Magnetic resonance angiography: a review

A Fully Automated Method for Segmenting Arteries and Quantifying Vessel Radii on Magnetic Resonance Angiography Images of Varying Projection Thickness

PURPOSE

Precise quantification of cerebral arteries can help with differentiation and prognostication of cerebrovascular disease. Existing image processing and segmentation algorithms for magnetic resonance angiography (MRA) are limited to the analysis of either 2D maximum intensity projection images or the entire 3D volume. The goal of this study was to develop a fully automated, hybrid 2D-3D method for robust segmentation of arteries and accurate quantification of vessel radii using MRA at varying projection thicknesses.

METHODS

A novel algorithm that employs an adaptive Frangi filter for segmentation of vessels followed by estimation of vessel radii is presented. The method was evaluated on MRA datasets and corresponding manual segmentations from three healthy subjects for various projection thicknesses. In addition, the vessel metrics were computed in four additional subjects. Three synthetically generated angiographic datasets resembling brain vasculature were also evaluated under different noise levels. Dice similarity coefficient, Jaccard Index, F-score, and concordance correlation coefficient were used to measure the segmentation accuracy of manual versus automatic segmentation.

RESULTS

Our new adaptive filter rendered accurate representations of vessels, maintained accurate vessel radii, and corresponded better to manual segmentation at different projection thicknesses than prior methods. Validation with synthetic datasets under low contrast and noisy conditions revealed accurate quantification of vessels without distortions.

CONCLUSION

We have demonstrated a method for automatic segmentation of vascular trees and the subsequent generation of a vessel radii map. This novel technique can be applied to analyze arterial structures in healthy and diseased populations and improve the characterization of vascular integrity.

Sensing lanthanide metal content in biological tissues with magnetic resonance spectroscopy

The development and validation of MRI contrast agents consisting of a lanthanide chelate often requires a determination of the concentration of the agent in ex vivo tissue. We have developed a protocol that uses 70% nitric acid to completely digest tissue samples that contain Gd(III), Dy(III), Tm(III), Eu(III), or Yb(III) ions, or the MRI contrast agent gadodiamide. NMR spectroscopy of coaxial tubes containing a digested sample and a separate control solution of nitric acid was used to rapidly and easily measure the bulk magnetic susceptibility (BMS) shift caused by each lanthanide ion and gadodiamide. Each BMS shift was shown to be linearly correlated with the concentration of each lanthanide ion and gadodiamide in the 70% nitric acid solution and in digested rat kidney and liver tissues. These concentration measurements had outstanding precision, and also had good accuracy for concentrations ≥10 mM for Tm(III) Eu(III), and Yb(III), and ≥3 mM for Gd(III), gadodiamide, and Dy(III). Improved sample handling methods are needed to improve measurement accuracy for samples with lower concentrations.

A fast and fully automatic method for cerebrovascular segmentation on time-of-flight (TOF) MRA image

The precise three-dimensional (3-D) segmentation of cerebral vessels from magnetic resonance angiography (MRA) images is essential for the detection of cerebrovascular diseases (e.g., occlusion, aneurysm). The complex 3-D structure of cerebral vessels and the low contrast of thin vessels in MRA images make precise segmentation difficult. We present a fast, fully automatic segmentation algorithm based on statistical model analysis and improved curve evolution for extracting the 3-D cerebral vessels from a time-of-flight (TOF) MRA dataset. Cerebral vessels and other tissue (brain tissue, CSF, and bone) in TOF MRA dataset are modeled by Gaussian distribution and combination of Rayleigh with several Gaussian distributions separately. The region distribution combined with gradient information is used in edge-strength of curve evolution as one novel mode. This edge-strength function is able to determine the boundary of thin vessels with low contrast around brain tissue accurately and robustly. Moreover, a fast level set method is developed to implement the curve evolution to assure high efficiency of the cerebrovascular segmentation. Quantitative comparisons with 10 sets of manual segmentation results showed that the average volume sensitivity, the average branch sensitivity, and average mean absolute distance error are 93.6%, 95.98%, and 0.333 mm, respectively. By applying the algorithm to 200 clinical datasets from three hospitals, it is demonstrated that the proposed algorithm can provide good quality segmentation capable of extracting a vessel with a one-voxel diameter in less than 2 min. Its accuracy and speed make this novel algorithm more suitable for a clinical computer-aided diagnosis system.

