Whole body MRI: improved lesion detection and characterization with diffusion weighted techniques

Rajpaul Attariwala, Wayne Picker, Rajpaul Attariwala, Wayne Picker

Abstract

Diffusion-weighted imaging (DWI) is an established functional imaging technique that interrogates the delicate balance of water movement at the cellular level. Technological advances enable this technique to be applied to whole-body MRI. Theory, b-value selection, common artifacts and target to background for optimized viewing will be reviewed for applications in the neck, chest, abdomen, and pelvis. Whole-body imaging with DWI allows novel applications of MRI to aid in evaluation of conditions such as multiple myeloma, lymphoma, and skeletal metastases, while the quantitative nature of this technique permits evaluation of response to therapy. Persisting signal at high b-values from restricted hypercellular tissue and viscous fluid also permits applications of DWI beyond oncologic imaging. DWI, when used in conjunction with routine imaging, can assist in detecting hemorrhagic degradation products, infection/abscess, and inflammation in colitis, while aiding with discrimination of free fluid and empyema, while limiting the need for intravenous contrast. DWI in conjunction with routine anatomic images provides a platform to improve lesion detection and characterization with findings rivaling other combined anatomic and functional imaging techniques, with the added benefit of no ionizing radiation.

Keywords: MRI; whole body MRI; apparent diffusion coefficient ADC; b-value; diffusion-weighted imaging DWI; oncology imaging.

Copyright © 2013 Wiley Periodicals, Inc.

Figures

Figure 1
Figure 1
Application of water motion probing diffusion sensitizing gradients between polarizing RF pulses. Free unrestricted water movement in between application of the diffusion sensitizing gradients results in low signal. Increased signal is produced in tissue where water is restricted from moving between the two motion probing diffusion sensing gradient applications (bottom row).
Figure 2
Figure 2
b-value, or diffusion gradient field strength. It is dependent on gradient field strength amplitude, A, duration of application of the diffusion gradient, d, and the time interval between applying the two motion probing pulses, t.
Figure 3
Figure 3
Diffusion imaging of a cross section through the abdomen at b-values of 0 (a), 200 (b), 800 (c), and 1000(d) s/mm2. At a b-value of 0, note the dark areas representing fluid, flowing or static. At a b-value of 200, flowing fluids are no longer visible. As b-values increase, there is a resultant loss of background tissue, with minimal normal background liver seen at b-value of 1000 (d).
Figure 4
Figure 4
Generic body tissue diffusion curve. Log signal intensity versus b-values for most body tissues show a biexponential behavior with an inflection around b-value of 100 s/mm2. At b-values below 100 (shaded), there is a tissue-dependent and additive perfusion flow effect resulting in increased signal intensity which can skew ADC calculations. At b-values above 100, the perfusion effects in the body are limited, resulting in an essentially linear true diffusion slope.
Figure 5
Figure 5
Tissue diffusion IVIM curve. The apparent diffusion (ADC) is the absolute value of the slope of the curve. As higher b-values are used, the background signal decreases.
Figure 6
Figure 6
Tissue diffusion curve behavior for native tissue, and a restricted lesion within the tissue (a). The restricted lesion has a less steep slope and thus low ADC value. In body imaging typically the greatest separation in signal intensity between native and restricted tissue with background tissue visibility occurs near b-value of 500 s/mm2 (b). Outlines the difference in slope/ADC from near horizontal for solid tissue to the steepest for vascular lesions. The slope differences represent the premise for assessing ADC change of a solid restricted mass initially becoming edematous with treatment with resultant rising ADC values.
Figure 7
Figure 7
ADC misregistration due to breathing. Upper left b-500, lower left b-50 demonstrates a lesion which is conspicuous from background tissue, with the lesion signal intensity dropping on the b-500 image. The relative signal change is typical for a simple cyst, as confirmed with hyperintense features on the axial T2 (lower middle) and coronal STIR sequences (right). The ADC map (upper center) shows no apparent hyperintense signal characteristic of a cyst due to the misregistration. Note the noise of the ADC map in the liver from breathing movement, which is not as apparent in the left kidney due to less movement.
Figure 8
Figure 8
Coronal whole-body images. The b-value image at b-0, shown as white on black, represents a fat saturated fluid sensitive sequence (a), however, the purpose of DWI as a functional technique is to maximize lesion conspicuity by maximizing signal to noise. Typically this is performed with 3 × 3 mm by 5 mm thick slices, as compared with the 1.6 mm × 1.6 mm inplane STIR sequence which demonstrates exquisite anatomic detail (b).
Figure 9
Figure 9
Axial b-500 image (a) demonstrates loss of signal within the left aspect of the liver from cardiac pulsation. The anatomy is not obscured on the axial T2 (b) image. This loss of signal is less problematic at low b-values and can be practically minimized by increasing the number of averages for DWI, or cardiac gating.
