(108 days)
Yes
The device description explicitly states that it implements artificial intelligence (AI) utilizing non-adaptive machine learning algorithms and a deep neural network (DNN) model.
No
The device is described as an assistive tool for measurement and is not intended to provide treatment or therapy. It informs clinical management but does not replace clinical decision-making.
Yes
Explanation: The device is intended for "measurements of bladder volume" which provides specific anatomical information for clinical diagnosis and management, such as assessing bladder function or fluid balance. While it is an assistive tool and not intended to replace clinical decision-making, it provides measurements that are used to inform clinical management, which is a key characteristic of a diagnostic device.
No
The device is described as "incorporated into the Clarius App software for use as part of the complete Clarius Ultrasound Scanner system product offering". It explicitly states "Clarius Bladder Al is not a stand-alone software device" and is intended for use with specific Clarius Ultrasound Scanner system transducers. This indicates it is a component of a larger hardware/software system, not a software-only device.
Based on the provided information, the Clarius Bladder AI device is not an In Vitro Diagnostic (IVD).
Here's why:
- IVDs are used to examine specimens derived from the human body. The Clarius Bladder AI processes ultrasound data acquired directly from the patient's body (non-invasive measurements of bladder volume on ultrasound data). It does not analyze blood, urine, tissue, or other biological samples.
- The intended use is for image processing and measurement. The device's primary function is to assist healthcare professionals in measuring bladder volume from ultrasound images. This is a function related to medical imaging and measurement, not the analysis of biological specimens.
- The device description clearly states it's a radiological (ultrasound) image processing software application. This further reinforces its role in medical imaging rather than in vitro testing.
While the device uses AI and provides measurements that can inform clinical management, its operation and intended use fall outside the definition of an In Vitro Diagnostic device.
No
The provided text does not contain any explicit statement that the FDA has reviewed and approved or cleared a Predetermined Change Control Plan (PCCP) for this specific device.
Intended Use / Indications for Use
Clarius Bladder AI is intended for semi-automatic non-invasive measurements of bladder volume on ultrasound data acquired by the Clarius Ultrasound Scanner (i.e., curvilinear and phased array scanners). The user shall be a healthcare professional trained and qualified in ultrasound. The ultimate responsibility of ascertaining the measurements based on standard practices and clinical judgment. Clarius Bladder AI is indicated for use in adult patients only.
Product codes
QIH
Device Description
Clarius Bladder AI is a radiological (ultrasound) image processing software application which implements artificial intelligence (Al), utilizing non-adaptive machine learning algorithms, and is incorporated into the Clarius App software for use as part of the complete Clarius Ultrasound Scanner system product offering in bladder ultrasound imaging applications. Clarius Bladder Al is intended for use by trained healthcare practitioners for non-invasive measurements of bladder volume on ultrasound data acquired by the Clarius Ultrasound Scanner system (i.e., curvilinear and phased array scanners) using an artificial intelligence (AI) image segmentation algorithm.
During the ultrasound imaging procedure, the anatomical site (bladder) is selected through a preset software selection (i.e., bladder) within the Clarius App in which Clarius Bladder Al will engage to segment the bladder and place calipers for calculation of bladder volume.
Clarius Bladder Al operates by performing the following automations:
- . Automatic detection and measurement of bladder depth
- . Automatic detection and measurement of bladder width
- . Automatic detection and measurement of bladder height
- . Automatic detection of the corresponding image view (sagittal vs. transverse)
Clarius Bladder Al operates by performing automatic measurements of bladder height, width, and length, and calculates bladder volume. The user has the option to manually adjust the measurements made by Clarius Bladder Al by moving the caliper crosshairs. Clarius Bladder Al does not perform any functions that could not be accomplished manually by a trained and qualified user. Clarius Bladder Al is intended for use in B-Mode only.
Clarius Bladder Al is an assistive tool intended to inform clinical management and is not intended to replace clinical decision-making. The clinician retains the ultimate responsibility of ascertaining the measurements based on standard practices and clinical judgment. Clarius Bladder Al is indicated for use in adult patients only.
Clarius Bladder AI is incorporated into the Clarius App software, which is compatible with iOS and Android operating systems two versions prior to the latest iOS or Android stable release build and is intended for use with the following Clarius Ultrasound Scanner system transducers (previously 510(k)-cleared in K213436). Clarius Bladder Al is not a stand-alone software device.
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
Ultrasound
Anatomical Site
Bladder
Indicated Patient Age Range
Adults
Intended User / Care Setting
Intended Users: Licensed healthcare professionals
Care Setting: Healthcare setting (e.g., hospital, clinic)
Description of the training set, sample size, data source, and annotation protocol
The Clarius Bladder Al deep neural network (DNN) model was trained using three data sets: training, validation (tuning), and testing. The validation (tuning) data was 10% of the training data. The DNN parameters and weights were updated based on the validation (tuning) data at each epoch.
Gender distribution of subjects in training dataset:
Female: 353
Male: 999
Age distribution of subjects in training dataset: Histograms are provided showing the age distribution, which is skewed to the right with a peak around 70 years old.
