Preliminary Results of High-Precision Computed Diffusion Weighted Imaging for the Diagnosis of Hepatocellular Carcinoma at 3 Tesla

Objective To compare the utility of high-precision computed diffusion-weighted imaging (hc-DWI) and conventional computed DWI (cc-DWI) for the diagnosis of hepatocellular carcinoma (HCC) at 3 T. Methods We subjected 75 HCC patients to DWI (b-value 150 and 600 s/mm2). To generate hc-DWI we applied non-rigid image registration to avoid the mis-registration of images obtained with different b-values. We defined c-DWI with a b-value of 1500 s/mm2 using DWI with b-value 150 and 600 s/mm2 as cc-DWI, and c-DWI with b-value 1500 s/mm2 using registered DWI with b-value 150 and 600 s/mm2 as hc-DWI. A radiologist recorded the contrast ratio (CR) between HCC and the surrounding hepatic parenchyma. Results The CR for HCC was significantly higher on hc- than cc-DWIs (median 2.0 vs. 1.8, P < 0.01). Conclusion The CR of HCC can be improved with image registration, indicating that hc-DWI is more useful than cc-DWI for the diagnosis of HCC.

[1]  L. Mazzoni,et al.  Effects of gadoxetic acid on quantitative diffusion‐weighted imaging of the liver , 2013, Journal of magnetic resonance imaging : JMRI.

[2]  U. Motosugi,et al.  High‐b‐value diffusion‐weighted MR imaging of hepatocellular lesions: Estimation of grade of malignancy of hepatocellular carcinoma , 2009, Journal of magnetic resonance imaging : JMRI.

[3]  A. Luciani,et al.  Liver Cirrhosis : Intravoxel Incoherent Motion MR Imaging — Pilot Study 1 , 2008 .

[4]  Daniel Rueckert,et al.  Nonrigid registration using free-form deformations: application to breast MR images , 1999, IEEE Transactions on Medical Imaging.

[5]  Jeong Min Lee,et al.  Evaluation of hepatic focal lesions using diffusion‐weighted MR imaging: Comparison of apparent diffusion coefficient and intravoxel incoherent motion‐derived parameters , 2014, Journal of magnetic resonance imaging : JMRI.

[6]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[7]  S. Nawano,et al.  The effect of simultaneous use of respiratory triggering in diffusion-weighted imaging of the liver. , 2006, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

[8]  Ludvig Paul Muren,et al.  Apparent Diffusion Coefficient (ADC) as a quantitative parameter in diffusion weighted MR imaging in gynecologic cancer: Dependence on b-values used , 2010, Acta oncologica.

[9]  K. Awai,et al.  Detectability of hepatocellular carcinoma by gadoxetate disodium‐enhanced hepatic MRI: Tumor‐by‐tumor analysis in explant livers , 2013, Journal of magnetic resonance imaging : JMRI.

[10]  T. Scheenen,et al.  Quantitative Evaluation of Computed High b Value Diffusion-Weighted Magnetic Resonance Imaging of the Prostate , 2013, Investigative radiology.

[11]  Dominic Holland,et al.  Distortion correction in diffusion‐weighted imaging of the breast: Performance assessment of prospective, retrospective, and combined (prospective + retrospective) approaches , 2017, Magnetic resonance in medicine.

[12]  Bülent Sankur,et al.  Survey over image thresholding techniques and quantitative performance evaluation , 2004, J. Electronic Imaging.

[13]  Y. Ohno,et al.  Computed diffusion-weighted imaging using 3-T magnetic resonance imaging for prostate cancer diagnosis , 2013, European Radiology.

[14]  A. Luciani,et al.  Diffusion-weighted MR imaging of the pancreas: current status and recommendations. , 2015, Radiology.

[15]  William E. Lorensen,et al.  Increasing the impact of medical image computing using community-based open-access hackathons: The NA-MIC and 3D Slicer experience , 2016, Medical Image Anal..

[16]  D. Collins,et al.  Distortion correction of echo‐planar diffusion‐weighted images of uterine cervix , 2015, Journal of magnetic resonance imaging : JMRI.

[17]  Joseph O Deasy,et al.  Motion correction of multi-b-value diffusion-weighted imaging in the liver. , 2012, Academic radiology.

[18]  V.R.S Mani,et al.  Survey of Medical Image Registration , 2013 .

