3D MRA visualization and artery-vein separation using blood-pool contrast agent MS-325.

RATIONALE AND OBJECTIVESMagnetic resonance angiography (MRA) is establishedas an important complementary technique to conventionalangiography, and contrast–enhanced MRA (CE-MRA)offers even higher contrast between the vascular lumenand surrounding structures. MS-325 is a gadolinium-basedMR contrast agent designed specifically for blood-poolimaging, or MRA, and is the only gadolinium-based intra-vascular contrast agent undergoing trials in humans. MS-325 provides excellent vascular and selective arterial en-hancement during dynamic MRA. The long blood resi-dence time also allows acquisition of steady-state imagesof the arteries and veins with excellent spatial resolution(1,2).With the increasing use of CE-MRA, venous contami-nation of arterial images becomes a common concern (ie,venous enhancement may confound the visualization ofarteries). Currently available viewing techniques, such astargeted maximum intensity projection, multiplanar refor-mation, and “fly through” used in virtual endoscopy, canbe used only to minimize this problem but not to solve it(3,4). These techniques are also time intensive and requiremore operators. Although the ability to acquire dynamicimages may facilitate artery-vein separation by providingan artery mask that can be applied to steady-state images,this approach requires motion correction and image regis-tration between dynamic and steady-state images.The separation of artery and vein is of significant im-portance to correctly diagnose and treat peripheral vascu-lar diseases. The strategies for artery-vein separation in-clude both acquisition methods and postprocessing tech-niques. Among the current developments, acquisitionmethods include phase-contrast and time-resolved acquisi-tion approaches (5–7), and postprocessing techniquescover correlation analysis and graph searching methods(8–10). The shortcomings of these approaches are thelimitations of their applications and the costs. For in-stance, phase-contrast acquisition approaches (5) are lim-ited to cases in which the blood flow directions in arteryand vein are opposite to each other. In the time-resolvedacquisition approaches (6,7), the image must be acquiredduring the first pass of a contrast agent or accomplishedwith cardiac gating. Correlation analysis (8) requiresseven or eight MRA data sets in a single breath hold fora three-dimensional (3D) angiogram of the lung. In graphsearching approaches (9), the node costs require 3D edgestrength and a model of preferred branch direction. Theenhanced artery visualization method (10) is limited tothe segmentation of a small number of the main overlap-ping veins in the peripheral vasculature. Clearly, a moregeneral approach for artery-vein separation is desirable.MATERIALS AND METHODS

[1]  R. Dolan,et al.  MS-325: albumin-targeted contrast agent for MR angiography. , 1998, Radiology.

[2]  D M Shames,et al.  Mammary carcinoma model: correlation of macromolecular contrast-enhanced MR imaging characterizations of tumor microvasculature and histologic capillary density. , 1996, Radiology.

[3]  J A SCHILLING,et al.  Studies of fibroplasia in wound healing. , 1953, Surgery, gynecology & obstetrics.

[4]  T. Hunt,et al.  Time line of wound healing. , 1998, Clinics in podiatric medicine and surgery.

[5]  E M Haacke,et al.  Coronary MR angiography. , 1999, Magnetic resonance imaging clinics of North America.

[6]  Max A. Viergever,et al.  Enhanced Artery Visualization in Blood Pool MRA: Results in the Peripheral Vasculature , 1999, IPMI.

[7]  Supun Samarasekera,et al.  Fuzzy Connectedness and Object Definition: Theory, Algorithms, and Applications in Image Segmentation , 1996, CVGIP Graph. Model. Image Process..

[8]  Jie Tian,et al.  Automatic clutter-free volume rendering for MR angiography using fuzzy connectedness , 1997, Medical Imaging.

[9]  D M Shames,et al.  Quantification of tissue gadolinium concentration using magnetic resonance imaging: comparison of ultrashort inversion time inversion recovery echoplanar and dynamic three-dimensional spoiled gradient-recalled approaches with in vitro measurements. , 1996, Academic radiology.

[10]  J. Udupa,et al.  A new computer-assisted method for the quantification of enhancing lesions in multiple sclerosis. , 1997, Journal of computer assisted tomography.

[11]  Claudio Gatti,et al.  Vascular visualization using IAP , 1999, Medical Imaging.

[12]  J K Udupa,et al.  Computer-assisted quantitation of enhancing lesions in multiple sclerosis: correlation with clinical classification. , 1997, AJNR. American journal of neuroradiology.

[13]  Ridgway Pf Tumours : wounds that do not heal. , 2002 .

[14]  G L Wolf,et al.  Relaxation of water protons in the intra‐ and extracellular regions of blood containing Gd(DTPA) , 1986, Magnetic resonance in medicine.

[15]  J K Udupa,et al.  Relapsing-remitting multiple sclerosis: longitudinal analysis of MR images--lack of correlation between changes in T2 lesion volume and clinical findings. , 1999, Radiology.

[16]  Jayaram K. Udupa,et al.  Scale-Based Fuzzy Connected Image Segmentation: Theory, Algorithms, and Validation , 2000, Comput. Vis. Image Underst..