Description of the test set, sample size, data source, and annotation protocol
The Clarius Bladder Al deep neural network (DNN) model was trained using three data sets: training, validation (tuning), and testing. The test data was independent and labelled by experts. The model's generalizability was evaluated on the test data. The test data was exclusive and independent to ensure robust results.
Gender distribution of subjects in test dataset:
Female: 12
Male: 43
Age distribution of subjects in test dataset: Histograms are provided showing the age distribution, which is also skewed to the right with a peak around 65 years old.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
Retrospective Verification Study
- Study type: Retrospective analysis of anonymized ultrasound images.
- Sample size: 66 subjects (10 female, 38 male, gender unknown for remainder).
- Data source: Anonymized multi-center database of images predominantly from the United States. Institutions included in the Bladder Al model training and tuning dataset were excluded from this study.
- Annotation protocol: For each subject, images of the bladder in sagittal and transverse views were included. Bladder volume measurements were performed by 3 reviewers (clinical truthers). Each reviewer was blinded to the Clarius Bladder Al output and the other reviewers' annotations. The ground truth for bladder volume was the mean measurement among the three clinical experts. Each reviewer manually measured bladder volume using 2 views (sagittal and transverse), measuring length, width, and height, and calculating volume. Clarius Bladder Al then measured the same images.
- Key results: The automatic bladder volume measurement was found to be non-inferior to manual measurement by expert clinicians. The absolute percent (%) difference between Clarius Bladder Al and mean reviewer measurement was compared to the difference between reviewer pairs using a one-sided t-test and an equivalence margin of 25%.
- p-value: 1.87e-22 (indicating non-inferiority).
- Mean difference: between percent differences of the clinical expert mean, and Bladder Al mean was 0.0548 (95% Cl 0.010, 0.099).
- Strong agreement was shown between Clarius Bladder Al measurements and the mean of expert clinicians' measurements, as well as with individual expert measurements.
- Intraclass correlation coefficients (ICC) for inter-rater reliability were calculated. Average dice scores and Jaccard index were also calculated.
- The difference between auto-measurements and manual measurements was found to be no greater than the mean difference between manual reviewer measurements within the clinically significant margin and with a statistical significance level of 0.05.
Prospective Verification Study
- Study type: Prospective study.
- Sample size: 58 subjects (40 female, 18 male).
- Data source: Healthcare institution in the United States.
- Annotation protocol: Only adult subjects were included. For each subject, images of the bladder in sagittal and transverse views were obtained. Bladder volume measurements were performed by 3 reviewers (clinical truthers) who were qualified experts with clinical experience in bladder ultrasound. Length, width, and height of the bladder were measured, and volume calculated. Clarius Bladder Al then measured the same images. All exams were captured using a Clarius C3 or PA ultrasound scanner. Subjects' demographic information (age, gender, height, and weight) was collected. The ground truth was the mean bladder volume measurement among the three clinical experts.
- Key results: The automatic bladder volume measurement was found to be non-inferior to manual measurement by expert clinicians. The absolute percent (%) difference between Clarius Bladder Al and mean reviewer measurement was compared to the difference between reviewer pairs using a one-sided t-test and an equivalence margin of 25%.
- p-value: 1.36e-14 (indicating non-inferiority).
- Mean difference: between percent differences of the clinical expert mean, and Bladder Al mean was -0.0228 (95% Cl -0.074, 0.028).
- Strong agreement was shown between Clarius Bladder Al measurements and expert clinicians' measurements, as well as with individual expert measurements.
- Intraclass correlation coefficients (ICC) for inter-rater reliability were calculated. Average dice scores and Jaccard index were also calculated.
- The difference between auto-measurements and manual measurements was found to be no greater than the mean difference between manual reviewer measurements within the clinically significant margin and with a statistical significance level of 0.05.
- The algorithm's performance was consistent among various patient demographics including age, gender, and BMI.
Clinical Validation Study
- Study type: Clinical validation study to evaluate design and clinical utility.
- Key results: The study showed consistent results among all users, meeting pre-defined acceptance criteria. Users successfully activated Bladder AI with both C3 and PA scanners, imaged the bladder, performed live segmentation, automatic measurements (height, width, length), calculated bladder volume, manually adjusted measurements, changed segmentation mask opacity, and saved measurements. Determined that Clarius Bladder Al performs as intended and meets user needs for semi-automated bladder volume measurements in ultrasound applications.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
- Non-inferiority with a p-value of 1.87e-22 (retrospective study)
- Mean difference between percent differences of the clinical expert mean, and Bladder Al mean was 0.0548 (95% Cl 0.010, 0.099) (retrospective study)
- Non-inferiority with a p-value of 1.36e-14 (prospective study)
- Mean difference between percent differences of the clinical expert mean, and Bladder Al mean was -0.0228 (95% Cl -0.074, 0.028) (prospective study)
- Intraclass Correlation Coefficients (ICC) for inter-rater reliability
- Average Dice scores
- Jaccard index
Predicate Device(s)
Reference Device(s)
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found
§ 892.2050 Medical image management and processing system.