A review on MR vascular image processing algorithms: acquisition and prefiltering: part I

Vascular segmentation has recently been given much attention. This review paper has two parts. Part I focuses on the physics of magnetic resonance angiography (MRA) generation and prefiltering techniques applied to MRA data sets. Part II of the review focuses on the vessel segmentation algorithms. The first section of this paper introduces the five different sets of receive coils used with the MRI system for magnetic resonance angiography data acquisition. This section then presents the five different types of the most popular data acquisition techniques: time-of-flight (TOF), phase-contrast, contrast-enhanced, black-blood, T2-weighted, and T2*-weighted, along with their pros and cons. Section II of this paper focuses on prefiltering algorithms for MRA data sets. This is necessary for removing the background nonvascular structures in the MRA data sets. Finally, the paper concludes with a clinical discussion on the challenges and the future of the data acquisition and the automated filtering algorithms.

Pediatric magnetic resonance imaging techniques

Optimization of the MR image requires an understanding of technical parameters, pulse sequences, artifacts, and the use of contrast agents. More technical information and in-depth details about the practical concepts for performing MRI in children can be found in the references accompanying this article.

Gray-scale skeletonization of small vessels in magnetic resonance angiography

Interpretation of magnetic resonance angiography (MRA) is problematic due to complexities of vascular shape and to artifacts such as the partial volume effect. We present new methods to assist in the interpretation of MRA. These include methods for detection of vessel paths and for determination of branching patterns of vascular trees. They are based on the ordered region growing (ORG) algorithm that represents the image as an acyclic graph, which can be reduced to a skeleton by specifying vessel endpoints or by a pruning process. Ambiguities in the vessel branching due to vessel overlap are effectively resolved by heuristic methods that incorporate a priori knowledge of bifurcation spacing. Vessel paths are detected at interactive speeds on a 500-MHz processor using vessel endpoints. These methods apply best to smaller vessels where the image intensity peaks at the center of the lumen which, for the abdominal MRA, includes vessels whose diameter is less than 1 cm.

Accuracy of normal-dose contrast-enhanced MR angiography in assessing renal artery stenosis and accessory renal arteries

OBJECTIVE

The purpose of this study was to evaluate the accuracy of breath-hold contrast-enhanced MR angiography in the assessment of renal artery stenosis and accessory renal arteries using a standard dose of gadolinium.

SUBJECTS AND METHODS

Thirty-eight patients suspected of having renal artery stenosis underwent MR angiography and intraarterial digital subtraction angiography, which was the method of reference. Three-dimensional gradient-echo MR subtraction angiography (TR/TE, 5.8/1.8 msec) was performed on a 1.5-T imager using a phased array body coil. Before imaging, a separate timing bolus sequence was used, administering 1.0 ml of contrast agent. Gadopentetate dimeglumine (15 ml) was injected using an MR power injector. Two observers, who were unaware of each other's interpretation and of MR findings, assessed digital subtraction angiography. Likewise, two other observers assessed MR angiography.

RESULTS

Digital subtraction angiography depicted 75 main and 17 accessory renal arteries (n = 92). All main renal arteries and 13 accessory renal arteries were identified on MR angiography. Compared with digital subtraction angiography, MR imaging correctly classified 57 of 66 arteries without a hemodynamically significant stenosis (0-49%), 22 of 22 arteries as significantly stenotic (50-99%), and four of four occluded arteries; five stenoses were overestimated. There was one false-positive finding of an accessory renal artery on MR angiography that was identified retrospectively on digital subtraction angiography. Interobserver agreement was high. Sensitivity and specificity for grading significant stenosis were 100% and 85%, respectively.

CONCLUSION

Contrast-enhanced MR angiography, using +/-0.1 mmol/kg of gadolinium, is an accurate method in the assessment of renal artery stenosis and accessory renal arteries.

Radiology at the turn of the millennium

Herein, the authors (a) review the status of the specialty; (b) report and analyze the various areas in which progress has occurred, namely, conventional radiology and picture archiving and communication systems (or PACS), ultrasonography, computed tomography, magnetic resonance imaging, interventional radiology, and nuclear medicine; and (c) discuss the problems radiology faces as it enters the new millennium. The problems are those facing medicine as a whole, as well as those threatening the future of radiology. These include the following: Will there be a need for radiologists in the future? Will radiology be too costly to be affordable? How can turf wars and fragmentation be solved? Possible remedies are suggested. Positive aspects are discussed in the light of the challenge to demonstrate value. Medical imaging is entering the new millennium with a solid record of recent advances in digital, cross-sectional, and interventional radiology. These advances have made the specialty indispensable in the treatment of patients. Careful statesmanship will be needed to solve the many problems that face medicine as a whole and radiology in particular.