Name: Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI
Uploaded: 2023-07-21T12:10:00
Description: Watch this Scientific Journal Video about Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI at JoVE.com

This publication was supported by the fifth national traditional Chinese medicine clinical excellent talents research program organized by the National Administration of Traditional Chinese Medicine. The official network link is &#39;http://www.natcm.gov.cn/renjiaosi/zhengcewenjian/2021-11-04/23082.html. &#39;

This study utilized 3D-digital LSD modeling to reconstruct the liver of a typical patient with clinically confirmed hepatic fibrosis. The patient was recruited from a well-known liver disease treatment institution, &#34;You An Hospital&#34; in Beijing, China, and underwent routine upper abdominal magnetic resonance imaging (MRI) and MRE imaging after providing consent. The patient was chosen as the case study for this research method due to the confirmation of hepatic fibrosis staging through pathological examination and...

Quantitative Analysis of Liver Stiffness Distribution

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In clinical practice, it is challenging to accurately quantify and track the condition of early-stage hepatic fibrosis patients. The comparison shown in Figure 9 fully reflects the degree of hepatic fibrosis in the patient compared to a healthy liver; of course, this figure can also be a comparison between two different periods for the patient, used for evaluation of treatment efficacy. This precise quantification method is the core critical step of this study. Furthermore, the calculation m...

Hepatic fibrosis refers to the formation of excessive scar tissue in the liver, usually as a result of liver damage or disease1,2,3,4. It frequently arises as a consequence of chronic liver injury and is commonly associated with liver diseases, such as chronic viral hepatitis, non-alcoholic fatty liver disease, and alcoholic liver disease. If left untreated, hepatic fibrosis can progress to cirrhosis, a potentially life-threatening condition associated with significant morbidity and mortality.
Active research in this area aims to elucidate the cellular and molecular mechanisms underlying the pathogenesis of hepatic fibrosis, as well as to develop novel diagnostic and therapeutic strategies to improve patient outcomes. Another objective is the noninvasive detection of the hepatic fibrosis stage, which is a critical aspect that directly correlates with disease diagnosis, treatment selection, and prognosis evaluation. Despite the importance of accurate diagnosis and the monitoring of hepatic fibrosis, traditional diagnostic methods, such as liver biopsy, are invasive and associated with significant risks. In contrast, magnetic resonance elastography5,6 (MRE) is a promising non-invasive imaging technique that has demonstrated potential in the diagnosis and monitoring of hepatic fibrosis by quantifying liver stiffness.
In recent years, there has been significant research focused on evaluating the accuracy and reliability of MRE in the diagnosis of hepatic fibrosis, as well as its potential advantages over traditional diagnostic methods. The liver stiffness metric of MRE has been granted approval by the United States Food and Drug Administration (FDA) for clinical diagnosis, and extensive comparative analysis with pathological results has been conducted in clinical practice. The results have shown that the stiffness maps generated by MRE exhibit a strong positive correlation with various stages of liver fibrosis7,8,9,10,11,12. Yet so far, the work of accurately evaluating and tracking the progression of liver fibrosis in patients through quantitative analysis of liver stiffness distribution (LSD) by matching liver structure images with MRE has not made much progress.
In this study, the medical imaging group analysis technique13,14,15 is introduced to achieve accurate alignment of the liver structure images with the stiffness map generated by MRE in 3D space, enabling the calculation of liver stiffness values for each voxel of the entire liver. Based on the 3D-digital model of LSD, the exact distribution of patient-specific liver fibrosis staging can be calculated and evaluated. This lays a solid foundation for the precise quantitative diagnosis of early-stage liver fibrosis.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>MATLAB</td>
			<td>MathWorks&#160;</td>
			<td>2022B</td>
			<td>Computing and visualization&#160;</td>
		</tr>
		<tr>
			<td>Mimics</td>
			<td>Materialise</td>
			<td>Mimics Research V20</td>
			<td>Model format transformation</td>
		</tr>
		<tr>
			<td>Tools for 3D_LSD</td>
			<td>Intelligent&#160;Entropy</td>
			<td>HepaticFibrosis V1.0</td>
			<td>Beijing Intelligent Entropy Science &#38; Technology Co Ltd. 
			Modeling for CT/MRI fusion</td>
		</tr>
	</tbody>
</table>

a three-dimensional digital model for early diagnosis of hepatic fibrosis based on magnetic resonance elastography

Hepatic fibrosis is an early stage of liver cirrhosis, and there are no better non-invasive and convenient methods for the detection and evaluation of the disease. Despite the good progress made with the liver stiffness map (LSM) based on magnetic resonance elastography (MRE), there are still some limitations that need to be overcome, including manual focus determination, manual selection of regions of interest (ROIs), and discontinuous LSM data without structural information, which makes it impossible to evaluate the liver as a whole. In this study, we propose a novel three-dimensional (3D) digital model for the early diagnosis of hepatic fibrosis based on MRE.
MRE is a non-invasive imaging technique that employs magnetic resonance imaging (MRI) to measure the liver stiffness at the scanning site through human-computer interaction. Studies have indicated a significant positive correlation between the LSM obtained through MRE and the degree of hepatic fibrosis. However, for clinical purposes, a comprehensive and precise quantification of the degree of hepatic fibrosis is necessary. To address this, the concept of Liver Stiffness Distribution (LSD) was proposed in this study, which refers to the 3D stiffness volume of each liver voxel obtained by the alignment of 3D liver tissue images and MRE indicators. This provides a more effective clinical tool for the diagnosis and treatment of hepatic fibrosis.

Author Spotlight: Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI 

A Three-Dimensional Digital Model for Early Diagnosis of Hepatic Fibrosis Based on Magnetic Resonance Elastography

By utilizing the information in the Description_Name field of DICOM files, the original MRI folder can be renamed to facilitate the rapid localization of the required imaging sequence during the analysis process in the imaging group.&#160;The MRI-IDEAL out-phase sequence is the type of MRI sequence used for providing clearer descriptions of liver tissue boundaries. This is because the MRI-IDEAL out-of-phase sequence can better differentiate the magnetization strength and angle of different tissues throug...

Watch this Scientific Journal Video about Advancing Hepatic Fibrosis Diagnosis Using Magnetic Resonance Elastography and AI at JoVE.com

The objective of this study was to develop a novel three-dimensional digital model for the early diagnosis of hepatic fibrosis, which includes the stiffness of each voxel in the patient's liver and can thus, be used to calculate the distribution ratio of the patient's liver at different fibrosis stages.

Hepatic fibrosis is an early stage of liver cirrhosis, and there are no better non-invasive and convenient methods for the detection and evaluation of the ...

The scope of the research is to develop a three dimensional digital model for the early diagnosis of hepatic fibrosis based on magnetic resonance elastography. The research aims to address the limitations of current methods and provide a noninvasive and quantitative approach for the accurate assessment and monitoring of hepatic fibrosis. Some of the current experimental challenges in the field of hepatic fibrosis research include improving the scanning accuracy and imaging techniques of non-invasive methods like magnetic resonance elastography, standardizing computational protocols for consistent results and accumulating more comprehensive, and that was data size for accurate classification and diagnosis.The liver MRI structural images were accurately aligned with MRE images, enabling the three dimensional distribution of liver stiffness, distribution, and achieving precise quantification in 3D space. It is possible to accurately establish a liver's stiffness distribution map for a healthy liver, and conveniently utilize it for the diagnosis and the treatment of patients with different stages of liver cirrhosis. In the future, we want to address AI-driven diagnosis, treatment, and prognosis of liver diseases, as well as the development of herbal medicines related to liver diseases.