGTON, DISTRICT OF COLUMBIA 20001
Re: K242292
Trade/Device Name: uAI Easy Triage ICH Regulation Number: 21 CFR 892.2080 Regulation Name: Radiological Computer Aided Triage And Notification Software Regulatory Class: Class II Product Code: QAS Dated: August 1, 2024 Received: August 2, 2024
Dear Nima Akhlaghi:
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"
1
(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 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 (OS) 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 Rule"). 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-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 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-regulatory
2
assistance/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,
Samuel for
Jessica Lamb, Ph.D. Assistant Director Imaging Software Team 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
3
Indications for Use
Submission Number (if known)
Device Name
uAl Easy Triage ICH
Indications for Use (Describe)
uAl Easy Triage ICH is a radiological computer-assisted triage and notification software device indicated for analysis of non-enhanced head CT images. The device is intended to assist hospital networks and trained radiologists in workflow triage by flagging and prioritizing studies with suspected positive findings of Intracranial Hemorrhage (ICH).
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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4
510 (k) SUMMARY
1. Date of Preparation:
August 01, 2024
2. Sponsor Identification
Shanghai United Imaging Intelligence Co., Ltd. No. 701 Yunjin Road, Xuhui District, Shanghai, 200232, PEOPLE'S REPUBLIC OF CHINA
Primary Contact Correspondent : MCRA Digital Health Contact Person: Nima Akhlaghi Position: Director, Digital Health, AI & Imaging Center Lead Tel: 202-742-3889 Email: nakhlaghi(@mcra.com
Applicant Contact Person: Zhao Xiaojing Position: Quality & Regulatory Manager Tel: +86-021-67076888-5386 Email: xiaojing.zhao@uii-ai.com
3. Identification of Proposed Device
Trade Name: uAI Easy Triage ICH Common Name: Radiological computer aided triage and notification software Model(s): uAI Easy Triage ICH
Regulatorv Information
Classification Name: Radiological computer aided triage and notification software Classification: II Product Code: QAS Regulation Number: 21 CFR 892.2080 Review Panel: Radiology
-
- Identification of Predicate Device(s)
Page 1 of 12
- Identification of Predicate Device(s)
5
Predicate Device 510(k) Number: K221716 Device Name: CINA
5. Device Description
uAI Easy Triage ICH is a radiological computer-assisted triage and notification software intended to assist radiologists by flagging potential intracranial hemorrhage (ICH) in non-contrast head CT images. The Triage Software is a component of the uAI Easy Triage platform, a comprehensive medical imaging communication system designed to integrate and deploy specialized image processing applications.
The uAI Easy Triage ICH algorithm uses artificial intelligence CNN (convolutional neural networks) and advanced image processing to triage the non-contrast CT images for suspicious intracranial hemorrhage.
To train and internally test this ICH CADt device, a total of 9791 data points were collected from multiple sites as well as cases in China. Only cases that met the inclusion criteria were used. The reference standard (ground truth) was established in the form of ICH positive/negative by radiologists.
To clarify, 9791 cases were only used for training and internal testing and final validation data was from USA and independent from those used for training and internal testing.
6. Indications for use
uAI Easy Triage ICH is a radiological computer-assisted triage and notification software device indicated for analysis of non-enhanced head CT images. The device is intended to assist hospital networks and trained radiologists in workflow triage by flagging and prioritizing studies with suspected positive findings of Intracranial Hemorrhage (ICH).
7. Summary of Technological Characteristics
uAI Easy Triage ICH is a radiological computer-assisted triage and notification software intended to assist radiologists by flagging potential ICH in non-contrast head CT images. The software is a component of the uAI Easy Triage platform, a
6
comprehensive medical imaging communication system designed to integrate and deploy specialized image processing applications.
The uAI Easy Triage ICH alerts users to new studies with suspicious ICH findings via pop-up notifications. The software provides both active and passive notification mechanisms. Active notifications are presented as an alert icon with a count of pending cases, and an alert status bar displaying patient details, suspected findings, and the time of examination. Passive notifications are represented by an icon beside the patient's name in the list for cases with detected ICH findings. Additionally, the application offers a DICOM image preview feature for radiologists to review. This preview is strictly informational, devoid of diagnostic markers, and is not to be used for definitive diagnosis.
The uAI Easy Triage ICH embodies the core algorithmic technology that identifies image characteristics consistent with intracranial hemorrhage. The application reads DICOM files, verifies their compatibility with the prescribed acquisition protocols, executes the triage algorithm, and communicates findings in DICOM format, compatible with the uAI Easy Triage Platform.
