Volume rendering compared with maximum intensity projection for magnetic resonance angiography measurements of the abdominal aorta

Persson, Anders; Dahlström, Nils; Engellau, Lena; Larsson, Elna‐Marie; Brismar, Torkel B.; Smedby, Örjan

doi:10.1080/02841850410006876

Cited by 22 publications

(12 citation statements)

References 15 publications

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“…Because single‐voxel thick reformations show only short vascular segments, maximum intensity projection (MIP) is a useful complementary postprocessing technique for combining information from multiple slices to see longer segments of vessels (99–103). Using MIP, the user specifies the subvolume thickness and obliquity.…”

Section: Postprocessing and Displaymentioning

confidence: 99%

3D contrast‐enhanced MR angiography

Zhang

Maki

Prince

2006

Magnetic Resonance Imaging

138

103

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Safe, fast, accurate contrast arteriography can be obtained utilizing gadolinium (Gd) and 3D MR data acquisition for diagnosing vascular diseases. Optimizing contrast enhanced MRA (CE MRA), however, requires understanding the complex interplay between Gd injection timing, the Fourier mapping of 3D MR data acquisition and a multitude of parameters determining resolution, anatomic coverage, and sensitivity to motion artifacts. It is critical to time the bolus peak to coincide with central k-space data acquisition, which dominates image contrast. Oversampling the center of k-space allows reconstruction of multiple 3D acquisitions in rapid succession to time-resolve the passage of the contrast bolus. Parallel imaging increases resolution, shortens scan time and compresses the center of k-space into a shorter period of time, thereby minimizing motion and timing artifacts. Absence of ionizing radiation allows MRA to be repeated and combined with additional sequences to more fully characterize anatomy, flow, and physiology. Utilizing stepping table technology and thigh compression, whole body MRA is possible with a single contrast injection. As MR technology continues to advance, CE MRA becomes better and simpler to perform, increasing its efficacy in the diagnosis and management of vascular diseases.

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Section: Postprocessing and Displaymentioning

confidence: 99%

3D contrast‐enhanced MR angiography

Zhang

Maki

Prince

2006

Magnetic Resonance Imaging

138

103

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“…While existing methods are limited to applying vessel enhancement filters to either the original non-projected 3D images or a single MIP through the entire imaged volume (Gao et al, 2011;Hsu et al, 2017;Phellan and Forkert, 2017), there has been little investigation of the influence of projection thickness on the effectiveness of vessel segmentation. Of the few studies reported, one showed similarity between vessel radii measurements extracted from parameter-dependent MIP MRA and digital subtraction angiography derived from high contrast x-ray images (Persson et al, 2004). Another group showed that MIP images using a slab thickness of 8 mm are superior in the detection of pulmonary nodules (Kawel et al, 2009).…”

Section: Introductionmentioning

confidence: 98%

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

et al. 2020

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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.

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“…In a material of 20 patients previously examined with gadolinium-enhanced MRA and with DSA for abdominal aortic aneurysm, rendering of MRA 3D datasets was performed with three new techniques for standardized TF. Details of the MRA sequences and DSA procedure have been described previously (3,10). For the present study, all MRA datasets were transferred to a 3D workstation (Leonardo with 3D MIP software and Inspace interactive 3D Viewer; Siemens Medical Solutions Computed Tomography, Forchheim, Germany) equipped with a real-time volume-rendering graphic accelerator card (VolumePro 1000; TeraRecon, Inc., San Mateo, Calif., USA).…”

Section: Methodsmentioning

confidence: 99%

Standardized volume rendering for magnetic resonance angiography measurements in the abdominal aorta

et al. 2006

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Purpose: To compare three methods for standardizing volume rendering technique (VRT) protocols by studying aortic diameter measurements in magnetic resonance angiography (MRA) datasets. Material and Methods: Datasets from 20 patients previously examined with gadolinium-enhanced MRA and with digital subtraction angiography (DSA) for abdominal aortic aneurysm were retrospectively evaluated by three independent readers. The MRA datasets were viewed using VRT with three different standardized transfer functions: the percentile method (Pc-VRT), the maximum-likelihood method (ML-VRT), and the partial range histogram method (PRH-VRT). The aortic diameters obtained with these three methods were compared with freely chosen VRT parameters (F-VRT) and with maximum intensity projection (MIP) concerning inter-reader variability and agreement with the reference method DSA. Results: F-VRT parameters and PRH-VRT gave significantly higher diameter values than DSA, whereas Pc-VRT gave significantly lower values than DSA. The highest interobserver variability was found for F-VRT parameters and MIP, and the lowest for Pc-VRT and PRH-VRT. All standardized VRT methods were significantly superior to both MIP and F-VRT in this respect. The agreement with DSA was best for PRH-VRT, which was the only method with a mean error below 1 mm and which also had the narrowest limits of agreement (95% of cases between 2.1 mm below and 3.1 mm above DSA). Conclusion: All the standardized VRT methods compare favorably with MIP and VRT with freely selected parameters as regards interobserver variability. The partial range histogram method, although systematically overestimating vessel diameters, gives results closest to those of DSA.

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Volume rendering compared with maximum intensity projection for magnetic resonance angiography measurements of the abdominal aorta

Abstract: VRT is not suitable for diameter measurements of the abdominal aorta with fixed parameter settings but may be useful with user-selected settings.

Cited by 22 publications

References 15 publications

3D contrast‐enhanced MR angiography

3D contrast‐enhanced MR angiography

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

Standardized volume rendering for magnetic resonance angiography measurements in the abdominal aorta

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