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Three-dimensional ultrasound (US) of abdominal aortic aneurysms (AAAs) is limited by the field-of-view of the 3D-US transducer. To obtain an extended field-of-view (XFoV), two transducer navigation system-assisted US protocols have been developed: XFoV-2D and XFoV-3D. In this study, the XFoV US protocols were compared with the currently available 3D-US protocol with standard field-of-view (FoV-st) and the established gold standard, computed tomography angiography (CTA). A total of 65 patients with AAA were included, and AAA imaging was processed offline with prototype software. The novel XFoV-2D and XFoV-3D protocols allowed for assessment of full AAA volume in significantly more patients (45/65 [69%] and 43/65 [66%], respectively), compared with the current 3D-US standard, FoV-st (30/65 [46%] patients). The mean difference in AAA volume estimation between each XFoV US protocol and 3-D CTA differed significantly (XFoV-2D: 16.9 mL, XFoV-3D: 7.6 mL, p = 0.002), indicating that XFoV-3D agreed best with 3D-CTA. No significant difference was found in the variance of full AAA volume quantification between each XFoV US protocol and CTA (p = 0.49). It is concluded that the XFoV US protocols improved the generation of full AAA volumes compared with the currently available 3D-US technology, with AAA volume estimates comparable to CTA estimates.

Objective: The relationship between intraluminal thrombus (ILT) and abdominal aortic aneurysm (AAA) growth and rupture risk remains ambiguous. Studies have shown a limited effect of antiplatelet therapy on ILT size, whereas the impact of anticoagulant therapy on ILT is unresolved. This study aims to evaluate an association between antithrombotic therapy and ILT size assessed with three-dimensional contrast-enhanced ultrasound (3D-CEUS) examination in a cohort of patients with AAA. Methods: In a cross-sectional study, 309 patients with small AAAs were examined with 3D-CEUS. Patients were divided into three groups based on prescribed antithrombotic therapy: anticoagulant (n = 36), antiplatelet (n = 222), and no antithrombotic therapy (n = 51). Patient ILT size was calculated in volume and thickness and compared between the three groups. Results: Patients on anticoagulants had a significantly lower estimated marginal mean ILT volume of 16 mL (standard error [SE], ±3.2) compared with 28 mL (SE, ±2.7) in the no antithrombotic group and 30 mL (SE, ±1.3) in the antiplatelet group when adjusting for AAA volume (P < .001) and comorbidities (P < .001). In addition, patients on anticoagulant therapy had significantly lower estimated marginal mean ILT thickness of 10 mm (SE, ±1.1) compared with 13 mm (SE, ±0.9) in the no antithrombotic group of and 13mm (SE, ±0.4) in the antiplatelet group when adjusting for AAA diameter (P = .03) and comorbidities (P = .035). Conclusions: A 3D-CEUS examination is applicable for ILT assessment and demonstrates that patients with AAA on anticoagulant therapy have lower ILT thickness and volume than patients with AAA on antiplatelet therapy and those without antithrombotic therapy. Causality between anticoagulants and ILT size, and extrapolation to AAA growth and rupture risk, is unknown and merits further investigations, to further nuance US-based AAA surveillance strategy.

OBJECTIVE Conventional two-dimensional ultrasound (2D-US) has been the recommended and preferred modality for the diagnosis and surveillance of abdominal aortic aneurysms (AAAs). Measurement of the aneurysm diameter using three-dimensional ultrasound (3D-US) has shown promising results in a research setting, improving agreement and reproducibility. However, studies evaluating 3D-US in a clinical context are lacking, which could hinder the optimal usage of this new modality. In the present study, we investigated the clinical value of 3D-US for AAA surveillance compared with the current standard 2D-US examination. METHODS Data from 126 patients with infrarenal AAAs

