Assessment of geometrical remodelling of the aortic arch after hybrid treatment.

OBJECTIVES: The aim of this study was to measure the morphological remodelling of the ascending aorta, aortic arch and thoracic aorta after aortic arch hybrid treatment including debranching and stent graft implantation. METHODS: Preoperative, 1-month and 1-year follow-up of computed tomography angiography scans of 22 patients were analysed to compute the lumen centreline from the aortic root to the coeliac trunk, and the following measurements were derived: the total centreline length, distance from the aortic root to the left subclavian artery, distance from the left subclavian artery to the distal landing zone. For both pre- and postoperative centrelines, the pointwise curvature was measured at the proximal and the distal landing zones. The mean curvature values of the whole aortic segment and the endografting region of the ascending and the descending aorta were measured. Surface outerline was computed as well, and curvature values at the endograft landing points were extracted. RESULTS: At the 1-month follow-up, centreline length were already significantly increased (382.66 ± 48.69 to 388.1 ± 50.75 mm; P = 0.01). Centreline pointwise curvature increased in the proximal (+29%, P = 0.011) and the distal zones (+63%, P = 0.004). Similarly, pointwise curvature of the outerline significantly increased in the proximal (+77%, P = 0.01) and the distal landing zones (+100%, P = 0.04). The centreline mean curvature increased in the ascending aorta (+7%, P = 0.02) and decreased in the endografting region (-3.3%, P = 0.004). No evidence of a relationship of such a remodelling with the type of endograft and the type of pathology was observed. This remodelling trend was confirmed by the analysis of 1-year computed tomography angiographies. CONCLUSIONS: Hybrid arch repair was associated with a significant elongation of the vessel and a significant increase in the curvature on the ascending aorta and the descending aorta and on the endograft proximal and the distal landing zones.

Midterm Follow-up Geometrical Analysis of Thoracoabdominal Aortic Aneurysms Treated with Multilayer Flow Modulator.

BACKGROUND: Aim of our study is the analysis of clinical results and aneurysmal sac evolution after multilayer flow modulator (MFM) placement, in patients with thoracoabdominal aortic aneurysms (TAAs). METHODS: All patients with asymptomatic TAA treated at our institution between 2012 and 2014 with MFM were retrospectively analyzed. Thirty-day evaluated outcomes were mortality and complications. Follow-up evaluated outcomes were mortality, aneurysm collateral branches patency, and reintervention. A geometrical analysis of 2-year follow-up computed tomography scans was carried out to evaluate the total aneurysm volume, the percentage of aneurysm growth, and the evolution of maximum aneurysm diameter. RESULTS: Seven patients (mean age: 71.8 years, range: 63-85 years) were considered in the study. Mean preoperative aneurysm diameter was 6.8 cm (range 6-8.3 cm). No 30-day mortality or complications were observed. Mean follow-up was 29.4 months. During follow-up, 3 deaths (42.8%) were observed, not related to MFM complications. Reintervention rate was 42.8%, occurred in all cases after 2-year follow-up; in 2 cases, the reintervention was necessary due to an excessive increase of the aneurysmal sac. During the follow-up, a mean growth rate of 6 mm/year (4 patients) for the diameter of the aneurysm external wall and a total aneurysm volume increase from 2.45 × 105 mm3 to 3.50 × 105 mm3 (4 patients) was evaluated. CONCLUSIONS: Our results have shown no mortality related to aneurysm rupture during the follow-up and high rate of reinterventions after MFM placement. Further geometrical analyses, based on the proposed approach, regarding a larger group of patients with long-term follow-up are required to draw indications about the MFM use.

A patient-specific aortic valve model based on moving resistive immersed implicit surfaces.