(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).
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Image /page/0/Picture/0 description: The image shows the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: a symbol on the left and the FDA name and title on the right. The symbol on the left is a stylized representation of a human figure, while the text on the right reads "FDA U.S. FOOD & DRUG ADMINISTRATION" in blue letters.
Clarius Mobile Health Corp. Agatha Szeliga Director, Regulatory Affairs 205-2980 Virtual Way Vancouver, British Columbia V5M 4X3 Canada
Re: K232257
November 13, 2023
Trade/Device Name: Clarius Bladder AI Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: QIH Dated: October 20, 2023 Received: October 23, 2023
Dear Agatha Szeliga:
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, Ph.D. Assistant Director Imaging Software Team DHT 8B: Division of Radiological Imaging Devices and Electronic Products OHT 8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
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Indications for Use
510(k) Number (if known) K232257
Device Name Clarius Bladder AI
Indications for Use (Describe)
Clarius Bladder AI is intended for semi-automatic non-invasive measurements of bladder volume on ultrasound data acquired by the Clarius Ultrasound Scanner (i.e., curvilinear and phased array scanners). The user shall be a healthcare professional trained and qualified in ultrasound. The ultimate responsibility of ascertaining the measurements based on standard practices and clinical judgment. Clarius Bladder AI is indicated for use in adult patients only.
Type of Use (Select one or both, as applicable) | |
---|---|
X Prescription Use (Part 21 CFR 801 Subpart D) | Over-The-Counter Use (21 CFR 801 Subpart C) |
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Image /page/3/Picture/0 description: The image shows the Clarius logo. The logo consists of an orange symbol that looks like three concentric letter C's, followed by the word "clarius" in dark teal. To the right of "clarius" are the words "ultrasound anywhere" in a smaller font, also in dark teal. The logo is simple and modern, and the colors are bright and eye-catching.
510(k) Summary
This 510(k) summary of safety and effectiveness information is submitted in accordance with the requirements of 21 CFR § 807.92.
Subject Device Trade Name: | Clarius Bladder | |
---|---|---|
-- | ---------------------------- | ----------------- |
Device Classification Name: Automated Radiological Image Processing Software
Regulation Number, Name and Product Code:
Regulation Number | Regulation Name | Product Code |
---|---|---|
21 CFR § 892.2050 | Medical Image Management and Processing System | QIH |
FDA 510(k) Review Panel: | Radiology | |
Classification: | Class II | |
Manufacturer: | Clarius Mobile Health Corp. | |
205-2980 Virtual Way | ||
Vancouver, BC V5M 4X3 Canada | ||
Contact Name: | Agatha Szeliga | |
Director, Regulatory Affairs | ||
agatha.szeliga@clarius.com | ||
Date 510(k) Summary Prepared: | October 20, 2023 |
Predicate Device Information:
Device Trade Name: | Bladder AI (AIBV01) |
---|---|
510(k) Reference: | K230497 |
Manufacturer Name: | Exo Inc. |
Regulation Name: | Medical Image Management and Processing System |
Device Classification Name: | Automated Radiological Image Processing Software |
Product Code(s): | QIH |
Regulation Number: | 21 CFR § 892.2050 |
Regulatory Class: | Class II |
Note: The predicate device has not been subject to a design-related recall.
Reference Device Information:
Device Trade Name: | LVivo Software Application (LVivo Bladder) |
---|---|
510(k) Reference: | K200232 |
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Image /page/4/Picture/0 description: The image shows the Clarius logo. The logo consists of an orange symbol that looks like three curved lines forming a C shape. To the right of the symbol is the word "clarius" in dark teal, followed by the words "ultrasound anywhere" stacked on top of each other, also in dark teal.
Manufacturer Name: | DiA Imaging Analysis Ltd |
---|---|
Regulation Name: | Medical Image Management and Processing System |
Device Classification Name: | Automated Radiological Image Processing Software |
Product Code(s): | QIH |
Regulation Number: | 21 CFR § 892.2050 |
Regulatory Class: | Class II |
Device Description
Clarius Bladder AI is a radiological (ultrasound) image processing software application which implements artificial intelligence (Al), utilizing non-adaptive machine learning algorithms, and is incorporated into the Clarius App software for use as part of the complete Clarius Ultrasound Scanner system product offering in bladder ultrasound imaging applications. Clarius Bladder Al is intended for use by trained healthcare practitioners for non-invasive measurements of bladder volume on ultrasound data acquired by the Clarius Ultrasound Scanner system (i.e., curvilinear and phased array scanners) using an artificial intelligence (AI) image segmentation algorithm.
During the ultrasound imaging procedure, the anatomical site (bladder) is selected through a preset software selection (i.e., bladder) within the Clarius App in which Clarius Bladder Al will engage to segment the bladder and place calipers for calculation of bladder volume.
