Literature DB >> 30527302

Grading and proliferation assessment of diffuse astrocytic tumors with monoexponential, biexponential, and stretched-exponential diffusion-weighted imaging and diffusion kurtosis imaging.

Ju Zhang1, Xiaowei Chen2, Dong Chen3, Zhenxiong Wang4, Shihui Li5, Wenzhen Zhu6.   

Abstract

PURPOSE: To compare the main parameters derived from monoexponential, biexponential and stretched-exponential diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) with respect to diagnostic performance for tumor grading and proliferation assessment in diffuse astrocytic tumors (DATs).
MATERIALS AND METHODS: Fifty-eight pathologically confirmed DAT patients who underwent DWI and DKI on a 3-T scanner were prospectively collected and retrospectively reviewed. Measurements including the apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), heterogeneity index (α), mean diffusivity (MD), fractional anisotropy (FA), and mean kurtosis (MK) were compared between tumor grades (Ⅱ, Ⅲ, and Ⅳ) by using a Jonckheere-Terpstra test. Receiver operating characteristic (ROC) curves were used to assess the diagnostic efficacy of these parameters. Spearman's rho with the Ki-67 labeling index (LI) was calculated for each parameter.
RESULTS: MK values differed significantly between all DAT subtypes and increased with grade. The ADC, D, f, DDC, α and MD values were significantly higher in grade Ⅱ tumors than in grade Ⅲ/Ⅳ tumors. D* values were significantly lower in grade Ⅱ tumors than in grade Ⅳ tumors (all P < 0.05). In discriminating between grade Ⅱ and Ⅲ tumors, α, MK, MD, D and f had significantly greater area under the ROC curve (AUC) values than D* and FA (0.927, 0.901, 0.896, 0.895, and 0.889, respectively vs 0.659 and 0.598, respectively, P < 0.05). In discriminating between grade Ⅲ and Ⅳ tumors, only MK demonstrated acceptable discrimination (AUC = 0.711). MK and D showed a strong correlation with the Ki-67 LI (ρ = 0.791 and -0.789, respectively, P < 0.001). D*, f, MD, ADC, DDC and α showed a moderate correlation (|ρ| ranged from 0.415 to 0.698, P < 0.05).
CONCLUSION: MK and D have considerable potential to predict the degree of proliferation of DATs. MK could effectively characterize microstructural changes throughout the malignant transformation of DATs and provided useful complementary information for grading.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Biexponential model; Diffuse astrocytic tumors; Diffusion kurtosis imaging; Diffusion-weighted imaging; Ki-67; Stretched-exponential model

Mesh:

Year:  2018        PMID: 30527302     DOI: 10.1016/j.ejrad.2018.11.003

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  7 in total

1.  Evaluation of diffuse glioma grade and proliferation activity by different diffusion-weighted-imaging models including diffusion kurtosis imaging (DKI) and mean apparent propagator (MAP) MRI.

Authors:  Sheng-Hui Xie; Rui Lang; Bo Li; He Zhao; Peng Wang; Jin-Long He; Xue-Ying Ma; Qiong Wu; Shao-Yu Wang; Hua-Peng Zhang; Yang Gao; Jian-Lin Wu
Journal:  Neuroradiology       Date:  2022-07-15       Impact factor: 2.995

2.  Minimal apparent diffusion coefficient in predicting the Ki-67 proliferation index of pancreatic neuroendocrine tumors.

Authors:  Yijing Xie; Shipeng Zhang; Xianwang Liu; Xiaoyu Huang; Qing Zhou; Yongjun Luo; Qian Niu; Junlin Zhou
Journal:  Jpn J Radiol       Date:  2022-03-14       Impact factor: 2.701

3.  Identification of histological features of endometrioid adenocarcinoma based on amide proton transfer-weighted imaging and multimodel diffusion-weighted imaging.

Authors:  Fangfang Fu; Nan Meng; Zhun Huang; Jing Sun; Xuejia Wang; Jie Shang; Ting Fang; Pengyang Feng; Kaiyu Wang; Dongming Han; Meiyun Wang
Journal:  Quant Imaging Med Surg       Date:  2022-02

4.  Feasibility of generalised diffusion kurtosis imaging approach for brain glioma grading.

Authors:  E L Pogosbekian; I N Pronin; N E Zakharova; A I Batalov; A M Turkin; T A Konakova; I I Maximov
Journal:  Neuroradiology       Date:  2021-01-07       Impact factor: 2.804

5.  Study of Diffusion Weighted Imaging Derived Diffusion Parameters as Biomarkers for the Microenvironment in Gliomas.

Authors:  Yan Bai; Taiyuan Liu; Lijuan Chen; Haiyan Gao; Wei Wei; Ge Zhang; Lifu Wang; Lingfei Kong; Siyun Liu; Huan Liu; Neil Roberts; Meiyun Wang
Journal:  Front Oncol       Date:  2021-10-12       Impact factor: 6.244

6.  XGboost Prediction Model Based on 3.0T Diffusion Kurtosis Imaging Improves the Diagnostic Accuracy of MRI BiRADS 4 Masses.

Authors:  Wan Tang; Han Zhou; Tianhong Quan; Xiaoyan Chen; Huanian Zhang; Yan Lin; Renhua Wu
Journal:  Front Oncol       Date:  2022-03-17       Impact factor: 6.244

7.  Preoperatively Grading Rectal Cancer with the Combination of Intravoxel Incoherent Motions Imaging and Diffusion Kurtosis Imaging.

Authors:  Zhijun Geng; Yunfei Zhang; Shaohan Yin; Shanshan Lian; Haoqiang He; Hui Li; Chuanmiao Xie; Yongming Dai
Journal:  Contrast Media Mol Imaging       Date:  2020-10-12       Impact factor: 3.161

  7 in total

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