Computer-assisted valve in valve in a deteriorated Mosaic valve using a library of bioprostheses.

Valve-in-valve (ViV) procedures have emerged from an off-label procedure to a safe and efficient alternative to redo aortic valve replacement in the treatment of symptomatic structural valve deterioration (SVD). During ViV procedures, optimal placement of the transcatheter heart valve (THV) inside the degenerated bioprosthesis is of paramount importance regarding complications such as device embolization, coronary obstruction, periprosthetic regurgitation, residual gradients, and mitral valve injury, but also for the attainment of optimal hemodynamics. In the case of the Mosaic (Medtronic, Minneapolis, MN) valve, the limited radiopaque landmarks represent a challenge to a reproducible, optimal implantation. Such implantation may require multiple contrast injections and transesophageal echocardiogram (TEE) guidance. We herein describe a computer-assisted ViV procedure inside a deteriorated Mosaic valve, achieving reproducible optimal placement using a preacquired library of bioprostheses 3D models. Our approach suggests an evolving paradigm in ViV procedures, from safe and efficient toward optimal therapy for symptomatic SVD.

Deformable image registration for radiation therapy: principle, methods, applications and evaluation.

Background: Deformable image registration (DIR) is increasingly used in the field of radiation therapy (RT) to account for anatomical deformations. The aims of this paper are to describe the main applications of DIR in RT and discuss current DIR evaluation methods. Methods: Articles on DIR published from January 2000 to October 2018 were extracted from PubMed and Science Direct. Our search was restricted to articles that report data obtained from humans, were written in English, and address DIR methods for RT. A total of 207 articles were selected from among 2506 identified in the search process. Results: At planning, DIR is used for organ delineation using atlas-based segmentation, deformation-based planning target volume definition, functional planning and magnetic resonance imaging-based dose calculation. In image-guided RT, DIR is used for contour propagation and dose calculation on per-treatment imaging. DIR is also used to determine the accumulated dose from fraction to fraction in external beam RT and brachytherapy, both for dose reporting and adaptive RT. In the case of re-irradiation, DIR can be used to estimate the cumulated dose of the two irradiations. Finally, DIR can be used to predict toxicity in voxel-wise population analysis. However, the evaluation of DIR remains an open issue, especially when dealing with complex cases such as the disappearance of matter. To quantify DIR uncertainties, most evaluation methods are limited to geometry-based metrics. Software companies have now integrated DIR tools into treatment planning systems for clinical use, such as contour propagation and fraction dose accumulation. Conclusions: DIR is increasingly important in RT applications, from planning to toxicity prediction. DIR is routinely used to reduce the workload of contour propagation. However, its use for complex dosimetric applications must be carefully evaluated by combining quantitative and qualitative analyses.

Use of Numerical Simulation to Predict Iliac Complications During Placement of An Aortic Stent Graft.

BACKGROUND: During endovascular aneurysm repair (EVAR), complex iliac anatomy is a source of complications such as unintentional coverage of the hypogastric artery. The aim of our study was to evaluate ability to predict coverage of the hypogastric artery using a biomechanical model simulating arterial deformations caused by the delivery system. METHODS: The biomechanical model of deformation has been validated by many publications. The simulations were performed on 38 patients included retrospectively, for a total of 75 iliac arteries used for the study. On the basis of objective measurements, two groups were formed: one with "complex" iliac anatomy (n = 38 iliac arteries) and the other with "simple" iliac anatomy (n = 37 iliac arteries). The simulation enabled measurement of the lengths of the aorta and the iliac arteries once deformed by the device. Coverage of the hypogastric artery was predicted if the deformed renal/iliac bifurcation length (Lpre) was less than the length of the implanted device (Lstent-measured on the postoperative computed tomography [CT]) and nondeformed Lpre was greater than Lstent. RESULTS: Nine (12%) internal iliac arteries were covered unintentionally. Of the coverage attributed to perioperative deformations, 1 case (1.3%) occurred with simple anatomy and 6 (8.0%) with complex anatomy (P = 0.25). All cases of unintentional coverage were predicted by the simulation. The simulation predicted hypogastric coverage in 35 cases (46.7%). There were therefore 26 (34.6%) false positives. The simulation had a sensitivity of 100% and a specificity of 60.6%. On multivariate analysis, the factors significantly predictive of coverage were the iliac tortuosity index (P = 0.02) and the predicted margin between the termination of the graft limb and the origin of the hypogastric artery in nondeformed (P = 0.009) and deformed (P = 0.001) anatomy. CONCLUSIONS: Numerical simulation is a sensitive tool for predicting the risk of hypogastric coverage during EVAR and allows more precise preoperative sizing. Its specificity is liable to be improved by using a larger cohort.