7
Table 1 Substantial Equivalence Table
| Item | Proposed Device
uAI Easy Triage ICH | Predicate Device
CINA (K221716) | Remark |
|---------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Device Classification Name | Radiological Computer Aided
Triage And Notification Software | Radiological Computer Aided
Triage And Notification Software | Same |
| Product Code | QAS | QAS | Same |
| Regulation Number | 21 CFR 892.2080 | 21 CFR 892.2080 | Same |
| Device Class | II | II | Same |
| Classification Panel | Radiology | Radiology | Same |
| Intended Use/Indications for
Use | uAI Easy Triage ICH is a
radiological computer-assisted
triage and notification software
device indicated for analysis of
non-enhanced head CT images.
The device is intended to assist
hospital networks and trained
radiologists in workflow triage by | Cina is a radiological computer
aided triage and notification
software indicated for use in the
analysis of (1) non-enhanced head
CT images and (2) CT
angiography of the head.
The device is intended to assist | Compared to predicate device, the
proposed device provides one
applications for ICH while the
predicate device CINA (K221716)
provides two applications for ICH
and LVO.
uAI Easy Triage ICH and the
predicate device CINA(K221716)
have the same intended use |
| Item | Proposed Device
uAI Easy Triage ICH | Predicate Device
CINA (K221716) | Remark |
| | flagging and prioritizing studies
with suspected positive findings of
Intracranial Hemorrhage (ICH). | hospital networks and trained
radiologists in workflow triage by
flagging and communicating
suspected positive findings of (1)
head CT images for Intracranial
Hemorrhage (ICH) and (2) head
CT angiography for large vessel
occlusion (LVO) of the anterior
circulation (distal ICA, MCA-M1
or proximal MCA-M2).
Cina uses an artificial intelligence
algorithm to analyze images and
highlight cases with detected (1)
ICH or (2) LVO on a standalone
Web application in parallel to the
ongoing standard of care image
interpretation. The user is
presented with notifications for
cases with suspected ICH or LVO | and\indications for use in terms of
finding suspected intracranial
hemorrhage in non-enhanced head
CT, flagging suspected cases, and
indicating the case to the attention of
the clinician. |
| Item | Proposed Device
uAI Easy Triage ICH | Predicate Device
CINA (K221716) | Remark |
| | | findings.
Notifications include compressed
preview images that are meant for
informational purposes only, and
are not intended for diagnostic use
beyond notification. The device
does not alter the original medical
image, and it is not intended to be
used as a diagnostic device.
The results of Cina are intended to
be used in conjunction with other
patient information and based on
professional judgement to assist
with triage/prioritization of
medical images. Notified
clinicians are ultimately
responsible for reviewing full
images per the standard of care. | |
| Item | Proposed Device
uAI Easy Triage ICH | Predicate Device
CINA (K221716) | Remark |
| User population | Radiologist | Radiologist | Same |
| Anatomical region of interest | Head | Head | Same |
| Data acquisition protocol | Non-contrast CT scan of the head | Non-contrast CT scan of the head
or neck and CT angiogram images
of the brain | Compared to predicate device, the
proposed device supports non-
contrast head CT data for ICH
application while the predicate device
support non-contrast head CT data for
ICH application or neck and brain CT
angiogram data for LVO application.
The difference between the proposed
device and the predicate device will
not impact the safety and
effectiveness of the subject device. |
| View DICOM data | DICOM information about the
patient, study and current image | DICOM information about the
patient, study and current image | Same |
| Segmentation of region of
interest | No; device does not mark,
highlight, or direct users' attention
to a specific location in the | No; device does not mark,
highlight, or direct users' attention
to a specific location in the | Same |
8
UNITED IMAGING C Intelligence
Page 5 of 12
9
UNITED IMAGING Intelligence
C
10
UNITED IMAGING Intelligence
C
11
UNITED IM/GING ██ Intelligence
| 1 |
|---|
| Item | Proposed Device
uAI Easy Triage ICH | Predicate Device
CINA (K221716) | Remark |
|----------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| | original image | original image | |
| Algorithm | Artificial intelligence algorithm
with database of images | Artificial intelligence algorithm
with database of images | Same |
| Notification /
Prioritization | Yes | Yes | Same |
| Preview
images | Presentation of a preview of the
study for initial assessment not
meant for diagnostic purposes.
The device operates in parallel
with the standard of care, which
remains the default option for all
cases. | Presentation of a preview of the
study for initial assessment not
meant for diagnostic purposes.
The device operates in parallel
with the standard of care, which
remains the default option for all
cases. | Same |
| Alteration of
original image | No | No | Same |
| Removal of | No | No | Same |
| Item | Proposed Device
uAI Easy Triage ICH | Predicate Device
CINA (K221716) | Remark |
| cases from
worklist queue | | | |
| Structure | - ICH image processing
applications
- uAI Easy Triage Platform,
including Alert Icon, Patient
Management, and Image Viewer. | - LVO and ICH image processing
applications - Cina Platform (worklist and
Image Viewer) | Compared to predicate device, the
proposed device have same software
structure and add an alert icon
module to pop-up the suspected
positive findings of ICH. The
difference between the proposed
device and the predicate device will
not impact the safety and
effectiveness of the subject device. |
12
UNITED IMΛGING Intelligence 바
13
8. Performance Data
The following performance data were provided in support of the substantial equivalence determination.