To compare aortic sac changes after endovascular aneurysm repair (EVAR) assessed by three-dimensional ultrasound (3D-US), two-dimensional ultrasound (2D-US), and traditional computed tomographic angiography (CTA).Using volume assessment with three-dimensional CTA (3D-CTA-volume) as the gold standard, this study investigated aortic sac changes at three and 12 months after EVAR with three different ultrasound methods (2D-US anterior-posterior (AP) diameter, 3D-US AP centerline diameter, and 3D-US partial volume), and traditional CT multiplanar outer-to-outer diameter (CT-MPR OTO diameter). From august 1st, 2011 to January 2014, consecutive EVAR patients (n = 113) were available for analysis in two time intervals; 1) between preoperative and three-month follow-up and 2) between three and 12 month follow-up.The risk of missing true aortic sac growth (false negative finding) at three-month postoperative visit using 3D-US partial volume, 3D-US AP centerline diameter, 2D-US AP diameter, and CT-MPR OTO diameter was 19%, 21%, 22%, and 18%, respectively. Corresponding low sensitivities (0% to 21%) and kappa-values (0.50) in detecting aortic sac changes were found. The risk of missing true growth between three and 12 months were lower (6%, 5%, 6%, and 6%, respectively), and matching sensitivities 33%, 33%, 17%, and 17%, respectively.All tested methods for aortic sac changes were as good as traditional CT-MPR OTO diameter and corresponded poorly with 3D-CTA-volume at three months postoperative visit but substantially better after 12 months where the residual sac change was more profound.

Background "Profiling" is a new method based on three-dimensional ultrasound (3D-US) allowing for direct comparison of baseline and follow-up diameters along the AAA length. This study aimed to evaluate the feasibility of profiling to visualize AAA changes at sub-maximum diameters, and to categorize the growth profiles. Methods Retrospective analysis of prospectively and consecutively included patients under AAA surveillance at a tertiary referral centre. 3D-US images of AAAs at baseline and at one-year follow-up were segmented, generating a centerline and a mesh of the aneurysm geometry. The mesh was processed to illustrate diameter changes of a given AAA. Three growth profiles were identified: A) Peak Growth: the largest, significant (≥3.6 mm) diameter difference occurred within a 10 mm margin to either side of the maximum baseline diameter; B) Edge Growth: at least one significant diameter difference and the criteria for Peak Growth did not apply; C) No Growth: all diameter differences were nonsignificant. A centerline length of ≥60 mm was assumed to capture a comparable segment of the wall geometry at baseline and follow-up. Cohen's kappa and Kaplan Meier analysis were used to analyze data. Results In total, 186 patients had growth profiles generated. Of these, 28 (15%) were discarded, mainly based on inadequate centerline lengths (n= 21, 11.3%). The remaining patients were categorized into Edge Growth (n=83, 52%), No Growth (n=47, 30%), and Peak Growth (n=28, 18%). Conclusions Profiling interprets AAA growth at sub-maximum diameters. Half of the cohort had Edge Growth. These AAAs risk being classified as stable.

Magnetic resonance imaging (MRI) is the preferred modality to assess hemodynamics in healthy and diseased blood vessels. As an affordable and non-invasive alternative, Color-Doppler imaging is a good candidate. Nevertheless, Color-Doppler acquisitions provide only partial information on the blood velocity within the vessel. We present a framework to reconstruct 2D velocity fields in the aorta. We generated 2D Color-Doppler-like images from patient-specific Computational Fluid Dynamics (CFD) models of abdominal aortas and evaluated the framework's performance. The 2D velocity field reconstruction is based on the minimization of a cost function, in which the reconstructed velocities are constrained to satisfy fluid dynamics principles. The numerical evaluations show that the reconstructed vector flow fields agree with ground-truth velocities, with an average magnitude error of less than 4% and an average angular error of less than 2

