Laurence Rouet

Measuring the maximum diameter of native abdominal aortic aneurysms: review and critical analysis.

OBJECTIVES Maximum diameter is a determinant parameter for the clinical management of asymptomatic abdominal aortic aneurysm (AAA). However, its measurement is not standardised. We review the different methods used to measure AAA maximum diameter, with ultrasound (US) or computed tomography (CT). METHODS A review of maximum diameter measurement methods with US and CT was performed, focussing on screening, surveillance before repair and decision for intervention. Diameter measurement methodology was described according to four parameters: plane of acquisition, axis of measurement, position of callipers and selected diameter. A quality score to evaluate methodology descriptions was defined (plane, axis, callipers placement and selected diameter), ranging from 0 (worst) to 4 (best). RESULTS Review showed a wide range of definitions and practices. The mean value of the quality score was 2.52 in screening studies, 1.66 in guidelines for screening, 2.81 in follow-up studies and 1.63 in studies describing decision for intervention. CONCLUSION To improve the efficiency of AAA management (in screening programmes, follow-up and decision for intervention), and enable comparison between future studies, a standardised methodology for AAA maximum diameter measurement is necessary. Until such a consensus is reached, publications should at least clearly report the method of measurement.

Volume Estimation of the Aortic Sac after EVAR Using 3-D Ultrasound – A Novel, Accurate and Promising Technique

OBJECTIVES Volume estimation is more sensitive than diameter measurement for detection of aneurysm growth after endovascular aneurysm repair (EVAR), but this has only been confirmed on three-dimensional, reconstructed computer tomography (3-D CT). The potential of 3-D ultrasound (3-D US) for volume estimation in EVAR surveillance is unknown. DESIGN Prospective validation study comparing 3-D US with 3-D CT, using 3-D CT as the gold standard. MATERIALS AND METHODS From August 2011 to March 2012, 93 consecutive EVAR patients were enrolled and examined with both 3-D US and CT angiography (CTA). Image data were analysed in a mutual blinded setup using a 3-D interactive segmentation technique. RESULTS The technical success rate of 3D-US was 98% (91/93). In 91 EVAR patients (F/M; 10/81) eligible for further analysis, the mean maximum volume (SD) was 126 (58) ml using 3-D US and 128 (58) ml using 3-D CT. The mean difference was 1 ml (0.4%) and the limits of agreement were -14 to 16 ml (-11; 12%). CONCLUSION Volume estimation of the aortic sac after EVAR using 3-D US is a feasible and accurate method using 3-D CT as the gold standard.

Three-dimensional Ultrasound Improves the Accuracy of Diameter Measurement of the Residual Sac in EVAR Patients

OBJECTIVES Discrepancy between maximum diameters obtained with two-dimensional ultrasound and computed tomography (CT) after endovascular aneurysm repair (EVAR) is well known. The maximal diameter is ideally measured perpendicular to the centerline, a methodology so far only feasible with three-dimensional (3D) CT and magnetic resonance angiography (MRA). We aimed to investigate the agreement between 3D ultrasound and 3D CT and to determine reproducibility measures. METHODS Prospective study comparing 3D ultrasound with 3D CT in 124 consecutive patients seen 3 or 12 month after EVAR. RESULTS Replacing 2D with 3D ultrasound, the mean difference was improved from 6.0 mm to -1.3 mm (p < .001), and the range of variability was reduced from 9.4 mm to 6.6 mm (p = .009) using 3D CT as the gold standard. The mean difference between 3D ultrasound and 3D CT maximum diameter of the residual sac was -1.3 mm with upper and lower limits of agreement of 5.2 mm and -7.9 mm, respectively. Reproducibility measures of 3D ultrasound were ± 4 mm. CONCLUSION 3D ultrasound correlate significantly better to 3D CT than the currently used 2D ultrasound method when assessing maximum diameter of the residual sac after EVAR, and reproducibility measures were within clinical acceptable values.

