Patient-specific left atrium contraction quantification associated with atrial fibrillation: A region-based approach.

BACKGROUND AND OBJECTIVES: Atrial fibrillation (AF) is a widespread cardiac arrhythmia that significantly impacts heart function. AF disrupts atrial mechanical contraction, leading to irregular, uncoordinated, and slow blood flow inside the atria which favors the formation of clots, primarily within the left atrium (LA). A standardized region-based analysis of the LA is missing, and there is not even any consensus about how to define the LA regions. In this study we propose an automatic approach for regionalizing the LA into segments to provide a comprehensive 3D region-based LA contraction assessment. LA global and regional contraction were quantified in control subjects and in AF patients to describe mechanical abnormalities associated with AF. METHODS: The proposed automatic approach for LA regionalization was tested in thirteen control subjects and seventeen AF patients. After dividing LA into standard regions, we evaluated the global and regional mechanical function by measuring LA contraction parameters, such as regional volume, global and regional strains, regional wall motion and regional shortening fraction. RESULTS: LA regionalization was successful in all study subjects. In the AF group compared with control subjects, results showed: a global impairment of LA contraction which appeared more pronounced along radial and circumferential direction; a regional impairment of radial strain which was more pronounced in septal, inferior, and lateral regions suggesting a greater reduction in mechanical efficiency in these regions in comparison to the posterior and anterior ones. CONCLUSION: An automatic approach for LA regionalization was proposed. The regionalization method was proved to be robust with several LA anatomical variations and able to characterize contraction changes associated with AF.

A detailed mathematical model of the human atrial cardiomyocyte: integration of electrophysiology and cardiomechanics.

Mechano-electric regulations (MER) play an important role in the maintenance of cardiac performance. Mechano-calcium and mechano-electric feedback (MCF and MEF) pathways adjust the cardiomyocyte contractile force according to mechanical perturbations and affects electro-mechanical coupling. MER integrates all these regulations in one unit resulting in a complex phenomenon. Computational modelling is a useful tool to accelerate the mechanistic understanding of complex experimental phenomena. We have developed a novel model that integrates the MER loop for human atrial cardiomyocytes with proper consideration of feedforward and feedback pathways. The model couples a modified version of the action potential (AP) Koivumäki model with the contraction model by Quarteroni group. The model simulates iso-sarcometric and isometric twitches and the feedback effects on AP and Ca2+ -handling. The model showed a biphasic response of Ca2+ transient (CaT) peak to increasing pacing rates and highlights the possible mechanisms involved. The model has shown a shift of the threshold for AP and CaT alternans from 4.6 to 4 Hz under post-operative atrial fibrillation, induced by depressed SERCA activity. The alternans incidence was dependent on a chain of mechanisms including RyRs availability time, MCF coupling, CaMKII phosphorylation, and the stretch levels. As a result, the model predicted a 10% slowdown of conduction velocity for a 20% stretch, suggesting a role of stretch in creation of substrate formation for atrial fibrillation. Overall, we conclude that the developed model provides a physiological CaT followed by a physiological twitch. This model can open pathways for the future studies of human atrial electromechanics. KEY POINTS: With the availability of human atrial cellular data, interest in atrial-specific model integration has been enhanced. We have developed a detailed mathematical model of human atrial cardiomyocytes including the mechano-electric regulatory loop. The model has gone through calibration and evaluation phases against a wide collection of available human in-vitro data. The usefulness of the model for analysing clinical problems has been preliminaryly tested by simulating the increased incidence of Ca2+ transient and action potential alternans at high rates in post-operative atrial fibrillation condition. The model determines the possible role of mechano-electric feedback in alternans incidence, which can increase vulnerability to atrial arrhythmias by varying stretch levels. We found that our physiologically accurate description of Ca2+ handling can reproduce many experimental phenomena and can help to gain insights into the underlying pathophysiological mechanisms.

Preliminary findings on left atrial appendage occlusion simulations applying different endocardial devices.