Due to a high heterogeneity in pose and size and to a limited number of available data, segmentation of pediatric images is challenging for deep learning methods. In this work, we propose a new CNN architecture that is pose and scale invariant thanks to the use of Spatial Transformer Network (STN). Our architecture is composed of three sequential modules that are estimated together during training: (i) a regression module to estimate a similarity matrix to normalize the input image to a reference one; (ii) a differentiable module to find the region of interest to segment; (iii) a segmentation module, based on the popular UNet architecture, to delineate the object. Unlike the original UNet, which strives to learn a complex mapping, including pose and scale variations, from a finite training dataset, our segmentation module learns a simpler mapping focusing on images with normalized pose and size. Furthermore, the use of an automatic bounding box detection through STN allows saving time and especially memory, while keeping similar performance. We test the proposed method in kidney and renal tumor segmentation on abdominal pediatric CT scanners. Results indicate that the estimated STN homogenization of size and pose accelerates the segmentation (25h), compared to standard data-augmentation (33h), while obtaining a similar quality for the kidney (88.01\% of Dice score) and improving the renal tumor delineation (from 85.52\% to 87.12\%)., Comment: ISBI 2021

Objective Three-dimensional ultrasound (3D-US) has already demonstrated improved reproducibility with a high degree of agreement (intermodality variability), reproducibility (interoperator variability), and repeatability (intraoperator variability) compared with conventional two-dimensional ultrasound (2D-US) when estimating the maximum diameter of native abdominal aortic aneurysms (AAAs). The aim of the present study was, in a clinical, multicenter setting, to evaluate the accuracy of 3D-US with aneurysm model quantification software (3D-US abdominal aortic aneurysm [AAA] model) for endovascular aortic aneurysm repair (EVAR) sac diameter assessment vs that of computed tomography angiography (CTA) and 2D-US. Methods A total of 182 patients who had undergone EVAR from April 2016 to December 2017 and were compliant with a standardized EVAR surveillance program were enrolled from five different vascular centers (Rigshospitalet, Copenhagen, Denmark; Catharina Ziekenhuis, Eindhoven, Netherlands; L'hospital de la Timone, Paris, France; Cleveland Clinic, Cleveland, Ohio; and The Christ Hospital, Cincinnati, Ohio) in four countries. All image acquisitions were performed at the local sites (ie, 2D-US, 3D-US, CTA). Only the 2D-US and CTA readings were performed both locally and centrally. All images were read centrally by the US and CTA core laboratory. Anonymized image data were read in a randomized and blinded manner. Results The sample used to estimate the accuracy of the 3D-US AAA model and 2D-US included 164 patients and 177 patients, respectively. The Bland-Altman analysis revealed that the mean difference between CTA and 3D-US was −2.43 mm (95% confidence interval [CI], −5.20 to 0.14; P = .07) with a lower and upper limit of agreement of −8.9 mm (95% CI, −9.3 to −8.4) and 2.7 mm (95% CI, 2.3-3.2), respectively. For 2D-US and CTA, the mean difference was −3.62 mm (95% CI, −6.14 to −1.10; P = .002), with a lower and upper limit of agreement of −10.3 mm (95% CI, −10.8 to −9.8) and 2.5 mm (95% CI, 2-2.9), respectively. Conclusions The 3D-US AAA model showed no significant difference compared with CTA for measuring the anteroposterior diameter, indicating less bias for 3D-US compared with 2D-US. Thus, 3D-US with AAA model software is a viable modality for anteroposterior diameter assessment for surveillance after EVAR.

Volume assessment of abdominal aortic aneurysms (AAAs) using 3-D ultrasound (US) is an innovative technique reporting good agreement with computed tomography angiography. One major limitation of the current 3-D US technique is a limited field of view, allowing full AAA acquisition in only 60% of patients. This study presents two new US acquisition protocols using magnetic field tracking, providing an “extended field of view” (XFoV-2-D and XFoV-3-D) with the aim of including both the aortic bifurcation and neck for full-volume assessment, and compares these methods with the current standard 3-D US protocol and with computed tomography angiography. A total of 20 AAA patients were included and underwent the current standard 3-D US protocol and the two novel 3-D US “extended field of view” protocols. Four patients were excluded from further analysis because of low image quality, leaving 16 patients eligible for analysis. Full AAA volume was achieved in 8 patients (50%) using the standard 3-D US protocol, in 11 patients (69%) with the XFoV-2-D protocol and in 13 patients (81%) with the XFoV-3-D protocol. In conclusion, this article describes two new and feasible US protocols applicable for full-AAA-volume estimation in most patients and should initiate further research into the added value of full volume in AAA surveillance.

