Aortic dissection: magnetic resonance imaging

Fifteen patients with suspected or known aortic dissection were imaged with magnetic resonance (MR). Thirteen of these patients were eventually shown to have dissection. In most instances the diagnosis was established by aortography and/or computed tomography (CT) prior to the MR study. Surgical proof (6/13) and/or aortographic proof (10/13) were available in 11/13 patients with aortic dissection. MR demonstrated the intimal flap and determined whether the dissection was type A or type B. In addition, MR: differentiated between the true and false lumens; determined the origins of the celiac, superior mesenteric, and renal arteries from the true or false lumen in the cases where the dissection extended into the abdominal aorta (8/12); allowed post-surgical surveillance of the dissection; and identified aortoannular ectasia in the three patients who had Marfan syndrome. In addition to the 13 cases with dissection, there were two cases in whom the diagnosis of dissection was excluded by MR. Our early experience suggests that MR can serve as the initial imaging test in clinically suspected cases of aortic dissection and that the information provided by MR is sufficient to manage many cases. Additionally, MR obviates the use of iodinated contrast media.     

Peripheral vascular disease: correlation of MR imaging and angiography

The capability of magnetic resonance (MR) imaging for detecting aortic, iliac, and femoral stenoses and occlusions was evaluated. Multisection spin-echo studies at 0.35 tesla were obtained of the infrarenal aorta to the femoral bifurcation in 24 patients, all of whom had undergone intraarterial angiography within 14 days of imaging. Transaxial MR images were compared with the angiograms. Arterial stenoses and occlusions in these vessels detected by MR imaging correlated with angiographic findings in 91% of the instances. Protrusional atherosclerotic plaques and occlusions and stenoses in the aortoiliac region were demonstrated accurately on MR images; complications of previous vascular surgery, such as aneurysms at sites of previous anastomoses or endarterectomy, were also identified. Due to the limited spatial resolution, MR images failed to demonstrate some femoral stenoses. MR imaging may be used for evaluation of aortoiliac vascular disease and for follow-up study after surgical revascularization. However, the limited spatial resolution, noncomposite display of the aortoiliofemoral circulation, and lack of evaluation of peripheral runoff provided by current MR imaging techniques militate against its replacing angiography prior to vascular intervention.     

Attenuation coefficients of body tissues using principal-components analysis

Principal-components analysis is used to obtain a set of parameters for dual-energy radiography that completely describes the attenuation coefficient of any tissue over a given energy range. These parameters are the weighted averages of the densities of the elements present in a substance. Principal-components (PC) parameters are calculated for several soft tissues from measured attenuation coefficients published by Phelps et al. The calculated PC parameters are compared to the more conventional dual-energy representations of the attenuation coefficient: (1) the electron density/effective atomic number (or Compton/photoelectric) representation and (2) the equivalent water/equivalent aluminum thickness representation. The principal-components parameters represent the attenuation coefficients more accurately, and are more stable than the currently used parameters. In addition, these new parameters are sensitive to differences in the chemical composition and density, whereas the previous representations are primarily sensitive to changes in the density. It is concluded that the principal-components method provides a more sensitive and accurate indicator of changes in tissue composition than previous characterizations of the linear attenuation coefficient. The principal-components method provides a means for improving the accuracy of the characterization of tissues in dual-energy computed tomographic imaging and in dual-energy digital radiography.