Literature DB >> 29753491

Comparison of the Diagnostic Value of Monoexponential, Biexponential, and Stretched Exponential Diffusion-weighted MRI in Differentiating Tumor Stage and Histological Grade of Bladder Cancer.

Yanchun Wang1, Daoyu Hu1, Hao Yu1, Yaqi Shen1, Hao Tang1, Ihab R Kamel2, Zhen Li3.   

Abstract

RATIONALE AND
OBJECTIVES: We aimed to determine the utility of various diffusion parameters obtained from monoexponential, biexponential, and stretched exponential diffusion-weighted imaging (DWI) models in differentiating tumor stage and grade of bladder cancer.
MATERIALS AND METHODS: Forty-five patients with pathologically confirmed bladder cancer underwent multi-b-value DWI. An apparent diffusion coefficient (ADC) was calculated from DWI by using a monoexponential model. A true diffusion coefficient (D), perfusion-related pseudo-diffusion coefficient (D*), and perfusion fraction (f) were calculated from DWI by using a biexponential model. A water molecular diffusion heterogeneity index (α) and distributed diffusion coefficient (DDC) were calculated from DWI by using a stretched exponential model. All parameters were compared between different stages and grades by using the Mann-Whitney U test. Receiver operating characteristic and intrareader correlation coefficient analysis were used for statistical evaluations.
RESULTS: ADC, D, f, and DDC values were significantly higher in the non-muscle-invasive vs muscle-invasive bladder cancers (P = .000, .000, .002, and .000, respectively) and in low-grade vs high-grade ones (P = .000, .000, .018, and .000, respectively). D* value was significantly lower in the low-grade bladder cancers compared to high-grade ones (P = .012). The areas under the receiver operating characteristic curve of ADC, D, and DDC values were 0.945, 0.912, and 0.946 in staging bladder cancers; 0.866, 0.862, and 0.856 in grading bladder cancers, respectively.
CONCLUSION: Biexponential and stretched exponential DWI models may provide more parameters in staging and grading bladder cancers and show a slight difference between DDC and ADC values in staging bladder cancers. These two DWI models, as well as the monoexponential models, were very helpful in staging and grading bladder cancers.
Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Monoexponential model; biexponential model; bladder cancer; magnetic resonance imaging; stretched exponential model

Mesh:

Year:  2018        PMID: 29753491     DOI: 10.1016/j.acra.2018.04.016

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


  4 in total

1.  Differentiation of high-grade from low-grade diffuse gliomas using diffusion-weighted imaging: a comparative study of mono-, bi-, and stretched-exponential diffusion models.

Authors:  Masaoki Kusunoki; Kazufumi Kikuchi; Osamu Togao; Koji Yamashita; Daichi Momosaka; Yoshitomo Kikuchi; Daisuke Kuga; Nobuhiro Hata; Masahiro Mizoguchi; Koji Iihara; Satoshi O Suzuki; Toru Iwaki; Yuta Akamine; Akio Hiwatashi
Journal:  Neuroradiology       Date:  2020-05-18       Impact factor: 2.804

2.  Predicting Grade of Esophageal Squamous Carcinoma: Can Stretched Exponential Model-Based DWI Perform Better Than Bi-Exponential and Mono-Exponential Model?

Authors:  Hui Yang; Xubo Ge; Xiuzhu Zheng; Xiaoqian Li; Jiang Li; Min Liu; Jianzhong Zhu; Jian Qin
Journal:  Front Oncol       Date:  2022-07-14       Impact factor: 5.738

3.  Evaluation of intratumoral heterogeneity by using diffusion kurtosis imaging and stretched exponential diffusion-weighted imaging in an orthotopic hepatocellular carcinoma xenograft model.

Authors:  Ran Guo; Shuo-Hui Yang; Fang Lu; Zhi-Hong Han; Xu Yan; Cai-Xia Fu; Meng-Long Zhao; Jiang Lin
Journal:  Quant Imaging Med Surg       Date:  2019-09

Review 4.  Study Progress of Noninvasive Imaging and Radiomics for Decoding the Phenotypes and Recurrence Risk of Bladder Cancer.

Authors:  Xiaopan Xu; Huanjun Wang; Yan Guo; Xi Zhang; Baojuan Li; Peng Du; Yang Liu; Hongbing Lu
Journal:  Front Oncol       Date:  2021-07-15       Impact factor: 6.244

  4 in total

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