Atrial fibrillation (AF) is one of the most investigated arrhythmias since it is associated with a five-fold increase in the risk of strokes. Left atrium dilation and unbalanced and irregular contraction caused by AF favour blood stasis and, consequently, stroke risk. The left atrial appendage (LAA) is the site of the highest clots formation, increasing the incidence of stroke in AF population. For many years oral anticoagulation therapy has been the most used AF treatment option available to decrease stroke risk. Unfortunately, several contraindications including bleeding risk increase, interference with other drugs and with multiorgan functioning, might outweigh its remarkable benefits on thromboembolic events. For these reasons, in recent years, other approaches have been designed, including LAA percutaneous closure. Unfortunately, nowadays, LAA occlusion (LAAO) is restricted to small subgroups of patients and require a certain level of expertise and training to successfully complete the procedure without complications. The most critical clinical problems associated with LAAO are represented by peri-device leaks and device related thrombus (DRT). The anatomical variability of the LAA plays a key role in the choice of the correct LAA occlusion device and in its correct positioning with respect to the LAA ostium during the implant. In this scenario, computational fluid dynamics (CFD) simulations could have a crucial role in improving LAAO intervention. The aim of this study was to simulate the fluid dynamics effects of LAAO in AF patients to predict hemodynamic changes due to the occlusion. LAAO was simulated by applying two different types of closure devices based on the plug and the pacifier principles on 3D LA anatomical models derived from real clinical data in five AF patients. CFD simulations were performed on the left atrium model before and after the LAAO intervention with each device. Blood velocity, particle washout and endothelial damage were computed to quantify flow pattern changes after the occlusion in relation to the thrombogenic risk. Our preliminary results confirmed an improved blood washout after the simulated implants and the capability of foreseeing thrombogenic risk based on endothelial damage and maximum blood velocities in different scenarios. This tool may help to identify effective device configurations in limiting stroke risk for patient-specific LA morphologies.

Indocyanine green fluorescence angiography after full-thickness bowel resection for rectosigmoid endometriosis: A multicentric experience with quantitative analysis.

OBJECTIVE: To evaluate effectiveness and reproducibility of qualitative and quantitative near-infrared indocyanine green (NIR-ICG) analyses as a tool for anastomotic perfusion assessment after full-thickness bowel resection for rectosigmoid endometriosis (RSE). METHODS: Symptomatic women with RSE undergoing minimally invasive full-thickness surgical excision of RSE and NIR-ICG evaluation from November 2019 to July 2020 were included. Study outcomes were the accuracy of qualitative and quantitative NIR-ICG analyses in predicting bowel fistula and their reproducibility. NIR-ICG predictive accuracy was assessed by calculating sensitivity, specificity, and area under the curve on receiver operating characteristic curves with 95% confidence intervals (CI). NIR-ICG reproducibility was assessed through Cohen's k coefficient to determine interoperator agreement between two observers. RESULTS: Of 33 patients, 2 (6%) developed bowel fistula. In predicting bowel fistula, qualitative and quantitative NIR-ICG evaluations showed sensitivity of 100% and 100%, specificity of 71% and 93%, and area under the curve of 0.86 (95% CI 0.67-1.00) and 0.96 (95% CI 0-1.00), respectively. Regarding interoperator agreement rate, it was reported as excellent for the qualitative analysis and very good for the quantitative analysis. CONCLUSION: Qualitative and quantitative NIR-ICG evaluations might be effective and reproducible tools for anastomotic perfusion assessment after discoid or segmental resection for RSE. Quantitative evaluation might be even more effective than qualitative evaluation in predicting bowel fistula.

Computational Analysis of Mapping Catheter Geometry and Contact Quality Effects on Rotor Detection in Atrial Fibrillation.

Atrial fibrillation (AF) is the most common cardiac arrhythmia and catheter mapping has been proved to be an effective approach for detecting AF drivers to be targeted by ablation. Among drivers, the so-called rotors have gained the most attention: their identification and spatial location could help to understand which patient-specific mechanisms are acting, and thus to guide the ablation execution. Since rotor detection by multi-electrode catheters may be influenced by several structural parameters including inter-electrode spacing, catheter coverage, and endocardium-catheter distance, in this study we proposed a tool for testing the ability of different catheter shapes to detect rotors in different conditions. An approach based on the solution of the monodomain equations coupled with a modified Courtemanche ionic atrial model, that considers an electrical remodeling, was applied to simulate spiral wave dynamics on a 2D model for 7.75 s. The developed framework allowed the acquisition of unipolar signals at 2 KHz. Two high-density multipolar catheters were simulated (Advisor™ HD Grid and PentaRay®) and placed in a 2D region in which the simulated spiral wave persists longer. The configuration of the catheters was then modified by changing the number of electrodes, inter-electrodes distance, position, and atrial-wall distance for assessing how they would affect the rotor detection. In contact with the wall and at 1 mm distance from it, all the configurations detected the rotor correctly, irrespective of geometry, coverage, and inter-electrode distance. In the HDGrid-like geometry, the increase of the inter-electrode distance from 3 to 6 mm caused rotor detection failure at 2 mm distance from the LA wall. In the PentaRay-like configuration, regardless of inter-electrode distance, rotor detection failed at 3 mm endocardium-catheter distance. The asymmetry of this catheter resulted in rotation-dependent rotor detection. To conclude, the computational framework we developed is based on realistic catheter shapes designed with parameter configurations which resemble clinical settings. Results showed it is well suited to investigate how mapping catheter geometry and location affect AF driver detection, therefore it is a reliable tool to design and test new mapping catheters.

A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging.

Segmentation of medical images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) used for visualizing diseased atrial structures, is a crucial first step for ablation treatment of atrial fibrillation. However, direct segmentation of LGE-MRIs is challenging due to the varying intensities caused by contrast agents. Since most clinical studies have relied on manual, labor-intensive approaches, automatic methods are of high interest, particularly optimized machine learning approaches. To address this, we organized the 2018 Left Atrium Segmentation Challenge using 154 3D LGE-MRIs, currently the world's largest atrial LGE-MRI dataset, and associated labels of the left atrium segmented by three medical experts, ultimately attracting the participation of 27 international teams. In this paper, extensive analysis of the submitted algorithms using technical and biological metrics was performed by undergoing subgroup analysis and conducting hyper-parameter analysis, offering an overall picture of the major design choices of convolutional neural networks (CNNs) and practical considerations for achieving state-of-the-art left atrium segmentation. Results show that the top method achieved a Dice score of 93.2% and a mean surface to surface distance of 0.7 mm, significantly outperforming prior state-of-the-art. Particularly, our analysis demonstrated that double sequentially used CNNs, in which a first CNN is used for automatic region-of-interest localization and a subsequent CNN is used for refined regional segmentation, achieved superior results than traditional methods and machine learning approaches containing single CNNs. This large-scale benchmarking study makes a significant step towards much-improved segmentation methods for atrial LGE-MRIs, and will serve as an important benchmark for evaluating and comparing the future works in the field. Furthermore, the findings from this study can potentially be extended to other imaging datasets and modalities, having an impact on the wider medical imaging community.

Impedance mapping with constant contact force on 3D electroanatomic map to characterize tissues at pulmonary veno-atrial junction.

PURPOSE: Generator impedance (Im) mapping with constant contact force (CF) by tip catheter at PV isolation (PVI) was assessed for a proposal of tissue characterization at PV-LA junction (PV-LAJ). METHODS: In this observational, prospective, single-center study, Im mapping at constant CF = 10 g (± 2 g) was performed before PVI at PV-LAJ. PV in-vein, PV ostium (PVos), and antrum (PVan) contours were manually traced based on the 3D electroanatomic map (3DEAM) integrating intracardiac echocardiography and computerized tomography. PVan contour-methods based on Im mapping was defined on 3DEAM as the atrial-like Im contour closest to PVos, and its distance from anatomical PVan contour > 5 mm was assumed as the non-concordance marker between contour and methods. RESULTS: Sixty-two patients (62 ± 9 years; 43 males) were enrolled, and 244 PV-LAJ were assessed. From in-vein PV to LA and, less prominently, from PVos to PVan and LA, Im showed a unidirectional decrease with highly variable individual-specific distribution and values. PVan non-concordance was found in 59/665 segments (8.8%), 18% of PV-LAJs, and 53% of pts; it prevailed in superior PV-LAJ and measured on average 7.2 ± 1.1 mm. Im decrease patterns and non-concordance were not associated with any clinical or anatomical feature, including PV dimensions and shape. CONCLUSIONS: Im mapping of LA-PVJ at constant CF added to 3DEAM may consistently track the tissue transition from PV to LA. PVan identified by Im was often located more toward LA than the 3D anatomical PVan, particularly in LSPV, suggesting the potential advantage of avoiding ablation of venous-like tissue. Im mapping can deserve further investigation for target characterization at LA-PVJ.

A fully automated left atrium segmentation approach from late gadolinium enhanced magnetic resonance imaging based on a convolutional neural network.

BACKGROUND: Several studies suggest that the evaluation of left atrial (LA) fibrosis is a relevant information for the assessment of the appropriate strategy in catheter ablation in atrial fibrillation (AF). Late gadolinium enhanced (LGE) cardiac magnetic resonance imaging (MRI) is a non-invasive technique, which might be employed for the non-invasive quantification of LA myocardial fibrotic tissue in patients with AF. Nowadays, the analysis of LGE MRI relies on manual tracing of LA boundaries and this procedure is time-consuming and prone to high inter-observer variability given the different degrees of observers' experience, LA wall thickness and data resolution. Therefore, an automated segmentation approach of the atrial cavity for the quantification of scar tissue would be highly desirable. METHODS: This study focuses on the design of a fully automated LGE MRI segmentation pipeline which includes a convolutional neural network (CNN) based on the successful architecture U-Net. The CNN was trained, validated and tested end-to-end with the data available from the Statistical Atlases and Computational Modelling of the Heart 2018 Atrial Segmentation Challenge (100 cardiac data). Two different approaches were tested: using both stacks of 2-D axial slices and using 3-D data (with the appropriate changes in the baseline architecture). In the latter approach, thanks to the 3-D convolution operator, all the information underlying 3-D data can be exploited. Once the training was completed using 80 cardiac data, a post-processing step was applied on 20 predicted segmentations belonging to the test set. RESULTS: By applying the 2-D and 3-D approaches, average Dice coefficient and mean Hausdorff distances were 0.896, 0.914, and 8.98 mm, 8.34 mm, respectively. Volumes of the anatomical LA meshes from the automated analysis were highly correlated with the volumes from ground truth [2-D: r=0.978, y=0.94x+0.07, bias=3.5 ml (5.6%), SD=5.3 mL (8.5%); 3-D: r=0.982, y=0.92x+2.9, bias=2.1 mL (3.5%), SD=5.2 mL (8.4%)]. CONCLUSIONS: These results suggest the proposed approach is feasible and provides accurate results. Despite the increase of the number of trainable parameters, the proposed 3-D CNN learns better features leading to higher performance, feasible for a real clinical application.

A Proof of Concept for Computational Fluid Dynamic Analysis of the Left Atrium in Atrial Fibrillation on a Patient-Specific Basis.

Atrial fibrillation (AF) is associated with a fivefold increase in the risk of cerebrovascular events, being responsible of 15-18% of all strokes. The morphological and functional remodeling of the left atrium (LA) caused by AF favors blood stasis and, consequently, stroke risk. In this context, several clinical studies suggest that the stroke risk stratification could be improved by using hemodynamic information on the LA and the left atrial appendage (LAA). The goal of this study was to develop a personalized computational fluid dynamics (CFD) model of the LA which could clarify the hemodynamic implications of AF on a patient-specific basis. In this paper, we present the developed model and its application to two AF patients as a preliminary advancement toward an optimized stroke risk stratification pipeline.

A Computational Framework to Benchmark Basket Catheter Guided Ablation in Atrial Fibrillation.

Catheter ablation is a curative therapeutic approach for atrial fibrillation (AF). Ablation of rotational sources based on basket catheter measurements has been proposed as a promising approach in patients with persistent AF to complement pulmonary vein isolation. However, clinically reported success rates are equivocal calling for a mechanistic investigation under controlled conditions. We present a computational framework to benchmark ablation strategies considering the whole cycle from excitation propagation to electrogram acquisition and processing to virtual therapy. Fibrillation was induced in a patient-specific 3D volumetric model of the left atrium, which was homogeneously remodeled to sustain reentry. The resulting extracellular potential field was sampled using models of grid catheters as well as realistically deformed basket catheters considering the specific atrial anatomy. The virtual electrograms were processed to compute phase singularity density maps to target rotor tips with up to three circular ablations. Stable rotors were successfully induced in different regions of the homogeneously remodeled atrium showing that rotors are not constrained to unique anatomical structures or locations. Density maps of rotor tip trajectories correctly identified and located the rotors (deviation < 10 mm) based on catheter recordings only for sufficient resolution (inter-electrode distance ≤3 mm) and proximity to the wall (≤10 mm). Targeting rotor sites with ablation did not stop reentries in the homogeneously remodeled atria independent from lesion size (1-7 mm radius), from linearly connecting lesions with anatomical obstacles, and from the number of rotors targeted sequentially (≤3). Our results show that phase maps derived from intracardiac electrograms can be a powerful tool to map atrial activation patterns, yet they can also be misleading due to inaccurate localization of the rotor tip depending on electrode resolution and distance to the wall. This should be considered to avoid ablating regions that are in fact free of rotor sources of AF. In our experience, ablation of rotor sites was not successful to stop fibrillation. Our comprehensive simulation framework provides the means to holistically benchmark ablation strategies in silico under consideration of all steps involved in electrogram-based therapy and, in future, could be used to study more heterogeneously remodeled disease states as well.

Towards a repository of synthetic electrograms for atrial activation detection in atrial fibrillation.

BACKGROUND: Recently, the analysis of the spatio-temporal behavior of atrial fibrillation activation patterns has been widely investigated with the aim to better understand the arrhythmia implications on the heart electrical activity. Most of the proposed techniques are based on atrial activation timing detections. Unfortunately atrial activation timings are not easily recognizable on the electrograms (EGMs) and an approach to support the validation of such techniques is highly desirable. The aim of this study is to provide an effective workflow for the generation of synthetic unipolar atrial electrograms (SEGMs) in atrial fibrillation (AF) condition and with different levels of noise. METHOD: Real EGMs signals were obtained from a dataset of 6 subjects that underwent ablation. Each SEGM was obtained by modeling the three principal components of an EGM starting from real signals: atrial far-field (Afar), atrial near-field (Anear) and the ventricular far-field (Vfar). Afar was generated using an autoregressive model applied on segments from real EGMs not characterized by ventricular or atrial activations; Anear and Vfar were extracted directly from the real signals. A Gamma distribution and an atrio-ventricular node model were used to locate both Anear and Vfar on Afar, respectively. Three electrophysiologists with different levels of expertise evaluated the realism of the SEGMs on a set of 100 randomly selected signals including 50 EGMs and 50 SEGMs. Analysis was repeated by the three experts on a subset of 21 signals. RESULTS: The time required to generate the synthetic EGMs was less than 1 min once annotated EGMs are available. The cardiologists succeeded in distinguishing real from synthetic EGMs in 45%, 43% and 35% of the signals, respectively. By repeating the evaluation, 28%, 0% and 48% of signals were classified differently, including 67%, 52% and 36% of correct classifications. CONCLUSION: The proposed approach proved to be effective in producing SEGMs which are difficult to distinguish from real EGMs. This study provides a tool for realistic SEGM generation from real EGMs in AF condition with different levels of noise and at different AF rates. The tool may be easily adopted to obtain SEGMs in different arrhythmic conditions. SEGMs generated in this study are shared with the scientific community as a first step towards a repository of synthetic and real atrial signals supporting the benchmarking of new approaches to investigate AF.

A Review of the Imaging Techniques for Measuring Kidney and Cyst Volume in Establishing Autosomal Dominant Polycystic Kidney Disease Progression.

BACKGROUND: Autosomal dominant polycystic kidney disease (ADPKD) is the commonest inherited renal disorder; it is defined by progressive renal cyst formation and subsequent renal enlargement that leads to end-stage renal disease. Until recently, only symptomatic treatments for ADPKD existed. However, therapies that address the underlying pathophysiology of ADPKD are now available and accurate identification of the rate of disease progression is essential. SUMMARY: Published data on the different imaging modalities for measuring kidney and cyst volumes in ADPKD are reviewed. The advantages and drawbacks of the different techniques for calculating kidney volume from renal imaging are also examined, including the use of manual planimetry, stereology, and the ellipsoid equation, as well as the prospect of semi- and fully automatic techniques. The translation of these approaches into clinical practice and their role in informing treatment decisions is discussed. Key Messages: These new therapies require the accurate monitoring of disease progression, which along with diagnosis and prognosis, relies on the effective use of renal imaging techniques. There is growing support for the use of total kidney volume as a measure of cyst burden and as a prognostic predictor of renal function in ADPKD, showing promise as a marker of disease progression.

Heart-Brain Interactions in the MR Environment: Characterization of the Ballistocardiogram in EEG Signals Collected During Simultaneous fMRI.

The ballistocardiographic (BCG) artifact is linked to cardiac activity and occurs in electroencephalographic (EEG) recordings acquired inside the magnetic resonance (MR) environment. Its variability in terms of amplitude, waveform shape and spatial distribution over subject's scalp makes its attenuation a challenging task. In this study, we aimed to provide a detailed characterization of the BCG properties, including its temporal dependency on cardiac events and its spatio-temporal dynamics. To this end, we used high-density EEG data acquired during simultaneous functional MR imaging in six healthy volunteers. First, we investigated the relationship between cardiac activity and BCG occurrences in the EEG recordings. We observed large variability in the delay between ECG and subsequent BCG events (ECG-BCG delay) across subjects and non-negligible epoch-by-epoch variations at the single subject level. The inspection of spatial-temporal variations revealed a prominent non-stationarity of the BCG signal. We identified five main BCG waves, which were common across subjects. Principal component analysis revealed two spatially distinct patterns to explain most of the variance (85% in total). These components are possibly related to head rotation and pulse-driven scalp expansion, respectively. Our results may inspire the development of novel, more effective methods for the removal of the BCG, capable of isolating and attenuating artifact occurrences while preserving true neuronal activity.

Fully Automated Segmentation of Polycystic Kidneys From Noncontrast Computed Tomography: A Feasibility Study and Preliminary Results.

RATIONALE AND OBJECTIVES: Total kidney volume is an important biomarker for the evaluation of autosomal dominant polycystic kidney disease progression. In this study, we present a novel approach for automated segmentation of polycystic kidneys from non-contrast-enhanced computed tomography (CT) images. MATERIALS AND METHODS: Non-contrast-enhanced CT images were acquired from 21 patients with a diagnosis of autosomal dominant polycystic kidney disease. Kidney volumes obtained from the fully automated method were compared to volumes obtained by manual segmentation and evaluated using linear regression and Bland-Altman analyses. Dice coefficient was used for performance evaluation. RESULTS: Kidney volumes from the automated method well correlated with the ones obtained by manual segmentation. Bland-Altman analysis showed a low percentage bias (-0.3%) and narrow limits of agreements (11.0%). The overlap between the three-dimensional kidney surfaces obtained with our approach and by manual tracing, expressed in terms of Dice coefficient, showed good agreement (0.91 ± 0.02). CONCLUSIONS: This preliminary study showed the proposed fully automated method for renal volume assessment is feasible, exhibiting how a correct use of biomedical image processing may allow polycystic kidney segmentation also in non-contrast-enhanced CT. Further investigation on a larger dataset is needed to confirm the robustness of the presented approach.

3D patient-specific models for left atrium characterization to support ablation in atrial fibrillation patients.