In this paper, we propose a full computational framework to simulate the hemodynamics in the aorta including the valve. Closed and open valve surfaces, as well as the lumen aorta, are reconstructed directly from medical images using new ad hoc algorithms, allowing a patient-specific simulation. The fluid dynamics problem that accounts from the movement of the valve is solved by a new 3D-0D fluid-structure interaction model in which the valve surface is implicitly represented through level set functions, yielding, in the Navier-Stokes equations, a resistive penalization term enforcing the blood to adhere to the valve leaflets. The dynamics of the valve between its closed and open position is modeled using a reduced geometric 0D model. At the discrete level, a finite element formulation is used and the SUPG stabilization is extended to include the resistive term in the Navier-Stokes equations. Then, after time discretization, the 3D fluid and 0D valve models are coupled through a staggered approach. This computational framework, applied to a patient-specific geometry and data, allows to simulate the movement of the valve, the sharp pressure jump occurring across the leaflets, and the blood flow pattern inside the aorta.

Numerical modeling of hemodynamics scenarios of patient-specific coronary artery bypass grafts.

A fast computational framework is devised to the study of several configurations of patient-specific coronary artery bypass grafts. This is especially useful to perform a sensitivity analysis of the hemodynamics for different flow conditions occurring in native coronary arteries and bypass grafts, the investigation of the progression of the coronary artery disease and the choice of the most appropriate surgical procedure. A complete pipeline, from the acquisition of patient-specific medical images to fast parameterized computational simulations, is proposed. Complex surgical configurations employed in the clinical practice, such as Y-grafts and sequential grafts, are studied. A virtual surgery platform based on model reduction of unsteady Navier-Stokes equations for blood dynamics is proposed to carry out sensitivity analyses in a very rapid and reliable way. A specialized geometrical parameterization is employed to compare the effect of stenosis and anastomosis variation on the outcome of the surgery in several relevant cases.

Fractional flow reserve based on computed tomography: an overview.

Computed tomography coronary angiography (CTCA) is a technique proved to provide high sensitivity and negative predictive value for the identification of anatomically significant coronary artery disease (CAD) when compared with invasive X-ray coronary angiography. While the CTCA limitation of a ionizing radiation dose delivered to patients is substantially overcome by recent technical innovations, a relevant limitation remains the only anatomical assessment of coronary stenoses in the absence of evaluation of their functional haemodynamic significance. This limitation is highly important for those stenosis graded as intermediate at the anatomical assessment. Recently, non-invasive methods based on computational fluid dynamics were developed to calculate vessel-specific fractional flow reserve (FFR) using data routinely acquired by CTCA [computed tomographic fractional flow reserve (CT-FFR)]. Here we summarize methods for CT-FFR and review the evidence available in the literature up to June 26, 2016, including 16 original articles and one meta-analysis. The perspective of CT-FFR may greatly impact on CAD diagnosis, prognostic evaluation, and treatment decision-making. The aim of this review is to describe technical characteristics and clinical applications of CT-FFR, also in comparison with catheter-based invasive FFR, in order to make a cost-benefit balance in terms of clinical management and patient's health.

Towards the Personalized Treatment of Glioblastoma: Integrating Patient-Specific Clinical Data in a Continuous Mechanical Model.

Glioblastoma multiforme (GBM) is the most aggressive and malignant among brain tumors. In addition to uncontrolled proliferation and genetic instability, GBM is characterized by a diffuse infiltration, developing long protrusions that penetrate deeply along the fibers of the white matter. These features, combined with the underestimation of the invading GBM area by available imaging techniques, make a definitive treatment of GBM particularly difficult. A multidisciplinary approach combining mathematical, clinical and radiological data has the potential to foster our understanding of GBM evolution in every single patient throughout his/her oncological history, in order to target therapeutic weapons in a patient-specific manner. In this work, we propose a continuous mechanical model and we perform numerical simulations of GBM invasion combining the main mechano-biological characteristics of GBM with the micro-structural information extracted from radiological images, i.e. by elaborating patient-specific Diffusion Tensor Imaging (DTI) data. The numerical simulations highlight the influence of the different biological parameters on tumor progression and they demonstrate the fundamental importance of including anisotropic and heterogeneous patient-specific DTI data in order to obtain a more accurate prediction of GBM evolution. The results of the proposed mathematical model have the potential to provide a relevant benefit for clinicians involved in the treatment of this particularly aggressive disease and, more importantly, they might drive progress towards improving tumor control and patient's prognosis.

Computational generation of the Purkinje network driven by clinical measurements: the case of pathological propagations.

