Share：
Share this content in WeChat
X
[Chinese][PDF]88681
• Clinical Article •
Comparison of stretched-exponential model and mono-exponential model DWI in differentiation of prostate cancer and benign prostatic hyperplasia
CHEN Yufei  HE Wei  LIU Jianyu 

Cite this article as: Chen YF, He W, Liu JY. Comparison of stretched-exponential model and mono-exponential model DWI in differentiation of prostate cancer and benign prostatic hyperplasia. Chin J Magn Reson Imaging, 2019, 10(3): 206-211. DOI:10.12015/issn.1674-8034.2019.03.009.


[Abstract] Objective: To compare the value of stretched-exponential model and mono-exponential model diffusion weighted imaging (DWI) in the differentiation of prostate cancer (PCa) and benign prostatic hyperplasia (BPH).Materials and Methods: The data of DWI (b from 0 to 2000 s/mm2) of 61 PCa patients and 49 BPH patients confirmed by pathology were retrospectively analyzed. The parameters apparent diffusion coefficient (ADC), distributed diffusion coefficient (DDC) and α values of these lesions were calculated. All parameters were compared between PCa and BPH using independent-samples t test, and their diagnostic performance was analyzed by receiver operating characteristic (ROC) curves.Results: ADC, DDC and α values of PCa were (0.714±0.170)×10-3 mm2/s, (0.711±0.262)×10-3 mm2/s and 0.730±0.070, while of BPH were (1.139±0.163)×10-3 mm2/s, (1.435±0.267)×10-3 mm2/s and 0.766±0.067. All parameters in PCa were significantly lower than those in BPH (P<0.01). The area under the curves (AUCs) of DDC and ADC were 0.955 and 0.950, with no significant difference (P>0.05). The AUC in α was significantly lower than ADC and DDC (P<0.05). The ADC and DDC values of prostate cancer were negatively correlated to the Gleason scores (P<0.05).Conclusions: DDC derived from stretched-exponential model DWI can be used in differentiation of PCa and BPH. The stretched-exponential model was not superior to the mono-exponential model.
[Keywords] prostate cancer；benign prostatic hyperplasia；diffusion weighted imaging；mono-exponential model；stretched-exponential model

CHEN Yufei Department of Radiology, Peking University Third Hospital, Beijing 100191, China

HE Wei Department of Radiology, Peking University Third Hospital, Beijing 100191, China

LIU Jianyu* Department of Radiology, Peking University Third Hospital, Beijing 100191, China

*Correspondence to: Liu JY, E-mail: jyliubysy@163.com

Conflicts of interest   None.

Received  2018-09-15
Accepted  2018-11-20
DOI: 10.12015/issn.1674-8034.2019.03.009
Cite this article as: Chen YF, He W, Liu JY. Comparison of stretched-exponential model and mono-exponential model DWI in differentiation of prostate cancer and benign prostatic hyperplasia. Chin J Magn Reson Imaging, 2019, 10(3): 206-211. DOI:10.12015/issn.1674-8034.2019.03.009.