ContextVariability in 2D ultrasound (US) is related to the acquisition of planes of reference and the positioning of callipers and could be reduced in combining US volume acquisitions and anatomical structures recognition.ObjectivesThe primary objective is to assess the consistency between 3D measurements (automated and manual) extracted from a fetal US volume with standard 2D US measurements (I). Secondary objectives are to evaluate the feasibility of the use of software to obtain automated measurements of the fetal head, abdomen and femur from US acquisitions (II) and to assess the impact of automation on intraobserver and interobserver reproducibility (III).Methods and analysis225 fetuses will be measured at 16–30 weeks of gestation. For each fetus, six volumes (two for head, abdomen and thigh, respectively) will be prospectively acquired after performing standard 2D biometry measurements (head and abdominal circumference, femoral length). Each volume will be processed later by both a software and an operator to extract the reference planes and to perform the corresponding measurements. The different sets of measurements will be compared using Bland-Altman plots to assess the agreement between the different processes (I). The feasibility of using the software in clinical practice will be assessed through the failure rate of processing and the score of quality of measurements (II). Interclass correlation coefficients will be used to evaluate the intraobserver and interobserver reproducibility (III).Ethics and disseminationThe study and related consent forms were approved by an institutional review board (CPP SUD-EST 3) on 2 October 2018, under reference number 2018–033 B. The study has been registered inhttps://clinicaltrials.govregistry on 23 January 2019, under the numberNCT03812471. This study will enable an improved understanding and dissemination of the potential benefits of 3D automated measurements and is a prerequisite for the design of intention to treat randomised studies assessing their impact.Trial registration numberNCT03812471; Pre-results.

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.

Motion estimation is a key building block of image processing pipelines in many different contexts, ranging from efficient coding of video sequences in the consumer electronics domain (TV, DVD, BD) to professional medical applications. Many block-matching approaches have been proposed in the literature for motion detection and compensation in general, including both lossless and lossy algorithms. However, in real-time medical imaging applications, characterized by high frame rates, the needs for low latency and jitter, accuracy and robustness against noise are quite difficult to achieve with standard block-matching methods. We introduce a new hybrid image processing approach to block-matching that takes advantage of both types of algorithms (lossless and lossy), adapts to the image content and noise, and provides high flexibility for the speed/accuracy tradeoff. The presented approach has been successfully tested on interventional X-ray fluoroscopy and cardiac ultrasound images sequences.

