K213776 · Resonance Health Analysis Services Pty, Ltd. · PCS · Dec 29, 2021 · Radiology
Device Facts
Record ID
K213776
Device Name
LiverSmart
Applicant
Resonance Health Analysis Services Pty, Ltd.
Product Code
PCS · Radiology
Decision Date
Dec 29, 2021
Decision
SESE
Submission Type
Special
Regulation
21 CFR 892.1001
Device Class
Class 2
Attributes
AI/ML, Software as a Medical Device
AI Performance
Output
Algorithm
Acceptance
Observed
Dev DS
Dev Readers
Test DS
Test Readers
Liver Iron Concentration
Convolutional neural networks
—
—
—
—
—
—
Volumetric Liver Fat Fraction
Convolutional neural networks
—
—
—
—
—
—
Proton Density Fat Fraction
Convolutional neural networks
—
—
—
—
—
—
Steatosis Grade
Convolutional neural networks
—
—
—
—
—
—
Indications for Use
For Liver: (i) For the measurement of R2 and iron concentration in the liver from MRI scans. (ii) For quantitative measurement of the triglyceride fat fraction in magnetic resonance images of the liver, also known as volumetric liver fat fraction (VLFF).
Device Story
LiverSmart is a software platform that consolidates results from two existing FDA-cleared devices, HepaFat-AI and FerriSmart, into a single multiparametric report. The device takes as input a zipped folder containing DICOM MRI datasets acquired via established HepaFat-AI and FerriSmart protocols. It utilizes a Data Preparation Module to sort and route these datasets to the respective analysis engines, which employ convolutional neural networks to process the images. The system produces a summary report containing volumetric liver fat fraction (VLFF), proton density fat fraction (PDFF), steatosis grade, and liver iron concentration (LIC). Used in clinical settings by radiologists, the software requires no user input for analysis, minimizing human error. The output provides quantitative metrics that assist physicians in diagnosing and monitoring liver iron overload and fatty liver disease, supporting clinical decision-making and patient management.
Clinical Evidence
No clinical data. Substantial equivalence is supported by bench testing and verification of the data preparation and report generation modules. Testing confirmed that the device correctly detects anomalies in sequence acquisition and produces identical results to the predicate devices when processing the same image datasets.
Technological Characteristics
Standalone software platform; cloud-based or on-site hosting. Utilizes DICOM MRI datasets. Analysis employs convolutional neural networks for image processing, with algorithmic conversion of R2 to LIC and Alpha to VLFF. Complies with ISO 13485 and 21 CFR 820 quality system regulations.
Indications for Use
Indicated for: Liver Iron Concentration: measure liver iron concentration in individuals with confirmed or suspected systemic iron overload; monitor liver iron burden in transfusion dependent thalassemia patients and patients with sickle cell disease receiving blood transfusions; aid in the identification and monitoring of non-transfusion-dependent thalassemia patients receiving therapy with Deferasirox. Liver Fat Assessment: assess volumetric liver fat fraction, proton density fat fraction, and steatosis grade in individuals with confirmed or suspected fatty liver disease. When interpreted by a trained physician, results can be used to: monitor liver fat content in patients undergoing weight loss management; aid in assessment and screening of living donors for liver transplant.
Regulatory Classification
Identification
The liver iron concentration imaging companion diagnostic for deferasirox is an image processing device intended to aid in the identification and monitoring of non-transfusion-dependent thalassemia patients receiving therapy with deferasirox. The device calculates a numeric value for liver iron concentration based on magnetic resonance images acquired under controlled conditions. The calculated numeric value is used to assess the need for deferasirox treatment and for monitoring treatment in patients with non-transfusion-dependent thalassemia. The liver iron concentration imaging companion diagnostic for deferasirox is essential to the safe and effective use of deferasirox in patients with non-transfusion-dependent thalassemia.
Special Controls
In combination with the general controls of the FD&C Act, the Liver Iron Concentration Imaging Companion Diagnostic for Deferasirox is subject to the following special controls:
(1) Labeling must specify instructions for acceptance testing of images prior to processing.
