Computed diffusion-weighted MR imaging may improve tumor detection.

PURPOSE To describe computed diffusion weighted (DW) magnetic resonance (MR) imaging as a method for obtaining high-b-value images from DW MR imaging performed at lower b values and to investigate the feasibility of the technique to improve lesion detection in oncologic cases. MATERIALS AND METHODS The study was approved by the institutional and research committee, and written informed consent was obtained from all patients. DW MR imaging was performed on a CuSO(4) phantom at 1.5 T with a range of b values and compared with computed DW MR imaging images synthesized from lower b values (0 and 600 sec/mm(2)). The signal-to-noise ratio (SNR) was compared, and agreement between the SNR of computed DW MR imaging and theoretical estimation assessed. Computed DW MR imaging was evaluated in 10 oncologic patients who underwent whole-body DW MR imaging with b values of 0 and 900 sec/mm(2). Computed DW MR images at computed b values of 1500 and 2000 sec/mm(2) were generated. The image quality and background suppression of acquired and computed images were rated by a radiologist using a four-point scale. The diagnostic performance for malignant lesion detection using these images was evaluated and compared by using the McNemar Test. RESULTS The SNR of computed DW MR imaging of the phantom conformed closely to theoretical predictions. Computed DW MR imaging resulted in a higher SNR compared with acquired DW MR imaging, especially at b values greater than 840 sec/mm(2). In patients, images with a computed b value of 2000 sec/mm(2) produced good image quality and high background suppression (mean scores of 2.8 and 4.0, respectively). Evaluation of images with a computed b value of 2000 sec/mm(2) resulted in higher overall diagnostic sensitivity (96.0%) and specificity (96.6%) compared with images with an acquired b value of 900 sec/mm(2) (sensitivity, 89.4%; specificity, 87.5%; P < .01). CONCLUSION Computed DW MR imaging in the body allows higher-b-value images to be obtained with a good SNR. Clinical computed DW MR imaging is feasible and may improve disease detection. SUPPLEMENTAL MATERIAL http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.11101919/-/DC1.

[1]  N M Hylton,et al.  Signal to Noise in Derived NMR Images , 1984, Magnetic resonance in medicine.

[2]  J N Lee,et al.  Automated MR image synthesis: feasibility studies. , 1984, Radiology.

[3]  Denis Le Bihan,et al.  Imagerie de diffusion in-vivo par résonance magnétique nucléaire , 1985 .

[4]  P. Grenier,et al.  MR imaging of intravoxel incoherent motions: application to diffusion and perfusion in neurologic disorders. , 1986, Radiology.

[5]  J. Hyde,et al.  Characterization of continuously distributed cortical water diffusion rates with a stretched‐exponential model , 2003, Magnetic resonance in medicine.

[6]  T. Takahara,et al.  Diffusion weighted whole body imaging with background body signal suppression (DWIBS): technical improvement using free breathing, STIR and high resolution 3D display. , 2004, Radiation medicine.

[7]  P. Kingsley,et al.  Introduction to diffusion tensor imaging mathematics: Part III. Tensor calculation, noise, simulations, and optimization , 2006 .

[8]  Dow-Mu Koh,et al.  Practical aspects of assessing tumors using clinical diffusion-weighted imaging in the body. , 2007, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

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

[10]  K. Chang,et al.  High b-Value Diffusion (b = 3000 s/mm2) MR Imaging in Cerebral Gliomas at 3T: Visual and Quantitative Comparisons with b = 1000 s/mm2 , 2008, American Journal of Neuroradiology.

[11]  S. Matsumoto,et al.  Non-small cell lung cancer: whole-body MR examination for M-stage assessment--utility for whole-body diffusion-weighted imaging compared with integrated FDG PET/CT. , 2008, Radiology.

[12]  K. Sugimura,et al.  High b-value diffusion-weighted imaging in normal and malignant peripheral zone tissue of the prostate: effect of signal-to-noise ratio. , 2008, Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine.

[13]  Namkug Kim,et al.  Node-by-node correlation between MR and PET/CT in patients with uterine cervical cancer: diffusion-weighted imaging versus size-based criteria on T2WI , 2009, European Radiology.

[14]  Zeynep Firat,et al.  High b-value diffusion-weighted MR imaging of normal brain at 3T. , 2009, European journal of radiology.

[15]  Y. Yamashita,et al.  Ultra-high-b-value diffusion-weighted MR imaging for the detection of prostate cancer: evaluation in 201 cases with histopathological correlation , 2010, European Radiology.

[16]  M. Forsting,et al.  Diagnostic value of diffusion-weighted magnetic resonance imaging (DWI) compared to FDG PET/CT for whole-body breast cancer staging , 2010, European Journal of Nuclear Medicine and Molecular Imaging.

[17]  R. Birdwell 1H MR Spectroscopy and Diffusion-Weighted Imaging of the Breast: Are They Useful Tools for Characterizing Breast Lesions Before Biopsy? , 2010 .