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Detection, stratification and differentiation of prostate cancer by intravoxel incoherent motion imaging
GAO Yanru  LI Huabing 

Cite this article as: Gao YR, Li HB. Detection, stratification and differentiation of prostate cancer by intravoxel incoherent motion imaging. Chin J Magn Reson Imaging, 2020, 11(11): 1067-1070. DOI:10.12015/issn.1674-8034.2020.11.026.


[Abstract] In recent years, the morbidity of prostate cancer has increased dramatically, so it is very important to make early diagnosis and judge the malignant degree of the tumor. Transrectal ultrasound guided biopsy is the gold standard for the diagnosis of prostate cancer, and it can also be classified pathologically, but it is invasive and may cause adverse side effects, so it is not the first choice. Multiparametric magnetic resonance imaging is the best imaging method for the diagnosis of early prostate cancer, among which diffusion-weighted imaging (DWI) is widely used to reflect the diffusion of water molecules in tissue and improve the detection rate of lesions. With the development of magnetic resonance imaging technology, the intravoxel incoherent motion (IVIM) model developed on the basis of DWI is gradually used in clinic. It uses a variety of b values and does not need intravenous injection of gadolinium contrast agent to obtain tissue diffusion and microcirculation perfusion information respectively. The potential value may be better than that of traditional DWI. This article reviews the role of IVIM imaging in prostate cancer.
[Keywords] prostate cancer；diffusion-weighted imaging；intravoxel incoherent motion imaging；magnetic resonance imaging；differential diagnosis

GAO Yanru Department of Medical Imaging, Shanxi Medical University, Taiyuan 030001, China

LI Huabing* Department of MRI, Shanxi Jincheng General Hospital, Shanxi Medical University, Jincheng 048006, China

*Correspondence to: Li HB, E-mail:lihuabing3668960@163.com

Conflicts of interest   None.

Received  2020-05-13
Accepted  2020-09-28
DOI: 10.12015/issn.1674-8034.2020.11.026
Cite this article as: Gao YR, Li HB. Detection, stratification and differentiation of prostate cancer by intravoxel incoherent motion imaging. Chin J Magn Reson Imaging, 2020, 11(11): 1067-1070. DOI:10.12015/issn.1674-8034.2020.11.026.