ABDOMINAL AORTIC ANEURYSM IMAGING WITH 3-D ULTRASOUND: 3-D-BASED MAXIMUM DIAMETER MEASUREMENT AND VOLUME QUANTIFICATION

The clinical reliability of 3-D ultrasound imaging (3-DUS) in quantification of abdominal aortic aneurysm (AAA) was evaluated. B-mode and 3-DUS images of AAAs were acquired for 42 patients. AAAs were segmented. A 3-D-based maximum diameter (Max3-D) and partial volume (Vol30) were defined and quantified. Comparisons between 2-D (Max2-D) and 3-D diameters and between orthogonal acquisitions were performed. Intra- and inter-observer reproducibility was evaluated. Intra- and inter-observer coefficients of repeatability (CRs) were less than 5.18 mm for Max3-D. Intra-observer and inter-observer CRs were respectively less than 6.16 and 8.71 mL for Vol30. The mean of normalized errors of Vol30 was around 7%. Correlation between Max2-D and Max3-D was 0.988 (p < 0.0001). Max3-D and Vol30 were not influenced by a probe rotation of 90°. Use of 3-DUS to quantify AAA is a new approach in clinical practice. The present study proposed and evaluated dedicated parameters. Their reproducibility makes the technique clinically reliable.

Compliance of Abdominal Aortic Aneurysms before and after Stenting with Tissue Doppler Imaging : Evolution during Follow-Up and Correlation with Aneurysm Diameter

Usual imaging after endovascular aneurysm repair (EVAR) of abdominal aortic aneurysm (AAA) consists of AAA diameter monitoring and endoleak detection. Among additional predictor parameters previously proposed to help clinicians in better identifying subgroups of AAA still at risk of rupture, AAA wall motion after EVAR has been studied, but its value was not clearly established. Tissue Doppler imaging (TDI) is an ultrasonographic modality which allows wall motion measurements along an arterial segment. The aim of the current study was to analyze AAA wall motion with TDI before and after EVAR and to describe its evolution in patients with more than 1 month of follow-up. Twenty-five consecutive patients undergoing EVAR between February 2005 and June 2007 gave informed consent to be prospectively investigated with the TDI system before EVAR and at each visit during follow-up. The mean (SD) follow-up was 13.7 (9.7) months. Maximum mean segmental dilation (MMSD), segmental compliance, dilation at maximum diameter, pressure strain elastic modulus (Ep), and stiffness were compared between three periods (before stenting, before discharge, and at last follow-up), and their relation with AAA diameter was analyzed. A significant decrease in AAA compliance was immediately observed after successful EVAR and remained stable during later follow-up. On the other hand, AAA diameter progressively decreased along time and was statistically lower at the last control compared to the initial value. MMSD, segmental compliance, and dilation at maximum diameter were positively related to AAA diameter. This means that the larger the AAA diameter after stenting, the higher the value for these parameters can be expected. On the contrary, percentage of AAA diameter decrease and percentage of MMSD decrease were not related after successful EVAR. There was no parallelism between loss in compliance and diameter decrease along time, and there is not a unique pattern of AAA diameter and compliance evolution after EVAR. Even if comparison between patients without and with endoleak was weak due to the small sample of the latter group (five patients with endoleak), compliance tended to be greater in case of endoleak. AAA wall motion after successful EVAR reflects complex interactions between all the components of the stented aneurysm which evolve over time, including true compliance of the aneurysm wall itself; intra-aneurysm sac pressure with possible different effects for peak, mean, and pulse pressures; remodeling of the thrombus; stiffness characteristics of the graft; and systemic pressure. Combining simultaneous MMSD records with actual intrasaccular pressure measurements in patients with and without endoleak would improve our understanding of the clinical pulsatility mechanism within AAA after EVAR.

Registration of free-breathing abdominal 3d contrast-enhanced CT

CT perfusion imaging is used for the follow-up of abdominal tumors. A specificity of our work is that patients are breathing freely during image acquisition (5 minutes). We propose an automatic 3D image registration to compensate for respiratory motion. The registration is computed in two main steps: global translation in the z-direction and 3D multiresolution blockmatching. Within this algorithm, the choice of similarity measure largely determines the algorithm robustness in presence of intensity shifts due to contrast diffusion. We exploit a modified entropy-based similarity measure to improve the quality of registration. We also propose two relevant criteria allowing to quantify the registration quality: one based on the gradients of difference images and one based on the smoothness of enhanced-intensity curves.