Objective To evaluate whether an automated tool can recognize a structure of interest and measure fetal head circumference (HC), abdominal circumference (AC) and femur length (FL) on frozen two-dimensional ultrasound images. Methods Ultrasound examinations were performed in 100 singleton pregnancies between 20 and 40 weeks of gestation, ensuring an even distribution throughout gestational age. In each pregnancy, three standard biometric variables (HC, AC, FL) were measured each in three different images obtained for this purpose (i.e. nine independent image acquisitions). An algorithm (Philips Research) was used to detect the structure of interest and automatically place calipers for measurement. Caliper placement was assessed in two ways. First, subjective clinical assessment was performed to determine whether the caliper placement was correct, and caliper position was classified as 'acceptable for clinical use', 'minor adjustment required' or 'major adjustment required'. Second, the resulting automatic measurements were compared with manual measurements, taken in real time. Mean difference errors were calculated and expressed as percentages to correct for fetal growth with advancing gestation. Results After exclusion of one pregnancy due to missing images, a total of 891 images (297 for each biometric variable) from 99 pregnancies were analyzed. The algorithm failed to place calipers for the AC in nine images, whereas there were no failures in caliper placement for measurement of HC and FL. On subjective quality assessment of automatic caliper placement, in 475 (53.3%) images position of the calipers was judged to be clinically acceptable and did not require any adjustment, while in 317 (35.6%) and 90 images (10.1%) minor and major adjustments were required, respectively. The mean error between manual and automatic measurement of HC was -0.21 cm corresponding to a percentage error of -0.81% with 95% limits of agreement (LOA) between -3.73% and 2.12%. For AC and FL measurements, the mean error was, respectively, 0.72 cm (percentage error, 2.40%) with LOA between -9.48% and 14.27%, and 0.21 cm (percentage error, 3.76%) with LOA between -8.38% and 15.91%. Conclusions The automated tool identified correctly the biometric variable of interest in 99% of frozen images. The resulting measurements had a high degree of accuracy and compared well with previously published manual-to-manual agreement. The measurements exhibited bias, with the automated tool underestimating biometry; this could be overcome by further improvements in the algorithm. Nevertheless, adjustable calipers for manual correction remains a requirement. Copyright © 2018 ISUOG. Published by John Wiley & Sons Ltd.

3D ultrasound (US) is a promising technique to perform automatic extraction of standard planes for fetal anatomy assessment. This requires prior organ localization, which is difficult to obtain with direct learning approaches because of the high variability in fetus size and orientation in US volumes. In this paper, we propose a methodology to overcome this spatial variability issue by scaling and automatically aligning volumes in a common 3D reference coordinate system. This preprocessing allows the organ detection algorithm to learn features that only encodes the anatomical variability while discarding the fetus pose. All steps of the approach are evaluated on 126 manually annotated volumes, with an overall mean localization error of 11.9 mm, showing the feasibility of multi-organ detection in 3D fetal US with machine learning.

Ultrasound is increasingly becoming a 3D modality. Mechanical and matrix array transducers are able to deliver 3D images with good spatial and temporal resolution. The 3D imaging facilitates the application of automated image analysis to enhance workflows, which has the potential to make ultrasound a less operator dependent modality. However, the analysis of the more complex 3D images and definition of all examination standards on 2D images pose barriers to the use of 3D in daily clinical practice. In this paper, we address a part of the canonical fetal screening program, namely the localization of the abdominal cross-sectional plane with the corresponding measurement of the abdominal circumference in this plane. For this purpose, a fully automated pipeline has been designed starting with a random forest based anatomical landmark detection. A feature trained shape model of the fetal torso including inner organs with the abdominal cross-sectional plane encoded into the model is then transformed into the patient space using the landmark localizations. In a free-form deformation step, the model is individualized to the image, using a torso probability map generated by a convolutional neural network as an additional feature image. After adaptation, the abdominal plane and the abdominal torso contour in that plane are directly obtained. This allows the measurement of the abdominal circumference as well as the rendering of the plane for visual assessment. The method has been trained on 126 and evaluated on 42 abdominal 3D US datasets. An average plane offset error of 5.8 mm and an average relative circumference error of 4.9 % in the evaluation set could be achieved.