[1]
De Vente C, Vos P, Hosseinzadeh M, et al. Deep learning regression for prostate cancer detection and grading in bi-parametric MRI. IEEE Trans Biomed Eng, 2020. DOI: 10.1109/TBME.2020.2993528
[2]
张配配，王良,闵祥德，等. DWI单指数和双指数模型在前列腺癌Gleason分级中的应用：基于三维立体直方图分析．磁共振成像, 2017, 8(9): 668-674. DOI: 10.12015/issn.1674-8034.2017.09.005
[3]
Thai JN, Narayanan HA, George AK, et al. Validation of PI-RADS version 2 in transition zone lesions for the detection of prostate cancer. Radiology, 2018, 288(2): 485-491. DOI: 10.1148/radiol.2018170425
[4]
单春辉，暴云锋，赵明娟，等. IVIM-DWI技术对前列腺癌内分泌治疗效果的应用研究．磁共振成像, 2020, 11(4): 291-295. DOI: 10.12015/issn.1674-8034.2020.04.010
[5]
Le Bihan D, Breton E, Lallemand D, et al. Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. Radiology, 1988, 168(2): 497-505. DOI: 10.1148/radiology.168.2.3393671
[6]
Le Bihan D, Breton E, Lallemand D, et al. MR imaging of intravoxel incoherent motions:application to diffusion and perfusion in neurologic disorders. Radiology, 1986, 161(2): 401-407. DOI: 10.1148/radiology.161.2.3763909
[7]
Kuru TH, Roethke MC, Stieltjes B, et al. Intravoxel incoherent motion (IVIM) diffusion imaging in prostate cancer- what does it add? J Comput Assist Tomogr, 2014, 38(4): 558-564. DOI: 10.1097/RCT.0000000000000088
[8]
刘洪源，李勤. IVIM扩散加权成像在前列腺疾病中的研究进展．中国医学物理学杂志, 2018, 35(6): 666-669. DOI: 10.3969/j.issn.1005-202X.2018.06.009
[9]
Rosenkrantz AB, Hindman N, Lim RP, et al. Diffusion-weighted imaging of the prostate: comparison of b1000 and b2000 image sets for index lesion detection. J Magn Reson Imaging, 2013, 38(3): 694-700. DOI: 10.1002/jmri.24016
[10]
Jendoubi S, Wagner M, Montagne S, et al. MRI for prostate cancer: can computed high b-value DWI replace native acquisitions? Eur Radiol, 2019, 29(10): 5197-5204. DOI: 10.1007/s00330-019-06085-z
[11]
周蕾，彭俊红，胡浩，等．体素内不相干运动扩散加权成像中分子扩散系数值对前列腺癌诊断价值的Meta分析．放射学实践, 2019, 34(9): 1007-1012. DOI: 10.13609/j.cnki.1000-0313.2019.09.015
[12]
Pesapane F, Patella F, Fumarola EM, et al. Intravoxel incoherent motion (IVIM) diffusion weighted imaging (DWI) in the periferic prostate cancer detection and stratification. Med Oncol, 2017, 34(3): 35. DOI: 10.1007/s12032-017-0892-7
[13]
张杨贵，陈珊红，温志玲，等．体素内不相干运动MRI与DWI对前列腺癌的诊断．中国CT和MRI杂志, 2016, 14(3): 78-80. DOI: 10.3969/j.issn.1672-5131.2016.03.024
[14]
冯朝燕,闵祥德，李拔森，等．不同b值范围扩散加权成像定量参数在外周带前列腺癌诊断中的价值比较．影像诊断与介入放射学, 2017, 26(1): 8-14. DOI: 10.3969/j.issn.1005-8001.2017.01.002
[15]
冷晓明，韩晓蕊，赵曼，等. IVIM-DWI在前列腺癌与前列腺增生鉴别诊断中的应用价值及其与Gleason评分的相关性．放射学实践, 2016, 31(8): 760-763. DOI: 10.13609/j.cnki.1000-0313.2016.08.020
[16]
Kuru TH, Roethke MC, Seidenader J, et al. Critical evaluation of magnetic resonance imaging targeted, transrectal ultrasound guided transperineal fusion biopsy for detection of prostate cancer. J Urol, 2013, 190(4): 1380-1386. DOI: 10.1016/j.juro.2013.04.043
[17]
Shinmoto H, Tamura C, Soga S, et al. An intravoxel incoherent motion diffusion-weighted imaging study of prostate cancer. AJR Am J Roentgenol, 2012, 199(4): W496-500. DOI: 10.2214/AJR.11.8347
[18]
Pang Y, Turkbey B, Bernardo M, et al. Intravoxel incoherent motion MR imaging for prostate cancer: an evaluation of perfusion fraction and diffusion coefficient derived from different b-value combinations. Magn Reson Med, 2013, 69(2): 553-62. DOI: 10.1002/mrm.24277
[19]
Cohen AD, Schieke MC, Hohenwalter MD, et al. The effect of low b-values on the intravoxel incoherent motion derived pseudodiffusion parameter in liver. Magn Reson Med, 2015, 73(1): 306-311. DOI: 10.1002/mrm.25109
[20]
程亮，徐嘉雯，王丽莎，等. 2016版WHO前列腺肿瘤新分类解读．中华病理学杂志, 2016, 45(8): 513-518. DOI: 10.3760/cma.j.issn.0529-5807.2016.08.003
[21]
Park SY, Oh YT, Jung DC, et al. Diffusion-weighted imaging predicts upgrading of Gleason score in biopsy-proven low grade prostate cancers. BJU international,2017,119(1):57-66. DOI: 10.1111/bju.13436
[22]
陈雨菲，何为，刘剑羽．拉伸指数和单指数模型DWI应用于前列腺癌和前列腺增生鉴别诊断的对照．磁共振成像, 2019, 10(3): 206-211. DOI: 10.12015/issn.1674-8034.2019.03.009
[23]
Zhang YD, Wang Q, Wu CJ, et al. The histogram analysis of diffusion-weighted intravoxel incoherent motion (IVIM) imaging for differentiating the gleason grade of prostate cancer. Eur Radiol, 2015, 25(4): 994-1004. DOI: 10.1007/s00330-014-3511-4
[24]