To properly describe the electrical activity of the left ventricle, it is necessary to model the Purkinje fibers, responsible for the fast and coordinate ventricular activation, and their interaction with the muscular propagation. The aim of this work is to propose a methodology for the generation of a patient-specific Purkinje network driven by clinical measurements of the activation times related to pathological propagations. In this case, one needs to consider a strongly coupled problem between the network and the muscle, where the feedback from the latter to the former cannot be neglected as in a normal propagation. We apply the proposed strategy to data acquired on three subjects, one of them suffering from muscular conduction problems owing to a scar and the other two with a muscular pre-excitation syndrome (Wolff-Parkinson-White). To assess the accuracy of the proposed method, we compare the results obtained by using the patient-specific Purkinje network generated by our strategy with the ones obtained by using a non-patient-specific network. The results show that the mean absolute errors in the activation time is reduced for all the cases, highlighting the importance of including a patient-specific Purkinje network in computational models.

Patient-specific generation of the Purkinje network driven by clinical measurements of a normal propagation.

The propagation of the electrical signal in the Purkinje network is the starting point for the activation of the ventricular muscular cells leading to the contraction of the ventricle. In the computational models, describing the electrical activity of the ventricle is therefore important to account for the Purkinje fibers. Until now, the inclusion of such fibers has been obtained either by using surrogates such as space-dependent conduction properties or by generating a network based on an a priori anatomical knowledge. The aim of this work was to propose a new method for the generation of the Purkinje network using clinical measures of the activation times on the endocardium related to a normal electrical propagation, allowing to generate a patient-specific network. The measures were acquired by means of the EnSite NavX system. This system allows to measure for each point of the ventricular endocardium the time at which the activation front, that spreads through the ventricle, has reached the subjacent muscle. We compared the accuracy of the proposed method with the one of other strategies proposed so far in the literature for three subjects with a normal electrical propagation. The results showed that with our method we were able to reduce the absolute errors, intended as the difference between the measured and the computed data, by a factor in the range 9-25 %, with respect to the best of the other strategies. This highlighted the reliability of the proposed method and the importance of including a patient-specific Purkinje network in computational models.

Helical flows and asymmetry of blood jet in dilated ascending aorta with normally functioning bicuspid valve.

Bicuspid aortic valve (BAV) is associated with aortic dilatation and aneurysm. Several studies evidenced an eccentric systolic flow in ascending aorta associated with increased wall shear stresses (WSS) and the occurrence of an helical systolic flow. This study seeks to elucidate the connections between jet asymmetry and helical flow in patients with normally functioning BAV and dilated ascending aorta. We performed a computational parametric study by varying, for a patient-specific geometry, the valve area and the flow rate entering the aorta and drawing also a tricuspid valve (TAV). We considered also phase-contrast magnetic resonance imaging of four BAV and TAV patients. Measurement of normalized flow asymmetry index, systolic WSS and of a new index (positive helix fraction, PHF) quantifying the presence of a single a single helical flow were performed. In our computation, BAV cases featured higher values of all indices with respect to TAV in both numerical and imaged-based results. Moreover, all indices increased with decreasing valve area and/or with increasing flow rate. This allowed to separate the BAV and TAV cases with respect to the jet asymmetry, WSS localization and helical flow. Interestingly, these results were obtained without modeling the leaflets.

Introducing the Jacobian-volume-histogram of deforming organs: application to parotid shrinkage evaluation.

The Jacobian of the deformation field of elastic registration between images taken during radiotherapy is a measure of inter-fraction local deformation. The histogram of the Jacobian values (Jac) within an organ was introduced (JVH-Jacobian-volume-histogram) and first applied in quantifying parotid shrinkage. MVCTs of 32 patients previously treated with helical tomotherapy for head-neck cancers were collected. Parotid deformation was evaluated through elastic registration between MVCTs taken at the first and last fractions. Jac was calculated for each voxel of all parotids, and integral JVHs were calculated for each parotid; the correlation between the JVH and the planning dose-volume histogram (DVH) was investigated. On average, 82% (±17%) of the voxels shrinks (Jac < 1) and 14% (±17%) shows a local compression >50% (Jac < 0.5). The best correlation between the DVH and the JVH was found between V10 and V15, and Jac < 0.4-0.6 (p < 0.01). The best constraint predicting a higher number of largely compressing voxels (Jac0.5<7.5%, median value) was V15 ≥ 75% (OR: 7.6, p = 0.002). Jac and the JVH are promising tools for scoring/modelling toxicity and for evaluating organ/contour variations with potential applications in adaptive radiotherapy.

