Enhancing pancreatic adenocarcinoma delineation in diffusion derived intravoxel incoherent motion f-maps through automatic vessel and duct segmentation

Magnetic Resonance in Medicine

Volumn 66, Issue 5, 2011, Pages 1327-1332

  Re, Thomas J ^a,b   Lemke, Andreas ^c   Klauss, Miriam ^c   Laun, Fredrik B ^a   Simon, Dirk ^a   Grünberg, Katharina ^a   Delorme, Stefan ^a   Grenacher, Lars ^c   Manfredi, Riccardo ^b   Mucelli, Roberto Pozzi ^b   Stieltjes, Bram ^a  

^a GERMAN CANCER RESEARCH CENTER DKFZ   (Germany)

^b UNIVERSITY OF VERONA   (Italy)

^c UNIVERSITY OF HEIDELBERG   (Germany)

Author keywords

diffusion; IVIM; pancreas; segmentation

Indexed keywords

DIAGNOSIS; DIFFUSION; IMAGE SEGMENTATION; TUMORS;

AREA UNDER THE CURVES; AUTOMATED SEGMENTATION; AUTOMATIC SEGMENTATIONS; INTRAVOXEL INCOHERENT MOTIONS; IVIM; PANCREAS; PANCREATIC ADENOCARCINOMA; RECEIVER OPERATING CHARACTERISTIC ANALYSIS;

DUCTS;

ADULT; AGED; ARTICLE; CLINICAL ARTICLE; CONTROLLED STUDY; DIAGNOSTIC PROCEDURE; DIFFUSION WEIGHTED IMAGING; FEMALE; HUMAN; MALE; PANCREAS ADENOCARCINOMA; PANCREAS DUCT;

EID: 80054809351     PISSN: 07403194     EISSN: 15222594     Source Type: Journal    
DOI: 10.1002/mrm.22931     Document Type: Article

References (27)

