Shape Of Ventricle Research Articles

Ductal stenting for retraining the left ventricle in patients with transposition of great arteries with intact ventricular septum: a single-centre experience.

Ductal stenting in late presenters with transposition of great arteries with intact ventricular septum retrains the left ventricle before arterial switch operation. However, the experience is limited for its efficacy and safety. This study aims to highlight the efficacy and safety of ductal stenting for retraining the left ventricle. Eight children with transposition of great arteries-intact ventricular septum and regressed left ventricle underwent ductal stenting. Serial echocardiographic measurements of left ventricle shape, mass, volume, free wall thickness, and function were done, and arterial switch operation was performed once the left ventricle was adequately prepared. Post-operative outcome in terms of duration of mechanical ventilation, ICU stay, and improvement in left ventricle function were monitored. The procedure was successful in all patients. Babies were divided into two groups on basis of age at ductal stenting (group 1 age less than 90 days and group 2 age more than 90 days) and were evaluated for the degree of left ventricle retraining as evidenced by echocardiographic parameters and post-operative variables. The left ventricle posterior wall thickness and mass index after ductal stenting increased significantly in both the groups. Postoperatively, one baby of group two expired after seven days due to severe left ventricle dysfunction. Rest babies had an uneventful post-operative ICU stay with no statistical difference in the duration of invasive mechanical ventilation or ICU stay. On six-month follow-up, all surviving babies were doing well with normal left ventricle function. Ductal stenting is a good alternative measure as compared to surgical procedures for left ventricle retraining in transposition of great arteries with regressed left ventricle.

Importance of environmental signals for cardiac morphological development in Atlantic salmon.

The hearts of salmonids display remarkable plasticity, adapting to various environmental factors that influence cardiac function and demand. For instance, in response to cold temperature, the salmonid heart undergoes growth and remodeling to counterbalance the reduced contractile function associated with dropping temperatures. Alongside heart size, the distinct pyramidal shape of the wild salmonid heart is essential for optimal cardiac performance, yet the environmental drivers behind this optimal cardiac morphology remain to be fully understood. Intriguingly, farmed salmonids often have rounded, asymmetrical ventricles and misaligned bulbi from an early age. These deformities are noteworthy given that farmed salmon are often not exposed to natural cues, such as a gradual temperature increase and changing day lengths, during critical developmental stages. In this study, we investigated whether natural environmental conditions during early life stages are pivotal for proper cardiac morphology. Atlantic salmon were raised under simulated natural conditions (low temperature with a natural photoperiod; SimNat) and compared with those reared under simulated farming conditions (SimFarm). Our findings reveal that the ventricle shape and bulbus alignment in SimNat fish closely resemble those of wild salmon, while functional analyses indicate significant differences between SimNat and SimFarm hearts, suggesting diastolic dysfunction and higher cardiac workload in SimFarm hearts. These findings highlight the profound influence of environmental factors such as water temperature and photoperiod on the structural development of the salmonid heart, underscoring the importance of early environmental conditions for cardiac health.

Image-based simulation of mitral valve dynamic closure including anisotropy

Simulation of the dynamic behavior of mitral valve closure could improve clinical treatment by predicting surgical procedures outcome. We propose here a method to achieve this goal by using the immersed boundary method. In order to go towards patient-based simulation, we tailor our method to be adapted to a valve extracted from medical image data. It includes investigating segmentation process, smoothness of geometry, case setup and the shape of the left ventricle. We also study the influence of leaflet tissue anisotropy on the quality of the valve closure by comparing with an isotropic model. As part of the anisotropy analysis, we study the influence of the principal material direction by comparing methods to obtain them without dissection.Results show that our method can be scaled to various image-based data. We evaluate the mitral valve closure quality based on measuring bulging area, contact map, and flow rate. The results show also that the anisotropic material model more precisely represents the physiological characteristics of the valve tissue. Furthermore, results indicate that the orientation of the principal material direction plays a role in the effectiveness of the valve seal.