Clarius Bladder Al operates by performing the following automations:
- . Automatic detection and measurement of bladder depth
- . Automatic detection and measurement of bladder width
- . Automatic detection and measurement of bladder height
- . Automatic detection of the corresponding image view (sagittal vs. transverse)
Clarius Bladder Al operates by performing automatic measurements of bladder height, width, and length, and calculates bladder volume. The user has the option to manually adjust the measurements made by Clarius Bladder Al by moving the caliper crosshairs. Clarius Bladder Al does not perform any functions that could not be accomplished manually by a trained and qualified user. Clarius Bladder Al is intended for use in B-Mode only.
Clarius Bladder Al is an assistive tool intended to inform clinical management and is not intended to replace clinical decision-making. The clinician retains the ultimate responsibility of ascertaining the measurements based on standard practices and clinical judgment. Clarius Bladder Al is indicated for use in adult patients only.
Clarius Bladder AI is incorporated into the Clarius App software, which is compatible with iOS and Android operating systems two versions prior to the latest iOS or Android stable release build and is intended for use with the following Clarius Ultrasound Scanner system transducers (previously 510(k)-cleared in K213436). Clarius Bladder Al is not a stand-alone software device.
Clarius Ultrasound Transducers | C3 HD3 and PA HD3 |
---|---|
Clarius App Software | Clarius Ultrasound App (Clarius App) for iOS; |
Clarius Ultrasound App (Clarius App) for Android |
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Image /page/5/Picture/0 description: The image shows the Clarius ultrasound logo. The logo consists of an orange symbol that looks like three letter C's nested inside each other, followed by the word "clarius" in dark teal. To the right of "clarius" are the words "ultrasound anywhere" in a smaller font, also in dark teal.
Indications for Use for Clarius Bladder Al
Clarius Bladder Al is intended for semi-automatic non-invasive measurements of bladder volume on ultrasound data acquired by the Clarius Ultrasound Scanner (i.e., curvilinear and phased array scanners). The user shall be a healthcare professional trained and qualified in ultrasound. The user shall retain the ultimate responsibility of ascertaining the measurements based on standard practices and clinical judgment. Clarius Bladder AI is indicated for use in adult patients only.
Comparison of the Subject Device and Legally Marketed Devices for Demonstration of Substantial Equivalence
The following table provides a comparison of the subject device, Clarius Bladder AI, to the predicate device and reference device. A comparison of the subject device to the predicate device and reference device shows that the subject device has the same intended use, similar indications for use, the same principle of operation, and is based on a similar Al/ML algorithm providing automated radiological image processing with segmentation and measurement of bladder volume, comparable to the legally marketed devices referenced herein.
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Image /page/6/Picture/0 description: The image shows the Clarius ultrasound anywhere logo. The logo consists of an orange symbol that looks like three concentric letter C's. To the right of the symbol is the word "clarius" in dark teal, followed by the words "ultrasound anywhere" in a smaller font and the same dark teal color.
Table 1 - Comparison of the Subject Device to the Legally Marketed Devices
Criteria | SUBJECT DEVICE | PREDICATE DEVICE | REFERENCE DEVICE | RATIONALE |
---|---|---|---|---|
Clarius Bladder Al | Bladder AI (AIBV01) | LVivo Software | ||
Application (LVivo | ||||
Bladder) | (if subject device differs | |||
from predicate device) | ||||
510(k) Holder/ | ||||
Manufacturer | Clarius Mobile Health | |||
Corp. | Exo Inc. | DiA Imaging Analysis Ltd | Not applicable | |
Submission Reference | Current Submission | K230497 | K200232 | Not applicable |
Product Code(s) | QIH | QIH | QIH | Same as predicate device |
and reference device | ||||
Device Classification Name | Automated Radiological | |||
Image Processing Software | Automated Radiological | |||
Image Processing Software | Automated Radiological | |||
Image Processing Software | Same as predicate device | |||
and reference device | ||||
Regulation Number | 21 CFR 892.2050 | 21 CFR 892.2050 | 21 CFR 892.2050 | Same as predicate device |
and reference device | ||||
Regulation Name | Medical Image | |||
Management and | ||||
Processing System | Medical Image | |||
Management and | ||||
Processing System | Medical Image | |||
Management and | ||||
Processing System | Same as predicate device | |||
and reference device | ||||
Intended Use | Non-invasive processing of | |||
ultrasound images using | ||||
automatic image | ||||
segmentation and | ||||
measurement of | ||||
anatomical structures | ||||
utilizing artificial | ||||
intelligence/machine- | ||||
learning algorithms. | Non-invasive processing of | |||
ultrasound images using | ||||
automatic image | ||||
segmentation and | ||||
measurement of | ||||
anatomical structures | ||||
utilizing artificial | ||||
intelligence/machine | ||||
learning algorithms. | Non-invasive processing of | |||