Automatic aortic root segmentation and anatomical landmarks detection for TAVI procedure planning.

PURPOSE: Minimally invasive trans-catheter aortic valve implantation (TAVI) has emerged as a treatment of choice for high-risk patients with severe aortic stenosis. However, the planning of TAVI procedures would greatly benefit from automation to speed up, secure and guide the deployment of the prosthetic valve. We propose a hybrid approach allowing the computation of relevant anatomical measurements along with an enhanced visualization. MATERIAL AND METHODS: After an initial step of centerline detection and aorta segmentation, model-based and statistical-based methods are used in combination with 3 D active contour models to exploit the complementary aspects of these methods and automatically detect aortic leaflets and coronary ostia locations. Important anatomical measurements are then derived from these landmarks. RESULTS: A validation on 50 patients showed good precision with respect to expert sizing for the ascending aorta diameter calculation (2.2 ± 2.1 mm), the annulus diameter (1.31 ± 0.75 mm), and both the right and left coronary ostia detection (1.96 ± 0.87 mm and 1.80 ± 0.74 mm, respectively). The visualization is enhanced thanks to the aorta and aortic root segmentation, the latter showing good agreement with manual expert delineation (Jaccard index: 0.96 ± 0.03). CONCLUSION: This pipeline is promising and could greatly facilitate TAVI planning.

An improved nonlinear diffusion in Laplacian pyramid domain for cone beam CT denoising during image-guided vascular intervention.

BACKGROUND: Cone-beam computed tomography (CBCT) acquisition during endovascular aneurysm repair is an emergent technology with more and more applications. It may provide 3-D information to achieve guidance of intervention. However, there is growing concern on the overall radiation doses delivered to patients, thus a low dose protocol is called when scanning. But CBCT images with a low dose protocol are degraded, resulting in streak artifacts and decreased contrast-to-noise ratio (CNR). In this paper, a Laplacian pyramid-based nonlinear diffusion is proposed to improve the quality of CBCT images. METHOD: We first transform the CBCT image into its pyramid domain, then a modified nonlinear diffusion is performed in each level to remove noise across edges while keeping edges as far as possible. The improved diffusion coefficient is a function of the gradient magnitude image; the threshold in the modified diffusion function is estimated using the median absolute deviation (MAD) estimator; the time step is automatically determined by iterative image changes and the iteration is stopped according to mean absolute error between two adjacent diffusions. Finally, we reconstruct the Laplacian pyramid using the processed pyramid images in each level. RESULT: Results from simulation show that the filtered image from the proposed method has the highest peak signal-noise ratio (81.92), the highest correlation coefficient (99.77%) and the lowest mean square error (27.61), compared with the other four methods. In addition, it has highest contrast-to-noise ratio and sharpness in ROIs. Results from real CBCT images show that the proposed method shows better smoothness in homogeneous regions meanwhile keeps bony structures clear. CONCLUSION: Simulation and patient studies show that the proposed method has a good tradeoff between noise/artifacts suppression and edge preservation.

Device-specific evaluation of intraventricular left ventricular assist device position by quantitative coaxiality analysis.

