Computerized Analysis of Digital Subtraction Angiography: A Tool for Quantitative In-vivo Vascular Imaging

Kagadis, George C.; Spyridonos, Panagiota; Karnabatidis, Dimitris; Diamantopoulos, Athanasios; Athanasiadis, Emmanouil; Daskalakis, Antonis; Κατσάνος, Κωνσταντίνος; Cavouras, D.; Mihailidis, Dimitris; Siablis, Dimitris; Nikiforidis, George

doi:10.1007/s10278-007-9047-2

Cited by 14 publications

(16 citation statements)

References 27 publications

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“…The proposed methodology is applied in DSA images acquired for either clinical or experimental purposes. We have previously developed an automated tool for the analysis of macro-and micro-vascular networks in DSA images which can be easily used in either experimental or clinical studies [5]. Its main disadvantage was the inability to differentiate between big arterial branches and smaller vessel categories.…”

Section: Discussionmentioning

confidence: 99%

“…All images used for the purposes of this paper were acquired from a DSA unit (DVI-S Philips) using a previously described acquisition protocol [5,6]. In brief, after trans-auricular endovascular access a 4-Fr catheter was advanced to the subject's abdominal aorta [8].…”

Section: Image Acquisitionmentioning

confidence: 99%

“…DSA) applications [5,7]. To our knowledge segmentation of vessels and classification according to size has not been applied in in-vivo applications.…”

Section: Introductionmentioning

confidence: 99%

“…Unfortunately, these methods lack in spatial resolution compared to in-vitro techniques. Digital Subtraction Angiography (DSA) is considered as the method of choice for the dynamic in-vivo visualization of the microvascular networks in angiogenesis experimental models [4,5]. Its main advantage is the ability to depict the progress (increase or decrease) of angiogenesis and thus evaluate the result of treatment [5,6].…”

Section: Introductionmentioning

confidence: 99%

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An automated computerized methodology for the segmentation of in vivo acquired DSA images: application in the New Zealand hindlimb ischemia model

et al. 2009

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In-vivo dynamic visualization and accurate quantification of vascular networks is a prerequisite of crucial importance in both therapeutic angiogenesis and tumor anti-angiogenesis studies. A user independent computerized tool was developed, for the automated segmentation and quantitative assessment of in-vivo acquired DSA images. Automatic vessel assessment was performed employing the concept of image structural tensor. Initially, vasculature was estimated according to the largest eigenvalue of the structural tensor. The resulted eigenvalue matrix was treated as gray-matrix from which the vessels were gradually segmented and then categorized in three main sub-groups; large, medium and small-size vessels. The histogram percentiles, corresponding to 85%, 65% and 47% of prime eigenvalue gray-matrix were optimally found to give the thresholds T1, T2 and T3 respectively, for extracting vessels of different size. The proposed methodology was tested on a series of DSA images in both normal rabbits (group A) and in rabbits

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Section: Discussionmentioning

confidence: 99%

Section: Image Acquisitionmentioning

confidence: 99%

“…DSA) applications [5,7]. To our knowledge segmentation of vessels and classification according to size has not been applied in in-vivo applications.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An automated computerized methodology for the segmentation of in vivo acquired DSA images: application in the New Zealand hindlimb ischemia model

et al. 2009

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“…Both filters were based on the 2D multiscale vessel enhancement filter described by Kagadis et al (14). The filter is based on eigen analysis of the Hessian matrix (H), which describes the curvature as a function of direction.…”

Section: Filteringmentioning

confidence: 99%

Automated multiscale vessel analysis for the quantification of MR angiography of peripheral arteriogenesis

Jaspers

Slenter

Leiner

et al. 2011

Magnetic Resonance Imaging

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Purpose: To automatically analyze the time course of collateralization in a rat hindlimb ischemia model based on signal intensity distribution (SID). Materials and Methods:Time-of-flight magnetic resonance angiograms (TOF-MRA) were acquired in eight rats at 2, 7, and 21 days after unilateral femoral artery ligation. Analysis was performed on maximum intensity projections filtered with multiscale vessel enhancement filter. Differences in SID between ligated limb and a reference region were monitored over time and compared to manual collateral artery identification.Results: The differences in SID correlated well with the number of collateral arteries found with manual quantification. The time courses of ultrasmall (diameter (0.5 mm) and small (diameter %0.5 mm) collateral artery development could be differentiated, revealing that maturation of the collaterals and enlargement of their feeding arteries occurred mainly after the first week postligation.Conclusion: SID analysis performed on axial maximum intensity projections is easy to implement, fast, and objective and provides more insight in the time course of arteriogenesis than manual identification. COLLATERAL ARTERIES developing from preexistent arterioles can act as natural bypasses in patients with peripheral or coronary arterial occlusive disease (1). Currently, therapies stimulating the formation of collateral arteries (ie, arteriogenesis) and restoring the impaired blood supply are explored (2-4). Accurate evaluation of such novel treatments strongly depends on image acquisition and analysis techniques that can detect and quantify the vascular responses both in experimental and clinical settings. Previously, noncontrast-enhanced inflow magnetic resonance angiography (MRA) techniques such as time-of-flight (TOF) MRA have been successfully used to noninvasively quantify collateralization in small animal ischemic hindlimb models (5-8).Collaterals are usually identified and quantified manually on (rotating) maximum intensity projections (MIPs) using the Longland definition (9), which requires identification of the collateral stem, mid-, and reentry zone. Visualization of complete trajectories is challenging due to inflow artifacts, flow voids for in-plane arteries (10), and the ultrasmall collateral artery calibers ((0.5 mm). Moreover, manual quantification is time-consuming, observer-dependent, and provides little information on changes in vessel size and physiological impact. A physiologically more relevant measure would be the blood volume or flow of the collateral arteries. Wagner et al (5) proposed a method to quantify collateral flow based on the dependence between pixel signal intensity and the amount and speed of inflow of unsaturated blood spins. The signal intensity histogram of TOF angiograms may provide surrogate parameters for changes in vessel morphology, as the signal intensity distribution depends on vessel size (11). A problem to overcome is the small volume fraction of arteries in hindlimbs compared to the large volume of background tissue. ...

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Classification of Tree and Network Topology Structures in Medical Images

Skoura

Megalooikonomou

Διαμαντόπουλος

et al. 2012

Data Mining for Biomarker Discovery

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Computerized Analysis of Digital Subtraction Angiography: A Tool for Quantitative In-vivo Vascular Imaging

Cited by 14 publications

References 27 publications

An automated computerized methodology for the segmentation of in vivo acquired DSA images: application in the New Zealand hindlimb ischemia model

An automated computerized methodology for the segmentation of in vivo acquired DSA images: application in the New Zealand hindlimb ischemia model

Automated multiscale vessel analysis for the quantification of MR angiography of peripheral arteriogenesis

Classification of Tree and Network Topology Structures in Medical Images

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