ultrasound images using | ||||
automatic image | ||||
segmentation and | ||||
measurement of | ||||
anatomical structures | ||||
utilizing artificial | ||||
intelligence/machine | ||||
learning algorithms. | Same as predicate device | |||
and reference device | ||||
Indications for Use | Clarius Bladder Al is | |||
intended for semi- | ||||
automatic non-invasive | ||||
measurements of bladder | ||||
volume on ultrasound data | ||||
acquired by the Clarius | ||||
Ultrasound Scanner (i.e., | ||||
curvilinear and phased | ||||
array scanners). The user | Bladder Al uses machine- | |||
learning techniques to aid | ||||
in the quantification of | ||||
bladder volume from | ||||
ultrasound images. The | ||||
device is intended to be | ||||
used on images of patients | ||||
aged two years or | ||||
older. | LVivo platform is intended | |||
for non-invasive processing | ||||
of ultrasound images to | ||||
detect, measure, and | ||||
calculate relevant medical | ||||
parameters of structures | ||||
and function of patients | ||||
with suspected disease. | The Clarius Bladder Al | |||
indications for use are very | ||||
similar to the predicate | ||||
device's indications for use | ||||
as both devices are | ||||
indicated for measurement | ||||
of bladder volume from | ||||
ultrasound image data. | ||||
Criteria | SUBJECT DEVICE | PREDICATE DEVICE | REFERENCE DEVICE | RATIONALE |
Clarius Bladder Al | Bladder AI (AIBV01) | LVivo Software | ||
Application (LVivo | ||||
Bladder) | (if subject device differs | |||
from predicate device) | ||||
shall be a healthcare | ||||
professional trained and | ||||
qualified in | ||||
ultrasound. The user shall | ||||
retain the ultimate | ||||
responsibility of | ||||
ascertaining the | ||||
measurements based on | ||||
standard practices and | ||||
clinical judgment. | ||||
Radiological application/ | ||||
Supported modality | Ultrasound | Ultrasound | Ultrasound | Same as predicate device |
and reference device | ||||
Compatible Scanner | ||||
Frequency | C3: 2 to 6 MHz | |||
PA: 1 to 5 MHz | 1.3 to 9 MHz | Not available | The subject device's | |
compatible scanner | ||||
frequency falls within the | ||||
range of the predicate | ||||
device's compatible | ||||
scanner frequency | ||||
Principle of Operation/ | ||||
Technology | Ultrasound image | |||
processing software | ||||
application implementing | ||||
artificial intelligence | ||||
including non-adaptive | ||||
machine learning | ||||
algorithms trained with | ||||
clinical and/or artificial | ||||
data intended for non- | ||||
invasive segmentation and | ||||
measurements of | Ultrasound image | |||
processing software | ||||
application implementing | ||||
artificial intelligence | ||||
including non-adaptive | ||||
machine learning | ||||
algorithms trained with | ||||
clinical and/or artificial | ||||
data intended for non- | ||||
invasive segmentation and | ||||
measurements of | Ultrasound image | |||
processing software | ||||
application implementing | ||||
artificial intelligence | ||||
including non-adaptive | ||||
machine learning | ||||
algorithms trained with | ||||
clinical and/or artificial | ||||
data intended for non- | ||||
invasive segmentation and | ||||
measurements of | Same as predicate device | |||
and reference device | ||||
Criteria | SUBJECT DEVICE | PREDICATE DEVICE | REFERENCE DEVICE | RATIONALE |
Clarius Bladder Al | Bladder AI (AIBV01) | LVivo Software | ||
Application (LVivo | ||||
Bladder) | (if subject device differs | |||
from predicate device) | ||||
Segmentation | Yes - Segmentation of | |||
anatomical structures | ||||
(bladder) | Yes - Segmentation of | |||
anatomical structures | ||||
(bladder) | Yes - Segmentation of | |||
anatomical structures | ||||
(bladder) | Same as predicate device | |||
and reference device | ||||
Measurement | Yes - Measurement of | |||
anatomical structures | ||||
(bladder) | Yes - Measurement of | |||
anatomical structures | ||||
(bladder) | Yes - Measurement of | |||
anatomical structures | ||||
(bladder) | Same as predicate device | |||
and reference device | ||||
Frame | Transverse and Sagittal | Transverse and Sagittal | Transverse and Sagittal | Same as predicate device |
and reference device | ||||
Quantitative Analysis | Distance, Bladder Volume | Distance, Bladder Volume | Distance, Bladder Volume | Same as predicate device |
and reference device | ||||
AI/ML Algorithm | Image segmentation for | |||
border detection, and | ||||
bladder view classification | ||||
using a Deep Neural | ||||
Network. | Image segmentation for | |||
border detection. | Image segmentation for | |||
border detection using | ||||
machine learning and | ||||
active contour. | Similar to predicate device | |||
and reference device | ||||
Automation | ||||
(Yes or No) | Yes | Yes | Yes | Same as predicate device |
and reference device | ||||
Display Calipers | Yes | Yes | Yes | Same as predicate device |
and reference device | ||||
Manual adjustment/ | ||||
Manual editing by user | ||||
capability | ||||
(Yes or No) | Yes | Yes | Yes | Same as predicate device |
and reference device | ||||
Operating System | iOS and Android | Web browser (Google | ||
Chrome) | Web browser (Google | |||
Chrome) and Android | Similar to predicate device | |||
Anatomical Site | Bladder | Bladder | Bladder | Same as predicate device |
and reference device | ||||
Environment of Use | Healthcare setting (e.g., | |||