Yang DM, Kim HC, Kim SW, et al. Prostate cancer: correlation of intravoxel incoherent motion MR parameters with Gleason score. Clin Imaging, 2016, 40(3): 445-50. DOI: 10.1016/j.clinimag.2016.01.001
[25]
Valerio M, Zini C, Fierro D, et al. 3T multiparametric MRI of the prostate: does intravoxel incoherent motion diffusion imaging have a role in the detection and stratification of prostate cancer in the peripheral zone? Eur J Radiol, 2016, 85(4): 790-4. DOI: 10.1016/j.ejrad.2016.01.006
[26]
Byun J, Park KJ, Kim MH, et al. Direct comparison of PI-RADS version 2 and 2.1 in transition zone lesions for detection of prostate cancer: preliminary experience. J Magn Reson Imaging, 2020, 52(2): 577-586. DOI: 10.1002/jmri.27080
[27]
Thai JN, Narayanan HA, George AK, et al. Validation of PI-RADS version 2 in transition zone lesions for the detection of prostate cancer. Radiology, 2018, 288(2): 485-491. DOI: 10.1148/radiol.2018170425
[28]
Weinreb JC, Barentsz JO, Choyke PL, et al. PI-RADS prostate imaging-reporting and data system: 2015, version 2. Eur Urol, 2016, 69(1): 16-40. DOI: 10.1016/j.eururo.2015.08.052
[29]
Oto A, Kayhan A, Jiang Y, et al. Prostate cancer: differentiation of central gland cancer from benign prostatic hyperplasia by using diffusion-weighted and dynamic contrast-enhanced MR imaging. Radiology, 2010, 257(3): 715-23. DOI: 10.1148/radiol.10100021
[30]
Bao J, Wang X, Hu C, et al. Differentiation of prostate cancer lesions in the Transition Zone by diffusion-weighted MRI. Eur J Radiol Open, 2017, 4: 123-128. DOI: 10.1016/j.ejro.2017.08.003
[31]
Cui Y, Li C, Liu Y, et al. Differentiation of prostate cancer and benign prostatic hyperplasia: comparisons of the histogram analysis of intravoxel incoherent motion and monoexponential model with in-bore MR-guided biopsy as pathological reference. Abdom Radiol (NY), 2020, 45(10): 3265-3277. DOI: 10.1007/s00261-019-02227-5
[32]
Liu X, Zhou L, Peng W, et al. Differentiation of central gland prostate cancer from benign prostatic hyperplasia using monoexponential and biexponential diffusion-weighted imaging. Magn Reson Imaging, 2013, 31(8): 1318-24. DOI: 10.1016/j.mri.2013.03.002
[33]
Lemke A, Stieltjes B, Schad LR, et al. Toward an optimal distribution of b values for intravoxel incoherent motion imaging. Magn Reson Imaging, 2011, 29(6): 766-76. DOI: 10.1016/j.mri.2011.03.004
[34]
Kawada H, Kanematsu M, Goshima S, et al. Multiphase contrast-enhanced magnetic resonance imaging features of Bacillus Calmette-Guérin-induced granulomatous prostatitis in five patients. Korean J Radiol, 2015, 16(2): 342-8. DOI: 10.3348/kjr.2015.16.2.342
[35]
Meier-Schroers M, Kukuk G, Wolter K, et al. Differentiation of prostatitis and prostate cancer using the prostate imaging-reporting and data system (PI-RADS). Eur J Radiol, 2016, 85(7): 1304-1311. DOI: 10.1016/j.ejrad.2016.04.014
[36]
Liu X, Peng W, Zhou L, et al. Biexponential apparent diffusion coefficients values in the prostate: comparison among normal tissue, prostate cancer, benign prostatic hyperplasia and prostatitis. Korean J Radiol, 2013, 14(2): 222-32. DOI: 10.3348/kjr.2013.14.2.222
[37]
Tong T, Lu H, Zong J, et al. Chemotherapy-related cognitive impairment in patients with breast cancer based on MRS and DTI analysis. Breast Cancer, 2020, 27(5): 893-902. DOI: 10.1007/s12282-020-01094-z
[38]
Tian W, Zhang J, Tian F, et al. Correlation of diffusion tensor imaging parameters and Gleason scores of prostate cancer. Exp Ther Med, 2018, 15(1): 351-356. DOI: 10.3892/etm.2017.5363
[39]
Jensen JH, Helpern JA, Ramani A, et al. Diffusional kurtosis imaging: the quantification of non-gaussian water diffusion by means of magnetic resonance imaging. Magn Reson Med, 2005, 53(6): 1432-1440. DOI: 10.1002/mrm.20508
[40]
Rosenkrantz AB, Sigmund EE, Johnson G, et al. Prostate cancer: feasibility and preliminary experience of a diffusional kurtosis model for detection and assessment of aggressiveness of peripheral zone cancer. Radiology, 2012, 264(1): 126-135. DOI: 10.1148/radiol.12112290
[41]
Chatterjee A, Harmath C, Oto A. New prostate MRI techniques and sequences. Abdom Radiol (NY), 2020. DOI: 10.1007/s00261-020-02504-8

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