Objectives The impact of intraluminal thrombus (ILT) on abdominal aortic aneurysm (AAA) progression can be investigated non-invasively by three dimensional contrast enhanced ultrasound (3D-CEUS). The aim was to validate 3D-CEUS ILT volume and thickness measurements against computed tomography angiography (CTA), and to determine inter- and intra-operator reproducibility. Methods The design was for a planned comparison of 3D-CEUS and CTA and of repeated 3D-CEUS measurements in a blinded set up. Consecutive patients with asymptomatic AAA (n = 137, maximum diameter 30–55 mm) from a single centre were consecutively assessed by CTA and 3D-CEUS in a blinded setup. After exclusion of failed CTA (n = 2) and inconclusive 3D-CEUS (n = 8), 127 3D-CEUS/CTA pairs were analysed by Bland–Altman plots. 3D-CEUS inter- and intra-operator reproducibility were determined in a subgroup (n = 30) measured twice by two blinded investigators. Results In 24 of 127 (19%) patients, no ILT was found on 3D-CEUS. Intraluminal thrombus absence was confirmed by 3D-CTA analysis in all but two cases. Mean ILT volume difference between 3D-CEUS and CTA was 2.2 mL (5% of mean volume) and range of variability (ROV) amounted to ± 10.2 mL. Mean ILT thickness difference was 0.6 mm with a ROV of ± 4.6 mm 3D-CEUS inter-operator variations of ILT volume and thickness measurements were low (ROV ± 8.8 mL and ±2.9 mm, respectively). The corresponding intra-operator ROVs were ±7.5 mL and ±3.3 mm, respectively. Conclusions 3D-CEUS demonstrated good reproducibility and a good agreement with CTA when estimating ILT volume and maximum thickness in AAA patients. It is a promising research tool to investigate potential interactions between ILT, AAA growth, and rupture.

International audience; 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.

Objectives Rupture risk in abdominal aortic aneurysms (AAAs) is assessed using AAA diameter; yet 10% of ruptures occur in a small aneurysm. This underlines the inadequacy of diameter as a standalone parameter. In this prospective follow-up study, ultrasound determined aneurysm diameter was compared with aneurysm volume determined by three dimensional ultrasound (3D-US) in a group of 179 AAAs. Design This was a prospective cohort study with repeated diameter and volume measurements by 3D-US. Material and methods In total, 179 patients with small infrarenal AAAs (diameter 30–55 mm) were enrolled consecutively. At enrolment and at 12 month follow-up, maximum diameter, using dual plane technique, and three dimensional volume were measured. Based on a previous accuracy study, significant change in diameter and volume were defined as an increase exceeding the known range of variability (ROV) of each US technique; ±3.7 mm and ±8.8 mL, respectively. Post-hoc Kaplan–Meier analysis was performed to estimate time to conversion to treatment after the conclusion of the follow-up period between two groups. Results In total, 125 patients (70%) had an unchanged diameter during follow-up. In this group, 50 patients (40%) had an increasing aortic volume. Forty-five (83%) of the 54 patients with an increasing aortic diameter showed a corresponding volume increase. During a median follow-up of 367 days (364–380 days), a mean increase in diameter of 2.7 mm (±2.6 mm) and a mean increase in volume of 11.6 mL (±9.9 mL) were recorded. In post-hoc analysis, it was found that more AAAs with a stable diameter and a growing volume than AAAs with a stable diameter and volume were undergoing aortic repair during follow-up, based on the maximum diameter. Conclusion In this cohort of small AAAs, 40% of patients with a stable diameter had an increasing volume at 12 month follow-up. From this perspective, 3D-US could have a future supplemental role in AAA surveillance programmes.

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.