Figure 10
Figure 10
Whole-body coronal T1, DWI (b-500 shown as black on white), and STIR images demonstrating the conspicuity of the left adnexal subacute hemorrhage in an endometrioma due to the paramagnetic effects and restricted diffusion of blood degradation products.
Figure 11
Figure 11
Axial b-500 (a) readily demonstrates the increased signal from localized pyelonephritis, which cannot be identified on axial T2 (b) images. The subtle loss of arterial phase enhancement from pyelonephritis is shown in (c), with near complete loss of lesion conspicuity on delayed contrast enhanced images (d).
Figure 12
Figure 12
Prostate imaging. DWI b-800 demonstrates marked susceptibility from gas in the rectum (a) obscuring visualization of the peripheral zone. This can be simply rectified noninvasively by prone positioning (b) of the patient, or with rectal gel.

References

    1. Eustace S, Tello R, DeCarvalho V, Carey J, Melhem E, Yucel EK. Whole body turbo STIR MRI in unknown primary tumor detection. J Magn Reson Imaging. 1998;8:751–753.
    1. Steinborn MM, Heuck AF, Tiling R, Bruegel M, Gauger L, Reiser MF. Whole-body bone marrow MRI in patients with metastatic disease to the skeletal system. J Comput Assist Tomogr. 1999;23:123–129.
    1. Lauenstein TC, Freudenberg LS, Goehde SC, et al. Whole-body MRI using a rolling table platform for the detection of bone metastases. Eur Radiol. 2002;12:2091–2099.
    1. Kruger DG, Riederer SJ, Grimm RC, Rossman PJ. Continuously moving table data acquisition method for long FOV contrast-enhanced MRA and whole-body MRI. Magn Reson Med. 2002;47:224–231.
    1. Engelhard K, Hollenbach HP, Wohlfart K, von Imhoff E, Fellner FA. Comparison of whole-body MRI with automatic moving table technique and bone scintigraphy for screening for bone metastases in patients with breast cancer. Eur Radiol. 2004;14:99–105.
    1. LeBihan D, Breton E. Imagerie de diffusion in-vivo par resonance. C R Acad Sci. 1985;301:1109–1112. (Paris)
    1. Muller MF, Edelman RR. Echo planar imaging of the abdomen. Top Magn Reson Imaging. 1995;7:112–119.
    1. Wang Y. Description of parallel imaging in MRI using multiple coils. Magn Reson Med. 2000;44:495–499.
    1. Schmidt GP, Schoenberg SO, Schmid R, et al. Screening for bone metastases: whole-body MRI using a 32-channel system versus dual-modality PET-CT. Eur Radiol. 2007;17:939–949.
    1. Stejskal EO, Tanner JE. Spin diffusion measurements: spin echoes in the presence of a time-dependent field gradient. J Chem Phys. 1965;42:288–293.
    1. Einstein A. On the movement of small particles suspended in stationary liquids required by the kinetic theory of heat. Ann Der Physik. 1905;17:549–560.
    1. Takahara T, Imai Y, Yamashita T, et al. Diffusion weighted whole body imaging with background body signal suppression (DWIBS): technical improvement using free breathing, STIR and high resolution 3D display. Radiat Med. 2004;22:275–282.
    1. Koh D-M, Blackledge M, Padhani AR, et al. Whole-body diffusion-weighted MRI: tips, tricks, and pitfalls. AJR Am J Roentgenol. 2012;199:252–262.
    1. LeBihan D, Breton E, Lallemand D, Grenier P, Cabanis E, Laval-Jeantet M. MR Imaging of incoherent motion: application to diffusion and perfusion in neurologic disorders. Radiology. 1986;161:401–407.
    1. Koh DM, Collins DJ, Orton MR. Intravoxel incoherent motion in body diffusion-weighted MRI: reality and challenges. AJR Am J Roentgenol. 2011;196:1351–1361.
    1. LeBihan D, Turner R. The capillary network: a link between IVIM and classical perfusion. Magn Reson Med. 1992;27:171–178.
    1. Lemke A, Laun FB, Simon D, Stieltjes B, Schad LR. An in vivo verification of the intravoxel incoherent motion effect in diffusion-weighted imaging of the abdomen. Magn Reson Med. 2010;64:1580–1585.
    1. Uto T, Takehara Y, Nakamura Y, et al. Higher sensitivity and specificity for diffusion-weighted imaging of malignant lung lesions without apparent diffusion coefficient quantification. Radiology. 2009;252:247–254.
    1. Baysal T, Bulut T, Gokirmak M, et al. Diffusion-weighted MR imaging of pleural fluid: differentiation of transudative vs exudative pleural effusions. Eur Radiol. 2004;14:890–896.