[1]
Torre LA, Bray F, Siegel RL, et al. Global cancer statistics, 2012. CA Cancer J Clin, 2015, 65(2): 87-108.
[2]
Cornud F, Legmann P, Delongchamps NB. Can multiparametric MRI rule in or rule out significant prostate cancer? Curr Opin Urol, 2015, 25(6): 490-497.
[3]
Katahira K, Takahara T, Kwee TC, et al. Ultra-high-b-value diffusion-weighted MR imaging for the detection of prostate cancer: evaluation in 201 cases with histopathological correlation. Eur Radiol, 2011, 21(1): 188-196.
[4]
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.
[5]
Bennett KM, Schmainda KM, Bennett RT, et al. Characterization of continuously distributed cortical water diffusion rates with a stretched-exponential model. Magn Reson Med, 2003, 50(4): 727-734.
[6]
Kitzing YX, Prando A, Varol C, et al. Benign conditions that mimic prostate carcinoma: MR imaging features with histopathologic correlation. Radiographics, 2016, 36(1): 162-175.
[7]
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.
[8]
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.
[9]
Mazaheri Y, Hotker AM, Shukla-Dave A, et al. Model selection for high b-value diffusion-weighted MRI of the prostate. Magn Reson Imaging, 2018, 46: 21-27.
[10]
Vargas HA, Akin O, Franiel T, et al. Diffusion-weighted endorectal MR imaging at 3 T for prostate cancer: tumor detection and assessment of aggressiveness. Radiology, 2011, 259(3): 775-784.
[11]
宋志强，杜向东，马静，等. ADC值在前列腺癌诊断及临床评估中的价值．实用放射学杂志, 2015, 31(10): 1653-1656.
[12]
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.
[13]
Hectors SJ, Semaan S, Song C, et al. Advanced diffusion-weighted imaging modeling for prostate cancer characterization: correlation with quantitative histopathologic tumor tissue composition-A hypothesis-generating study. Radiology, 2017, 286(3): 918-928.
[14]
Li C, Chen M, Wan B, et al. A comparative study of gaussian and non-gaussian diffusion models for differential diagnosis of prostate cancer with in-bore transrectal MR-guided biopsy as a pathological reference. Acta Radiol, 2018, 59(11): 1395-1402.
[15]
Liu X, Zhou L, Peng W, et al. Comparison of stretched-Exponential and monoexponential model diffusion-weighted imaging in prostate cancer and normal tissues. J Magn Reson Imaging, 2015, 42(4): 1078-1085.
[16]
Feng Z, Min X, Margolis DJ, et al. Evaluation of different mathematical models and different b-value ranges of diffusion-weighted imaging in peripheral zone prostate cancer detection using b-value up to 4500 s/mm2. PLoS One, 2017, 12(2): e0172127.
[17]
闵祥德，王良，冯朝燕，等. MR扩散加权成像不同模型诊断前列腺癌的价值．中华放射学杂志, 2015, 49(11): 838-842.
[18]
Peng Y, Jiang Y, Antic T, et al. Apparent diffusion coefficient for prostate cancer imaging: impact of B values. AJR Am J Roentgenol, 2014, 202(3): W247-253.
[19]
Merisaari H, Toivonen J, Pesola M, et al. Diffusion-weighted imaging of prostate cancer: effect of b-value distribution on repeatability and cancer characterization. Magn Reson Imaging, 2015, 33(10): 1212-1218.
[20]
Epstein JI, Egevad L, Amin MB, et al. The 2014 international society of urological pathology (ISUP) consensus conference on gleason grading of prostatic carcinoma: definition of grading patterns and proposal for a new grading system. Am J Surg Pathol, 2016, 40(2): 244-252.
[21]
Liu W, Liu XH, Tang W, et al. Histogram analysis of stretched-exponential and monoexponential diffusion-weighted imaging models for distinguishing low and intermediate/high gleason scores in prostate carcinoma. J Magn Reson Imaging, 2018, 48(2): 491-498.
[22]
Matoso A, Epstein JI. Grading of prostate cancer: past, present, and future. Curr Urol Rep, 2016, 17(3): 25.
[23]
Portalez D, Rollin G, Leandri P, et al. Prospective comparison of T2W-MRI and dynamic-contrast-enhanced MRI, 3D-MR spectroscopic imaging or diffusion-weighted MRI in repeat TRUS-guided biopsies. Eur Radiol, 2010, 20(12): 2781-2790.
[24]
Sarici H, Telli O, Yigitbasi O, et al. Predictors of Gleason score upgrading in patients with prostate biopsy Gleason score </=6. Can Urol Assoc J, 2014, 8(5-6): E342-346.

PREV Application of 3.0 T whole body diffusion-weighted imaging for the evaluation of tumor response to induction chemotherapy in patients with multiple myeloma
NEXT Gliosarcoma: a case report and its misdiagnosis analysis
  


LINK


Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn