Background: Cardiotoxicity is a well-known adverse effect of various chemotherapeutic agents that can be monitored by echocardiography. A decrease in left ventricular ejection fraction (LVEF) triggers consideration for therapy modification or interruption. The aim of this study was to evaluate how variability in LVEF estimates computed using three-dimensional echocardiography could influence cardiotoxicity onset detection. Methods: One hundred eighty one patients with breast cancer treated with anthracycline and trastuzumab were analyzed. LVEF was computed using two commercial software packages. In a subgroup of 40 patients, three-dimensional echocardiographic data were reanalyzed to assess intra-and interobserver variability by two expert investigators using both packages. Global longitudinal strain (GLS) imaging was evaluated in 64 patients. Results: End-diastolic volume, end-systolic volume, and LVEF measurements obtained applying the two software packages were in good agreement, with small bias and acceptable limits of agreement. Intra-and interobserver variability was smaller using one of the two software packages. However, for both packages, variability indexes were in the range of affecting LVEF estimates at a level that could lead to an inaccurate assessment of cardiac adverse effects of cancer therapeutic drugs. On the basis of LVEF, 11 of 181 patients (6.1%) had cardiotoxicity at 3-month follow-up. The absolute value of GLS was smaller in 16 of 64 patients (25%) thought to have cardiotoxicity on the basis of GLS results, including six of seven patients who had cardiotoxicity considering LVEF in this subgroup. Conclusions: Following clinical definition of cardiotoxicity onset, variability in LVEF computation by threedimensional echocardiography could be a confounding factor for cardiotoxicity diagnosis, and different software packages should not be used interchangeably for LVEF monitoring. GLS confirms its predictive value for subsequent cardiotoxicity.

The aim of this retrospective study was to detect early cardiotoxicity by speckle tracking analysis. We analyzed 2D and 3D echocardiographic datasets (2DE and 3DE) in 65 patients treated for breast cancer with anthracycline and trastuzumab. We compared the temporal variations of the left ventricular ejection fraction (LVEF) obtained analyzing 2D and 3D datasets and of the strain values computed before, during and after chemotherapy administration. In addition, in a subgroup of 45 patients a complete echocardiographic examination was performed 6 months after completion of therapy. Cardiotoxicity onset definition varies depending on the method used to compute LVEF (16.9% by 2DE and 50.8% by 3DE). Thirty-three patients developed cardiotoxicity. Nine of them showed a reduction of longitudinal and radial strain values before LVEF reduction at the 16th week. Through 3D speckle tracking analysis early diagnosis of the cardio-toxicity onset seems achievable allowing the planning of cardio protective therapy without interrupting chemotherapy administration.

The aim of this study was to evaluate if variability in EF estimate from echocardiographic data acquired with two dimensional (2DE) and three-dimensional (3DE) systems and analyzed using different software packages could affect cardio-toxicity assessment. We analyzed 2DE and 3DE datasets in 94 patients treated for breast cancer with anthracycline and trastuzumab. EF was computed from 2DE and 3DE data using two software packages (EchoPAC, GE Healthcare and TomTec 4D LV analysis). Corresponding estimates were compared. In addition, in a subgroup of 20 patients 3DE data were re-analyzed and intra-observer and inter-observer variability by three investigators were computed, using both software packages. As expected 2DE-based estimates significantly underestimated 3DE-based estimates. Intra-observer and inter-observer variability using both analysis packages showed a huge variability, due to significant differences in end systolic volume and EF. Following clinical definition of cardio-toxicity onset, these variability results could be a confounding factor since variations in EF measurement are in the range of EF decrease due to cardiac adverse effects from cancer therapeutic drugs.

Tricuspid valve (TV) dilatation is associated with tricuspid regurgitation and right ventricular failure. Pulmonary hypertension (PH) secondary to mitral valve disease is a common cause of TV dilatation. Decision regarding when to surgically repair the TV, while operating on the mitral valve, is a topic of debate, and is frequently based solely on 2D echocardiographic measurement of TV diameters. To facilitate decision-making, we sought to develop software for 3D analysis of TV morphology from real-time 3D echocardiographic images. Novel custom software was used to trace and measure TV annulus (TA) in 10 patients with PH and 10 control subjects (CTRL). To trace the TA, 10 rotated planes (18° apart) were displayed and two TA points were selected in each plane. Points were interpolated using smooth splines. The following parameters were automatically computed in 3D: area, perimeter, height, eccentricity, segment lengths, diameters and segmental annulus curvature. Compared to CTRL, in patients with PH, the TA was: (1) bigger and less planar; (2) less elliptical, i.e. more round Interestingly, changes in annular shape were not uniform, as the anterior and posterior segments showed altered segment lengths and curvature, while the septal segment remained unchanged Our new software revealed that PH affects both size and shape of the TA, suggesting that 3D analysis may be useful for pre-surgical evaluation of TV pathology.

Cardiotoxicity is a well-known adverse effect of various chemotherapeutic agents that can be monitored by echocardiography. A decrease of left ventricular ejection fraction (LVEF) during the therapy might indicate dangerous effects of the drug on the myocardium and triggers consideration of therapy modification or interruption. We hypothesized myocardial deformation could identify preclinical myocardial dysfunction earlier than conventional LVEF allowing the administration of treatments to avoid cardiac side-effects. Sixty-five patients who were newly diagnosed with breast cancer, were enrolled to be evaluated by echocardiography before cancer therapy, during the therapy at 16 weeks (16w) and at follow up after 32 weeks (32w). Following the recommendation, 24 patients (36.9%) showed cardiotoxicity; 11 (16.9%) interrupted the therapy due to a severe cardiac dysfunction and at 32w only 4 patients recovered. In this group at 16w, strain analysis showed a significant reduction for all strain values that were all predictive of cardiotoxicity independently from LVEF and radial strain resulted an independent prognostic index of cardiotoxicity. The assessment of myocardial deformation indexes might provide additional echocardiographic tools to assess cardio-toxic effects beyond LVEF.

The goal of this study was to develop a near-automated technique for the segmentation of left ventricular (LV) endo- and epicardial as well as right ventricular (RV) endocardial contours from cardiac magnetic resonance (CMR) images. The newly developed technique was tested against conventional manual tracing. Our approach is based on a 3D narrow-band statistical level-set algorithm (applied to a stack of CMR short-axis images) followed by several refinement steps. This technique was tested on steady-state free precession (SSFP) CMR images acquired during 10-15 sec breathholds in 6 patients, including a total of 120 images. Computational time was around 3 min for a stack of 10 slices. For performance evaluation, an experienced interpreter manually traced ventricular contours on all the images. Quantitative error metrics (Hausdorff distance, HD; mean absolute distance, MAD, Dice coefficient, DC) were computed between automatically identified and manually traced contours. Bland-Altman and linear regression analyses were also performed between automatically and manually computed ventricular volumes. The results (MAD: LV Endo = 1.3±0.7 px, RV Endo = 1.7±1.2 px, LV Epi = 1.5±0.7 px) indicate that fast and accurate identification of LV and RV contours using 3D narrow-band statistical level-sets is feasible.

The first part of this chapter reviews the design, implementation, and customer experience with the OLDES SW tele-care platform developed within the EU project Older people’s e-services at home. The OLDES solution has been successfully tested at two different locations: in Italy with the participation of a group of 100 seniors (including 10 senior citizens suffering from heart disease), and in the Czech Republic, with the involvement of a group of 10 diabetic patients. The suggested OLDES approach proved to be an effective solution for municipalities, hospitals, and their contact centres for providing health and social services. The project partners therefore decided to develop a second generation of the system called SPES (Support to Patients through E-Service Solutions), which started in April 2011. The SPES project aims at transferring the original approach and results achieved in implementing the OLDES focusing on new target problem domains: dementia, mobility-challenged persons, respiratory problems, and social exclusion.

The angle between the mitral and aortic valves (MAA) facilitates blood flow ejection in physiological condition. Also the narrowing of MAA increases the risk of systolic anterior movement. By convention, MAA is measured in the 2D echo image (2DE) representing the 3-chambers view (3-ch). However, changes in 3-ch view selection may lead to significant changes in the measured 2D angle, due to the 3D shape of the two annuli. Real-time 3D echo (3DE) represents an alternative way to study MAA. Accordingly, our aim was to measure the impact of minimal variation in 3-ch selection on MAA computation, compared to MAA measured with 3DE (MAA3D). On 3DE data of 21 randomly chosen subjects, aortic and mitral annuli (AoA, MA) were traced using custom software. MAA3D was measured as the angle between the best fitting planes of the two traced annuli. To simulate 2D MAA measurements, the 3D data was sliced: 1) at the position corresponding to 3-ch; 2) using 20 translated planes (1mm step) on both sides of the 3-ch; 3) using 40 rotated planes (1 degree step) around MA saddle point. The intersection of the traced annuli with these planes was used to automatically measure MAA in 2D. Results showed that even slight misalignment (>1mm and >10°) of 2D cut-plane from the ideal 3-ch leads to MAA measures that differ from MAA3D.

Delayed Enhancement Magnetic Resonance Imaging can be used to non-invasively differentiate viable from non-viable myocardium within the Left Ventricle in patients suffering from myocardial diseases. Automated segmentation of scarified tissue can be used to accurately quantify the percentage of myocardium affected. This paper presents a method for cardiac scar detection and segmentation based on supervised learning and level set segmentation. First, a model of the appearance of scar tissue is trained using a Support Vector Machines classifier on image-derived descriptors. Based on the areas detected by the classifier, an accurate segmentation is performed using a segmentation method based on level sets.

PURPOSE To develop and validate a technique for near-automated definition of myocardial regions of interest suitable for perfusion evaluation during vasodilator stress cardiac magnetic resonance (MR) imaging. MATERIALS AND METHODS The institutional review board approved the study protocol, and all patients provided informed consent. Image noise density distribution was used as a basis for endocardial and epicardial border detection combined with nonrigid registration. This method was tested in 42 patients undergoing contrast material-enhanced cardiac MR imaging (at 1.5 T) at rest and during vasodilator (adenosine or regadenoson) stress, including 15 subjects with normal myocardial perfusion and 27 patients referred for coronary angiography. Contrast enhancement-time curves were near-automatically generated and were used to calculate perfusion indexes. The results were compared with results of conventional manual analysis, using quantitative coronary angiography results as a reference for stenosis greater than 50%. Statistical analyses included the Student t test, linear regression, Bland-Altman analysis, and κ statistics. RESULTS Analysis of one sequence required less than 1 minute and resulted in high-quality contrast enhancement curves both at rest and stress (mean signal-to-noise ratios, 17±7 [standard deviation] and 22±8, respectively), showing expected patterns of first-pass perfusion. Perfusion indexes accurately depicted stress-induced hyperemia (increased upslope, from 6.7 sec(-1)±2.3 to 15.6 sec(-1)±5.9; P<.0001). Measured segmental pixel intensities correlated highly with results of manual analysis (r=0.95). The derived perfusion indexes also correlated highly with (r up to 0.94) and showed the same diagnostic accuracy as manual analysis (area under the receiver operating characteristic curve, up to 0.72 vs 0.73). CONCLUSION Despite the dynamic nature of contrast-enhanced image sequences and respiratory motion, fast near-automated detection of myocardial segments and accurate quantification of tissue contrast is feasible at rest and during vasodilator stress. This technique, shown to be as accurate as conventional manual analysis, allows detection of stress-induced perfusion abnormalities.

Cardiac resynchronization therapy (CRT) is an effective treatment for chronic symptomatic systolic heart failure with cardiac dyssynchrony, but about one-third of patients do not respond favorably to the therapy. We tested the hypothesis that changes in the movements of coronary sinus (CS) electrode tip during the cardiac cycle, induced by the start of biventricular pacing could be related to resynchronization process and predictive of CRT response. In 13 CHF patients submitted to CRT implant, a previously validated method for CS lead tracking throughout cardiac cycles in 3D was applied, before (t-1) and immediately after (t0) the turn-on of biventricular pacing. The variations in several parameters describing CS lead's 3D trajectory at t0 with respect to t-1 were compared between echo responder and non-responder patients. Preliminary data showed a significantly more circular and smooth trajectory as an immediate result of the CRT turning-on in the echo-responder group. Therefore, 3D trajectories could describe features of resynchronization start-up in CRT recipients and could help to understand the reasons of therapy failure in non-responder patients.

We developed an automated technique for non-rigid image registration as a basis for tracking the heart in contrast-enhanced cardiac magnetic resonance (CMR) image sequences. The goal of the present work was to validate this technique against conventional manual analysis. Our approach is based on a multi-scale extension of the normalized 2D cross-correlation algorithm in combination with level-set methods. This technique was tested on short-axis CMR (Philips 1.5T) image sequences obtained in 11 patients at the mid level of the left ventricle during first pass of a gadolinium bolus. Myocardial identification required around 5s for a 60-frame sequence. To validate the technique, myocardial boundaries were manually traced on all frames by an experienced interpreter. Comparison between automatically registered and manually traced boundaries was performed by computing Hausdorff distance (2.1±1.4px), mean absolute distance (0.9±0.7px), root mean square distance (1.0±0.8px) and Dice coefficient (0.8±0.1). These results indicate that the proposed technique allows fast and accurate non-rigid image registration, and may thus be successfully used for deformable object tracking in cardiac image sequences.

The left ventricle (LV) has been widely studied and many segmentation methods have been proposed allowing accurate volume estimation from cardiac magnetic resonance imaging (CMRI). Anatomical complexity of the right ventricle (RV) has made accurate determination of RV shape and volume difficult. We propose a fully automated method for both RV and LV segmentation from CMRI. Datasets were analysed using custom software based on a region-based level set model followed by a regularization motion, allowing dynamic endocardial contour detection. RV and LV contours were also manually traced at end-diastole (ED) and end-systole (ES). For both techniques, disk-area summation method was applied to compute volumes. Volumes at ED and ES and ejection fraction were compared. The results of this initial study provide the basis for automated, fast and accurate quantification of LV and RV size, function and volume change throughout the cardiac cycle.

Quantification of myocardial perfusion from cardiac magnetic resonance (CMR) images relies on manual tracing of myocardial regions of interest (ROIs) and their repositioning frame-by-frame throughout the contrast-enhanced image sequence. Additionally, out-of-plane motion due to patient’s respiration frequently requires that myocardial ROIs to be redrawn.This tedious and potentially inaccurate methodology hinders widespread clinical use of imaging-based quantification of myocardial perfusion.

The need for high-quality out-of-hospital healthcare is a known socioeconomic problem. Exploiting ICT's evolution, ad-hoc telemedicine solutions have been proposed in the past. Integrating such ad-hoc solutions in order to cost-effectively support the entire healthcare cycle is still a research challenge. In order to handle the heterogeneity of relevant information and to overcome the fragmentation of out-of-hospital instrumentation in person-centric healthcare systems, a shared and open source interoperability component can be adopted, which is ontology driven and based on the semantic web data model. The feasibility and the advantages of the proposed approach are demonstrated by presenting the use case of real-time monitoring of patients' health and their environmental context.

Late gadolinium enhancement cardiac magnetic resonance imaging (LGE-CMRI) is the technique of choice to detect myocardial scars and assess myocardial viability. In clinical practice, this analysis is performed qualitatively or by manually tracing the enhanced area in each acquired slice. The purpose of this study was to test and validate a technique for automated localization and quantification of scar extent. CMRI data in patients with previous myocardial infarction were analyzed using custom software from which the myocardium was automatically identified from steady-state free precession images and registered on LGE-CMRI data. Scar tissue was defined as myocardium with signal intensity ≥80% of its maximum and quantified on each slice. Scar location and extent were assessed and compared with expert analysis. Preliminary results showed that automatic localization of scar from LGE-CMRI is feasible and scar quantification is accurate and reliable.

Although cardiac resynchronization therapy (CRT) is an effective treatment for chronic systolic heart failure with dyssynchrony, about one-third of patients do not respond favorably. The interaction between the pacing lead and the coronary sinus (CS) branches is of paramount importance for an effective resynchronization. Minor changes in lead position overtime could interfere with CRT mechanics, without affecting even biophysical parameters or ECG morphology. Although late post-implant CS lead dislodgement rate is consistent, lead movements have been little investigated and only with bi-dimensional methods. The aim of this study was (1) to develop a method for quantifying CS lead position in the 3D domain throughout the cardiac cycle and (2) to test it by comparing the CS lead position at implant and at follow-up, using chest fluoroscopy. Method performance, its accuracy and reproducibility were qualitatively and quantitatively assessed. Intra- and inter-observer percent discordance between trajectories were also computed. The accuracy of the procedure resulted in 0.3 ± 0.1 mm and its resolution was 0.5 mm. Intra- and inter-observer discordances were 2.2 ± 1.5 and 5.5 ± 3.6 mm, respectively. The proposed method for measuring the CS lead dynamic placement in 3D space seems accurate and reproducible. Investigating CS lead 3D dynamics could provide further insights into CRT mechanics.

Introduction Quantification of first-pass myocardial perfusion from cardiac magnetic resonance (CMR) images relies on the definition of myocardial regions of interest (ROI). This is usually achieved by manually drawing ROIs in one frame and then adjusting their position on subsequent frames. This methodology is tedious and potentially inaccurate. We recently developed a technique based on image noise density distribution for automated dynamic endocardial border detection as a basis for quantification of left ventricular size and function.

The aim of this study was to gain a wide perspective of the arrhythmogenic right ventricular dysplasia (ARVD) by developing algorithms for Cardiac Magnetic Resonance Imaging. We developed a semi-automatic procedure to assess the Right Ventricle (RV) volumes and to quantify RV wall motion; moreover, with the increased visible details in a single MR image, a manual method to evaluate the trabeculae mass was performed. All the algorithms used were based on the level set theory which allows detecting both endocardial and wall surfaces, as well as the black parts characterizing the trabeculae. 6 normal subjects and 6 subjects with ARVD have been investigated. Our method and the standard manual method for volume estimation were significantly correlated (y=0.92×+6.56), (r=0.92 p<;0.001). Wall Motion results showed a significant reduction of RV segmental function in patients with ARVD, Inferior Wall was the most involved with more than 80% reduction (p<;0.001) compared with normal subjects, while RV outflow tract (RVOT) was the least involved with less than 50% reduction (p<;0.001) compared to normal subjects. A repeatability test was executed on trabeculae mass assessment, which showed a high intra observer correlation, in fact the results were significant at 95% of the cases.