    1. Inan N, Arslan A, Akansel G, et al. Diffusion-weighted MRI in the characterization of pleural effusions. Diag Interv Radiol. 2009;15:13–18.
    1. Bozkurt M, Doganay S, Kantarci M, et al. Comparison of peritoneal tumor imaging using conventional MR imaging and diffusion-weighted MR imaging with different b values. Eur J Radiol. 2011;80:224–228.
    1. Low RN, Sebrechts CP, Barone RM, Muller W. Diffusion-weighted MRI of peritoneal tumors: comparison with conventional MRI and surgical and histopathologic findings–a feasibility study. AJR Am J Roentgenol. 2009;193:461–470.
    1. Padhani AR, Liu G, Koh DM, et al. Diffusion-weighted magnetic resonance imaging as a cancer biomarker: consensus and recommendations. Neoplasia. 2009;11:102–125.
    1. Rosenkrantz AB, Oei M, Babb JS, Niver BE, Taouli B. Diffusion-weighted imaging of the abdomen at 3.0 Tesla: image quality and apparent diffusion coefficient reproducibility compared with 1.5 Tesla. J Magn Reson Imaging. 2011;33:128–135.
    1. Ziegelberger G, Ingolstaedter L. ICNIRP Statement on the “guidelines for limiting exposure to time-varying electric, magnetic and electromagnetic fields (up to 300GHz)”. Health Phys. 2009;97:257–258.
    1. International Commission on Non-Ionizing Radiation Protection. Guidelines on limiting exposure to static magnetic fields. Health Phys. 2009;96:504–514.
    1. Harvey PR, Zhai Z, Morich M, et al. SAR behavior during whole-body multitransmit RF shimming at 3.0T. In: Proceedings of the 17th Annual Meeting of ISMRM. Honolulu. 2009 (abstract 4786)
    1. Neufeld E, Gosselin M-C, Murbach M, et al. Analysis of the local worst-case SAR exposure caused by an MRI multi-transmit body coil in anatomical models of the human body. Phys Med Biol. 2011;56:4649–4659.
    1. Enroth-Cugell C, Shapley RM. Flux, not retinal illumination, is what cat retinal ganglion cells really care about. J Physiol. 1973;233:311–326.
    1. Padhani AR, Koh DM, Collins DJ. Whole-body diffusion-weighted MR imaging in cancer: current status and research directions. Radiology. 2011;261:700–718.
    1. Atlas SW, DuBois P, Singer MB, Lu D. Diffusion measurements in intracranial hematomas: implications for MR imaging of acute stroke. AJNR Am J Neuroradiol. 2000;21:1190–1194.
    1. Goodsitt MM, Hoover P, Veldee MS, Hsueh SL. The composition of bone marrow for a dual-energy quantitative computed tomography technique. A cadaver and computer simulation study. Invest Radiol. 1994;29:695–704.
    1. Stecco A, Lombardi M, Leva L, et al. Diagnostic accuracy and agreement between whole-body diffusion MRI and bone scintigraphy in detecting bone metastases. Radiol Med. 2013;118:465–475.
    1. Mosavi F, Johansson S, Sandberg DT, Turesson I, Sorensen J, Ahlstrom H. Whole-body diffusion-weighted MRI compared with (18)F-NaF PET/CT for detection of bone metastases in patients with high-risk prostate carcinoma. AJR Am J Roentgenol. 2012;199:1114–1120.
    1. Liu X, Zhou L, Peng W, Qian M. Effect of intravenous gadolinium-DTPA on diffusion-weighted imaging for prostate lesions and normal tissue at 3.0-Tesla magnetic resonance imaging. Acta Radiol. 2011;52:575–580.
    1. Wang CL, Chea YW, Boll DT, et al. Effect of gadolinium chelate contrast agents on diffusion weighted MR imaging of the liver, spleen, pancreas and kidney at 3 T. Eur J Radiol. 2011;80:e1–e7.
    1. Kinner S, Umutlu L, Blex S, et al. Diffusion weighted MR imaging in patients with HCC and liver cirrhosis after administration of different gadolinium contrast agents: is it still reliable? Eur J Radiol. 2012;81:e625–e628.
    1. Kwee TC, van Ufford HM, Beek FJ, et al. Whole-body MRI, including diffusion-weighted imaging, for the initial staging of malignant lymphoma: comparison to computed tomography. Invest Radiol. 2009;44:683–690.
    1. Gu J, Chan T, Zhang J, Leung AY, Kwong YL, Khong PL. Whole-body diffusion-weighted imaging: the added value to whole-body MRI at initial diagnosis of lymphoma. AJR Am J Roentgenol. 2011;197:W384–W391.