Le suivi habituel d'un anevrysme de l'aorte abdominale (AAA) apres traitement par endoprothese (EVAR) comporte la surveillance de son diametre et la detection d'une endofuite. Parmi les autres parametres proposes au clinicien pour identifier les AAA restant a risque de rupture, figure la compliance de l'AAA mais son interet n'est pas clairement defini. Le doppler tissulaire (TDI) est une modalite echographique permettant la mesure des deplacements des parois de l'AAA. Le but de cette etude etait d'analyser la compliance des AAA avant et apres EVAR, et d'en decrire l'evolution chez des patients ayant plus d'un mois de suivi. Vingt cinq patients consecutifs traites par EVAR entre fevrier 2005 et juin 2007 ont donne leur consentement eclaire pour avoir une analyse prospective du mouvement des parois de l'AAA par TDI avant EVAR et lors de chaque visite au cours du suivi. Le suivi moyen (ET) etait de 13,7 (9,7) mois. La dilatation segmentaire maximale moyenne (MMSD), la compliance segmentaire, la dilatation au diametre maximal, le module elastique de contrainte de pression (Ep) et l'indice de raideur etaient compares entre trois periodes (avant EVAR, avant la sortie et lors du dernier controle) et leur relation avec le diametre de l'AAA etait analysee. La compliance des AAA diminuait significativement immediatement apres une implantation reussie et restait stable au cours du suivi, alors que le diametre des AAA diminuait progressivement et etait statistiquement plus petit lors du dernier controle comparativement au diametre initial. La MMSD, la compliance segmentaire et la dilatation au diametre maximal etaient correlees positivement au diametre de l'AAA. Cela signifie que plus le diametre de l'AAA etait large apres EVAR reussi, plus la compliance etait elevee. A l'oppose, les pourcentages de diminution du diametre de l'AAA et de la MMSD n'etaient pas correles: il n'y avait pas de parallelisme entre la perte de compliance et la retraction de l'AAA. Cela signifie qu'il existe des modeles de perte de compliance et de retraction variables d'un AAA a l'autre au cours du suivi. Meme si la comparaison des patients sans et avec endofuite etait difficile du fait du petit effectif de ce dernier groupe (5 patients), la compliance tendait a etre plus importante en cas d'endofuite. Les mouvements de paroi d'un AAA apres EVAR reussi refletent des interactions complexes entre les composants de l'AAA traite, eux meme evolutifs au cours du temps, incluant la compliance vraie de la coque de l'AAA, la pression intrasacculaire avec des effets possiblement differents entre la pression maximale, la pression moyenne et la pression pulsee, le remodelage du thrombus, les caracteristiques de l'endoprothese et la pression systemique intra aortique. Une mesure combinee de la MMSD et de la pression intrasacculaire chez des patients sans et avec endofuite pourrait permettre d'avancer dans la comprehension du mecanisme des mouvements de parois de l'AAA apres EVAR.

Las tecnicas de imagen habituales tras la reparacion endovascular de los aneurismas (REVA) en casos de aneurismas aorticos abdominales (AAA) estan destinadas a monitorizar el diametro del AAA y detectar endofugas. Entre los parametros predictivos adicionales propuestos para identificar mejor los subgrupos de AAA que siguen presentando riesgo de rotura, se ha estudiado la motilidad de la pared tras la REVA, pero no se ha establecido de forma clara su utilidad. La eco-Doppler tisular (TDI) es una modalidad ecografica que permite realizar mediciones de la motilidad parietal a lo largo de un segmento arterial. El objetivo de este estudio fue analizar la motilidad de la pared del AAA mediante TDI antes y despues de la REVA y describir su evolucion en los pacientes con un seguimiento mayor de 1 mes. Se obtuvo el consentimiento informado de 25 pacientes consecutivos sometidos a REVA entre febrero de 2005 y junio de 2007 para ser estudiados de forma prospectiva mediante el sistema TDI antes de la REVA y en cada visita del seguimiento. La media del seguimiento fue de 13,7 (DE 9,7) meses. La media de la dilatacion maxima del segmento (MDMS), la distensibilidad del segmento, la dilatacion, el modulo elastico presion-deformacion (Ep), y la rigidez se compararon entre 3 periodos (antes de la colocacion del stent, antes del alta, y en el ultimo seguimiento), y se analizo su relacion con el diametro del AAA. Se observo una reduccion significativa en la distensibilidad del AAA inmediatamente tras la REVA, que permanecio estable durante el seguimiento posterior. Por otro lado, el diametro del AAA disminuyo progresivamente con el tiempo y fue estadisticamente menor en el ultimo control en comparacion con los valores iniciales. La MDMS, la distensibilidad del segmento, y la dilatacion del diametro maximo estuvieron relacionadas directamente con el diametro del AAA. Esto significa que cuanto mayor es el diametro del AAA tras la colocacion del stent, mayor es la magnitud que cabe esperar para estos parametros. Por el contrario, los porcentajes de reduccion del diametro del AAA y de la MDMS no estuvieron relacionados tras una REVA satisfactoria. No existio ningun paralelismo entre la perdida de distensibilidad y la reduccion del diametro a lo largo del tiempo, y no existe un unico patron respecto al diametro del AAA y la evolucion de la distensibilidad tras la REVA. A pesar de que la comparacion entre pacientes con y sin endofugas fue debil debido al tamano reducido de la muestra del primer grupo (5 pacientes con endofuga), la distensibilidad tendio a ser mayor en casos de endofuga. La motilidad de la pared del AAA tras una REVA satisfactoria refleja las complejas interacciones entre todos los componentes del aneurisma tratado con endoprotesis que evolucionan a lo largo del tiempo, incluida la distensibilidad real de la propia pared del aneurisma; la presion del saco intraaneurismatico con diferentes posibles efectos en cuanto a la presion maxima, media y del pulso; el remodelado del trombo; las caracteristicas de rigidez del implante; y la presion sistemica. La combinacion de los registros simultaneos de la MDMS con las determinaciones reales de la presion intrasacular en los pacientes con y sin endofuga mejoraria nuestro conocimiento del mecanismo de la pulsatilidad clinica en el AAA tras la REVA.