Validation of an elastic registration technique to estimate anatomical lung modification in non-small-cell lung cancer tomotherapy.

BACKGROUND: The study of lung parenchyma anatomical modification is useful to estimate dose discrepancies during the radiation treatment of Non-Small-Cell Lung Cancer (NSCLC) patients. We propose and validate a method, based on free-form deformation and mutual information, to elastically register planning kVCT with daily MVCT images, to estimate lung parenchyma modification during Tomotherapy. METHODS: We analyzed 15 registrations between the planning kVCT and 3 MVCT images for each of the 5 NSCLC patients. Image registration accuracy was evaluated by visual inspection and, quantitatively, by Correlation Coefficients (CC) and Target Registration Errors (TRE). Finally, a lung volume correspondence analysis was performed to specifically evaluate registration accuracy in lungs. RESULTS: Results showed that elastic registration was always satisfactory, both qualitatively and quantitatively: TRE after elastic registration (average value of 3.6 mm) remained comparable and often smaller than voxel resolution. Lung volume variations were well estimated by elastic registration (average volume and centroid errors of 1.78% and 0.87 mm, respectively). CONCLUSIONS: Our results demonstrate that this method is able to estimate lung deformations in thorax MVCT, with an accuracy within 3.6 mm comparable or smaller than the voxel dimension of the kVCT and MVCT images. It could be used to estimate lung parenchyma dose variations in thoracic Tomotherapy.

An automatic deformable registration method to evaluate parotid glands shrinkage during radiotherapy treatment in Tomotherapy.

The aim of this study is to provide a method to track the anatomical alterations of parotid glands during radiation treatment. The method we implemented is based on an intensity-based free-form deformable registration to realign the planning kilo-Voltage CT (kVCT) and the daily Mega-Voltage (MVCT) image sets and on an automatic contour propagation algorithm based on surface construction by triangular mesh. The accuracy of the method was evaluated through visual inspection and comparison with manual contours drawn by expert physicians. The uncertainties of automatic contours were similar to those of manual contours, in terms of parotid volumes and center-of-mass distances. The parotid volumes decreased with a median total loss of 21.7%. We observed an average medial shift of parotid center-of-mass of 3.1 mm from the external part toward the midline. The deformable registration method presented in this work provides an accurate tool for the automatic evaluation of parotid changes occurring during a radiotherapy treatment period.

Lesion quantification in oncological positron emission tomography: a maximum likelihood partial volume correction strategy.

A maximum likelihood (ML) partial volume effect correction (PVEC) strategy for the quantification of uptake and volume of oncological lesions in 18F-FDG positron emission tomography is proposed. The algorithm is based on the application of ML reconstruction on volumetric regional basis functions initially defined on a smooth standard clinical image and iteratively updated in terms of their activity and volume. The volume of interest (VOI) containing a previously detected region is segmented by a k-means algorithm in three regions: A central region surrounded by a partial volume region and a spill-out region. All volume outside the VOI (background with all other structures) is handled as a unique basis function and therefore "frozen" in the reconstruction process except for a gain coefficient. The coefficients of the regional basis functions are iteratively estimated with an attenuation-weighted ordered subset expectation maximization (AWOSEM) algorithm in which a 3D, anisotropic, space variant model of point spread function (PSF) is included for resolution recovery. The reconstruction-segmentation process is iterated until convergence; at each iteration, segmentation is performed on the reconstructed image blurred by the system PSF in order to update the partial volume and spill-out regions. The developed PVEC strategy was tested on sphere phantom studies with activity contrasts of 7.5 and 4 and compared to a conventional recovery coefficient method. Improved volume and activity estimates were obtained with low computational costs, thanks to blur recovery and to a better local approximation to ML convergence.