Dependence of intravoxel incoherent motion diffusion MR threshold b -value selection for separating perfusion and diffusion compartments and liver fibrosis diagnostic performance

Abstract

Background

Intravoxel incoherent motion (IVIM) tissue parameters depend on the threshold b-value.

Purpose

To explore how threshold b-value impacts PF (f), D_slow (D), and D_fast (D*) values and their performance for liver fibrosis detection.

Material and Methods

Fifteen healthy volunteers and 33 hepatitis B patients were included. With a 1.5-T magnetic resonance (MR) scanner and respiration gating, IVIM data were acquired with ten b-values of 10, 20, 40, 60, 80, 100, 150, 200, 400, and 800 s/mm². Signal measurement was performed on the right liver. Segmented-unconstrained analysis was used to compute IVIM parameters and six threshold b-values in the range of 40–200 s/mm² were compared. PF, D_slow, and D_fast values were placed along the x-axis, y-axis, and z-axis, and a plane was defined to separate volunteers from patients.

Results

Higher threshold b-values were associated with higher PF measurement; while lower threshold b-values led to higher D_slow and D_fast measurements. The dependence of PF, D_slow, and D_fast on threshold b-value differed between healthy livers and fibrotic livers; with the healthy livers showing a higher dependence. Threshold b-value = 60 s/mm² showed the largest mean distance between healthy liver datapoints vs. fibrotic liver datapoints, and a classification and regression tree showed that a combination of PF (PF < 9.5%), D_slow (D_slow < 1.239 × 10^–3 mm²/s), and D_fast (D_fast < 20.85 × 10^–3 mm²/s) differentiated healthy individuals and all individual fibrotic livers with an area under the curve of logistic regression (AUC) of 1.

Conclusion

For segmented-unconstrained analysis, the selection of threshold b-value = 60 s/mm² improves IVIM differentiation between healthy livers and fibrotic livers.

Keywords

Magnetic resonance imaging (MRI)intravoxel incoherent motion (IVIM)diffusion perfusion liver fibrosis

Get full access to this article

View all access options for this article.

References

MacLachlan

Cowie

. Hepatitis B virus epidemiology. Cold Spring Harb Perspect Med 2015; 5: a021410–a021410.

Cornberg

Razavi

Alberti

et al.

A systematic review of hepatitis C virus epidemiology in Europe, Canada and Israel. Liver Int 2011; 31: (Suppl. 2): 30–60.

Weiskirchen

Tacke

. Liver fibrosis: from pathogenesis to novel therapies. Dig Dis 2016; 34: 410–422.

Sanyal

Friedman

McCullough

et al.

Challenges and opportunities in drug and biomarker development for nonalcoholic steatohepatitis: findings and recommendations from an American Association for the Study of Liver Diseases-U.S. Food and Drug Administration Joint Workshop. Hepatology 2015; 61: 1392–1405.

Le Bihan

Breton

Lallemand

et al.

MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 1986; 161: 401–407.

Le Bihan

Breton

Lallemand

et al.

Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology 1988; 168: 497–505.

Guiu

Cercueil

. Liver diffusion-weighted MR imaging: the tower of Babel? Eur Radiol 2011; 21: 463–467.

Moreno

Burchell

Rousselot

et al.

Portal blood flow in cirrhosis of the liver. J Clin Invest 1967; 46: 436–445.

Moreno

Rousselot

Panke

et al.

The rate of hepatic blood flow in normal subjects and in patients with portal hypertension. Surg Gynecol Obstet 1960; 111: 443–450.

10.

Yamada

Aung

Himeno

et al.

Diffusion coefficients in abdominal organs and hepatic lesions: evaluation with intravoxel incoherent motion echo-planar MR imaging. Radiology 1999; 210: 617–623.

11.

Cercueil

Yuan

et al.

Liver intravoxel incoherent motion (IVIM) magnetic resonance imaging: a comprehensive review of published data on normal values and applications for fibrosis and tumor evaluation. Quant Imaging Med Surg 2017; 7: 59–78.

12.

Wáng YXJ, Deng M, Li YT, et al. A combined use of intravoxel incoherent motion MRI parameters can differentiate early-stage Hepatitis-b fibrotic livers from healthy livers. SLAS Technol 2017. doi: 10.1177/2472630317717049.

13.

Patel

Shackel

. Current status of fibrosis markers. Curr Opin Gastroenterol 2014; 30: 253–259.

14.

Barbieri

Donati

Froehlich

et al.