hospital, clinic) | Healthcare setting (e.g., | |||
hospital, clinic) | Healthcare setting (e.g., | |||
hospital, clinic) | Same as predicate device | |||
and reference device | ||||
Intended Users | Licensed healthcare | |||
professionals | Licensed healthcare | |||
professionals | Licensed healthcare | |||
professionals | Same as predicate device | |||
and reference device | ||||
Criteria | SUBJECT DEVICE | PREDICATE DEVICE | REFERENCE DEVICE | RATIONALE |
Clarius Bladder AI | Bladder AI (AIBV01) | LVivo Software | ||
Application (LVivo | ||||
Bladder) | (if subject device differs | |||
from predicate device) | ||||
Patient Population | Adults | Adults and pediatrics (2 | ||
years and older) | Adults | Similar to the predicate | ||
device and same as the | ||||
reference device. |
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Image /page/9/Picture/0 description: The image contains the Clarius logo. On the left is an orange symbol that looks like a stylized letter C. To the right of the symbol is the word "clarius" in dark teal. To the right of "clarius" are the words "ultrasound anywhere" in a smaller font, also in dark teal.
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Image /page/10/Picture/0 description: The image shows the Clarius logo. The logo consists of an orange icon on the left and the word "clarius" in dark teal next to it. To the right of the word "clarius" is the text "ultrasound anywhere" in a smaller font, also in dark teal. The icon is a stylized "C" made up of three curved lines.
Non-Clinical Performance Testing Summary
Clarius Bladder AI was designed and developed by Clarius Mobile Health Corp. in accordance with the applicable requirements, design controls, and standards to establish safety and effectiveness of the device.
Non-clinical performance testing has demonstrated that Clarius Bladder Al complies with the following FDA-recognized consensus standards:
| Standard
Recognition
Number | Title of Standard |
---|---|
13-79 | IEC 62304:2006 + A1:2015 - Medical device software -- Software life cycle processes |
5-125 | ISO 14971:2019 Medical devices -- Application of risk management to medical devices |
12-349 | NEMA PS 3.1 - 3.20 (2022d) Digital Imaging and Communications in Medicine (DICOM) Set |
5-129 | IEC 62366-1:2015 + A1:2020 Medical devices -- Part 1: Application of usability engineering to |
medical devices | |
5-134 | ISO 15223-1:2021 Medical devices -- Symbols to be used with medical device labels, labelling |
and information to be supplied |
Safety and performance of Clarius Bladder Al has been evaluated through verification and validation testing in accordance with applicable specifications and performance standards. The traceability analysis provides traceability between the requirement specifications, risks, and verifications, risks, and verification testing of the subject device. All requirements and risk controls have been successfully verified and traced. A comprehensive risk analysis was performed for the subject device and appropriate risk controls have been implemented to mitigate hazards.
Software verification and validation activities were conducted in accordance with IEC 62304:2006 + AMD1:2015 – Medical device software – Software lifecycle processes and ISO 14971:2019 Medical devices – Application of risk management to medical devices, and in accordance with relevant FDA guidance documents, General Principles of Software Validation, Final Guidance for Industry and FDA Staff (issued January 11, 2002), Guidance for the Content of Premarket Submissions for Device Software Functions (issued June 14, 2023), and Content of Premarket Submissions for Management of Cybersecurity in Medical Devices (issued October 2, 2014).
Clarius conforms to the cybersecurity requirements by implementing a process of preventing unauthorized access, modifications, misuse or denial of use, or the unauthorized use of information that is stored, accessed or transferred from a medical device to an external recipient.
Clarius Bladder AI was tested and found to be safe and effective for the intended use, intended patient population, and use environments, as demonstrated through verification and validation testing. Validation testing was performed to ensure that the final product is capable of meeting the requirements for the specified clinical application and performs as intended to meet users' needs, while demonstrating substantial equivalence to the predicate device.
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Image /page/11/Picture/0 description: The image shows the Clarius logo. The logo consists of an orange icon on the left and the word "clarius" in dark teal next to it. To the right of the word "clarius" are the words "ultrasound anywhere" stacked on top of each other, also in dark teal. The icon on the left is a stylized "C" made up of three curved lines.
Clinical Performance Testing Summary
Following completion of the Clarius Bladder Al model training and tuning, which was conducted to create a documented baseline of the Al model, verification testing and clinical validation were performed.
The clinical performance of Clarius Bladder Al was evaluated through a retrospective analysis of anonymized ultrasound images and also through a prospective study. The verification data was entirely independent from the training, validation (tuning), and test datasets.
