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Intravoxel incoherent motion MRI 3-dimensional quantitative detection of tissue abnormality with improved data processing

A technology of data and organization, applied in the direction of image data processing, application, surgery, etc.

Pending Publication Date: 2020-02-11
THE CHINESE UNIVERSITY OF HONG KONG
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

But so far, attempts to detect liver fibrosis using IVIM technology have been unsuccessful

Method used

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  • Intravoxel incoherent motion MRI 3-dimensional quantitative detection of tissue abnormality with improved data processing
  • Intravoxel incoherent motion MRI 3-dimensional quantitative detection of tissue abnormality with improved data processing
  • Intravoxel incoherent motion MRI 3-dimensional quantitative detection of tissue abnormality with improved data processing

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0052] A study was conducted using MRI data from the Shenzhen 2012 / 2013 dataset to determine the feasibility of using multi-parameter analysis to distinguish between fibrotic and normal liver tissue (the dataset is described in: PXLu et al., “Decreases inmolecular diffusion, perfusion fraction and perfusion-related diffusion infibrotic livers: a prospective clinical intravoxel incoherent motion MRimaging study, "PLoS One 9(12):e113846(2014)). The individuals included 16 individuals with normal liver (F0 fibrosis stage) and 33 individuals with hepatitis B virus and different degrees of liver fibrosis (F1-F4 fibrosis stage). According to the routine diagnosis based on histology, the fibrosis stage of each individual is determined. In this example, the labeling of the fibrosis stage follows the conventional scheme, where F0 stage indicates no fibrosis; F1 stage indicates only mild fibrosis can be seen in the hepatic portal area; F2 stage indicates that fibrosis extends from the he...

Embodiment 2

[0072] Using MRI data from the Shenzhen 2012 / 2013 dataset (see the description of Example 1 above), a study was conducted to determine the best threshold b value for distinguishing healthy and fibrotic liver tissue. The right lobe of the liver is selected for analysis, and the definition of ROI is similar to image 3 Shown. Specifically, for each individual, manually position the ROI at b=10s / mm 2 To cover most of the right liver parenchyma, while avoiding large blood vessels; the same ROI extends to include all b-value images of the individual.

[0073] For each individual, figure 2 The analysis process of block 208 is executed 6 times, each time using a different threshold b value to determine D slow ; The threshold b value used is 40, 60, 80, 100, 150 and 200s / mm 2 . In each analysis, the images acquired with b value greater than or equal to the threshold are used to determine D slow ; Regardless of the threshold, all b values ​​are used in the subsequent analysis phase. S...

Embodiment approach

[0100] It is believed that the embodiments described herein provide a non-invasive technique that can produce reliable diagnostic indicators of liver fibrosis, including early liver fibrosis that can only be detected by invasive techniques such as liver biopsy so far.

[0101] Although the invention has been described in terms of specific embodiments, those skilled in the art will recognize that many modifications are possible. The specific data collection sequence and analysis process can be changed. Studying a larger number of individuals with known stages of fibrosis (including healthy livers) can allow the determination of an optimized set of diagnostic parameters. In addition, it is expected that in clinical practice, the diagnostic techniques described herein will be combined with other information about the patient's condition for diagnosis.

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PUM

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Abstract

Liver fibrosis can be detected using intravoxel incoherent motion (IVIM) MRI techniques. For example, using a diffusion weighted MRI imaging sequence, scans of a patient's liver can be made. Signal intensity data acquired in MRI scans can be fitted to a bi-exponential model of signal attenuation representing a combination of a fast component associated with perfusion and a slow component associated with diffusion in the tissue. This allows the extraction of parameters representing the slow and fast diffusion rates, as well as the fractional contributions of the fast and slow components. Analysis of a combination of these parameters in a multi-dimensional space (e.g., in a three-dimensional space) yields a metric that can distinguish healthy liver from fibrotic liver.

Description

Background technique [0001] The present application generally relates to the detection of liver fibrosis, and particularly relates to the use of intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and multidimensional (e.g., three-dimensional) analysis tools to detect tissue abnormalities, such as liver Fibrosis. [0002] Chronic liver disease is a major public health problem worldwide. Due to the aging of the population, the growth of obesity and non-alcoholic steatohepatitis, and chronic viral hepatitis, the growth trend of chronic liver disease is expected to intensify, and the above-mentioned problems may lead to liver fibrosis, cirrhosis and hepatocellular carcinoma. [0003] Liver fibrosis is a common feature of almost all chronic liver diseases and involves the accumulation of collagen, proteoglycans and other macromolecules in the extracellular matrix. Clinically, liver fibrosis is usually insidious and develops slowly over decades. Hepatic fibrosis was o...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B5/055G06T7/00
CPCA61B5/7207A61B5/7264A61B5/7267A61B5/055A61B5/4244G01R33/56341A61B2576/02A61B5/748G06T7/0012G06T2207/10092G06T2207/30056G16H30/40G16H50/20
Inventor 王毅翔陈蔚天李瑶邓敏梁志信
Owner THE CHINESE UNIVERSITY OF HONG KONG
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