Diagnostic value of DWI MRI between mono-exponential, bi-exponential and non-Gaussian kurtosis models in pancreatic ductal adenocarcinoma: a comparative study_Chinese Journal of Evidence-Based Medicine

Authors：

PENG Shengkun ,  ZHANG Jie , WU Xiaohua , PU Hong , YIN Longlin , WAN Shaoping

Affiliated Clinical Hospital of University of Electronic Science and Technology, Sichuan Provincial People’s Hospital, Chengdu 610072, P.R.China;

Corresponding author：

ZHANG Jie, Email: z85445417@163.com

Keywords：

Pancreatic ductal adenocarcinoma; Poorly differentiated; Magnetic resonance imaging; Diffusion-weighted imaging; Diagnostic value

DOI：

10.7507/1672-2531.201907075

Video：

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Abstract Full text Figures/Tables Video References Cited by

Objectives To investigate the diagnostic value of different diffusion-weighted MRI (DWI) models between two Gaussian DWI models including mono-exponential and bi-exponential, and the non-Gaussian kurtosis model in poorly differentiated pancreatic ductal adenocarcinoma.Methods Subjects comprised 52 patients with poorly differentiated pancreatic ductal adenocarcinoma which had been confirmed by surgery. All patients underwent DWI (1.5T, multi-b values: 0, 50, 100, 150, 200, 500, 800, 1000, 1 500, 2 000s/mm²). Mean values of DWI-derived metrics ADC_standard, ADC_slow, ADC_fast, f, MD, MK and ADC_standard were calculated from regions of interest in all tumours and non-tumorous parenchyma and compared. ANOVA and Mann Whitney U test was used to compare the MRI paremeters. ROC was used to evaluate the diagnostic efficiency.Results Mean ADC_standard, ADC_fast, f and MK values showed significant differences between tumours and non-tumorous parenchyma (P<0.05). AUC for ADC_standard, MD, ADC_fast and f were 0.705, 0.665, 0.648, 0.614, respectively. The ROC curve integrated with ADC_standard and MD had better diagnostic efficiency (AUC was about 0.754).Conclusions ADC_standard, ADC_fast, f and MK values can differentiate tumours from non-tumorous parenchyma. The combination of Gaussion distribution model and non-Gaussion distribution model has the potential to increase the diagnostic accuracy of DWI in patients with pancreatic ductal adenocarcinoma.

Citation： PENG Shengkun, ZHANG Jie, WU Xiaohua, PU Hong, YIN Longlin, WAN Shaoping. Diagnostic value of DWI MRI between mono-exponential, bi-exponential and non-Gaussian kurtosis models in pancreatic ductal adenocarcinoma: a comparative study. Chinese Journal of Evidence-Based Medicine, 2020, 20(4): 389-394. doi: 10.7507/1672-2531.201907075 Copy

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18.	何为, 周延, 刘剑羽, 等. MR扩散加权成像单指数模型及体素内不相干运动模型参数诊断胰腺癌的价值. 中华放射学杂志, 2016, 50(6): 427-431.
19.	王玉亮, 初建平. 磁共振扩散峰度成像(DKI)临床研究进展. 影像诊断与介入放射学杂志, 2015, 24(4): 340-345.
20.	Sheng RF, Wang HQ, Yang L, et al. Diffusion kurtosis imaging and diffusion-weighted imaging in assessment of liver fibrosis stage and necroinflammatory activity. Abdom Radiol (NY), 2017, 42(4): 1176-1182.
21.	Chen Y, Ren W, Zheng D, et al. Diffusion kurtosis imaging predicts neoadjuvant chemotherapy responses within 4 days in advanced nasopharyngeal carcinoma patients. J Magn Reson Imaging, 2015, 42(5): 1354-1361.
22.	Shen L, Zhou G, Tang F, et al. MR diffusion kurtosis imaging for cancer diagnosis: a meta-analysis of the diagnostic accuracy of quantitative kurtosis value and diffusion coefficient. Clin Imaging, 2018, 52: 44-56.
23.	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.
24.	Hu F, Tang W, Sun Y, et al. The value of diffusion kurtosis imaging in assessing pathological complete response to neoadjuvant chemoradiation therapy in rectal cancer: a comparison with conventional diffusion-weighted imaging. Oncotarget, 2017, 8(43): 75597-75606.