Surgical treatment of isolated tricuspid valve disease: indications, new evidence, and risk stratification

The tricuspid valve, long neglected as a passive structure and often termed the "forgotten valve", has recently gained attention from the international medical and cardiological community due to the association of tricuspid regurgitation with an unfavorable prognosis. Isolated tricuspid regurgitation represents a relatively unknown and variable condition, closely linked to the shape and function of the right ventricle and the state of the pulmonary circulation. Currently, guidelines are not clear regarding the optimal treatment strategy, the process of patient selection, and the surgical or transcatheter procedural timing, nor for predicting patient outcomes. Surgical procedures specifically aimed at correcting isolated tricuspid regurgitation, without other concomitant indications for open-heart surgery, have been considered complex and risky, with a high rate of postoperative complications and a poorly understood impact on patient survival and life expectancy. In this review, we will attempt to examine tricuspid valve pathology by analyzing preoperative assessment, essential for risk stratification, various surgical techniques, and outcomes.

Personalized evaluation of the passive myocardium in ischemic cardiomyopathy via computational modeling using Bayesian optimization.

Biomechanics-based patient-specific modeling is a promising approach that has proved invaluable for its clinical potential to assess the adversities caused by ischemic heart disease (IHD). In the present study, we propose a framework to find the passive material properties of the myocardium and the unloaded shape of cardiac ventricles simultaneously in patients diagnosed with ischemic cardiomyopathy (ICM). This was achieved by minimizing the difference between the simulated andthe target end-diastolic pressure-volume relationships (EDPVRs) using black-box Bayesian optimization, based on the finite element analysis (FEA). End-diastolic (ED) biventricular geometry and the location of the ischemia were determined from cardiac magnetic resonance (CMR) imaging. We employed our pipeline to model the cardiac ventricles of three patients aged between 57 and 66years, with and without the inclusion of valves. An excellent agreement between the simulated and thetarget EDPVRs has been reached. Our results revealed that the incorporation of valvular springs typically leads to lower hyperelastic parameters for both healthy and ischemic myocardium, as well as a higher fiber Green strain in the viable regions compared to models without valvular stiffness. Furthermore, the addition of valve-related effects did not result in significant changes in myofiber stress after optimization. We concluded that more accurate results could be obtained when cardiac valves were considered in modeling ventricles. The present novel and practical methodology paves the way for developing digital twins of ischemic cardiac ventricles, providing a non-invasive assessment for designing optimal personalized therapies in precision medicine.

Echocardiogram-based ventricular isogeometric cardiac analysis using multi-patch fitted NURBS

Monitoring the cardiac function often relies on non-invasive vital measurements, electrocardiograms, and low-resolution echocardiograms. The monitoring data can be augmented with numerical modeling results to support treatment-risk assessment. Often, medical images are not suitable for high-fidelity modeling due to their spatial sparsity and low resolution. In this work, we present a workflow that converts a limited number of two-dimensional (2D) echocardiogram images into analysis-suitable left-ventricle geometries for isogeometric analysis (IGA). The image data is fitted by reshaping a multi-patch NURBS template. This fitting procedure results in a smooth interpolation with a limited number of degrees of freedom. In addition, a coupled 3D-0D cardiac model is extended with a pre-stressing method to perform ventricular-cardiac-mechanic analyses based on in vivo images. The workflow is benchmarked using population-averaged imaging data, which demonstrates that both the shape of the left ventricle and its mechanical response are well predicted in sparse-data scenarios. The case of a clinical patient is considered to demonstrate the suitability of the workflow in a real-data setting.

Unsupervised ensemble-based phenotyping enhances discoverability of genes related to left-ventricular morphology

Recent genome-wide association studies have successfully identified associations between genetic variants and simple cardiac morphological parameters derived from cardiac magnetic resonance images. However, the emergence of large databases, including genetic data linked to cardiac magnetic resonance facilitates the investigation of more nuanced patterns of cardiac shape variability than those studied so far. Here we propose a framework for gene discovery coined unsupervised phenotype ensembles. The unsupervised phenotype ensemble builds a redundant yet highly expressive representation by pooling a set of phenotypes learnt in an unsupervised manner, using deep learning models trained with different hyperparameters. These phenotypes are then analysed via genome-wide association studies, retaining only highly confident and stable associations across the ensemble. We applied our approach to the UK Biobank database to extract geometric features of the left ventricle from image-derived three-dimensional meshes. We demonstrate that our approach greatly improves the discoverability of genes that influence left ventricle shape, identifying 49 loci with study-wide significance and 25 with suggestive significance. We argue that our approach would enable more extensive discovery of gene associations with image-derived phenotypes for other organs or image modalities.

