Separation of arteries and veins using flow-induced phase effects in contrast-enhanced MRA of the lower extremities

In vivo identification of arteries and veins using two-photon excitation elastin autofluorescence

Distinguishing arteries from veins in vivo has a great significance in clinical practices and preclinical studies. Optical imaging methods such as two-photon microscopy can provide high-resolution morphological information of tissue and are therefore extremely suitable for imaging small blood vessels. However, few optical imaging methods allow in vivo identification of arteries and veins merely utilizing the autofluorescence signal of blood vessels. In this report, we found the arterial wall generates a remarkably stronger two-photon excitation autofluorescence (TPEA) signal compared with the venous wall based on BALB/c mice. According to histological analysis and fluorescence characteristic measurement, the contrast signal is confirmed to be from elastin fibers. Employing this unique feature, we propose an objective and effective artery-vein separation strategy that considers the presence of the elastin-TPEA border as the indicator of arteries. Using this strategy, the arterial and venous networks of the dorsal skin and cerebral cortex of BALB/c mice are demonstrated to be excellently mapped and accurately separated in vivo without depending on any exogenous contrast agent, empirical knowledge, and algorithm. This study may provide a novel technique for mapping arterial and venous networks for anatomic research as well as an extra aid to basic researches on the mechanism, diagnosis, and treatment of blood vessel-related diseases.

Time-resolved MR angiography of the legs at 3 T using a low dose of gadolinium: initial experience and contrast dynamics

OBJECTIVE

This article describes our initial clinical experience with time-resolved MR angiography (MRA) of the legs using the time-resolved imaging with stochastic trajectories (TWIST) technique with a half dose of gadolinium.

MATERIALS AND METHODS

Thirty-four patients underwent a TWIST examination of the legs at 3 T. Thirty-three patients also underwent a bolus-chase MRA examination in the same setting. Times elapsed between the start of contrast injection and the appearance of contrast material (t(A)) and peak enhancement of the arteries in the legs (t(B)) were analyzed. The number of patients with examinations affected by venous contamination was determined. The differences in t(A) and t(B) between cases in which venous contamination was present or absent were evaluated using a two-tailed Student t test.

RESULTS

The TWIST technique using a half dose of gadolinium provided diagnostic-quality images of all patients. The mean t(A) was 35.5 ± 8.8 (SD) seconds (range, 17.8-60.4 seconds), and the mean t(B) was 59.1 ± 15.1 seconds (range, 31-98.8 seconds). Venous contamination was observed in bolus-chase MRA images of 52.9% of patients. The relationship between venous contamination and t(A) was not statistically significant (p = 0.13). The incidence of venous contamination was higher in patients with lower values of t(B) (p = 0.01).

CONCLUSION

The described low-dose clinical experience with TWIST and the contrast dynamics information gained from this study could aid radiologists in planning protocols for leg MRA examinations.

Simultaneous automatic arteries-veins separation and cerebral blood flow imaging with single-wavelength laser speckle imaging

Automatic separation of arteries and veins in optical cerebral cortex images is important in clinical practice and preclinical study. In this paper, a simple but effective automatic artery-vein separation method which utilizes single-wavelength coherent illumination is presented. This method is based on the relative temporal minimum reflectance analysis of laser speckle images. The validation is demonstrated with both theoretic simulations and experimental results applied to the rat cortex. Moreover, this method can be combined with laser speckle contrast analysis so that the artery-vein separation and blood flow imaging can be simultaneously obtained using the same raw laser speckle images data to enable more accurate analysis of changes of cerebral blood flow within different tissue compartments during functional activation, disease dynamic, and neurosurgery, which may broaden the applications of laser speckle imaging in biology and medicine.

Separation of arteries and veins in the cerebral cortex using physiological oscillations by optical imaging of intrinsic signal

An automated method is presented for artery-vein separation in cerebral cortical images recorded with optical imaging of the intrinsic signal. The vessel-type separation method is based on the fact that the spectral distribution of intrinsic physiological oscillations varies from arterial regions to venous regions. In arterial regions, the spectral power is higher in the heartbeat frequency (HF), whereas in venous regions, the spectral power is higher in the respiration frequency (RF). The separation method was begun by extracting the vascular network and its centerline. Then the spectra of the optical intrinsic signals were estimated by the multitaper method. A standard F-test was performed on each discrete frequency point to test the statistical significance at the given level. Four periodic physiological oscillations were examined: HF, RF, and two other eigenfrequencies termed F1 and F2. The separation of arteries and veins was implemented with the fuzzy c-means clustering method and the region-growing approach by utilizing the spectral amplitudes and power-ratio values of the four eigenfrequencies on the vasculature. Subsequently, independent spectral distributions in the arteries, veins, and capillary bed were estimated for comparison, which showed that the spectral distributions of the intrinsic signals were very distinct between the arterial and venous regions.

Basics of Magnetic Resonance Imaging and Magnetic Resonance Spectroscopy

In this chapter, the basic principles of magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) (Sects. 2.2, 2.3, and 2.4), the technical components of the MRI scanner (Sect. 2.5), and the basics of contrast agents and the application thereof (Sect. 2.6) are described. Furthermore, flow phenomena and MR angiography (Sect. 2.7) as well as diffusion and tensor imaging (Sect. 2.7) are elucidated.

The utility of superparamagnetic contrast agents in MRI: theoretical consideration and applications in the cardiovascular system

This review will discuss the in vivo physical chemical relaxation properties of superparamagnetic iron oxide particles. Various parameters such as size, magnetization, compartmentalization and water exchange effects and how these alter the behavior of the iron oxide particles in an in vitro vs an in vivo situation with special reference to the cardiovascular system will be exemplified. Furthermore, applications using iron oxide particles for vascular, perfusion and viability imaging as well as assessment of the inflammatory status of a given tissue will be discussed.

Level-set-based artery-vein separation in blood pool agent CE-MR angiograms

Blood pool agents (BPAs) for contrast-enhanced (CE) magnetic-resonance angiography (MRA) allow prolonged imaging times for higher contrast and resolution. Imaging is performed during the steady state when the contrast agent is distributed through the complete vascular system. However, simultaneous venous and arterial enhancement in this steady state hampers interpretation. In order to improve visualization of the arteries and veins from steady-state BPA data, a semiautomated method for artery-vein separation is presented. In this method, the central arterial axis and central venous axis are used as initializations for two surfaces that simultaneously evolve in order to capture the arterial and venous parts of the vasculature using the level-set framework. Since arteries and veins can be in close proximity of each other, leakage from the evolving arterial (venous) surface into the venous (arterial) part of the vasculature is inevitable. In these situations, voxels are labeled arterial or venous based on the arrival time of the respective surface. The evolution is steered by external forces related to feature images derived from the image data and by internal forces related to the geometry of the level sets. In this paper, the robustness and accuracy of three external forces (based on image intensity, image gradient, and vessel-enhancement filtering) and combinations of them are investigated and tested on seven patient datasets. To this end, results with the level-set-based segmentation are compared to the reference-standard manually obtained segmentations. Best results are achieved by applying a combination of intensity- and gradient-based forces and a smoothness constraint based on the curvature of the surface. By applying this combination to the seven datasets, it is shown that, with minimal user interaction, artery-vein separation for improved arterial and venous visualization in BPA CE-MRA can be achieved.