BACKGROUND: Patient-specific anatomy may influence the final intraventricular positioning of inflow cannula in left ventricular assist device (LVAD) recipients. An association exists between such positioning and clinical outcomes (specifically, orientation toward the interventricular septum has negative prognostic implications). Alternative commercially available LVADs are characterized by markedly different design, with potential consequences on intrathoracic fitting among individual patients. MATERIAL AND METHODS: A cohort of 13 LVAD recipients (either HeartMate II-group A or Jarvik 2000 Flowmaker-group B) was evaluated. On postoperative computed tomography scans, we reconstructed the implanted LVAD (semiautomatic segmentation), defined the target mitral orifice (3D Slicer software), and built a coordinate system to quantify the coaxiality of the cannula with the mitral valve axis (angles φ and θ, expressed as percentage variation from the ideal value φ = Î¸ = 0°). RESULTS: Group A presented significantly greater average percentage variation of the φ angle (significantly greater orientation of the intraventricular cannula toward the interventricular septum; 33.2% ± 32.1% versus 1.9% ± 0.9%, P = 0.001). Group A presented significantly greater average percentage variation of the θ angle (52.7% ± 23.6% versus 14.5% ± 6.3%, P = 0.013). CONCLUSIONS: The device assessed in group B showed in the present series better average coaxiality with the mitral orifice. Such finding is related with its design (total intraventricular placement) and interaction with thoracic structures. The present method is being integrated in the development of LVAD virtual implantation tools and may help physicians in patient-specific selection among alternative devices.

Virtual implantation of a novel LVAD: toward computer-assisted surgery for heart failure.

BACKGROUND: Mechanical and hemodynamic factors are among the determinants of patient-device interaction and early-term and long-term outcomes in left ventricular assist device (LVAD) recipients. MATERIAL AND METHODS: We are currently developing computer simulation tools aimed at (1) analyze the intrathoracic and intracavitary positioning of LVADs after implantation and establish correlation with clinical outcomes; (2) assist surgeons in the choice of device and of left ventricular coring site for optimized intrathoracic placement and function; and (3) facilitate the planning of less-invasive LVAD implantation. A virtual representation of LVAD (mesh device component) was created through cone-beam computed tomography and semiautomatic segmentation. A modular framework software (CamiTK, Grenoble, France) was used to create a three-dimensional representation of patients' computed tomography (CT) scan and incorporate the mesh device component for virtual implantation. RESULTS: Device reconstruction was included into a dedicated software with the purposes of virtual implantation, based on the preoperative CT scan of surgical candidates. CONCLUSIONS: We present herein the first digital reconstruction of the novel HeartMate 3 LVAD. Virtual implantation on the basis of preoperative CT scan is feasible within a user-friendly interactive software. Future studies will be focused on correlation with clinical variables.

Catheter navigation support for mechanical thrombectomy guidance: 3D/2D multimodal catheter-based registration with no contrast dye fluoroscopy.

PURPOSE: The fusion of pre-operative imaging and intra-operative fluoroscopy may support physicians during mechanical thrombectomy for catheter navigation from the aortic arch to carotids. Nevertheless, the aortic arch volume is too important for intra-operative contrast dye injection leading to a lack of common anatomical structure of interest that results in a challenging 3D/2D registration. The objective of this work is to propose a registration method between pre-operative 3D image and no contrast dye intra-operative fluoroscopy. METHODS: The registration method exploits successive 2D fluoroscopic images of the catheter navigating in the aortic arch. The similarity measure is defined as the normalized cross-correlation between a binary combination of catheter images and a pseudo-DRR resulting from the 2D binary projection of the pre-operative 3D image (MRA or CTA). The 3D/2D transformation is decomposed in out-plane and in-plane transformations to reduce computational complexity. The 3D/2D transformation is then obtained by maximizing the similarity measure through multiresolution exhaustive search. RESULTS: We evaluated the registration performance through dice score and mean landmark error. We evaluated the influence of parameters setting, aortic arch type and 2D navigation sequence duration. Results on a physical phantom and data from a patient who underwent a mechanical thrombectomy showed good registration accuracy with a dice score higher than 92% and a mean landmark error lower than the quarter of a carotid diameter (8-10 mm). CONCLUSION: A new registration method compatible with no contrast dye fluoroscopy has been proposed to guide the crossing from aortic arch to a carotid in mechanical thrombectomy. First evaluation showed the feasibility and accuracy of the method as well as its compatibility with clinical routine practice.