    1. Fischer MA, Nanz D, Hany T, et al. Diagnostic accuracy of whole-body MRI/DWI image fusion for detection of malignant tumours: a comparison with PET/CT. Eur Radiol. 2011;21:246–255.
    1. Manenti G, Ciccio C, Squillaci E, et al. Role of combined DWIBS/3D-CE-T1w whole-body MRI in tumor staging: comparison with PET-CT. Eur J Radiol. 2012;81:1917–1925.
    1. Xu GZ, Li CY, Zhao L, He ZY. Comparison of FDG whole-body PET/CT and gadolinium-enhanced whole-body MRI for distant malignancies in patients with malignant tumors: a meta-analysis. Ann Oncol. 2013;24:96–101.
    1. Sommer G, Klarhofer M, Lenz C, et al. Signal characteristics of focal bone marrow lesions in patients with multiple myeloma using whole body T1w-TSE, T2w-STIR and diffusion-weighted imaging with background suppression. Eur Radiol. 2011;21:857–862.
    1. Schmidt GP, Reiser MF, Baur-Melnyk A. Whole-body MRI for the staging and follow-up of patients with metastasis. Eur J Radiol. 2009;70:393–400.
    1. Marzolini M, Wong WL, Ardeshna K, Padhani A, D’Sa S. Diffusion-weighted MRI compared to FDG PET-CT in the staging and response assessment of Hodgkin lymphoma. Br J Hematol. 2012;156:557.
    1. Padhani AR, Gogbashian A. Bony metastases: assessing response to therapy with whole-body diffusion MRI. Cancer imaging. 2011;(11 Spec No):S129–S145.
    1. Thoeny HC, De Keyzer F, King AD. Diffusion-weighted MR imaging in the head and neck. Radiology. 2012;263:19–32.
    1. Mutlu H, Sivrioglu AK, Sonmez G, et al. Role of apparent diffusion coefficient values and diffusion-weighted magnetic resonance imaging in differentiation between benign and malignant thyroid nodules. Clin Imaging. 2012;36:1–7.
    1. Nakahira M, Saito N, Murata S-I, et al. Quantitative diffusion-weighted magnetic resonance imaging as a powerful adjunct to fine needle aspiration cytology for assessment of thyroid nodules. Am J Otolaryngol. 2012;33:408–416.
    1. Lambrecht M, Dirix P, Vandecaveye V, et al. Role and value of diffusion-weighted MRI in the radiotherapeutic management of head and neck cancer. Exp Rev Anticancer Ther. 2010;10:1451–1459.
    1. Wu L-M, Xu J-R, Liu M-J, et al. Value of magnetic resonance imaging for nodal staging in patients with head and neck squamous cell carcinoma: a meta-analysis. Acad Radiol. 2012;19:674.
    1. Yun TJ, Kim J-H, Kim KH, Sohn C-H, Park S-W. Head and neck squamous cell carcinoma: differentiation of histologic grade with standard-and high-b-value diffusion-weighted MRI. Head Neck. 2013;35:626–631.
    1. Nakamatsu S, Matsusue E, Miyoshi H, et al. Correlation of apparent diffusion coefficients measured by diffusion-weighted MR imaging and standardized uptake values from FDG PET/CT in metastatic neck lymph nodes of head and neck squamous cell carcinomas. Clin Imaging. 2012;36:90–97.
    1. Nakajo M, Nakajo M, Kajiya Y, et al. FDG PET/CT and diffusion-weighted imaging of head and neck squamous cell carcinoma: comparison of prognostic significance between primary tumor standardized uptake value and apparent diffusion coefficient. Clin Nucl Med. 2012;37:475–480.
    1. Quon H, Brizel DM. Predictive and prognostic role of functional imaging of head and neck squamous cell carcinomas. Semin Radiat Oncol. 2012;22:220–232.
    1. Berrak S, Chawla S, Kim S, et al. Diffusion-weighted imaging in predicting progression free survival in patients with squamous cell carcinomas of the head and neck treated with induction chemotherapy. Acad Radiol. 2011;18:1225–1232.
    1. Mutlu T, Yologlu DYS. Diffusion-weighted magnetic resonance imaging in differentiation of postobstructive consolidation from central lung carcinoma. Magn Reson Imaging. 2009;27:1447–1454.
    1. Regier M, Schwarz D, Henes FO, et al. Diffusion-weighted MR-imaging for the detection of pulmonary nodules at 1.5 Tesla: intraindividual comparison with multidetector computed tomography. J Med Imaging Radiat Oncol. 2011;55:266–274.
    1. Ohba Y, Nomori H, Mori T, et al. Is diffusion-weighted magnetic resonance imaging superior to positron emission tomography with fludeoxyglucose F 18 in imaging non-small cell lung cancer? J Thoracic Cardiovasc Surg. 2009;138:439–445.