The Clarius Bladder Al deep neural network (DNN) model was trained using three data sets: training, validation (tuning), and testing. The validation (tuning) data was 10% of the training data, while the test data was independent and labelled by experts. The DNN parameters and weights were updated based on the validation (tuning) data at each epoch. The model's generalizability was evaluated on the test data. The test data was exclusive and independent to ensure robust results.
The objective of clinical performance testing (verification) was to verify that Clarius Bladder Al automeasurements are non-inferior to manual measurements performed by qualified experts with relevant (i.e., bladder) ultrasound experience.
Demographic Distribution of the Datasets
| Subject Gender | Training Dataset Number of
Subjects | Test Dataset Number of
Subjects |
|----------------|----------------------------------------|------------------------------------|
| Female | 353 | 12 |
| Male | 999 | 43 |
Gender distribution of the subjects included in the training and test datasets are shown below.
Age distribution of the subjects included in the training and test datasets are shown below.
Image /page/11/Figure/10 description: The image contains two histograms showing the age distribution of a training dataset and a test dataset. The histogram on the left shows the age distribution of the training dataset, with the x-axis representing age and the y-axis representing the count. The age distribution of the training dataset is skewed to the right, with a peak around 70 years old. The histogram on the right shows the age distribution of the test dataset, with the x-axis representing age and the y-axis representing the count. The age distribution of the test dataset is also skewed to the right, with a peak around 65 years old.
Summary of the Retrospective Verification Study
Ultrasound images were randomly obtained from an anonymized multi-center database of images from predominantly the United States. Institutions included in the Bladder Al model training and tuning dataset were excluded from this study. For each subject, images of the bladder in sagittal and transverse views were included. The total sample size included in the study was 66 subjects, 10 were
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Image /page/12/Picture/0 description: The image shows the Clarius logo. The logo consists of an orange symbol that looks like three curved lines forming a C shape, followed by the word "clarius" in dark teal. To the right of "clarius" are the words "ultrasound anywhere" in a smaller font and the same dark teal color.
female, 38 were male, and the gender of the remaining was unknown. The age of the subjects ranged from 31 - 92 years. The ethnicities of the subjects were unknown.
The purpose of the retrospective study was to verify that the Clarius Bladder Al is non-inferior to manual measurement by the expert clinician. Each exam had bladder volume measurements performed by 3 reviewers (clinical truthers). Each reviewer was blinded to the Clarius Bladder Al output and the other reviewers' annotations as well. The ground truth used as the reference data for bladder volume was obtained as the mean bladder volume measurement among three clinical experts.
Each reviewer measured the bladder volume manually using 2 views (sagittal and transverse). The length, width and height of the bladder were measured, and the volume was calculated. Clarius Bladder Al was then used to measure the same images. All exams of the bladder were captured using a Clarius C3, C7 (curvilinear) or PA (phased array) ultrasound scanner.
An assessment of the magnitude of the difference between Clarius Bladder Al and human experts' bladder volume measurements was performed to ascertain whether Bladder Al measurement is non-inferior to those of human experts/ qualified ultrasound users.
The absolute percent (%) difference between reviewer pairs was calculated and compared to the absolute percent (%) difference between the Clarius Bladder Al measurement and mean reviewer measurement using a one-sided t-test and an equivalence margin of 25% (i.e., the mean difference between differences should be no greater than 25% of the measured bladder volume). The automatic bladder volume measurement was found to be non-inferior (p value of 1.87e-22). The mean difference between percent differences of the clinical expert mean, and Bladder Al mean was 0.0548 (95% Cl 0.010, 0.099).
Strong agreement was shown between the Clarius Bladder Al measurements and the mean of the expert clinicians' measurements. The Clarius Bladder Al model also showed strong agreements with individual expert measurements. The intraclass correlation coefficients (ICC) for inter-rater reliability were calculated between reviewer pairs and between the Clarius Bladder Al output and the mean reviewer measurement. The average dice scores and Jaccard index between the Clarius Bladder Al model vs. each reviewer and between each reviewer pair were also calculated.
The difference between auto-measurements and measurements was found to be no greater than the mean difference between manual reviewer measurements within the clinically significant margin and with a statistical significance level of 0.05.
The results of the retrospective analysis have demonstrated that Clarius Bladder Al measurement output adequately aligns with expert clinicians' manual measurement, confirming that Clarius Bladder Al measurements are non-inferior to those of human clinical experts. Therefore, the performance of Clarius Bladder Al has been verified for bladder volume measurement for use in bladder ultrasound applications and has been determined as reliable and accurate compared to clinical experts.
Summary of the Prospective Verification Study
The prospective study was performed at a healthcare institution in the United States. Only adult subjects were included in the study. For each subject, images of the bladder in sagittal and transverse views were obtained. The total sample size included in the study was 58 subjects of White, Black, Asian, and Hispanic
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Image /page/13/Picture/0 description: The image shows the Clarius ultrasound logo. The logo consists of an orange symbol resembling three curved lines forming a C shape, followed by the word "clarius" in dark teal. To the right of "clarius" are the words "ultrasound anywhere" stacked on top of each other, also in dark teal.
ethnicities; of the subjects, 40 were female and 18 were male. The subjects ranged from 21 -61 years.
