Literature DB >> 31361366

Comparison of tri-exponential decay versus bi-exponential decay and full fitting versus segmented fitting for modeling liver intravoxel incoherent motion diffusion MRI.

Olivier Chevallier1,2, Nan Zhou3, Jean-Pierre Cercueil2, Jian He3, Romaric Loffroy2, Yì Xiáng J Wáng1.   

Abstract

OBJECTIVES: To determine whether bi- or tri-exponential models, and full or segmented fittings, better fit the intravoxel incoherent motion (IVIM) imaging signal of healthy livers.
METHODS: Diffusion-weighted images were acquired with a 3 T scanner using a respiratory-triggered echo-planar sequence and 16 b-values (0-800 s/mm2 ). Eighteen healthy volunteers had their livers scanned twice in the same session, and then once in another session. Liver parenchyma region-of-interest-based measurements were processed with bi-exponential and tri-exponential models, with both full fitting and segmented fitting (threshold b-value = 200 s/mm2 ).
RESULTS: With the signal of all scans averaged, bi-exponential model full fitting showed Dslow  = 1.14 × 10-3  mm2 /s, Dfast  = 193.6 × 10-3  mm2 /s, and perfusion fraction (PF) = 16.9%, and segmented fitting showed Dslow  = 0.98 × 10-3  mm2 /s, Dfast  = 42.2 × 10-3  mm2 /s, and PF = 23.3%. IVIM parameters derived from the tri-exponential model were similar for full fitting and segmented fitting, with slow (D'slow  = 0.98 × 10-3  mm2 /s; F'slow  = 76.4 or 76.6%), fast (D'fast  = 15.1 or 15.4 × 10-3  mm2 /s; F'fast  = 11.8 or 11.7%) and very fast (D'Vfast  = 445.0 or 448.8 × 10-3  mm2 /s; F'Vfast  = 11.8 or 11.7%) diffusion compartments. The tri-exponential model provided an overall better fit than the bi-exponential model. For the bi-exponential model, full fitting provided a better fit at very low and low b-values compared with segmented fitting, with the latter tending to underestimate Dfast ; however, the segmented method demonstrated lower error in signal prediction for high b-values. Compared with full fitting, tri-exponential segmented fitting offered better scan-rescan reproducibility.
CONCLUSION: For healthy liver, tri-exponential modeling is preferred to bi-exponential modeling. For the bi-exponential model, segmented fitting underestimates Dfast , but offers a more accurate estimation of Dslow .
© 2019 John Wiley & Sons, Ltd.

Entities:  

Keywords:  bi-exponential; diffusion weighted imaging; full fitting; intravoxel incoherent motion; liver; reproducibility; segmented fitting; tri-exponential

Mesh:

Year:  2019        PMID: 31361366     DOI: 10.1002/nbm.4155

Source DB:  PubMed          Journal:  NMR Biomed        ISSN: 0952-3480            Impact factor:   4.044


  8 in total

Review 1.  Diffusion-weighted MRI of the liver: challenges and some solutions for the quantification of apparent diffusion coefficient and intravoxel incoherent motion.

Authors:  Yi Xiang J Wang; Hua Huang; Cun-Jing Zheng; Ben-Heng Xiao; Olivier Chevallier; Wei Wang
Journal:  Am J Nucl Med Mol Imaging       Date:  2021-04-15

Review 2.  Topics on quantitative liver magnetic resonance imaging.

Authors:  Yì Xiáng J Wáng; Xiaoqi Wang; Peng Wu; Yajie Wang; Weibo Chen; Huijun Chen; Jianqi Li
Journal:  Quant Imaging Med Surg       Date:  2019-11

3.  Precision of region of interest-based tri-exponential intravoxel incoherent motion quantification and the role of the Intervoxel spatial distribution of flow velocities.

Authors:  Gregory Simchick; Diego Hernando
Journal:  Magn Reson Med       Date:  2022-08-15       Impact factor: 3.737

4.  Bi-exponential fitting excluding b=0 data improves the scan-rescan stability of liver IVIM parameter measures and particularly so for the perfusion fraction.

Authors:  Cun-Jing Zheng; Ben-Heng Xiao; Hua Huang; Nan Zhou; Tai-Yu Yan; Yì Xiáng J Wáng
Journal:  Quant Imaging Med Surg       Date:  2022-06

5.  Simultaneous Quantification of Anisotropic Microcirculation and Microstructure in Peripheral Nerve.

Authors:  Samer Merchant; Stewart Yeoh; Mark A Mahan; Edward W Hsu
Journal:  J Clin Med       Date:  2022-05-27       Impact factor: 4.964

6.  Intravoxel Incoherent Motion Model in Differentiating the Pathological Grades of Esophageal Carcinoma: Comparison of Mono-Exponential and Bi-Exponential Fit Model.

Authors:  Nian Liu; Xiongxiong Yang; Lixing Lei; Ke Pan; Qianqian Liu; Xiaohua Huang
Journal:  Front Oncol       Date:  2021-04-12       Impact factor: 6.244

7.  Self-supervised neural network improves tri-exponential intravoxel incoherent motion model fitting compared to least-squares fitting in non-alcoholic fatty liver disease.

Authors:  Marian A Troelstra; Anne-Marieke Van Dijk; Julia J Witjes; Anne Linde Mak; Diona Zwirs; Jurgen H Runge; Joanne Verheij; Ulrich H Beuers; Max Nieuwdorp; Adriaan G Holleboom; Aart J Nederveen; Oliver J Gurney-Champion
Journal:  Front Physiol       Date:  2022-09-06       Impact factor: 4.755

8.  Characterisation of microvessel blood velocity and segment length in the brain using multi-diffusion-time diffusion-weighted MRI.

Authors:  Lauren A Scott; Ben R Dickie; Shelley D Rawson; Graham Coutts; Timothy L Burnett; Stuart M Allan; Geoff Jm Parker; Laura M Parkes
Journal:  J Cereb Blood Flow Metab       Date:  2020-12-16       Impact factor: 6.200

  8 in total

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