    1. Regier M, Derlin T, Schwarz D, et al. Diffusion weighted MRI and 18F-FDG PET/CT in non-small cell lung cancer (NSCLC): does the apparent diffusion coefficient (ADC) correlate with tracer uptake (SUV)? Eur J Radiol. 2012;81:2913–2918.
    1. Wu L-M, Xu J-R, Gu H-Y, et al. Preoperative mediastinal and hilar nodal staging with diffusion-weighted magnetic resonance imaging and fluorodeoxyglucose positron emission tomography/computed tomography in patients with non-small-cell lung cancer: which is better? J Surg Res. 2012;178:304–314.
    1. Pauls S, Schmidt SA, Juchems MS, et al. Diffusion-weighted MR imaging in comparison to integrated [18F]-FDG PET/CT for N-staging in patients with lung cancer. Eur J Radiol. 2012;81:178–182.
    1. Ohno Y, Koyama H, Onishi Y, 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. Radiology. 2008;248:643–654.
    1. Partridge SC, McKinnon GC, Henry RG, Hylton NM. Menstrual cycle variation of apparent diffusion coefficients measured in the normal breast using MRI. J Magn Reson Imaging. 2001;14:433–438.
    1. Partridge SC, Demartini WB, Kurland BF, Eby PR, White SW, Lehman CD. Differential diagnosis of mammographically and clinically occult breast lesions on diffusion-weighted MRI. J Magn Reson Imaging. 2010;31:562–570.
    1. Partridge SC, Rahbar H, Murthy R, et al. Improved diagnostic accuracy of breast MRI through combined apparent diffusion coefficients and dynamic contrast-enhanced kinetics. Magn Reson Med. 2011;1767:1759–1767.
    1. Partridge SC, DeMartini WB, Kurland BF, Eby PR, White SW, Lehman CD. Quantitative diffusion-weighted imaging as an adjunct to conventional breast MRI for improved positive predictive value. AJR Am J Roentgenol. 2009;193:1716–1722.
    1. Sigmund EE, Cho GY, Kim S, et al. Intravoxel incoherent motion imaging of tumor microenvironment in locally advanced breast cancer. Magn Reson Med. 2011;65:1437–1447.
    1. Kazama T, Kuroki Y, Kikuchi M, et al. Diffusion-weighted MRI as an adjunct to mammography in women under 50 years of age: an initial study. J Magn Reson Imaging. 2012;36:139–144.
    1. Jones RA, Grattan-Smith JD. Age dependence of the renal apparent diffusion coefficient in children. Pediatr Radiol. 2003;33:850–854.
    1. Verswijvel G, Vandecaveye V, Gelin G, et al. Diffusion-weighted MR imaging in the evaluation of renal infection: preliminary results. JBR-BTR. 2002;85:100–103.
    1. Macarini L, Stoppino LP, Milillo P, Ciuffreda P, Fortunato F, Vinci R. Diffusion-weighted MRI with parallel imaging technique: apparent diffusion coefficient determination in normal kidneys and in nonmalignant renal diseases. Clin Imaging. 2010;34:432–440.
    1. Cova M, Squillaci E, Stacul F, et al. Diffusion-weighted MRI in the evaluation of renal lesions: preliminary results. Br J Radiol. 2004;77:851–857.
    1. Thoeny HC, De Keyzer F, Oyen RH, Peeters RR. Diffusion-weighted MR imaging of kidneys in healthy volunteers and patients with parenchymal diseases: initial experience. Radiology. 2005;235:911–917.
    1. Thoeny HC, De Keyzer F. Diffusion-weighted MR imaging of native and transplanted kidneys. Radiology. 2011;259:25–38.
    1. Eisenberger U, Thoeny HC, Binser T, et al. Evaluation of renal allograft function early after transplantation with diffusion-weighted MR imaging. Eur Radiol. 2010;20:1374–1383.
    1. Cova M, Squillaci E, Stacul F, et al. Diffusion-weighted MRI in the evaluation of renal lesions: preliminary results. Br J Radiol. 2004;77:851–857.
    1. 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.
    1. Sandrasegaran K, Sundaram CP, Ramaswamy R, et al. Usefulness of diffusion-weighted imaging in the evaluation of renal masses. AJR Am J Roentgenol. 2010;194:438–45. Feb;
    1. Kim S, Jain M, Harris AB, et al. T1 hyperintense renal lesions: characterization with diffusion-weighted MR imaging versus contrast-enhanced MR imaging. Radiology. 2009;251:796–807.
    1. Wang H, Cheng L, Zhang X, et al. Renal cell carcinoma: diffusion-weighted MR imaging for subtype differentiation at 3.0 T. Radiology. 2010;257:135–143.