[19]  S. Feuerlein,et al.  Pitfalls in abdominal diffusion-weighted imaging: how predictive is restricted water diffusion for malignancy. , 2009, AJR. American journal of roentgenology.

[20]  Geoffrey D. Hugo,et al.  Estimation of optimal b-value sets for obtaining apparent diffusion coefficient free from perfusion in non-small cell lung cancer , 2015, Physics in medicine and biology.

[21]  A. Aisen,et al.  Abdominal MR imaging at 3.0 T. , 2007, Radiographics : a review publication of the Radiological Society of North America, Inc.

[22]  C. Kuhl,et al.  Sensitivity encoding for diffusion-weighted MR imaging at 3.0 T: intraindividual comparative study. , 2005, Radiology.

[23]  J. Babb,et al.  Diffusion‐weighted imaging of the abdomen at 3.0 Tesla: Image quality and apparent diffusion coefficient reproducibility compared with 1.5 Tesla , 2011, Journal of magnetic resonance imaging : JMRI.

[24]  C. Catalano,et al.  Intraindividual comparison of gadoxetate disodium-enhanced MR imaging and 64-section multidetector CT in the Detection of hepatocellular carcinoma in patients with cirrhosis. , 2010, Radiology.

[25]  Masatoshi Kudo,et al.  Multistep human hepatocarcinogenesis: correlation of imaging with pathology , 2009, Journal of Gastroenterology.

[26]  E. Marchiori,et al.  Is DWI/ADC a Useful Tool in the Characterization of Focal Hepatic Lesions Suspected of Malignancy? , 2014, PloS one.

[27]  Guang Yang,et al.  Improving the correction of eddy current-induced distortion in diffusion-weighted images by excluding signals from the cerebral spinal fluid , 2012, Comput. Medical Imaging Graph..

[28]  J. Bruix,et al.  Management of hepatocellular carcinoma: An update , 2011, Hepatology.

[29]  M Hedehus,et al.  Diffusion-tensor MR imaging at 1.5 and 3.0 T: initial observations. , 2001, Radiology.

[30]  K. Zhou,et al.  Detection of small hepatocellular carcinoma: comparison of dynamic enhancement magnetic resonance imaging and multiphase multirow-detector helical CT scanning. , 2007, World journal of gastroenterology.

[31]  H. Rusinek,et al.  Diagnosis of cirrhosis with intravoxel incoherent motion diffusion MRI and dynamic contrast‐enhanced MRI alone and in combination: Preliminary experience , 2010, Journal of magnetic resonance imaging : JMRI.

[32]  B. Taouli,et al.  Diffusion-weighted MR imaging of the liver. , 2010, Radiology.

[33]  D. Le Bihan,et al.  Separation of diffusion and perfusion in intravoxel incoherent motion MR imaging. , 1988, Radiology.

[34]  Stella K Kang,et al.  The Diagnostic Performance of Dynamic Contrast-enhanced MR Imaging for Detection of Small Hepatocellular Carcinoma Measuring Up to 2 cm: A Meta-Analysis. , 2016, Radiology.

[35]  G. Dusheiko,et al.  Management of hepatocellular carcinoma. , 1992, Journal of hepatology.

[36]  K. Togashi,et al.  Additional benefit of computed diffusion-weighted imaging for detection of hepatic metastases at 1.5T. , 2016, Clinical imaging.

[37]  B. Choi,et al.  Small (≤1-cm) hepatocellular carcinoma: diagnostic performance and imaging features at gadoxetic acid-enhanced MR imaging. , 2014, Radiology.

[38]  A. Levy,et al.  Focal Liver Lesion Detection and Characterization with Diffusion-weighted MR Imaging: Comparison with Standard Breath-hold T2-weighted Imaging , 2009 .

[39]  Namkug Kim,et al.  Malignant hepatic tumors: short-term reproducibility of apparent diffusion coefficients with breath-hold and respiratory-triggered diffusion-weighted MR imaging. , 2010, Radiology.

[40]  D. Collins,et al.  Computed diffusion-weighted MR imaging may improve tumor detection. , 2011, Radiology.

[41]  Thomas E Yankeelov,et al.  Motion correction in diffusion‐weighted MRI of the breast at 3T , 2011, Journal of magnetic resonance imaging : JMRI.

[42]  D. Collins,et al.  Diffusion-weighted MRI in the body: applications and challenges in oncology. , 2007, AJR. American journal of roentgenology.