1. 杨超, 罗国培. 2018年胰腺癌研究及诊疗新进展. 中国癌症杂志, 2019, 29(1): 1-8.
2. Bonekamp S, Corona-Villalobos CP, Kamel IR. Oncologic applications of diffusion-weighted MRI in the body. JMRI, 2012, 35(2): 257-279.
3. Fukukura Y, Shindo T, Hakamada H, et al. Diffusion-weighted MR imaging of the pancreas: optimizing b-value for visualization of pancreatic adenocarcinoma. Eur Radiol, 2016, 26(10): 3419-3427.
4. Maas MC, Fütterer JJ, Scheenen TW. Quantitative evaluation of computed high B value diffusion-weighted magnetic resonance imaging of the prostate. Invest Radiol, 2013, 48(11): 779-786.
5. Koh DM, Collins DJ. Diffusion-weighted MRI in the body: applications and challenges in oncology. AJR Am J Roentgenol, 2007, 188(6): 1622-1635.
6. Koh DM, Collins DJ, Orton MR. Intravoxel incoherent motion in body diffusion-weighted MRI: reality and challenges. AJR Am J Roentgenol, 2011, 196(6): 1351-1361.
7. Lyng H, Haraldseth O, Rofstad EK. Measurement of cell density and necrotic fraction in human melanoma xenografts by diffusion weighted magnetic resonance imaging. Magn Reson Med, 2000, 43(6): 828-836.
8. Barral M, Taouli B, Guiu B, et al. Diffusion-weighted MR imaging of the pancreas: current status and recommendations. Radiology, 2015, 274(1): 45-63.
9. Iima M, Le Bihan D. Clinical Intravoxel Incoherent Motion and Diffusion MR Imaging: Past, Present, and Future. Radiology, 2016, 278(1): 13-32.
10. LeBihan D. IVIM method measures diffusion and perfusion. Diagn Imaging (San Franc), 1990, 12(6): 133, 136.
11. De Robertis R, Cardobi N, Ortolani S. Intravoxel incoherent motion diffusion-weighted MR imaging of solid pancreatic masses: reliability and usefulness for characterization. Abdom Radiol (NY), 2019, 44(1): 131-139.
12. Li J, Liang L, Yu H, et al. Whole-tumor histogram analysis of non-Gaussian distribution DWI parameters to differentiation of pancreatic neuroendocrine tumors from pancreatic ductal adenocarcinomas. Magn Reson Imaging, 2019, 55: 52-59.
13. Lemke A, Laun FB, Simon D, et al. An in vivo verification of the intravoxel incoherent motion effect in diffusion-weighted imaging of the abdomen. Magn Reson Med, 2010, 64(6): 1580-1585.
14. 马婉玲, 魏梦绮, 任静, 等. 单指数, 双指数模型多b值DWI在胰腺癌的应用价值. 实用放射学杂志, 2017, 33(7): 1024-1028.
15. Lee JH, Cheong H, Lee SS, et al. Perfusion assessment using intravoxel incoherent motion-based analysis of diffusion-weighted magnetic resonance imaging: validation through phantom experiments. Invest Radiol, 2016, 51(8): 520-528.
16. Lee Y, Lee SS, Kim N, et al. Intravoxel incoherent motion diffusion-weighted MR imaging of the liver: effect of triggering methods on regional variability and measurement repeatability of quantitative parameters. Radiology, 2015, 274(2): 405-415.
17. Kartalis N, Manikis GC, Loizou L, et al. Diffusion-weighted MR imaging of pancreatic cancer: a comparison of mono-exponential, bi-exponential and non-Gaussian kurtosis models. Eur J Radiol Open, 2016, 3: 79-85.
18. 何为, 周延, 刘剑羽, 等. MR扩散加权成像单指数模型及体素内不相干运动模型参数诊断胰腺癌的价值. 中华放射学杂志, 2016, 50(6): 427-431.
19. 王玉亮, 初建平. 磁共振扩散峰度成像(DKI)临床研究进展. 影像诊断与介入放射学杂志, 2015, 24(4): 340-345.
20. Sheng RF, Wang HQ, Yang L, et al. Diffusion kurtosis imaging and diffusion-weighted imaging in assessment of liver fibrosis stage and necroinflammatory activity. Abdom Radiol (NY), 2017, 42(4): 1176-1182.
21. Chen Y, Ren W, Zheng D, et al. Diffusion kurtosis imaging predicts neoadjuvant chemotherapy responses within 4 days in advanced nasopharyngeal carcinoma patients. J Magn Reson Imaging, 2015, 42(5): 1354-1361.
22. Shen L, Zhou G, Tang F, et al. MR diffusion kurtosis imaging for cancer diagnosis: a meta-analysis of the diagnostic accuracy of quantitative kurtosis value and diffusion coefficient. Clin Imaging, 2018, 52: 44-56.
23. 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.
24. Hu F, Tang W, Sun Y, et al. The value of diffusion kurtosis imaging in assessing pathological complete response to neoadjuvant chemoradiation therapy in rectal cancer: a comparison with conventional diffusion-weighted imaging. Oncotarget, 2017, 8(43): 75597-75606.

Chinese Journal of Evidence-Based Medicine

Diagnostic value of DWI MRI between mono-exponential, bi-exponential and non-Gaussian kurtosis models in pancreatic ductal adenocarcinoma: a comparative study

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