    1. Goyal A, Sharma R, Bhalla AS, et al. Diffusion-weighted MRI in renal cell carcinoma: a surrogate marker for predicting nuclear grade and histological subtype. Acta Radiol. 2012;53:349–358.
    1. Zhang JL, Sigmund EE, Chandarana H, et al. Variability of renal apparent diffusion coefficients: limitations of the monoexponential model for diffusion quantification. Radiology. 2010;254:783–792.
    1. Zhang JL, Sigmund EE, Rusinek H, et al. Optimization of b-value sampling for diffusion-weighted imaging of the kidney. Magn Reson Med. 2012;67:89–97.
    1. Chandarana H, Lee VS, Hecht E, Taouli B, Sigmund EE. Comparison of biexponential and monoexponential model of diffusion-weighted imaging in evaluation of renal lesions: preliminary experience. Invest Radiol. 2011;46:285–291.
    1. Abou-El-Ghar ME, El-Assmy A, Refaie HF, El-Diasty T. Bladder cancer: diagnosis with diffusion-weighted MR imaging in patients with gross hematuria. Radiology. 2009;251:415–421.
    1. El-Assmy A, Abou-El-Ghar ME, Mosbah A, et al. Bladder tumour staging: comparison of diffusion-and T2-weighted MR imaging. Eur Radiol. 2009;19:1575–1581.
    1. Takeuchi M, Sasaki S, Ito M, et al. Urinary bladder cancer: diffusion-weighted MR imaging–accuracy for diagnosing T stage and estimating histologic grade. Radiology. 2009;251:112–121.
    1. Avcu S, Koseoglu MN, Ceylan K, Bulut MD, Dbulutand M, Unal O. The value of diffusion-weighted MRI in the diagnosis of malignant and benign urinary bladder lesions. Br J Radiol. 2011;84:875–882.
    1. Kobayashi S, Koga F, Yoshida S, et al. Diagnostic performance of diffusion-weighted magnetic resonance imaging in bladder cancer: potential utility of apparent diffusion coefficient values as a biomarker to predict clinical aggressiveness. Eur Radiol. 2011;21:2178–2186.
    1. Takeuchi M, Suzuki T, Sasaki S, et al. Clinicopathologic significance of high signal intensity on diffusion-weighted MR imaging in the ureter, urethra, prostate and bone of patients with bladder cancer. Acad Radiol. 2012;19:827–833.
    1. El-Assmy A, Abou-El-Ghar ME, Refaie HF, Mosbah A, El-Diasty T. Diffusion-weighted magnetic resonance imaging in follow-up of superficial urinary bladder carcinoma after transurethral resection: initial experience. BJU Int. 2012;110:e622–e627.
    1. 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.
    1. Thormer G, Otto J, Reiss-Zimmermann M, et al. Diagnostic value of ADC in patients with prostate cancer: influence of the choice of b values. Eur Radiol. 2012;22:1820–1828.
    1. Rosenkrantz AB, Mannelli L, Kong X, et al. Prostate cancer: utility of fusion of T2-weighted and high b-value diffusion-weighted images for peripheral zone tumor detection and localization. J Magn Reson Imaging. 2011;34:95–100.
    1. Hoeks CMA, Barentsz JO, Hambrock T, et al. Prostate cancer: multiparametric MR imaging for detection, localization, and staging. Radiology. 2011;261:46–66.
    1. Pang Y, Turkbey B, Bernardo M, et al. Intravoxel incoherent motion MR imaging for prostate cancer: an evaluation of perfusion fraction and diffusion coefficient derived from different b-value combinations. Magn Reson Med. 2013;69:553–562.
    1. Mazaheri Y, Vargas HA, Akin O, Goldman DA, Hricak H. Reducing the influence of b-value selection on diffusion-weighted imaging of the prostate: evaluation of a revised monoexponential model within a clinical setting. J Magn Reson Imaging. 2012;35:660–668.
    1. Rosenkrantz AB, Sigmund EE, Johnson G, et al. Prostate cancer: feasibility and preliminary experience of a diffusional kurtosis model for detection and assessment of aggressiveness of peripheral zone cancer. Radiology. 2012;264:126–135.
    1. Oto A, Yang C, Kayhan A, et al. Diffusion-weighted and dynamic contrast-enhanced MRI of prostate cancer: correlation of quantitative MR parameters with Gleason score and tumor angiogenesis. AJR Am J Roentgenol. 2011;197:1382–1390.
    1. Nagarajan R, Margolis D, Raman S, et al. Correlation of Gleason scores with diffusion-weighted imaging findings of prostate cancer. Adv Urol. 2012;(2012):374805.
    1. Litjens GJS, Hambrock T, Hulsbergen-van de Kaa C, Barentsz JO, Huisman HJ. Interpatient variation in normal peripheral zone apparent diffusion coefficient: effect on the prediction of prostate cancer aggressiveness. Radiology. 2012;265:260–266.