Impact of the calculation algorithm on biexponential fitting of diffusion-weighted MRI in upper abdominal organs. Magn Reson Med 2016; 75: 2175–2184.

15.

Park

Sung

Lee

et al.

Intravoxel incoherent motion diffusion-weighted MRI of the abdomen: The effect of fitting algorithms on the accuracy and reliability of the parameters. J Magn Reson Imaging 2017; 45: 1637–1647.

16.

Luciani

Vignaud

Cavet

et al.

Liver cirrhosis: intravoxel incoherent motion MR imaging–pilot study. Radiology 2008; 249: 891–899.

17.

Guiu

Petit

Capitan

et al.

Intravoxel incoherent motion diffusion-weighted imaging in nonalcoholic fatty liver disease: a 3.0-T MR study. Radiology 2012; 265: 96–103.

18.

Patel

Sigmund

Rusinek

et al.

Diagnosis of cirrhosis with intravoxel incoherent motion diffusion MRI and dynamic contrast-enhanced MRI alone and in combination: preliminary experience. J Magn Reson Imaging 2010; 31: 589–600.

19.

Huang

Yuan

et al.

Decreases in molecular diffusion, perfusion fraction and perfusion-related diffusion in fibrotic livers: a prospective clinical intravoxel incoherent motion MR imaging study. PLoS One 2014; 9: e113846–e113846.

20.

Chung

Lee

Kim

et al.

Intravoxel incoherent motion MRI for liver fibrosis assessment: a pilot study. Acta Radiol 2015; 56: 1428–1436.

21.

Ichikawa

Motosugi

Morisaka

et al.

MRI-based staging of hepatic fibrosis: Comparison of intravoxel incoherent motion diffusion-weighted imaging with magnetic resonance elastography. J Magn Reson Imaging 2015; 42: 204–210.

22.

Jeng

et al.

Assessing hepatic fibrosis: comparing the intravoxel incoherent motion in MRI with acoustic radiation force impulse imaging in US. Eur Radiol 2015; 25: 3552–3559.

23.

Wurnig

Donati

Ulbrich

et al.

Systematic analysis of the intravoxel incoherent motion threshold separating perfusion and diffusion effects: Proposal of a standardized algorithm. Magn Reson Med 2015; 74: 1414–1422.

24.

ter Voert

Delso

Porto

et al.

Intravoxel incoherent motion protocol evaluation and data quality in normal and malignant liver tissue and comparison to the literature. Invest Radiol 2016; 51: 90–99.

25.

Dijkstra

Wolff

van Melle

et al.

Diminished liver microperfusion in Fontan patients: A biexponential DWI study. PLoS One 2017; 12: e0173149–e0173149.

26.

Bedossa

Poynard

. The METAVIR Cooperative Study Group. An algorithm for the grading of activity in chronic hepatitis C. Hepatology 1996; 24: 289–293.

27.

Pavlov

Casazza

Nikolova

et al.

Transient elastography for diagnosis of stages of hepatic fibrosis and cirrhosis in people with alcoholic liver disease. Cochrane Database Syst Rev 2015; 1: CD010542–CD010542.

28.

Franciscus A. HCV diagnostic tools: grading and staging a liver biopsy (version 2.2). Available at: www.hcvadvocate.org.

29.

Chang

Lin

C-J

. LIBSVM: a library for support vector machines. ACM Transactions on Intelligent Systems and Technology (TIST) 2011; 2: 27–27.

30.

Woo

Leung

. Anthropometric cut points for definition of sarcopenia based on incident mobility and physical limitation in older Chinese people. J Gerontol A Biol Sci Med Sci 2016; 71: 935–940.

31.

Zhang

Wang

et al.

Cramér-Rao bound for intravoxel incoherent motion diffusion weighted imaging fitting. Conf Proc IEEE Eng Med Biol Soc 2013; 2013: 511–514.

32.

Zhang

Jin

Deng

et al.

Intra-voxel incoherent motion MRI in rodent model of diethylnitrosamine-induced liver fibrosis. Magn Reson Imaging 2013; 31: 1017–1021.

33.

Lemke

Stieltjes

Schad

et al.

Toward an optimal distribution of b values for intravoxel incoherent motion imaging. Magn Reson Imaging 2011; 29: 766–776.

34.

Cercueil

Petit

Nougaret

et al.

Intravoxel incoherent motion diffusion-weighted imaging in the liver: comparison of mono-, bi- and tri-exponential modelling at 3.0-T. Eur Radiol 2015; 25: 1541–1550.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

1.03 MB