BACKGROUND: Radiofrequency ablation (RFA) is an important and promising therapy for atrial fibrillation (AF) patients. Optimization of patient selection and the availability of an accurate anatomical guide could improve RFA success rate. In this study we propose a unified, fully automated approach to build a 3D patient-specific left atrium (LA) model including pulmonary veins (PVs) in order to provide an accurate anatomical guide during RFA and without PVs in order to characterize LA volumetry and support patient selection for AF ablation. METHODS: Magnetic resonance data from twenty-six patients referred for AF RFA were processed applying an edge-based level set approach guided by a phase-based edge detector to obtain the 3D LA model with PVs. An automated technique based on the shape diameter function was designed and applied to remove PVs and compute LA volume. 3D LA models were qualitatively compared with 3D LA surfaces acquired during the ablation procedure. An expert radiologist manually traced the LA on MR images twice. LA surfaces from the automatic approach and manual tracing were compared by mean surface-to-surface distance. In addition, LA volumes were compared with volumes from manual segmentation by linear and Bland-Altman analyses. RESULTS: Qualitative comparison of 3D LA models showed several inaccuracies, in particular PVs reconstruction was not accurate and left atrial appendage was missing in the model obtained during RFA procedure. LA surfaces were very similar (mean surface-to-surface distance: 2.3±0.7mm). LA volumes were in excellent agreement (y=1.03x-1.4, r=0.99, bias=-1.37ml (-1.43%) SD=2.16ml (2.3%), mean percentage difference=1.3%±2.1%). CONCLUSIONS: Results showed the proposed 3D patient-specific LA model with PVs is able to better describe LA anatomy compared to models derived from the navigation system, thus potentially improving electrograms and voltage information location and reducing fluoroscopic time during RFA. Quantitative assessment of LA volume derived from our 3D LA model without PVs is also accurate and may provide important information for patient selection for RFA.

The Impact of Left Atrium Appendage Morphology on Stroke Risk Assessment in Atrial Fibrillation: A Computational Fluid Dynamics Study.

Atrial fibrillation (AF) carries out a 5-fold increase in stroke risk, related to embolization of thrombi clotting in left atrium (LA). Left atrial appendage (LAA) is the site with the highest blood stasis which causes thrombus formation. About 90 % of the intracardiac thrombi in patients with cardioembolic events originally develop in the LAA. Recent studies have been focused on the association between LAA anatomical features and stroke risk and provided conflicting results. Haemodynamic and fluid dynamic information on the LA and mostly on the LAA may improve stroke risk stratification. Therefore, the aim of this study was the design and development of a workflow to quantitatively define the influence of the LAA morphology on LA hemodynamics. Five 3D LA anatomical models, obtained from real clinical data, which were clearly different as regard to LAA morphology were used. For each LAA we identified and computed several parameters describing its geometry. Then, one LA chamber model was chosen and a framework was developed to connect the different LAAs belonging to the other four patients to this model. These new anatomical models represented the computational domain for the computational fluid dynamics (CFD) study; simulations of the hemodynamics within the LA and LAA were performed in order to evaluate the interplay of the LAA shape on the blood flow characteristics in AF condition. CFD simulations were carried out for five cardiac cycles. Blood velocity, vorticity, LAA orifice velocity, residence time computed in the five models were compared and correlated with LAA morphologies. Results showed that not only complex morphologies were characterized by low velocities, low vorticity and consequently could carry a higher thrombogenic risk; even qualitatively simple morphologies showed a thrombogenic risk equal, or even higher, than more complex auricles. CFD results supported the hypothesis that LAA geometric characteristics plays a key-role in defining thromboembolic risk. LAA geometric parameters could be considered, coupled with the morphological characteristics, for a comprehensive evaluation of the regional blood stasis. The proposed procedure might address the development of a tool for patient-specific stroke risk assessment and preventive treatment in AF patients, relying on morpho-functional defintion of each LAA type.

Reliability of Left Ventricular Ejection Fraction from Three-Dimensional Echocardiography for Cardiotoxicity Onset Detection in Patients with Breast Cancer.

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 three-dimensional 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.

Comparison of Total Kidney Volume Quantification Methods in Autosomal Dominant Polycystic Disease for a Comprehensive Disease Assessment.