    1. Busard MPH, Mijatovic V, van Kuijk C, Pieters-van den Bos IC, Hompes PGA, van Waesberghe JHTM. Magnetic resonance imaging in the evaluation of (deep infiltrating) endometriosis: the value of diffusion-weighted imaging. J Magn Reson Imaging. 2010;32:1003–1009.
    1. Inada Y, Matsuki M, Nakai G, et al. Body diffusion-weighted MR imaging of uterine endometrial cancer: is it helpful in the detection of cancer in nonenhanced MR imaging? Eur J Radiol. 2009;70:122–127.
    1. Chen J, Zhang Y, Liang B, Yang Z. The utility of diffusion-weighted MR imaging in cervical cancer. Eur J Radiol. 2010;74:e101–e106.
    1. Hoogendam JP, Klerkx WM, de Kort GAP, et al. The influence of the b-value combination on apparent diffusion coefficient based differentiation between malignant and benign tissue in cervical cancer. J Magn Reson Imaging. 2010;32:376–382.
    1. Thomassin-Naggara I, Toussaint I, Perrot N, et al. Characterization of complex adnexal masses: value of adding perfusion-and diffusion-weighted MR imaging to conventional MR imaging. Radiology. 2011;258:793–803.
    1. Thoeny HC, Forstner R, De Keyzer F. Genitourinary applications of diffusion-weighted MR imaging in the pelvis. Radiology. 2012;263:326–342.
    1. Sala E, Priest AN, Kataoka M, et al. Apparent diffusion coefficient and vascular signal fraction measurements with magnetic resonance imaging: feasibility in metastatic ovarian cancer at 3 Tesla: technical development. Eur Radiol. 2010;20:491–496.
    1. Sala E, Kataoka MY, Priest AN, et al. Advanced ovarian cancer: multiparametric MR imaging demonstrates response-and metastasis-specific effects. Radiology. 2012;263:149–159.
    1. Tang L, Zhang X-P, Sun Y-S, et al. Gastrointestinal stromal tumors treated with imatinib mesylate: apparent diffusion coefficient in the evaluation of therapy response in patients. Radiology. 2011;258:729–738.
    1. Avcu S, Arslan H, Unal O, Kotan C, Izmirli M. The role of diffusion-weighted MR imaging and ADC values in the diagnosis of gastric tumors. JBR-BTR. 2012;95:1–5.
    1. Sakurada A, Takahara T, Kwee TC, et al. Diagnostic performance of diffusion-weighted magnetic resonance imaging in esophageal cancer. Eur Radiol. 2009;19:1461–1469.
    1. Aoyagi T, Shuto K, Okazumi S, et al. Apparent diffusion coefficient correlation with oesophageal tumour stroma and angiogenesis. Eur Radiol. 2012;22:1172–1177.
    1. Oussalah A, Laurent V, Bruot O, et al. Diffusion-weighted magnetic resonance without bowel preparation for detecting colonic inflammation in inflammatory bowel disease. Gut. 2010;59:1056–1065.
    1. Kiryu S, Dodanuki K, Takao H, et al. Free-breathing diffusion-weighted imaging for the assessment of inflammatory activity in Crohn’s disease. J Magn Reson Imaging. 2009;29:880–886.
    1. Kilickesmez O, Atilla S, Bayramoglu S, Gurmen N. Diffusion-weighted imaging of the rectosigmoid colon. J Comput Assist Tomogr. 2009;33:863–866.
    1. Kılıckesmez O, Soylu A, Yaşar N, et al. Is quantitative diffusion-weighted MRI a reliable method in the assessment of the inflammatory activity in ulcerative colitis? Diag interv Radiol. 2010;16:293–298.
    1. Ichikawa T, Erturk SM, Motosugi U, et al. High-B-value diffusion-weighted MRI in colorectal cancer. AJR Am J Roentgenol. 2006;187:181–184.
    1. Hosonuma T, Tozaki M, Ichiba N, et al. Clinical usefulness of diffusion-weighted imaging using low and high b-values to detect rectal cancer. Magn Reson Med. 2006;5:173–177.
    1. Yoshikawa T, Kawamitsu H, Mitchell DG, et al. ADC measurement of abdominal organs and lesions using parallel imaging technique. AJR Am J Roentgenol. 2006;187:1521–1530.
    1. Schoennagel BP, Habermann CR, Roesch M, et al. Diffusion-weighted imaging of the healthy pancreas: apparent diffusion coefficient values of the normal head, body, and tail calculated from different sets of b-values. J Magn Reson Imaging. 2011;34:861–865.