[17]  Dewey Odhner,et al.  3DVIEWNIX: an open, transportable, multidimensional, multimodality, multiparametric imaging software system , 1994, Medical Imaging.

[18]  A de Roos,et al.  Equilibrium phase MR angiography of the aortic arch and abdominal vasculature with the blood pool contrast agent CMD‐A2‐Gd‐DOTA in pigs , 1999, Journal of magnetic resonance imaging : JMRI.

[19]  J. K. Udupa,et al.  Shell rendering : Graphics in medicine , 1993 .

[20]  Yutaka Hata,et al.  Automatic segmentation of blood vessels from MR angiography volume data by using fuzzy logic technique , 1999, Medical Imaging.

[21]  R J van der Geest,et al.  Infarcted myocardium in pigs: MR imaging enhanced with slow-interstitial-diffusion gadolinium compound P760. , 1999, Radiology.

[22]  J K Udupa,et al.  Comparison of T2 lesion volume and magnetization transfer ratio histogram analysis and of atrophy and measures of lesion burden in patients with multiple sclerosis. , 1998, AJNR. American journal of neuroradiology.

[23]  Jayaram K. Udupa,et al.  Shell rendering , 1993, IEEE Computer Graphics and Applications.

[24]  R. Ross The pathogenesis of atherosclerosis: a perspective for the 1990s , 1993, Nature.

[25]  J K Udupa,et al.  Differences between relapsing-remitting and chronic progressive multiple sclerosis as determined with quantitative MR imaging. , 1999, Radiology.

[26]  V. Fuster,et al.  The pathogenesis of coronary artery disease and the acute coronary syndromes (1). , 1992, The New England journal of medicine.

[27]  Stina Svensson,et al.  Gray-scale connectivity concept for visualizing MRA and CTA volumes , 1999, Medical Imaging.

[28]  T J Brady,et al.  Ferrite particles: a superparamagnetic MR contrast agent for the reticuloendothelial system. , 1987, Radiology.

[29]  Jayaram K. Udupa,et al.  Fuzzy connected object definition in images with respect to co-objects , 1999, Medical Imaging.

[30]  H. Dvorak Tumors: wounds that do not heal. Similarities between tumor stroma generation and wound healing. , 1986, The New England journal of medicine.

[31]  V M Runge,et al.  Contrast‐enhanced MR angiography , 1993, Journal of magnetic resonance imaging : JMRI.

[32]  D C Peters,et al.  Steady-state and dynamic MR angiography with MS-325: initial experience in humans. , 1998, Radiology.

[33]  Jayaram K. Udupa,et al.  3D MR angiographic visualization and artery-vein separation , 1999, Medical Imaging.

[34]  M. Ogan,et al.  Albumin labeled with Gd-DTPA: an intravascular contrast-enhancing agent for magnetic resonance blood pool imaging: preparation and characterization. , 1987, Investigative radiology.

[35]  Supun Samarasekera,et al.  Multiple sclerosis lesion quantification using fuzzy-connectedness principles , 1997, IEEE Transactions on Medical Imaging.

[36]  H. Bosmans,et al.  [Contrast-enhanced magnetic resonance angiography]. , 1999 .

[37]  J. Reiber,et al.  Scan optimization of gadolinium contrast-enhanced three-dimensional MRA of peripheral arteries with multiple bolus injections and in vitro validation of stenosis quantification. , 1999, Magnetic resonance imaging.

[38]  D. Hemmy,et al.  A Pentium Personal Computer‐Based Craniofacial Three‐Dimensional Imaging and Analysis System , 1997, The Journal of craniofacial surgery.

[39]  R. Brasch,et al.  Quantification of liver blood volume: comparison of ultra short ti inversion recovery echo planar imaging (ulstir‐epi), with dynamic 3d‐gradient recalled echo imaging , 1995, Magnetic resonance in medicine.

[40]  Isabelle Raynal,et al.  Physical, chemical, and biological evaluations of P760: A new gadolinium complex characterized by a low rate of interstitial diffusion , 2000, Journal of magnetic resonance imaging : JMRI.

[41]  J F Debatin,et al.  Human aorta: preliminary results with virtual endoscopy based on three-dimensional MR imaging data sets. , 1996, Radiology.

[42]  D M Shames,et al.  Measurement of capillary permeability to macromolecules by dynamic magnetic resonance imaging: A quantitative noninvasive technique , 1993, Magnetic resonance in medicine.

[43]  M R Prince,et al.  Optimizing three-dimensional gadolinium-enhanced magnetic resonance angiography. Original investigation. , 1998, Investigative radiology.

[44]  Jayaram K. Udupa,et al.  Scale-based fuzzy connectivity: a novel image segmentation methodology and its validation , 1999, Medical Imaging.

[45]  K. Williams,et al.  Atherosclerosis--an inflammatory disease. , 1999, The New England journal of medicine.

[46]  T. K. Hunt,et al.  Time line of wound healing. , 1998, Clinics in podiatric medicine and surgery.

[47]  P. Edwards,et al.  Atherosclerosis: basic mechanisms. Oxidation, inflammation, and genetics. , 1995, Circulation.