Computer-Assisted Transcatheter Mitral Valve Implantation for Valve-in-Valve Procedures.

Transcatheter mitral valve-in-valve is an alternative to high-risk reoperation on a failing bioprosthesis. It entails specific challenges such as left ventricular outflow tract obstruction. We propose a patient-specific augmented imaging based on preoperative planning to assist the procedure. Valve-in-valve simulation was performed to represent the optimal level of implantation and the neo-left ventricular outflow tract. These data were combined with intraoperative images through a real-time 3D/2D registration tool. All data were collected retrospectively on one case (pre and per-procedure imaging). We present for the first time an intraoperative guidance tool in transcatheter mitral valve-in-valve procedure.

Endovascular aortic repair of a postdissecting thoracoabdominal aneurysm using intraoperative fusion imaging.

Computer-aided imaging can aid complex endovascular repair of aortic dissections in locating the narrow true lumen and identifying perfusion of visceral vessels by the true and/or false lumen. Although these anatomic data are available for analysis during planning, they are not readily available during the procedure with conventional imaging systems. We report the use of "fusion imaging" to facilitate the treatment of a postdissection thoracoabdominal aneurysm. The preoperative computer tomographic angiograms were processed, and the true and the false lumens were individually color labeled. These data were then superimposed on the fluoroscopic images in order to facilitate deployment of a fenestrated endograft.

Computed tomography image processing to detect the real mechanism of bioprosthesis failure: implication for valve-in-valve implantation.

BACKGROUND AND AIM OF THE STUDY: Transcatheter valve-in-valve implantation is an emerging option for patients with structural deterioration of an aortic bioprosthesis and who are at a high surgical risk. The present case underlines the need for dedicated imaging to accurately understand the mechanism of valve failure, and the feasibility of a valve-in-valve procedure. METHODS: A patient with structural bioprosthetic deterioration at echocardiography was investigated using computed tomography (CT) scanning and novel 3D slicer software. The findings were compared with those revealed at intraoperative pathology. RESULTS: Post-processed CT images showed the bulk of calcifications to be located at the subvalvular level, suggesting the presence of calcified pannus. Pathology of the explanted valve confirmed that the valve stenosis was due primarily to pannus. Misdiagnosed calcified pannus represents a major threat during valve-in-valve procedures, due mainly to embolic risk. CONCLUSION: The 3D slicer elaboration of CT images may be invaluable in providing a precise definition of the mechanism of valve failure, and also to establish the feasibility of either a valve-in-valve procedure or conventional surgery.

Deep-learning approach to automate the segmentation of aorta in non-contrast CTs.

Purpose: Segmentation of vascular structures in preoperative computed tomography (CT) is a preliminary step for computer-assisted endovascular navigation. It is a challenging issue when contrast medium enhancement is reduced or impossible, as in the case of endovascular abdominal aneurysm repair for patients with severe renal impairment. In non-contrast-enhanced CTs, the segmentation tasks are currently hampered by the problems of low contrast, similar topological form, and size imbalance. To tackle these problems, we propose a novel fully automatic approach based on convolutional neural network. Approach: The proposed method is implemented by fusing the features from different dimensions by three kinds of mechanisms, i.e., channel concatenation, dense connection, and spatial interpolation. The fusion mechanisms are regarded as the enhancement of features in non-contrast CTs where the boundary of aorta is ambiguous. Results: All of the networks are validated by three-fold cross-validation on our dataset of non-contrast CTs, which contains 5749 slices in total from 30 individual patients. Our methods achieve a Dice score of 88.7% as the overall performance, which is better than the results reported in the related works. Conclusions: The analysis indicates that our methods yield a competitive performance by overcoming the above-mentioned problems in most general cases. Further, experiments on our non-contrast CTs demonstrate the superiority of the proposed methods, especially in low-contrast, similar-shaped, and extreme-sized cases.