    1. Wiggermann P, Grützmann R, Weissenbock A, Kamusella P, Dittert D-D, Stroszczynski C. Apparent diffusion coefficient measurements of the pancreas, pancreas carcinoma, and mass-forming focal pancreatitis. Acta Radiol. 2012;53:135–139.
    1. Kamisawa T, Takuma K, Anjiki H, et al. Differentiation of autoimmune pancreatitis from pancreatic cancer by diffusion-weighted MRI. Am J Gastroenterol. 2010;105:1870–1875.
    1. Ichikawa T, Erturk SM, Motosugi U, et al. High-b value diffusion-weighted MRI for detecting pancreatic adenocarcinoma: preliminary results. AJR Am J Roentgenol. 2007;188:409–414.
    1. Fukukura Y, Takumi K, Kamimura K, et al. Pancreatic adenocarcinoma: variability of diffusion-weighted MR imaging findings. Radiology. 2012;263:732–740.
    1. Mottola JC, Sahni VA, Erturk SM, Swanson R, Banks PA, Mortele KJ. Diffusion-weighted MRI of focal cystic pancreatic lesions at 3.0-Tesla: preliminary results. Abdom Imaging. 2012;37:110–117.
    1. Klauss M, Lemke A, Grunberg K, et al. Intravoxel incoherent motion MRI for the differentiation between mass forming chronic pancreatitis and pancreatic carcinoma. Invest Radiol. 2011;46:57–63.
    1. Lemke A, Laun FB, Klauss M, et al. 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.
    1. Kartalis N, Lindholm TL, Aspelin P, Permert J, Albiin N. Diffusion-weighted magnetic resonance imaging of pancreas tumours. Eur Radiol. 2009;19:1981–1990.
    1. Brenner R, Metens T, Bali M, Demetter P, Matos C. Pancreatic neuroendocrine tumor: added value of fusion of T2-weighted imaging and high b-value diffusion-weighted imaging for tumor detection. Eur J Radiol. 2012;81:e746–e749.
    1. Holzapfel K, Bruegel M, Eiber M, et al. Characterization of small (≤10 mm) focal liver lesions: value of respiratory-triggered echo-planar diffusion-weighted MR imaging. Eur J Radiol. 2010;76:89–95.
    1. Kim DJ, Yu J-S, Kim JH, Chung J-J, Kim KW. Small hypervascular hepatocellular carcinomas: value of diffusion-weighted imaging compared with “washout” appearance on dynamic MRI. Br J Radiol. 2012;85:e879–e886.
    1. Le Moigne F, Durieux M, Bancel B, et al. Impact of diffusion-weighted MR imaging on the characterization of small hepatocellular carcinoma in the cirrhotic liver. Magn Reson Imaging. 2012;30:656–665.
    1. Park M-S, Kim S, Patel J, et al. Hepatocellular carcinoma: detection with diffusion-weighted versus contrast-enhanced magnetic resonance imaging in pretransplant patients. Hepatology. 2012;56:140–148.
    1. Bruegel M, Holzapfel K, Gaa J, et al. Characterization of focal liver lesions by ADC measurements using a respiratory triggered diffusion-weighted single-shot echo-planar MR imaging technique. Eur Radiol. 2008;18:477–485.
    1. Bonekamp S, Corona-Villalobos CP, Kamel IR. Oncologic applications of diffusion-weighted MRI in the body. J Magn Reson Imaging. 2012;35:257–279.
    1. Parikh T, Drew SJ, Lee VS, et al. Focal liver lesion detection and characterization with diffusion-weighted MR imaging: comparison with standard breath-hold T2-weighted imaging. Radiology. 2008;246:812–822.
    1. 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.
    1. Donati F, Boraschi P, Gigoni R, Salemi S, Falaschi F, Bartolozzi C. Focal nodular hyperplasia of the liver: diffusion and perfusion MRI characteristics. Magn Reson Imaging. 2013;1:10–16.
    1. Agnello F, Ronot M, Valla DC, Sinkus R, Van Beers BE, Vilgrain V. High-b-value diffusion-weighted MR imaging of benign hepatocellular lesions: quantitative and qualitative analysis. Radiology. 2012;262:511–519.
    1. Luciani A, Vignaud A, Cavet M, et al. Liver cirrhosis: intravoxel incoherent motion MR imaging–pilot study. Radiology. 2008;249:891–899.
    1. 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.
    1. Nasu K, Kuroki Y, Tsukamoto T, Nakajima H, Mori K, Minami M. Diffusion-weighted imaging of surgically resected hepatocellular carcinoma: imaging characteristics and relationship among signal intensity, apparent diffusion coefficient, and histopathologic grade. AJR Am J Roentgenol. 2009;193:438–444.
    1. Li SP, Padhani AR. Tumor response assessments with diffusion and perfusion MRI. J Magn Reson Imaging. 2012;35:745–763.

Source: PubMed

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