(2) Labeling must specify data processing quality assurance protocols.
(3) Labeling must specify the sensitivity and specificity of liver iron concentration measurements.
(4) Nonclinical and clinical performance testing must be included in the premarket notification submission demonstrating the bias, precision, repeatability, and reproducibility of liver iron concentration measurements.
*Classification.* Class II (special controls). The special controls for this device are:(1) Design verification and validation must include nonclinical and clinical performance testing demonstrating the bias, precision, repeatability, and reproducibility of liver iron concentration measurements.
(2) Labeling must include specifying:
(i) Instructions for acceptance testing of images prior to processing;
(ii) Data processing quality assurance protocols; and
(iii) The sensitivity and specificity of liver iron concentration measurements.
{0}------------------------------------------------
December 29, 2021
Image /page/0/Picture/1 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). The logo consists of two parts: a symbol on the left and the text "FDA U.S. FOOD & DRUG ADMINISTRATION" on the right. The symbol on the left is the Department of Health & Human Services logo. The text is in blue, with "FDA" in a larger font size than the rest of the text.
Resonance Health Analysis Services Pty Ltd Mitchell Wells Official Correspondent 141 Burswood Road Perth, Western Australia 6100 Australia
### Re: K213776
Trade/Device Name: LiverSmart Regulation Number: 21 CFR 892.1001 Regulation Name: Liver Iron Concentrattion Imaging Companion Diagnostic For Deferasirox Regulatory Class: Class II Product Code: PCS, LNH Dated: November 24, 2021 Received: December 2, 2021
Dear Mitchell Wells:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for
{1}------------------------------------------------
devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.
For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).
Sincerely.
For
Thalia T. Mills, Ph.D. Director Division of Radiological Health OHT7: Office of In Vitro Diagnostics and Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
{2}------------------------------------------------
## Indications for Use
510(k) Number (if known) K213776
Device Name LiverSmart
Indications for Use (Describe) LiverSmart is indicated to:
For Liver Iron Concentration
1. measure liver iron concentration in individuals with confirmed or suspected systemic iron overload;
2. monitor liver iron burden in transfusion dependents and patients with sickle cell disease receiving blood transfusions:
3. aid in the identification and monitoring of non-transfusion-dependent thalassemia patients receiving therapy with Deferasirox.
For Liver Fat Assessment
1. assess the volumetric liver fat fraction, proton density fat fraction and steatosis grade in individuals with confirmed or suspected fatty liver disease.
When interpreted by a trained physician, the results can be used to:
2. monitor liver fat content in patients undergoing weight loss management;
3. aid in the assessment and screening of living donors for liver transplant.
| 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)
#### CONTINUE ON A SEPARATE PAGE IF NEEDED.
This section applies only to requirements of the Paperwork Reduction Act of 1995.
#### *DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.*
The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:
> Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff(@fda.hhs.gov
"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."
{3}------------------------------------------------
# K213776
# 510(k)SUMMARY
This Summary has been prepared in accordance with 21 CFR 807.92.
## GENERAL INFORMATION
| Date Prepared | 23 December 2021 |
|-----------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Submitted by | Resonance Health Analysis Service Pty Ltd<br>141 Burswood Rd<br>Burswood 6100<br>AUSTRALIA |
| Main Contact | Mr Mitchell Wells<br>Managing Director<br>mitchellw@resonancehealth.com<br>Tel: +61 8 9286 5300<br>Fax: +61 8 9286 5399 |
| US Contact (US Agent) | Michael van der Woude<br>Director & GM<br>Emergo Global Representation LLC<br>2500 Bee Cave Road, Building 1, Suite 300<br>Austin, TX 78746<br>Phone: 512 3279997<br>Fax: 512 3279998<br>Email: USAgent@ul.com |
# DEVICE INFORMATION
| Name of Device | LiverSmart |
|------------------------|-----------------------|
| Trade/proprietary Name | LiverSmart™ |
| Classification | Class II |
| Product Code | 90-PCS and LNH |
| CFR Section | 892.1001 and 892.1000 |
| Panel | Radiology |
{4}------------------------------------------------
#### Description of the Device
LiverSmart is software that utilizes two existing FDA cleared devices, HepaFat-AI (K201039) and FerriSmart (K182218) and combines their respective results into a singular consolidated multiparametric 'LiverSmart' report.