BACKGROUND: In recent times, the scientific community has been showing increasing interest in the treatments aimed at slowing the progression of the autosomal dominant polycystic kidney disease (ADPKD). Therefore, in this paper, we test and evaluate the performance of several available methods for total kidney volume (TKV) computation in ADPKD patients - from echography to MRI - in order to optimize patient classification. METHODS: Two methods based on geometric assumptions (mid-slice [MS], ellipsoid [EL]) and a third one on true contour detection were tested on 40 ADPKD patients at different disease stage using MRI. The EL method was also tested using ultrasound images in a subset of 14 patients. Their performance was compared against TKVs derived from reference manual segmentation of MR images. Patient clinical classification was also performed based on computed volumes. RESULTS: Kidney volumes derived from echography significantly underestimated reference volumes. Geometric-based methods applied to MR images had similar acceptable results. The highly automated method showed better performance. Volume assessment was accurate and reproducible. Importantly, classification resulted in 79, 13, 10, and 2.5% of misclassification using kidney volumes obtained from echo and MRI applying the EL, the MS and the highly automated method respectively. CONCLUSION: Considering the fact that the image-based technique is the only approach providing a 3D patient-specific kidney model and allowing further analysis including cyst volume computation and monitoring disease progression, we suggest that geometric assumption (e.g., EL method) should be avoided. The contour-detection approach should be used for a reproducible and precise morphologic classification of the renal volume of ADPKD patients.

Noninvasive quantification of blood potassium concentration from ECG in hemodialysis patients.

Blood potassium concentration ([K+]) influences the electrocardiogram (ECG), particularly T-wave morphology. We developed a new method to quantify [K+] from T-wave analysis and tested its clinical applicability on data from dialysis patients, in whom [K+] varies significantly during the therapy. To elucidate the mechanism linking [K+] and T-wave, we also analysed data from long QT syndrome type 2 (LQT2) patients, testing the hypothesis that our method would have underestimated [K+] in these patients. Moreover, a computational model was used to explore the physiological processes underlying our estimator at the cellular level. We analysed 12-lead ECGs from 45 haemodialysis and 12 LQT2 patients. T-wave amplitude and downslope were calculated from the first two eigenleads. The T-wave slope-to-amplitude ratio (TS/A) was used as starting point for an ECG-based [K+] estimate (KECG). Leave-one-out cross-validation was performed. Agreement between KECG and reference [K+] from blood samples was promising (error: -0.09 ± 0.59 mM, absolute error: 0.46 ± 0.39 mM). The analysis on LQT2 patients, also supported by the outcome of computational analysis, reinforces our interpretation that, at the cellular level, delayed-rectifier potassium current is a main contributor of KECG correlation to blood [K+]. Following a comprehensive validation, this method could be effectively applied to monitor patients at risk for hyper/hypokalemia.

Objective selection of short-axis slices for automated quantification of left ventricular size and function by cardiovascular magnetic resonance.

BACKGROUND: Quantification of left ventricular (LV) volume from cardiovascular magnetic resonance images relies on subjective and often challenging selection of short-axis (SAX) slices. We hypothesized that this could be solved by defining mitral annular (MA) plane and apex in long-axis (LAX) views, which could be combined with automated LV volume analysis that does not rely on manual tracing of the endocardial border. METHODS: SAX images from 50 subjects were analyzed using custom software. LV apex and insertion points of the mitral leaflets were marked on LAX views and used to approximate MA plane. End-systolic and end-diastolic LV volumes (ESV, EDV) were measured while including only slices or their parts located between MA plane and LV apex. Endocardial borders were automatically detected using our previously validated algorithm and also manually traced to obtain reference values. RESULTS: Selection of anatomic landmarks in LAX views allowed automated measurement of LV volumes without the need for subjective slice selection. Intertechnique comparisons resulted in high correlations (EDV: r=0.95; ESV: r=0.96) and small biases (1 and 9ml). Combined three-dimensional displays of LAX and SAX views with the MA plane showed that in 7/10 worst cases, intertechnique discordance was due to incorrect manual tracing at LV base that erroneously included part of atrial cavity in LV volume or excluded part of LV cavity, i.e., incorrect reference values. CONCLUSION: Defining the MA plane and apex in the LAX views obviates the need for subjective slice selection and eliminates errors in LV volume measurements.