ObjectivesSeveral studies have shown that an increase in abdominal aortic aneurysm (AAA) growth rate occurs when the diameter reaches 40 to 50 mm. AAA expansion is related to remodeling of the parietal extracellular matrix. The parietal mechanisms involved in this critical phase of sudden increase remain unexplained. Analysis of AAA wall movements and determination of AAA compliance may provide information about the constitution of the arterial wall. If a change in parietal wall motion somewhere between 40 and 50 mm could be shown, this would contribute to the understanding of the growth of AAA. Furthermore, it would provide a valuable additional parameter for AAA monitoring. This study had two aims: first, to evaluate the relationship between AAA compliance and maximum diameter using the tissue Doppler imaging system; and second, to test the hypothesis of a change in AAA behavior at around 45 mm in diameter.MethodsFifty-six patients with AAA (mean diameter, 39 mm) were prospectively investigated using the tissue Doppler imaging system, which provides information concerning arterial wall motion. Maximum mean segmental dilation (MMSD), segmental compliance, pressure strain elastic modulus (Ep), and stiffness were determined and related to the maximum diameter of AAA.ResultsAfter natural log transformation of all variables, there was a significant positive linear relationship between maximum diameter and both MMSD (P < .001) and segmental compliance (P < .001) but not with Ep or stiffness (P = .37 and .22, respectively). MMSD and segmental compliance were significantly higher in AAA ≥ 45 mm than in AAA < 45 mm (P < .0002 and

Today's 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.

Dynamic contrast-enhanced computed tomography (DCE-CT) is a valuable imaging modality to assess tissues properties, particularly in tumours, by estimating pharmacokinetic parameters from the evolution of pixels intensities in 3D+t acquisitions. However, this requires a registration of the whole sequence of volumes, which is challenging especially when the patient breathes freely. In this paper, we propose a generic, fast and automatic method to address this problem. As standard iconic registration methods are not robust to contrast intake, we rather rely on the segmentation of the organ of interest. This segmentation is performed jointly with the registration of the sequence within a novel co-segmentation framework. Our approach is based on implicit template deformation, that we extend to a co-segmentation algorithm which provides as outputs both a segmentation of the organ of interest in every image and stabilising transformations for the whole sequence. The proposed method is validated on 15 datasets acquired from patients with renal lesions and shows improvement in terms of registration and estimation of pharmacokinetic parameters over the state-of-the-art method.

International audience; Today's 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.

International audience; 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.