Diffusion-weighted MRI for early detection and characterization of prostate cancer in the transgenic adenocarcinoma of the mouse prostate model

Journal of Magnetic Resonance Imaging

Volumn 43, Issue 5, 2016, Pages 1207-1217

  Hill, Deborah K ^a,b   Kim, Eugene ^a,b   Teruel, Jose R ^a,b   Jamin, Yann ^c   Widerøe, Marius ^a   Søgaard, Caroline D ^a   Størkersen, Øystein ^b   Rodrigues, Daniel N ^c   Heindl, Andreas ^c,d   Yuan, Yinyin ^c,d   Bathen, Tone F ^a   Moestue, Siver A ^a,b  

^a NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

^b TRONDHEIM UNIVERSITY HOSPITAL   (Norway)

^c INSTITUTE OF CANCER RESEARCH   (United Kingdom)

^d ROYAL MARSDEN HOSPITAL   (United Kingdom)

Author keywords

ADC; cancer detection; diffusion weighted MRI; prostate cancer; transgenic adenocarcinoma of the mouse prostate

Indexed keywords

ANIMAL EXPERIMENT; ANIMAL MODEL; ANIMAL TISSUE; ARTICLE; CANCER CLASSIFICATION; CANCER MODEL; CANCER STAGING; CLINICAL DECISION MAKING; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIFFUSION WEIGHTED IMAGING; EARLY DIAGNOSIS; GLEASON SCORE; HISTOPATHOLOGY; IMAGE ANALYSIS; MALE; MALE GENITAL TRACT TUMOR; MORPHOLOGY; MOUSE; NONHUMAN; NUCLEAR MAGNETIC RESONANCE SCANNER; ORGAN SIZE; POORLY DIFFERENTIATED CANCER; PRIORITY JOURNAL; PROSTATE ADENOCARCINOMA; PROSTATE VOLUME; SEMINAL VESICLE TUMOR; SEMINAL VESICLE VOLUME; TIME SERIES ANALYSIS; TRANSGENIC ANIMAL; TUMOR VOLUME; VALIDATION PROCESS; WELL DIFFERENTIATED CANCER; ADENOCARCINOMA; ANIMAL; AUTOMATED PATTERN RECOGNITION; AUTOMATION; C57BL MOUSE; CANCER GRADING; CELL DIFFERENTIATION; DIAGNOSTIC IMAGING; DISEASE COURSE; HUMAN; IMAGE PROCESSING; METABOLISM; PATHOLOGY; PROSTATE; PROSTATE TUMOR; TRANSGENIC MOUSE; TUMOR INVASION;

TUMOR MARKER;

ADENOCARCINOMA; ANIMALS; AUTOMATION; BIOMARKERS, TUMOR; CELL DIFFERENTIATION; DIFFUSION MAGNETIC RESONANCE IMAGING; DISEASE PROGRESSION; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MALE; MICE; MICE, INBRED C57BL; MICE, TRANSGENIC; NEOPLASM GRADING; NEOPLASM INVASIVENESS; PATTERN RECOGNITION, AUTOMATED; PROSTATE; PROSTATIC NEOPLASMS;

EID: 84963865179     PISSN: 10531807     EISSN: 15222586     Source Type: Journal    
DOI: 10.1002/jmri.25087     Document Type: Article

References (37)

1. Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A,. Global cancer statistics, 2012. CA Cancer J Clin 2015; 65: 87-108.
2. Puech P, Rouvière O, Renard-Penna R, et al., Multiparametric MR-targeted biopsy with cognitive and transrectal US-MR fusion guidance versus systematic biopsy-prospective multicenter study. Radiology 2013; 268: 461-469.
3. Martiniello-Wilks R, Dane A, Voeks DJ, et al., Gene-directed enzyme prodrug therapy for prostate cancer in a mouse model that imitates the development of human disease. J Gene Med 2004; 6: 43-54.
4. Shukla S, Bhaskaran N, Babcook MA, Fu P, Maclennan GT, Gupta S,. Apigenin inhibits prostate cancer progression in TRAMP mice via targeting PI3K/Akt/FoxO pathway. Carcinogenesis 2014; 35: 452-460.
5. Gelman IH, Peresie J, Eng KH, Foster BA,. Differential requirement for Src family tyrosine kinases in the initiation, progression, and metastasis of prostate cancer. Mol Cancer Res 2014; 12: 1470-1479.
6. Gingrich JR, Greenberg NM,. A transgenic mouse prostate cancer model. Toxicol Pathol 1996; 24: 502-504.
7. Kaplan-Lefko PJ, Chen TM, Ittmann MM, et al., Pathobiology of autochthonous prostate cancer in a pre-clinical transgenic mouse model. Prostate 2003; 55: 219-237.
8. Greenberg NM, DeMayo F, Finegold MJ, et al., Prostate cancer in a transgenic mouse. Proc Natl Acad Sci U S A 1999; 92: 3439-3443.
9. Gingrich JR, Barrios RJ, Foster BA, Greenberg NM,. Pathologic progression of autochthonous prostate cancer in the TRAMP model. Prostate Cancer and Prostat Dis 1999; 2: 70-75.
10. Hurwitz AA, Foster BA, Allison JP, Greenberg NM, Kwon ED,. The TRAMP mouse as a model for prostate cancer. Curr Protoc Immunol 2001; 45: 1-23.
11. Hsu CX, Ross BD, Chrisp CE, et al., Longditudinal cohort analysis of lethal prostate cancer progression in transgenic mice. J Urol 1998; 160: 1500-1505.
12. Mazaheri Y, Shukla-Dave A, Muellner A, Hricak H,. MR imaging of the prostate in clinical practice. Magma 2008; 21: 379-392.
13. Kurhanewicz J, Vigneron D, Carroll P, Coakley F,. Multiparametric magnetic resonance imaging in prostate cancer: present and future. Curr Opin Urol 2008; 18: 71-77.
14. Degrassi A, Russo M, Scanziani E, et al., Magnetic resonance imaging and histopathological characterization of prostate tumors in TRAMP mice as model for pre-clinical trials. Prostate 2007; 67: 396-404.
15. Scheenen TWJ, Rosenkrantz AB, Haider MA, Fütterer JJ,. Multiparametric magnetic resonance imaging in prostate cancer management. Current status and future perspectives. Invest Radiol 2015; 50: 594-600.
16. Kirkham AP, Emberton M, Allen C,. How good is MRI at detecting and characterising cancer within the prostate? Eur Urol 2006; 50: 1163-1174; discussion 1175.
17. Padhani AR,. Integrating multiparametric prostate MRI into clinical practice. Cancer Imaging 2011; 11 (Spec No A): S27-37.
18. Tan CH, Wei W, Johnson V, Kundra V,. Diffusion-weighted MRI in the detection of prostate cancer: meta-analysis. AJR Am J Roentgenol 2012; 199: 822-829.
19. Lim HK, Kim JK, Kim KA, Cho K-SC,. Prostate cancer: apparent diffusion coefficient map with T2-weighted images for detection-a multireader study. Radiology 2009; 250: 145-151.
20. Boesen L, Chabanova E, Logager V, Balslev I, Thomsen HS,. Apparent diffusion coefficient ratio correlates significantly with prostate cancer gleason score at final pathology. J Magn Reson Imaging JMRI 2014; 42: 446-453.
21. Gatenby RA, Grove O, Gillies RJ,. Quantitative imaging in cancer evolution and ecology. Radiology 2013; 269: 8-15.
22. Gillies RJ, Verduzco D, Gatenby RA,. Evolutionary dynamics of carcinogenesis and why targeted therapy does not work. Nat Rev Cancer 2012; 12: 487-493.
23. Zhou M, Hall L, Goldgof D, et al., Radiologically defined ecological dynamics and clinical outcomes in glioblastoma multiforme: preliminary results. Transl Oncol 2014; 7: 5-13.
24. Ajibade AA, Kirk JS, Karasik E, et al., Early growth inhibition is followed by increased metastatic disease with vitamin D (calcitriol) treatment in the TRAMP model of prostate cancer. PloS One 2014; 9: e89555.
25. Arbab AS, Shankar A, Varma NR, et al., MRI to assess chemoprevention in transgenic adenocarcinoma of mouse prostate (TRAMP). BMC Med Imaging 2011; 11: 21.
26. Tani Y, Suttie A, Flake GP, Nyska A, Maronpot RR,. Epithelial-stromal tumor of the seminal vesicles in the transgenic adenocarcinoma mouse prostate model. Vet Pathol 2005; 42: 306-314.
27. Mack JT, Helke KL, Normand G, Green C, Townsend DM, Tew KD,. ABCA2 transporter deficiency reduces incidence of TRAMP prostate tumor metastasis and cellular chemotactic migration. Cancer Lett 2011; 300: 154-161.
28. Grabowska MM, DeGraff DJ, Yu X, et al., Mouse models of prostate cancer: picking the best model for the question. Cancer Metastasis Rev 2014; 33: 377-397.
29. Zhang J, Wang L, Zhang Y, et al., Chemopreventive effect of Korean Angelica root extract on TRAMP carcinogenesis and integrative "omic" profiling of affected neuroendocrine carcinomas. Mol Carcinog 2014; 54: 1567-1583.
30. Chiaverotti T, Couto SS, Donjacour A, et al., Dissociation of epithelial and neuroendocrine carcinoma lineages in the transgenic adenocarcinoma of mouse prostate model of prostate cancer. Am J Pathol 2008; 172: 236-246.
31. Jeet V, Russell PJ, Khatri A,. Modeling prostate cancer: a perspective on transgenic mouse models. Cancer Metastasis Rev 2010; 29: 123-142.
32. Itou Y, Nakanishi K, Narumi Y, Nishizawa Y, Tsukuma H,. Clinical utility of apparent diffusion coefficient (ADC) values in patients with prostate cancer: can ADC values contribute to assess the aggressiveness of prostate cancer? J Magn Reson Imaging JMRI 2011; 33: 167-172.
33. Miyazaki K, Jerome NP, Collins DJ, et al., Demonstration of the reproducibility of free-breathing diffusion-weighted MRI and dynamic contrast enhanced MRI in children with solid tumours: a pilot study. Eur Radiol 2015; 25: 2641-2650.
34. Winfield JM, deSouza NM, Priest AN, et al., Modelling DW-MRI data from primary and metastatic ovarian tumours. Eur Radiol 2015; 25: 2033-2040.
35. Jerome NP, Orton MR, d'Arcy JA, et al., Use of the temporal median and trimmed mean mitigates effects of respiratory motion in multiple-acquisition abdominal diffusion imaging. Phys Med Biol 2015; 60: N9-20.
36. Selnæs KM, Heerschap A, Jensen LR, et al., Peripheral zone prostate cancer localization by multiparametric magnetic resonance at 3 T-unbiased cancer identification by matching to histopathology. Invest Radiol 2012; 47: 624-633.
37. De Cobelli F, Ravelli S, Esposito A, et al., Apparent diffusion coefficient value and ratio as noninvasive potential biomarkers to predict prostate cancer grading: comparison with prostate biopsy and radical prostatectomy specimen. AJR Am J Roentgenol 2015; 204: 550-557.