Patient-specific finite element simulation of peripheral artery percutaneous transluminal angioplasty to evaluate the procedure outcome without stent implantation.

The purpose of this work is to present a patient-specific (PS) modeling approach for simulating percutaneous transluminal angioplasty (PTA) endovascular treatment and assessing the balloon sizing influence on short-term outcomes in peripheral arteries, i.e. without stent implantation. Two 3D PS stenosed femoral artery models, one with a dominant calcified atherosclerosis while the other with a lipidic plaque, were generated from pre-operative computed tomography angiography images. Elastoplastic constitutive laws were implemented within the plaque and artery models. Implicit finite element method (FEM) was used to simulate the balloon inflation and deflation for different sizings. Besides vessel strains, results were mainly evaluated in terms of the elastic recoil ratio (ERR) and lumen gain ratio (LGR) attained immediately after PTA. Higher LGR values were shown within the stenosed region of the lipidic patient. Simulated results also showed a direct and quantified correlation between balloon sizing and LGR and ERR for both patients after PTA, with a more significant influence on the lumen gain. The max principal strain values in the outer arterial wall increased at higher balloon sizes during inflation as well, with higher rates of increase when the plaque was calcified. Results show that our model could serve in finding a compromise for each stenosis type: maximizing the achieved lumen gain after PTA, but at the same time without damaging the arterial tissue. The proposed methodology can serve as a step toward a clinical decision support system to improve angioplasty balloon sizing selection prior to the surgery.

Computer-aided shape features extraction and regression models for predicting the ascending aortic aneurysm growth rate.

OBJECTIVE: ascending aortic aneurysm growth prediction is still challenging in clinics. In this study, we evaluate and compare the ability of local and global shape features to predict the ascending aortic aneurysm growth. MATERIAL AND METHODS: 70 patients with aneurysm, for which two 3D acquisitions were available, are included. Following segmentation, three local shape features are computed: (1) the ratio between maximum diameter and length of the ascending aorta centerline, (2) the ratio between the length of external and internal lines on the ascending aorta and (3) the tortuosity of the ascending tract. By exploiting longitudinal data, the aneurysm growth rate is derived. Using radial basis function mesh morphing, iso-topological surface meshes are created. Statistical shape analysis is performed through unsupervised principal component analysis (PCA) and supervised partial least squares (PLS). Two types of global shape features are identified: three PCA-derived and three PLS-based shape modes. Three regression models are set for growth prediction: two based on gaussian support vector machine using local and PCA-derived global shape features; the third is a PLS linear regression model based on the related global shape features. The prediction results are assessed and the aortic shapes most prone to growth are identified. RESULTS: the prediction root mean square error from leave-one-out cross-validation is: 0.112 mm/month, 0.083 mm/month and 0.066 mm/month for local, PCA-based and PLS-derived shape features, respectively. Aneurysms close to the root with a large initial diameter report faster growth. CONCLUSION: global shape features might provide an important contribution for predicting the aneurysm growth.

Assessment of shape-based features ability to predict the ascending aortic aneurysm growth.

The current guidelines for the ascending aortic aneurysm (AsAA) treatment recommend surgery mainly according to the maximum diameter assessment. This criterion has already proven to be often inefficient in identifying patients at high risk of aneurysm growth and rupture. In this study, we propose a method to compute a set of local shape features that, in addition to the maximum diameter D, are intended to improve the classification performances for the ascending aortic aneurysm growth risk assessment. Apart from D, these are the ratio DCR between D and the length of the ascending aorta centerline, the ratio EILR between the length of the external and the internal lines and the tortuosity T. 50 patients with two 3D acquisitions at least 6 months apart were segmented and the growth rate (GR) with the shape features related to the first exam computed. The correlation between them has been investigated. After, the dataset was divided into two classes according to the growth rate value. We used six different classifiers with input data exclusively from the first exam to predict the class to which each patient belonged. A first classification was performed using only D and a second with all the shape features together. The performances have been evaluated by computing accuracy, sensitivity, specificity, area under the receiver operating characteristic curve (AUROC) and positive (negative) likelihood ratio LHR+ (LHR-). A positive correlation was observed between growth rate and DCR (r = 0.511, p = 1.3e-4) and between GR and EILR (r = 0.472, p = 2.7e-4). Overall, the classifiers based on the four metrics outperformed the same ones based only on D. Among the diameter-based classifiers, k-nearest neighbours (KNN) reported the best accuracy (86%), sensitivity (55.6%), AUROC (0.74), LHR+ (7.62) and LHR- (0.48). Concerning the classifiers based on the four shape features, we obtained the best accuracy (94%), sensitivity (66.7%), specificity (100%), AUROC (0.94), LHR+ (+∞) and LHR- (0.33) with support vector machine (SVM). This demonstrates how automatic shape features detection combined with risk classification criteria could be crucial in planning the follow-up of patients with ascending aortic aneurysm and in predicting the possible dangerous progression of the disease.