The purpose of the prospective study was to verify that the Clarius Bladder Al is non-inferior to manual measurement by the expert clinician. Each exam had bladder volume measurements performed by 3 reviewers (clinical truthers). The length, width and height of the bladder were measured, and the volume was calculated. The reviewers were qualified experts with clinical experience in bladder ultrasound. Clarius Bladder Al was then used to measure the same images. All exams of the bladder were captured using a Clarius C3 (curvilinear) or a PA (phased array) ultrasound scanner. The subjects' demographic information was also collected (age, gender, height and weight). The ground truth used as the reference data for bladder volume was obtained as the mean bladder volume measurement among three clinical experts. An assessment of the magnitude of the difference between Clarius Bladder Al and human experts' bladder volume measurements was performed to ascertain whether Bladder Al measurement is non-inferior to those of human experts/ qualified ultrasound users.
The absolute percent (%) difference between reviewer pairs was calculated and compared to the absolute percent (%) difference between the Clarius Bladder Al measurement and mean reviewer measurement using a one-sided t-test and an equivalence margin of 25% (i.e., the mean difference between differences should be no greater than 25% of the measured bladder volume). The automatic bladder volume measurement was found to be non-inferior (p value of 1.36e-14). The mean difference between percent differences of the clinical expert mean, and Bladder Al mean was -0.0228 (95% Cl -0.074, 0.028).
Strong agreement was shown between the Clarius Bladder Al measurements and the expert clinicians' measurements. The Clarius Bladder Al model also showed strong agreements with individual expert measurements. The intraclass correlation coefficients (ICC) for inter-rater reliability were calculated between reviewer pairs and between the Clarius Bladder Al output and the mean reviewer measurement. The average dice scores and Jaccard index between the Clarius Bladder Al model vs. each reviewer and between each reviewer pair were also calculated.
The difference between auto-measurements and measurements was found to be no greater than the mean difference between manual reviewer measurements within the clinically significant margin and with a statistical significance level of 0.05.
The results of the prospective study have demonstrated that Clarius Bladder Al measurement output adequately aligns with expert clinicians' manual measurement, confirming that Clarius Bladder Al measurements are non-inferior to those of human clinical experts. The algorithm's performance was shown to be consistent among the various patient demographics including age, gender, and BMI. Therefore, the performance of Clarius Bladder Al has been verified for bladder volume measurement for use in bladder ultrasound applications and has been determined as reliable and accurate to clinical experts.
Summary of the Clinical Validation Study
A clinical validation study was conducted to evaluate the design and clinical utility of Clarius Bladder AI, as incorporated into the Clarius App software, to determine if the device performs as intended in a representative user environment, meets the product requirements, is clinically usable, and meets users' needs for use in semi-automated bladder volume measurements.
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Image /page/14/Picture/0 description: The image shows the Clarius ultrasound logo. The logo consists of an orange symbol that looks like three concentric letter C's, followed by the word "clarius" in dark teal. To the right of "clarius" are the words "ultrasound anywhere" stacked on top of each other, also in dark teal.
The results of the validation study showed consistent results among all users, meeting the pre-defined acceptance criteria. The users were able to activate Bladder AI using both scanners (C3 and PA), image the bladder, perform live segmentation using Clarius Bladder Al, perform automatic measurements of bladder height, width, and length, measure bladder volume, manually adjust the measurements, change the segmentation mask opacity, and save the bladder measurement with each exam.
Therefore, based on the results of the clinical validation study it has been determined that Clarius Bladder Al performs as intended and meets user needs for use in semi-automated bladder volume measurements in bladder ultrasound applications.
Conclusion & Summary of Substantial Equivalence
Based on the information presented in this Traditional 510(k) premarket notification and based on the fundamental scientific technology utilizing artificial intelligence/machine learning algorithms, technological characteristics, principle of operation, intended use, environment of use, and indications for use, Clarius Bladder Al has been determined to be substantially equivalent in terms of safety and effectiveness to the legally marketed predicate device.
The subject device and the predicate device are both radiological (ultrasound) image processing software applications which implement artificial intelligence/machine learning algorithms trained with clinical and/or artificial data intended for non-invasive measurements of ultrasound data, utilizing similar machine-learning based algorithms to detect, measure, and calculate relevant medical parameters of structures with manual adjustment capability by the user.
Performance testing of Clarius Bladder Al, including the results from verification and validation studies, has demonstrated that Clarius Bladder Al measurement output adequately aligns with expert clinicians' manual measurements, and thereby performs as intended for use in semi-automated bladder volume measurements and meets user needs.
Any minor differences in the indications for use between the subject device and the predicate device do not raise any issues related to safety or effectiveness. Therefore, Clarius Bladder AI is as safe and effective as the predicate device, Bladder Al (AIBV01) (K230497), and therefore substantially equivalent.