LiverSmart automatically sorts and sends magnetic resonance imaging (MRI) datasets to each of the existing HepaFat-AI and FerriSmart devices and then receives results from those devices to generate a summary report which combines the HepaFat-AI results (an estimate of the patient's volumetric liver fat fraction (VLFF), proton density fat fraction (PDFF), steatosis grade), and the FerriSmat result (an estimate of the patient's liver iron concentration (LIC)).
To conduct analysis, the user simply uploads a single zipped folder containing HepaFat-AI and FerriSmart DICOM images, acquired in accordance with their respective acquisition protocols, to the LiverSmart software. No user input is required for the analysis thereby minimising the impact of human error. The LiverSmart software requires image input data that has been acquired in accordance with the existing and now well established HepaFat-AI (K201039) and FerriSmart (K182218) imaging protocols.
LiverSmart has two new components that are in addition to the existing components of HepaFat-AI and FerriSmart, namely a:
- (i) Data Preparation Module; and
- (ii) Report Generation Module
The rest of the components for LiverSmart are the existing components of the FDA cleared HepaFat-AI and FerriSmart devices, as follows:
For HepaFat-AI:
- (i) Magnetic Resonance Imaging Protocol
- (ii) HepaFat-AI Analysis Software
- (iii) Volumetric Liver Fat Fraction Measurement
- (iv) Proton Density Fat Fraction Measurement
- (v) Steatosis Grade Measurement
For FerriSmart:
- (i) Magnetic Resonance Imaging Protocol
- (ii) FerriSmart Analysis Software
- (iii) Liver Iron Concentration Measurement
The above HepaFat-AI and FerriSmart components are the same as previously provided to the FDA as the time HepaFat-AI and FerriSmart regulatory clearances were sought (and subsequently obtained).
#### Intended Use
For Liver:
- (i) For the measurement of R2 and iron concentration in the liver from MRI scans.
- (ii) For quantitative measurement of the triglyceride fat fraction in magnetic resonance images of the liver, also known as volumetric liver fat fraction (VLFF).
{5}------------------------------------------------
### Indications for Use
LiverSmart is indicated to -
For Liver Iron Concentration:
- (i) measure liver iron concentration in individuals with confirmed or suspected systemic iron overload;
- (ii) monitor liver iron burden in transfusion dependent thalassemia patients and patients with sickle cell disease receiving blood transfusions; and
- (iii) aid in the identification and monitoring of non-transfusion-dependent thalassemia patients receiving therapy with Deferasirox.
For Liver Fat Assessment:
- (i) Assess the volumetric liver fat fraction, proton density fat fraction and steatosis grade in individuals with confirmed or suspected fatty liver disease.
when interpreted by a trained physician the results can be used to:
- (ii) Monitor liver fat content in patients undergoing weight loss management; and
- (iii) Aid in the assessment and screening of living donors for liver transplant
#### PREDICATE INFORMATION
LiverSmart is substantially equivalent to (and is a combination of) the following Resonance Health existing 510(k) cleared devices:
- FerriSmart - K182218
- HepaFat-AI - K201039
{6}------------------------------------------------
### SUBSTANTIAL EQUIVALENCE INFORMATION
The table below summarizes the main similarities and differences between LiverSmart and the predicates.