Validation of a Whole Heart Segmentation from Computed Tomography Imaging Using a Deep-Learning Approach.

The aim of this study is to develop an automated deep-learning-based whole heart segmentation of ECG-gated computed tomography data. After 21 exclusions, CT acquired before transcatheter aortic valve implantation in 71 patients were reviewed and randomly split in a training (n = 55 patients), validation (n = 8 patients), and a test set (n = 8 patients). A fully automatic deep-learning method combining two convolutional neural networks performed segmentation of 10 cardiovascular structures, which was compared with the manually segmented reference by the Dice index. Correlations and agreement between myocardial volumes and mass were assessed. The algorithm demonstrated high accuracy (Dice score = 0.920; interquartile range: 0.906-0.925) and a low computing time (13.4 s, range 11.9-14.9). Correlations and agreement of volumes and mass were satisfactory for most structures. Six of ten structures were well segmented. Deep-learning-based method allowed automated WHS from ECG-gated CT data with a high accuracy. Challenges remain to improve right-sided structures segmentation and achieve daily clinical application.

Statistical shape model of vessel centerline for endovascular paths comparison in mechanical thrombectomy.

Endovascular interventions are experiencing an important development. Despite many advantages of this type of intervention, catheter navigation is still a cause of difficulties or failure. Mechanical thrombectomy is one of these interventions where navigation difficulties are related to the ability to navigate the aortic arch and access the carotid. These difficulties are due to the selection of adequate catheters and guides for a specific anatomy and to the technical gesture to operate. The objective of this work is to propose a method to find similar endovascular navigation paths from pre-existing patients to support intervention in mechanical thrombectomy. For each patient, iso-centerlines of the aortic arch and supra-aortic trunks are extracted from pre-operative magnetic resonance angiography volume. A statistical shape model is computed from these vascular structure iso-centerlines. Euclidean distance between vectors of statistical shape model modes is used to compare endovascular navigation paths. A set of 6 patient cases was used to compute the statistical shape model. For validation, an additional set of 5 patient cases was considered to generate new iso-centerlines.Retrieval of closest iso-centerlines were correct in more than 95% of cases with the proposed method while this percentage goes down to 43% with Euclidean distance between 3D points of iso-centerlines.Clinical relevance-The presented method allows physicians to retrieve past navigation paths similar to a new one. Used in planning, this could allow to anticipate navigation difficulties in mechanical thrombectomy.

Numerical simulation of fenestrated graft deployment: Anticipation of stent graft and vascular structure adequacy.