Biocompatibility
Not Applicable to the proposed device, because the device is stand-alone software.
Electrical Safety and Electromagnetic Compatibility (EMC)
Not Applicable to the proposed device, because the device is stand-alone software.
Software Verification and Validation
Software verification and validation testing was provided to demonstrate safety and efficacy of the proposed device.
Per FDA Guidance "GUIDANCE FOR THE CONTENT OF PRE-MARKET SUBMISSIONS FOR SOFTWARE CONTAINED IN DEVICES", dated June 14, 2023, the Level of Concern of the software contained in the proposed device is determined to be: Basic Documentation Level.
Those documentations include:
- · Software Description
- Risk management File
- · Software Requirements Specification (SRS)
- · Software Architecture Diagram
- · Software Development Environment Description
- · Software Verification and Validation
- · Software Version History
- · Cybersecurity Documents
Animal Study
No animal study was required.
Clinical Studies
No clinical study was required.
Performance Testing
Algorithm training of uAI Portal software has been conducted on images collected from China as training dataset. The dataset ensures a variety of data for different gender,
Page 10 of 12
14
age, equipment and CT protocol. Algorithm validation has been conducted on data from the USA. To validate the uAI Easy Triage ICH software from a clinical perspective, the AI-based algorithm contained in the product underwent a retrospective study to evaluate the performance of uAI Easy Triage ICH in terms of sensitivity, specificity and time to notification to identify/notify patients with suspected Intracranial Hemorrhage (ICH) processing non-contrast CT images.
Sensitivity and specificity of uAI Easy Triage ICH in processing of non-contrast head CT have been analyzed by comparison to a ground truth established by majority read of 3 U.S .- board-certified neuroradiologists.
A total of 295 non-contrast CT scans (studies) were obtained from different zip codes across four U.S. states. There were approximately equal numbers of positive and negative cases (147 of images with ICH and 148 without ICH, respectively) included in the analysis.
Regarding the validation of the algorithm, the test data was used independently from that used for training, tuning and internal testing dataset.
The validation data demographic information is summarized below.
| Subgroup | Breakdown | Sample Size |
|---|---|---|
| Gender | Male | 49% |
| Female | 51% | |
| Age Ranges (Years) | 18-45 | 17% |
| 45-65 | 36% | |
| 65+ | 47% | |
| Race Group | White | 63% |
| Black | 18% | |
| others | 19% | |
| Equipment | GE | 17% |
| Philips | 21% | |
| Siemens | 62% | |
| ICH Subtypes | Intraparenchymal Hemorrhage (IPH) | 30% |
| Intraventricular Hemorrhage (IVH) | 17% | |
| Subarachnoid Hemorrhage (SAH) | 24% | |
| Subdural Hemorrhage (SDH) | 22% | |
| Extradural Hemorrhage (EDH) | 0.3% |
Table 2 Clinical testing data subgroup information
Comparing the uAI Easy Triage ICH software output to the ground truth, the sensitivity and specificity of uAI Easy Triage ICH are 92% (95% CI: 86%-96%) and 95% (95% CI: 90%-98%), respectively, exceeding the acceptance criteria of 80%.
Multiple subgroups of interest were considered in the analysis. In fact, the validation data was acquired from different regions across the U.S. to account for race/ethnicity
15
in the intended U.S. patient population. Detailed subgroup analysis were reported in the labeling.
The uAI Easy Triage ICH Time to Notification was measured during the study. The average Time to Notification in seconds was 41.1 with a 95% confidence interval (CI) for the mean equaling (40.1, 42.1).
In conclusion, the performance of the study for the validation of uAI Easy Triage ICH demonstrates that the device is effective for triage and notification as the performance levels (sensitivity and specificity) meet the predefined acceptance criteria and the time to notification of the device is similar to the predicate device's time.
Other Standards and Guidance
- · NEMA PS 3.1 3.20 Digital Imaging and Communications in Medicine (DICOM) Set
- · ISO 14971 Medical devices Application of risk management to medical devices (Third Edition 2019-12).
- · IEC 62304 Medical device software Software life cycle processes (Edition 1.1 2015-06 CONSOLIDATED VERSION).
- · Cybersecurity in Medical Devices: Quality System Considerations and Content of Premarket Submissions (Document issued on September 27, 2023).
9. Substantially Equivalent (SE) Conclusion
Compare to the predicate device, the subject device has a subset of the predicate application which resulted in a limited indication for use. The subject device has similar technological characteristics compare to the predicate device and the difference does not raise any new question of safety and effectiveness. Therefore the subject device is substantially equivalent to the proposed predicate.