Aortoiliac hemodynamic and morphologic adaptation to chronic spinal cord injury

BackgroundReduced lower limb blood flow and resistive hemodynamic conditions potentially promote aortic inflammation and aneurysmal degeneration. We used abdominal ultrasonography, magnetic resonance imaging, and computational flow modeling to determine the relationship between reduced infrarenal aortic blood flow in chronic spinal cord injury (SCI) subjects and risk for abdominal aortic aneurysm (AAA) disease.MethodsAortic diameter in consecutive SCI subjects (n = 123) was determined via transabdominal ultrasonography. Aortic anatomic and physiologic data were acquired via magnetic resonance angiography (MRA; n = 5) and cine phase-contrast magnetic resonance flow imaging (n = 4) from SCI subjects whose aortic diameter was less than 3.0 cm by ultrasonography. Computational flow models were constructed from magnetic resonance data sets. Results were compared with those obtained from ambulatory control subjects (ultrasonography, n = 129; MRA/phase-contrast magnetic resonance flow imaging, n = 6) who were recruited at random from a larger pool of risk factor–matched individuals without known AAA disease.ResultsAge, sex distribution, and smoking histories were comparable between the SCI and control groups. In the SCI group, time since injury averaged 26 ± 13 years (mean ± SD). Aortic diameter was larger (P < .01), and the prevalence of large (≥2.5 cm; P < .01) or aneurysmal (≥3.0 cm; P < .05) aortas was greater in SCI subjects. Paradoxically, common iliac artery diameters were reduced in SCI subjects (<1.0 cm; 48% SCI vs 26% control; P < .0001). Focal preaneurysmal enlargement was noted in four of five SCI subjects by MRA. Flow modeling revealed normal flow volume, biphasic and reduced oscillatory flow, slower pressure decay, and reduced wall shear stress in the SCI infrarenal aorta.ConclusionsCharacteristic aortoiliac hemodynamic and morphologic adaptations occur in response to chronic SCI. Slower aortic pressure decay and reduced wall shear stress after SCI may contribute to mural degeneration, enlargement, and an increased prevalence of AAA disease

Quantification of vessel wall motion and cyclic strain using cine phase contrast MRI: in vivo validation in the porcine aorta. Magnetic Resonance in Medicine 52

Artery wall motion and strain play important roles in vascular remodeling and may be important in the pathogenesis of vascular disease. In vivo observations of circumferentially nonuniform wall motion in the human aorta suggest that nonuniform strain may contribute to the localization of vascular pathology. A velocity-based method to investigate circumferential strain variations was previously developed and validated in vitro; the current study was undertaken to determine whether accurate displacement and strain fields can be calculated from velocity data acquired in vivo. Wall velocities in the porcine thoracic aorta were quantified with PC-MRI and an implanted coil and were then time-integrated to compute wall displacement trajectories and cyclic strain. Displacement trajectories were consistent with observed aortic wall motion and with the displacements of markers in the aortic wall. The mean difference between velocity-based and marker-based trajectory points was 0.1 mm, relative to an average pixel size of 0.4 mm. Propagation of error analyses based on the precision of the computed displacements were used to demonstrate that 10% strain results in a standard deviation of 3.6%. This study demonstrates that it is feasible to accurately quantify strain from low wall velocities in vivo and that the porcine thoracic aorta does not deform uniformly. Magn Reson Med 52:286 -295, 2004

Biomedical Paper Predictive Medicine: Computational Techniques in Therapeutic Decision-Making

ABSTRACT The current paradigm for surgery planning for the treatment of cardiovascular disease relies exclusively on diagnostic imaging data to define the present state of the patient, empirical data to evaluate the efficacy of prior treatments for similar patients, and the judgement of the surgeon to decide on a preferred treatment. The individual variability and inherent complexity of human biological systems is such that diagnostic imaging and empirical data alone are insufficient to predict the outcome of a given treatment for an individual patient. We propose a new paradigm of predictive medicine in which the physician utilizes computational tools to construct and evaluate a combined anatomic/physiologic model to predict the outcome of alternative treatment plans for an individual patient. The predictive medicine paradigm is implemented in a software system developed for Simulation-Based Medical Planning. This system provides an integrated set of tools to test hypotheses regarding the effect of alternate treatment plans on blood flow in the cardiovascular system of an individual patient. It combines an internet-based user interface developed using Java and VRML, image segmentation, geometric solid modeling, automatic finite element mesh generation, computational fluid dynamics, and scientific visualization techniques. This system is applied to the evaluation of alternate, patient-specific treatments for a case of lower extremity occlusive cardiovascular disease. Comp Aid Surg 4:231–247 (1999). ©1999 Wiley-Liss, Inc