| | LiverSmart (Subject Device) | FerriSmart (Predicate) | HepaFat-AI (Predicate) |
|---------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Regulatory Class | II | II | II |
| 510(k) number | K213776 | K182218 | K201039 |
| Classification<br>Name | Liver Iron Concentration Imaging<br>Companion Diagnostic for Deferasirox<br>System, Nuclear Magnetic Resonance<br>Imaging, System, Image Processing<br>Radiological | Liver Iron Concentration Imaging<br>Companion Diagnostic for Deferasirox | System, Nuclear Magnetic Resonance<br>Imaging, System, Image Processing<br>Radiological |
| CFR Section | 892.1001 and 892.1000 | 892.1001 | 892.1000 |
| Product Code and<br>Classification<br>Panel | 90 PCS and 90 LNH | 90 PCS | 90 LNH |
| Description | Standalone software package that<br>automatically analyses magnetic resonance<br>imaging (MRI) datasets to generate an<br>estimate of the patient's volumetric liver fat<br>fraction (VLFF), proton density fat fraction<br>(PDFF), steatosis grade, and liver iron<br>concentration (LIC). LiverSmart evaluates<br>images acquired using the FerriSmart and<br>HepaFat-AI protocols and analyses the<br>acquired data to produce a 'multi-<br>parametric' reporting both fat metrics and<br>LIC. | Standalone software package that<br>automatically analyses multi-slice, spin-<br>echo MRI data sets encompassing the<br>abdomen to provide objective and<br>reproducible determination of liver<br>parameters to support clinicians in the<br>assessment of liver iron status. The<br>software tool determines the signal decay<br>rate (R2) that is used to characterize iron<br>loading in the liver, which is then<br>transformed by a defined calibration curve<br>to provide a quantitative measure of liver<br>iron concentrations in vivo. | Standalone software platform designed to<br>automatically analyse within seconds<br>magnetic resonance imaging (MRI) datasets to<br>generate an estimate of the patient's<br>volumetric liver fat fraction (VLFF),<br>converted into proton density fat fraction<br>(PDFF) and steatosis grade. No user input is<br>required for the analysis thus minimising the<br>impact of human error on obtained results. |
| | LiverSmart (Subject Device) | FerriSmart (Predicate) | HepaFat-AI (Predicate) |
| Technology | Convolutional neural networks for the<br>image analysis.<br>Algorithmic for the image's quality checks,<br>R2 conversion into LIC, and Alpha<br>conversion into VLFF. | Convolutional neural networks for the<br>image analysis.<br>Algorithmic for the image's quality checks<br>and R2 conversion into LIC. | Convolutional neural networks for the image<br>analysis.<br>Algorithmic for the image's quality checking<br>and Alpha conversion into VLFF. |
| Intended<br>purpose(s) | 1. Supporting clinical diagnoses about the<br>status of LIC and the status of liver fat<br>content.<br>2. Supporting the subsequent clinical<br>decision-making processes.<br>3. Supporting the use in clinical research<br>trials, directed at studying changes in<br>LIC and liver fat as a result of<br>interventions. | 1. Supporting clinical diagnoses about the<br>status of LIC.<br>2. Supporting the subsequent clinical<br>decision-making processes.<br>3. Supporting the use in clinical research<br>trials, directed at studying changes in<br>LIC as a result of interventions. | 1. Supporting clinical diagnoses about the<br>status of liver fat content.<br>2. Supporting the subsequent clinical<br>decision-making processes.<br>3. Supporting the use in clinical research<br>trials, directed at studying changes in liver<br>fat as a result of interventions. |
| Intended Use | 1. For the measurement of R2 and iron<br>concentration in the liver from MRI<br>scans.<br>2. For quantitative measurement of the<br>triglyceride fat fraction in magnetic<br>resonance images of the liver, also<br>known as volumetric liver fat fraction<br>(VLFF). | 1. Measurement of R2 and iron<br>concentration in the liver from MRI<br>scans | 1. For quantitative measurement of the<br>triglyceride fat fraction in magnetic<br>resonance images of the liver, also known<br>as volumetric liver fat fraction (VLFF).<br>*It utilises magnetic resonance images that<br>exploit the difference in resonance frequencies<br>between hydrogen nuclei in water and<br>triglyceride fat. The quantitative triglyceride<br>fat fraction is based on the measurement of a<br>magnetic resonance parameter that reflects the<br>ratio of the proton density signal of<br>triglyceride fat to the total proton density<br>signal in the liver.<br>When interpreted by a trained physician, the<br>results provide information that can aid in<br>diagnosis. |