1. Stathis A, Moore MJ,. Advanced pancreatic carcinoma: current treatment and future challenges. Nat Rev Clin Oncol 2010; 7: 163-172.
2. Chakravarty K, Hsu JT, Liu KH, Yeh CN, Yeh TS, Hwang TL, Jan YY, Chen MF,. Prognosis and feasibility of en-bloc vascular resection in stage II pancreatic adenocarcinoma. World J Gastroenterol 2010; 16: 997-1002.
3. Kanda M, Fujii T, Sahin TT, Kanzaki A, Nagai S, Yamada S, Sugimoto H, Nomoto S, Takeda S, Kodera Y, Morita S, Nakao A,. Invasion of the splenic artery is a crucial prognostic factor in carcinoma of the body and tail of the pancreas. Ann Surg 2010; 251: 483-487.
4. D'Onofrio M, Zamboni G, Faccioli N, Capelli P, Pozzi Mucelli R,. Ultrasonography of the pancreas. 4. Contrast-enhanced imaging. Abdom Imaging 2007; 32: 171-181.
5. D'Onofrio M, Gallotti A, Pozzi Mucelli R,. Imaging techniques in pancreatic tumors. Expert Rev Med Devices 2010; 7: 257-273.
6. Fusari M, Maurea S, Imbriaco M, Mollica C, Avitabile G, Soscia F, Camera L, Salvatore M,. Comparison between multislice CT and MR imaging in the diagnostic evaluation of patients with pancreatic masses. Radiol Med 2010; 115: 453-466.
7. Yoshikawa T, Kawamitsu H, Mitchell D, Ohno Y, Ku Y, Seo Y, Fujii M, Sugimura K,. ADC measurement of abdominal organs and lesions using parallel imaging technique. Am J Roentgenol 2006; 187: 1521-1530.
8. Muraoka N, Uematsu H, Kimura H, Imamura Y, Fujiwara Y, Murakami M, Yamaguchi A, Itoh H,. Apparent diffusion coefficient in pancreatic cancer: characterization and histopathological correlations. J Magn Reson Imaging 2008; 27: 1302-1308.
9. Balci N, Perman WH, Saglam S, Akisik F, Fattahi R, Bilgin M,. Diffusion-weighted magnetic resonance imaging of the pancreas. Top Magn Reson Imaging 2009; 20: 43-47.
10. Balci N, Momtahen AJ, Akduman EI, Alkaade S, Bilgin M, Burton FR,. Diffusion-weighted MRI of the pancreas: correlation with secretin endoscopic pancreatic function test (ePFT). Acad Radiol 2008; 15: 1264-1268.
11. Inan N, Arslan A, Akansel G, Anik Y, Demirci A,. Diffusion-weighted imaging in the differential diagnosis of cystic lesions of the pancreas. Am J Roentgenol 2008; 191: 1115-1121.
12. Matsuki M, Inada Y, Nakai G, Tatsugami F, Tanikake M, Narabayashi I, Masuda D, Arisaka Y, Takaori K, Tanigawa N,. Diffusion-weighed MR imaging of pancreatic carcinoma. Abdom Imaging 2007; 32: 481-483.
13. Zhang J, Tehrani YM, Wang L, Ishill NM, Schwartz LH, Hricak H,. Renal masses: characterization with diffusion-weighted MR imaging-a preliminary experience. Radiology 2008; 247: 458-464.
14. Luciani A, Vignaud A, Cavet M, Nhieu JT, Mallat A, Ruel L, Laurent A, Deux JF, Brugieres P, Rahmouni A,. Liver cirrhosis: intravoxel incoherent motion MR imaging-pilot study. Radiology 2008; 249: 748-752.
15. Patel J, Sigmund EE, Rusinek H, Oei M, Babb JS, Taouli B,. Diagnosis of cirrhosis with intravoxel incoherent motion diffusion MRI and dynamic contrast-enhanced MRI alone and in combination: preliminary experience. J Magn Reson Imaging 2010; 31: 589-600.
16. Le Bihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M,. MR imaging of incoherent motions: application to diffusion and perfusion in neurologic disorders. Radiology 1986; 161: 401-407.
17. Le Bihan D, Breton E, Lallemand D, Aubin ML, Vignaud J, Laval-Jeantet M,. Separation of diffusion and perfusion in intra voxel incoherent motion MR imaging. Radiology 1988; 168: 497-505.
18. Le Bihan D,. Intravoxel incoherent motion perfusion MR imaging: a wake-up call. Radiology 2008; 249: 748-752.
19. Yamada I, Aung W, Himeno Y, Nakagawa T, Shibuya H,. Diffusion coefficients in abdominal organs and hepatic lesions: evaluation with intravoxel incoherent motion echo-planar MR imaging. Radiology 1999; 210: 617-623.
20. Lemke A, Laun FB, Klauß M, Re TJ, Simon D, Delorme S, Schad LR, Stieltjes B,. Differentiation of pancreas carcinoma from healthy pancreatic tissue using multiple b-values: comparison of apparent diffusion coefficient and intravoxel incoherent motion derived parameters. Invest Radiol 2009; 44: 769-775.
21. Klauß M, Lemke A, Simon D, Re TJ, Wente MN, Laun FB, Kauczor HU, Delorme S, Grenacher L, Stieltjes B,. Intravoxel incoherent motion MR imaging for the differentiation between mass forming chronic pancreatitis and pancreatic carcinoma. Invest Radiol 2011; 46: 57-63.
22. Kim T, Murakami T, Takahashi S, Okada A, Hori M, Narumi Y, Nakamura H,. Pancreatic CT imaging: effects of different injection rates and doses of contrast material. Radiology 1999; 212: 219-225.
23. Tamm EP, Silverman PM, Charnsangavej C, Evans DB,. Diagnosis, staging, and surveillance of pancreatic cancer. Am J Roentgenol 2003; 180: 1311-1323.
24. Bishop CM,. Pattern recognition and machine learning. Heidelberg, Germany: Springer; 2006. p 749.
25. Lemke A, Laun FB, Schad LR, Stieltjes B,. Towards an optimal distribution of b-values for IVIM imaging. Proc Intl Soc Mag Reson Med 2010; 18: 1750.
26. Dempster AP, Laird NM, Rubin DB,. Maximum likelihood from incomplete data via the EM algorithm. J Roy Stat Soc Series B (Meth) 1977; B-39: 1-38.
27. Hastie T, Tibshirani R, Friedman J,. The elements of statistical learning, data mining, inference, and prediction. Heidelberg, Germany: Springer; 2009. p 63.