Standardized evaluation framework for evaluating coronary artery stenosis detection, stenosis quantification and lumen segmentation algorithms in computed tomography angiography.

Though conventional coronary angiography (CCA) has been the standard of reference for diagnosing coronary artery disease in the past decades, computed tomography angiography (CTA) has rapidly emerged, and is nowadays widely used in clinical practice. Here, we introduce a standardized evaluation framework to reliably evaluate and compare the performance of the algorithms devised to detect and quantify the coronary artery stenoses, and to segment the coronary artery lumen in CTA data. The objective of this evaluation framework is to demonstrate the feasibility of dedicated algorithms to: (1) (semi-)automatically detect and quantify stenosis on CTA, in comparison with quantitative coronary angiography (QCA) and CTA consensus reading, and (2) (semi-)automatically segment the coronary lumen on CTA, in comparison with expert's manual annotation. A database consisting of 48 multicenter multivendor cardiac CTA datasets with corresponding reference standards are described and made available. The algorithms from 11 research groups were quantitatively evaluated and compared. The results show that (1) some of the current stenosis detection/quantification algorithms may be used for triage or as a second-reader in clinical practice, and that (2) automatic lumen segmentation is possible with a precision similar to that obtained by experts. The framework is open for new submissions through the website, at http://coronary.bigr.nl/stenoses/.

Evaluation framework for carotid bifurcation lumen segmentation and stenosis grading.

This paper describes an evaluation framework that allows a standardized and objective quantitative comparison of carotid artery lumen segmentation and stenosis grading algorithms. We describe the data repository comprising 56 multi-center, multi-vendor CTA datasets, their acquisition, the creation of the reference standard and the evaluation measures. This framework has been introduced at the MICCAI 2009 workshop 3D Segmentation in the Clinic: A Grand Challenge III, and we compare the results of eight teams that participated. These results show that automated segmentation of the vessel lumen is possible with a precision that is comparable to manual annotation. The framework is open for new submissions through the website http://cls2009.bigr.nl.

[Diagnosis of renal artery stenosis with magnetic resonance angiography and stenosis quantification]. / Diagnostic des sténoses de l'artère rénale en angiographie par résonance magnétique et appréciation du degré de sténose.

Atherosclerotic disease is the most common pathologic condition of renal artery stenosis, which typically compromises the ostium or the proximal 1-2 cm of renal arteries and is also usually present in the abdominal aorta. Fibromuscular dysplasia is the second most common cause of renal artery stenosis (RAS) which usually involves the distal two-third of the main renal artery with bed-like stenosis alternating with small fusiform or saccular aneurysms. Magnetic Resonance Angiography (MRA) was initially performed without contrast media injection using two- or three-dimensional Time-of-Flight (TOF) or Phase-Contrast (PC) techniques. Sensitivity and specificity of non-enhanced MRA in detection of proximal RAS are comprised between 53%-100% and 47%-97% respectively (table I). Main limitations of non-enhanced MRA are the long acquisition time, i.e. 5-8 min, the short field of view with lack of kidney visualization and major artifacts. Recent improvements allowed a three-dimensional acquisition during a single breath-hold (18-23 sec), associated to a bolus injection of a gadolinium chelate demonstrating a lack of nephrotoxicity. 3D gadolinium-enhanced ultrafast gradient-echo MRA techniques (3D enhanced-MRA) requires a precise technique. Firstly, kidney localization and morphologic imaging is performed before a 3D MRA data acquisition without injection (fig. 1). Secondly two successive 3D MRA sequences are performed synchronized with the gadolinium chelate bolus injection: the first acquisition corresponds to the arterial enhancement (fig. 4) and the second one to the venous enhancement. At last, a three-dimensional phase contrast could also be performed. After data acquisition, image post-processing is performed including image subtraction, maximum intensity projection (MIP) and reformation images of each renal artery, the abdominal aorta and its main branches (fig. 2, 3). The normal findings, pitfalls and anatomic variation are explained in detail. Particularly, when 3D enhanced MR angiography shows a normal artery, it is considered to be normal. It is also important to be aware of the existence of accessory or aberrant renal arteries that are well diagnosed by 3D enhanced MRA in 75% to 100% of the cases (fig. 2). 3D enhanced-MR angiography present several advantages in comparison to nonenhanced MRA: 1) a great field-of-view (30-36 cm) could be used allowing visualization of the abdominal aorta as well as its main branches; 2) the fast acquisition time allows an arterial imaging followed by a venous enhancement; 3) the kidneys are analyzed: kidney length, cortical thickness, corticomedullary differentiation and renal enhancement are well evaluated; 4) an accurate sensitivity and specificity in detection of proximal RAS comprised between 88%-100% and 71%-100% respectively (table II). Because a severe RAS (i.e. degree of stenosis > 50%) may cause renal ischemia leading to a blood pressure elevation that is often difficult to control with medical therapy, imaging has to assess the severity of RAS. MRA assessment of hemodynamic significance of RAS can be further refined by considering additional factors (fig. 4): arterial stop of signal, post stenotic dilatation, delayed renal enhancement and functional changes in the renal parenchyma (i.e. reduced kidney length and parenchymal thickness, loss of corticomedullary differentiation) (fig. 1). Precise evaluation of degree of stenosis requires the development of dedicated software such as MARACAS (MAgnetic Resonance Angiography Computer ASsisted analysis) software (fig. 5). In conclusions, 3D enhanced MRA allows an accurate diagnosis of proximal RAS, mainly due to atherosclerosis, without the risks associated with nephrotoxic contrast agents, ionizing radiation or arterial catheterization.

Image based renal stone tracking to improve efficacy in extracorporeal lithotripsy.

PURPOSE: We describe a method to reduce the number of shocks necessary to fragment renal stones during extracorporeal shock wave lithotripsy by automatically taking into account stone movements. MATERIALS AND METHODS: Echotrack computer software was developed and implemented on a lithotriptor. One software module uses image processing to detect instantaneous stone location based on ultrasound images generated by the lithotriptor. A second module uses the detected location to control the shock wave generator position, and automatically adjusts it to improve coincidence between the focal volume and stone. The reliability of the tracking algorithm was clinically tested in 65 patients with renal stones. These in vivo tests were qualitative and the goal was to assess software ability to track stones during actual treatments. A quantitative evaluation of the reduction in shocks necessary for fragmentation was performed in vitro. Artificial stones were moved according to computer generated trajectories. Each trajectory was applied once with and once without automatic adjustment of the generator position. RESULTS: The in vivo tests demonstrated software ability to track stones as far as they were visible in the images. During in vitro tests automatic adjustments of the generator position reduced the number of shocks necessary to fragment stones completely by a factor of 1.64. CONCLUSIONS: Image based renal stone tracking software that automatically adjusts the shock wave generator position according to the displacement of renal stones is useful during extracorporeal shock wave lithotripsy. Treatment time was significantly shorter with this software.

Improved vessel visualization in MR angiography by nonlinear anisotropic filtering.

This paper deals with a preprocessing technique of magnetic resonance angiography (MRA) images, applied before maximum-intensity-projection (MIP). The purpose was to recover small low-intensity vessels, visible in individual slices, but lost in MIP images that usually have higher background level than the individual slices. The authors have developed a nonlinear three-dimensional spatial filtering technique (called HD filter) based on anisotropic smoothing. The filter first searches for the local orientation of the vessel. It then performs a nonlinear smoothing in the vessel's local direction so as to avoid blurring its boundaries. Noise level reduction, contrast enhancement, and improved small vessel visibility achieved by this filter are illustrated on dynamic contrast-enhanced subtraction MRA images of the lower limbs.