| | LiverSmart (Subject Device) | FerriSmart (Predicate) | HepaFat-AI (Predicate) |
| Indications | LiverSmart is indicated to:<br><br>For Liver Iron Concentration<br><br>1. measure liver iron concentration in<br>individuals with confirmed or suspected<br>systemic iron overload;<br>2. monitor liver iron burden in transfusion<br>dependent thalassemia patients and<br>patients with sickle cell disease<br>receiving blood transfusions;<br>3. aid in the identification and monitoring<br>of non-transfusion-dependent<br>thalassemia patients receiving therapy<br>with Deferasirox.<br><br>For Liver Fat Assessment<br><br>1. assess the volumetric liver fat fraction,<br>proton density fat fraction and steatosis<br>grade in individuals with confirmed or<br>suspected fatty liver disease.<br>When interpreted by a trained physician, the<br>results can be used to:<br>2. monitor liver fat content in patients<br>undergoing weight loss management;<br>3. aid in the assessment and screening of<br>living donors for liver transplant. | FerriSmart is Indicated to:<br><br>1. measure liver iron concentration in<br>individuals with confirmed or<br>suspected systemic iron overload;<br>2. monitor liver iron burden in<br>transfusion dependent thalassemia<br>patients and patients with sickle cell<br>disease receiving blood transfusions;<br>3. aid in the identification and monitoring<br>of non-transfusion-dependent<br>thalassemia patients receiving therapy<br>with Deferasirox. | HepaFat-AI is indicated to:<br><br>1. assess the volumetric liver fat fraction,<br>proton density fat fraction and steatosis<br>grade in individuals with confirmed or<br>suspected fatty liver disease.<br>When interpreted by a trained physician, the<br>results can be used to:<br>2. monitor liver fat content in patients<br>undergoing weight loss management;<br>3. aid in the assessment and screening of<br>living donors for liver transplant. |
| User | Radiologist | Radiologist | Radiologist |
| Hosting platform | Cloud-based or on-site hosting | Cloud-based or on-site hosting | Cloud-based or onsite platform |
| | LiverSmart (Subject Device) | FerriSmart (Predicate) | HepaFat-AI (Predicate) |
| Image-type<br>utilized | Magnetic Resonance | Magnetic Resonance | Magnetic Resonance |
| Image format | DICOM | DICOM | DICOM |
| Data Acquisition<br>method | Single Spin Echo (SSE)<br>Gradient Recalled Echo (GRE) | Single Spin Echo (SSE) | Gradient Recalled Echo (GRE) |
| Anatomical Sites | Liver | Liver | Liver |
| Analysis System<br>Components | LiverSmart:<br>(i) Data Preparation Module; and<br>(ii) Report Generation Module<br><br>FerriSmart:<br>(i) Magnetic Resonance Imaging<br>Protocol;<br>(ii) FerriSmart Analysis Software; and<br>(iii) Liver Iron Concentration<br>Measurement.<br><br>HepaFat-AI:<br>(i) Magnetic Resonance Imaging<br>Protocol;<br>(ii) HepaFat-AI Analysis Software;<br>(iii) Volumetric Liver Fat Fraction<br>Measurement;<br>(iv) Proton Density Fat Fraction<br>Measurement | (i) Magnetic Resonance Imaging<br>Protocol<br>(ii) FerriSmart Analysis Software<br>(iii) Liver Iron Concentration<br>Measurement | (i) Magnetic Resonance Imaging Protocol<br>(ii) HepaFat-AI Analysis Software<br>(iii) Volumetric Liver Fat Fraction<br>Measurement<br>(iv) Proton Density Fat Fraction<br>Measurement<br>(v) Steatosis Grade Measurement |
| | LiverSmart (Subject Device) | FerriSmart (Predicate) | HepaFat-AI (Predicate) |