Fenestrated endovascular aneurism repair (FEVAR) is a minimally invasive technique, and its success depends on the adequacy of the correspondence between the visceral arteries ostia and position of the fenestrations of the stent graft (SG) during its deployment in juxtarenal aneurisms. However, the fenestration position is generally determined from a preoperative computerised tomography (CT) scan, without considering the vascular deformation induced by the insertion of the endovascular tools. Catheterisation difficulties may occur during clinical procedures. Accordingly, the objective of this work is to present an initial proof of concept aimed at anticipating and optimising the position of the fenestrations, while considering the vascular deformation induced by the insertion of the endovascular tools. The proposed method relies on the finite element method to simulate the SG deployment in a vascular structure (VS), and considers the vascular deformation induced by the tools. After determining the optimal simulation parameters for a patient-specific case, the robustness of the method is demonstrated on six other representative anatomies. The simulated SG is also compared with post-deployment CT observations, and demonstrates good adequacy. The results show that the numerically corrected fenestration positions, as determined from the simulated results following the insertion of the endovascular tools, deviate from those of the standard plan (as determined from the preoperative CT scan). This indicates that the SG-VS adequacy could be improved via simulation-based planning, to anticipate potential catheterisation difficulties.

Influence of balloon design, plaque material composition, and balloon sizing on acute post angioplasty outcomes: An implicit finite element analysis.

In this work we propose a generic modeling approach for simulating percutaneous transluminal angioplasty (PTA) endovascular treatment, and evaluating the influence of balloon design, plaque composition, and balloon sizing on acute post-procedural outcomes right after PTA, without stent implantation. Clinically-used PTA balloons were classified into two categories according to their compliance characteristics, and were modeled correspondingly. Self-defined elastoplastic constitutive laws were implemented within the plaque and artery models, after calibration based on experimental and clinical data. Finite element method (FEM) implicit solver was used to simulate balloon inflation and deflation. Besides balloon profile at max inflation, results are mainly assessed in terms of the elastic recoil ratio (ERR) and lumen gain ratio (LGR) obtained immediately after PTA. No variations in ERR nor LGR values were detected when the balloon design changed, despite the differences observed in their profile at max inflation. Moreover, LGR and ERR inversely varied with the augmentation of calcification level within the plaque (-11% vs. +4% respectively, from fully lipidic to fully calcified plaque). Furthermore, results showed a direct correlation between balloon sizing and LGR and ERR, with noticeably higher rates of change for LGR (+18% and +2% for LGR and ERR respectively for a calcified plaque and a balloon pressure increasing from 10 to 14 atm). However a larger LGR comes with a higher risk of arterial rupture. This proposed methodology opens the way for evaluation of angioplasty balloon selections towards clinical procedure optimization.

Sizing for endovascular aneurysm repair: clinical evaluation of a new automated three-dimensional software.

BACKGROUND: To assess the reproducibility and accuracy of the sizing procedure before aortic endograft implantation using new sizing automated software as compared with standard radiological procedures. METHODS: On the basis of original spiral-computed tomography images, the sizing of 32 patients with abdominal aortic aneurysm treated by endovascular aneurysm repair (EVAR) was retrospectively compared. The first sizing was performed by a radiologist using a standard workstation (General electrics) and software (Advanced vessel analysis). The second was performed twice by two surgeons using a personal computer with automatic three-dimensional sizing software (Endosize; Therenva, Rennes, France). All diameters and lengths required before EVAR were measured (17 items). Moreover, 13 qualitative criteria regarding EVAR feasibility, including neck length, were compared. Intra- and interobserver variability with Endosize, as well as the variability between the two measurement methods were analyzed using the intraclass correlation coefficient (ICC) and Bland and Altman's method. Qualitative variables were analyzed using Fischer's exact test and kappa coefficient. RESULTS: Intraobserver variability with Endosize proved to be efficient. None of the ICCs were lower than 0.9, and more than 90% of the absolute differences between two measurements were less than 2 mm. Interobserver variability with Endosize was assessed in a similar manner. Measurement variability of vessel diameters was less marked than that of vessel lengths. This trend was observed for all datasets. Comparison of the two measurement methods demonstrated a good correlation (minimum ICC = 0.697; maximum ICC = 0.974), although less so than that observed using Endosize. Mean time consumption using Endosize was 13.1 ± 4.53 minutes (range: 7.2-32.7). Analysis of the alarm sets demonstrated a high agreement between observers (kappa coefficient = 0.81). CONCLUSIONS: Sizing using the Endosize software is as reliable as conventional radiological procedures. Sizing by surgeons using an automated, user-friendly, and mobile tool appears to be reproducible.