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HepaFat-AI

Automated MRI Measurement Of Liver Fat

HepaFat-AI is a non-invasive MRI-based technique designed to automatically analyse MRI datasets to generate an estimate of the patient’s liver fat. These images, acquirable on most makes and models of 1.5 and 3 Tesla MRI machines, are obtained through a unique and standardised scanning sequence to ensure results are accurate, reliable, and reproducible over time and between hospitals and the various makes and models of MRI scanners.

Due to the quality-controlled, standardised nature of the test, a patient may have a HepaFat-AI scan at any HepaFat-AI verified MRI centre, anywhere in the world, and receive reproducible, and reliable results.

HepaFat-AI received 510(k) clearance from the US Food and Drug Administration (FDA) in December 2020. The FDA has cleared HepaFat-AI with the following indications:

  • 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 HepaFat-AI results can be used to:

  • Monitor liver fat content in patients undergoing weight loss management; and can be used to
  • Aid in the assessment and screening of living donors for liver transplant.

HepaFat-AI can be deployed either in the cloud or on premises and can be integrated directly into radiology workflows. For current availability, please contact us directly.

Comprehensive all-in-one Reporting

HepaFat-AI is a fully automated and comprehensive all-in-one liver fat solution that reports the following:

  • VLFF – (Volumetric Liver Fat Fraction)
  • PDFF – (Proton Density Fat Fraction)
  • Steatosis Grade

In the event that extremely high liver fat content is detected, the HepaFat AI analysis process will generate a different report with a warning message that indicates the value is outside the validated calibration range and that the associated uncertainty makes a precise estimate too unreliable for reporting.

In the event that high liver iron concentration is suspected, or that there is possible lung crest present due to incorrect slice position, a warning is given and no result will be shown on the generated HepaFat-AI report.

Key HepaFat-AI Features

Why Use HepaFat-AI to Measure Liver Fat

HepaFat-AI is quick, easy and painless, with an MRI scan time of only two minutes. HepaFat-AI does not require any contrast agents and being MRI based there is no risk from ionising radiation. Due to the automated nature of the technology, HepaFat-AI can also return a patient report in real-time back to the clinician.

Histopathological assessment of a patient’s liver fat levels from a liver biopsy is commonly considered the gold standard for clinical assessment of liver fat. However, it is subjective, has a poor reproducibility and significant sampling error and suffers from the risks associated with an invasive procedure.

Ultrasound, while widely available, only has a sensitivity of approximately 70% and this is further reduced in obese patients. It is additionally hampered by factors such as fibrosis, edema and extrahepatic adipose tissue.

CT is also a widely available imaging modality that evaluates hepatic steatosis indirectly based on hepatic x-ray attenuation. Several factors other than fat (e.g. iron, copper, glycogen, fibrosis, edema, ingestion of drugs such as amiodarone and gold) affect CT attenuation values, resulting in unavoidable errors in fat quantification and low sensitivity for mild-moderate steatosis. Moreover, as CT relies on ionizing radiation, it is not suitable for use in children and for longitudinal monitoring of adults with liver fat. MR has also been used for quantitative assessment of fat and is widely accepted as superior compared to ultrasound and CT.

HepaFat-AI is used in conjunction with a specific MRI data acquisition protocol that is a variation of the Dixon Method. Many MR fat quantification methods such as Magnetic Resonance Spectroscopy (MRS) and other Dixon based imaging methods report the fat:water proton ratio. This ratio is not directly comparable to a fat measurement from a liver biopsy specimen as it neither represents the percentage of parenchyma involved with fat nor the volume fraction of fat in the biopsy. Resonance Health has addressed this issue with HepaFat-AI.

Potential Clinical Applications

Gastroenterology and Hepatology Applications

Surgical Applications

Applications by Primary Care Physicians

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How does HepaFat-AI work?

HepaFat AI is based on the Dixon principle of measuring the in-phase and out-of-phase MRI signal in liver tissue. Measurements are achieved through the acquisition of a series of spoiled gradient recalled echo images at three specific echo times.

The process from data upload to report generation takes under 60 seconds for completion. HepaFat AI has been extensively validated to ensure the results are accurate and reproducible.

HepaFat-AI via Resonance Health

HepaFat-AI is a stand-alone software application that automatically analyses MRI (DICOM) images that are uploaded via the Resonance Health web portal. These images, acquirable on most makes and models of 1.5 and 3 Tesla MRI machines, are obtained through a unique and standardised scanning sequence to ensure results are accurate, reliable, and reproducible over time and between hospitals and the various makes and models of MRI scanners.

The entire HepaFat-AI analysis process is completely automated.  The HepaFat-AI technology will initially inspect all images to ensure that they have been acquired with the correct protocol.  If errors are detected in the method of data acquisition, HepaFat-AI will not analyse the data but will indicate the corrective steps that need to be taken to acquire compliant images. Uploading and analysis of data typically takes about 30 seconds.

Due to the quality-controlled, standardised nature of the test, a patient may have HepaFat-AI analysis at any HepaFat-verified MRI centre, anywhere in the world.

HepaFat-AI Resources

Click the link(s) below to access our resources. Need something else? Please contact our team at info@resonancehealth.com for further information.

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