Semi-automatic abdominal aortic aneurysms geometry assessment based on 3D ultrasound

This paper presents a new approach for improving the surveillance of the size of abdominal aortic aneurysms (AAA). Use of 3D ultrasound imaging combined with semi-automatic quantification provides automatic selection of the optimal plane for diameter measurement. Quantification parameters are defined to characterize the aneurysm with more accuracy. Volume imaging also provides 3D visualization of the AAA geometry and CT-like multi-planar reconstructions. Multiple volume registrations are proposed to overcome limited field of view issues. Quantification results show good correlation with 2D reference measurements and obtained Pearson correlation coefficients are significant for 30 patients.

Parameter estimation of perfusion models in dynamic contrast-enhanced imaging: a unified framework for model comparison

&NA; Patients follow‐up in oncology is generally performed through the acquisition of dynamic sequences of contrast‐enhanced images. Estimating parameters of appropriate models of contrast intake diffusion through tissues should help characterizing the tumour physiology. However, several models have been developed and no consensus exists on their clinical use. In this paper, we propose a unified framework to analyse models of perfusion and estimate their parameters in order to obtain reliable and relevant parametric images. After defining the biological context and the general form of perfusion models, we propose a methodological framework for model assessment in the context of parameter estimation from dynamic imaging data: global sensitivity analysis, structural and practical identifiability analysis, parameter estimation and model comparison. Then, we apply our methodology to five of the most widely used compartment models (Tofts model, extended Tofts model, two‐compartment model, tissue‐homogeneity model and distributed‐parameters model) and illustrate the results by analysing the behaviour of these models when applied to data acquired on five patients with abdominal tumours. HighlightsWe propose a mathematical framework to analyse models of perfusion.We estimate parameters from dynamic imaging data.We compare the most widely used compartment models of perfusion.We apply our methodology to data acquired on patients with abdominal tumours. Graphical abstract Figure. No caption available.

A minimally interactive and reproducible method for abdominal aortic aneurysm quantification in 3D ultrasound and computed tomography with implicit template deformations

The maximum diameter of abdominal aortic aneurysm (AAA) is a key quantification parameter for disease assessment. Although it is routinely measured on 2D-ultrasound images, using a volumetric approach is expected to improve measurement reproducibility. In this work, 3D-ultrasound or computed tomography imaging of patients with AAA was combined with a minimally interactive 3D segmentation based on implicit template deformation. Segmentation usability and reproducibility were evaluated on 81 patients, showing a mean measurement time of [2;8]min per case, and Dice coefficients of 0.87±0.12 for 3D-US and 0.81±0.08 for CT. Quantification parameters included a diameter measurement from 3D-US and CT volumes with respective confidence intervals of 0.51 [-2.5;3.52]mm and 1.00 [-1.68;3.67]mm. Additional volume measurements showed confidence intervals of 0.91 [-4.17;5.99]ml for 3D-US and 4.10 [-4.11;12.30]ml for CT.

A multi-task learning approach for compartmental model parameter estimation in DCE-CT sequences

Todays follow-up of patients presenting abdominal tumors is generally performed through acquisition of dynamic sequences of contrast-enhanced CT. Estimating parameters of appropriate models of contrast intake diffusion through tissues should help characterizing the tumor physiology, but is impeded by the high level of noise inherent to the acquisition conditions. To improve the quality of estimation, we consider parameter estimation in voxels as a multi-task learning problem (one task per voxel) that takes advantage from the similarity between two tasks. We introduce a temporal similarity between tasks based on a robust distance between observed contrast-intake profiles of intensity. Using synthetic images, we compare multi-task learning using this temporal similarity, a spatial similarity and a single-task learning. The similarities based on temporal profiles are shown to bring significant improvements compared to the spatial one. Results on real CT sequences also confirm the relevance of the approach.