| Result report<br>content | (v) Steatosis Grade Measurement<br><br>Page 1<br>(i) Report No., patient ID, patient name and<br>date of birth for full identification of the<br>patient.<br>(ii) Scan date, and analysis date.<br>(iii) Referrer and MRI centre.<br>(iv) Results displayed: LIC (mg/g dry<br>tissue), LIC (mmol/kg dry tissue),<br>associated with confidence intervals and<br>normal range.<br>(v) Results displayed: VLFF (%), PDFF (%)<br>and Steatosis grade, associated with<br>confidence intervals and normal range. | (i) Patient ID, patient name and date of<br>birth forfull identification of the<br>patient.<br>(ii) Scan date, and analysis date.<br>(iii) Referrer and MRI centre.<br>(iv) Results displayed: LIC (mg/g dry<br>tissue), LIC (mmol/kg dry tissue),<br>associated with confidence intervals<br>and normal range.<br>(v) Pictures of the 5 TEs of the analysed<br>slice.<br>(vi) LIC thresholds table | (i) Patient ID, patient name and date of<br>birth for full identification of the patient.<br>(ii) Scan date, and analysis date.<br>(iii) Referrer and MRI centre.<br>(iv) Results displayed: VLFF (%), PDFF (%)<br>and Steatosis grade, associated with<br>confidence intervals and normal range.<br>(v) NASH-CRN Steatosis Grading Guide<br>(vi) Pictures of the 3 TEs of the analysed<br>slice.<br>(vii) Liver colour map (for illustration<br>purpose only, not for diagnostic) |
| | Page 2<br><br>As per FerriSmart report<br><br>Page 3<br><br>As per HepaFat-AI report | | |
| Result report<br>format | HTML and PDF | HTML and PDF | HTML and PDF |
{7}------------------------------------------------
{8}------------------------------------------------
{9}------------------------------------------------
{10}------------------------------------------------
{11}------------------------------------------------
## SUMMARY OF CHANGE(S)
LiverSmart consists of two additional modules, over and above the FerriSmart and HepaFat-AI modules;
- (i) the Data Preparation Module, and
- (ii) the Report Generation Module.
## PERFORMANCE PARAMETERS
No change from the predicates, FerriSmart (K182218) and HepaFat-AI (K201039).
#### SUMMARY OF DESIGN CONTROL ACTIVITIES
Hazard analysis has been performed and documented. Hazard analysis is included in this submission. The test methods used are the same as those documented in the previously cleared submissions of the predicate devices, FerriSmart (K182218) and HepaFat-AI (201039). A statement of conformity with design controls is included in this submission.
### SAFETY
LiverSmart is designed and manufactured under the Quality System Regulations as outlined in 21 CFR § 820 and ISO 13485 Standards. LiverSmart is based upon the same technologies, operating principle, and software technology as the two predicate devices. Risk activities were conducted in concurrence with established medical device development standards and guidance.
### TESTING
Risk analy sis and verification testing conducted are documented and included in this submission, which demonstrate that the performance requirements have been met.
### SUBSTANTIAL EQUIVALENCE
Verification testing confirms that the data preparation module of LiverSmart detects anomalies in the sequence acquisition and reports the accurate error message. If an error is detected LiverSmart prevents further analysis. Additionally, LiverSmart yields identical results for VLFF, PDFF, steatosis grade, and LIC, when the same image datasets are analysed by HepaFat-AI and FerriSmart devices independently.
### CONCLUSION
The special 510(k) premarket notification for LiverSmart contains adequate information and data to enable the FDA-CDRH to determine substantial equivalence to the predicate devices. Resonance Health believes that enough evidence has been presented in this dossier to conclude that LiverSmart is safe, effective and performs as well as two the predicates.
Predicate graph will load when search results are available.
Embedding visualization will load when search results are available.
PDF viewer will load when search results are available.
Loading panels...
Select an item from Submissions
Click any panel, subpart, regulation, product code, or device to see details here.
Section Matches
Results will appear here.
Product Code Matches
Results will appear here.
Special Control Matches
Results will appear here.
Loading collections...
Loading
My Alerts
You will receive email notifications based on the filters and frequency you set for each alert.
Sort by:
Create Alert
Search Filters
Agent Token
Create a read-only bearer token for Claude, ChatGPT, or other agents that can call HTTP APIs.
Copy this now. It will not be shown again.
Connected apps
Apps you authorized through browser sign-in. Disconnecting revokes their access immediately.
Learn the FDA Browser
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.