Abnormal Shape and Size of the Cardiac Ventricles Are Associated with a Higher Risk of Neonatal Death in Fetuses with Isolated Left Congenital Diaphragmatic Hernia

Introduction: The objective of this study was to evaluate the association between fetal cardiac deformation analysis (CDA) and cardiac function with severe adverse perinatal outcomes in fetuses with isolated left congenital diaphragmatic hernia (CDH). Methods: CDA in each ventricle (contractility, size, and shape), evaluated by speckle tracking and novel FetalHQ software, and markers of cardiac function (E/A ratios, pulmonary and aortic peak systolic velocities, and sigmoid annular valve diameters), were evaluated in fetuses with isolated left CDH. Two evaluations were performed: at referral (CDA and function) and within 3 weeks of delivery (CDA). Severe adverse neonatal outcomes were considered neonatal death (ND) or survival with CDH-associated pulmonary hypertension (CDH-PH). Differences and associations between CDA, cardiac function, and severe adverse outcomes were estimated. Results: Fifty fetuses were included, and seventeen (34%) had severe adverse neonatal outcomes (11 ND and 6 survivors with CDH-PH). At first evaluation, the prevalence of a small left ventricle was 34% (17/50) with a higher prevalence among neonates presenting severe adverse outcomes (58.8 [10/17] vs. 21.2% [7/33]; p = 0.01; OR, 5.03 [1.4–19.1; p = 0.01]) and among those presenting with neonatal mortality (8/11 [72.7] vs. 9/39 [23.0%]; p = 0.03; OR, 8.9 [1.9–40.7; p = 0.005]). No differences in cardiac function or strain were noted between fetuses with or without severe adverse outcomes. Within 3 weeks of delivery, the prevalence of small left ventricle was higher (19/34; 55.8%) with a more globular shape (reduced transverse/longitudinal ratio). A globular right ventricle was significantly associated with ND or survival with CDH-PH (OR, 14.2 [1.5–138.3]; p = 0.02). Conclusion: Fetuses with isolated CDH at risk of perinatal death or survival with CDH-PH had a higher prevalence of a small left ventricle and abnormal shape of the right ventricle.

Endoscopic Cylinder Surgery for Ventricular Lesions.

Cylinder retractors have been developed to reduce the risk of brain retraction injury during surgery by dispersing retraction pressure on the brain. In recent years, various types of cylinder retractors have been developed and widely used in neurosurgery. The ventricles, being deep structures within the brain, present an effective area for cylinder retractor utilization. Endoscopy provides a bright, wide field of view in the deep surgical field, even through narrow corridors.This chapter introduces surgical techniques using an endoscope through a cylinder. Given the deep and complex shapes of the ventricles, preoperative planning is paramount. Two main surgical techniques are employed in endoscopic cylinder surgery. The wet-field technique involves the continuous irrigation of artificial cerebrospinal fluid (CSF) during the procedure, maintaining ventricle shape with natural water pressure, facilitating tumor border identification, and achieving spontaneous hemostasis. Conversely, the dry-field technique involves CSF drainage, providing a clear visual field even during hemorrhage encounters. In intraventricular surgery, both techniques are used and switched as needed.Specific approaches for lateral, third, and fourth ventricular tumors are discussed, considering their locations and surrounding anatomical structures. Detailed intraoperative findings and strategies for tumor removal and hemostasis are presented.Endoscopic cylinder surgery offers a versatile and minimally invasive option for intraventricular tumors, leading to improved surgical outcomes. Overall, this technique enhances surgical precision and patient outcomes in intraventricular tumor cases.

How the closure of atrial septal defect using a percutaneous device impacts the shape and function of the right ventricle

How the closure of atrial septal defect using a percutaneous device impacts the shape and function of the right ventricle

Evaluation of the changes in cardiac morphology of fetuses with congenital heart disease using fetalHQ

Objective: To evaluate the changes in cardiac morphology of fetuses with congenital heart disease (CHD) using the fetal heart quantitative technique (fetalHQ). Methods: A total of 20 normal pregnant women (control group) and 20 pregnant women suspected of fetal CHD (case group) were included in this study. The dynamic images of the four-chamber view of the fetal heart were recorded and analyzed using fetalHQ. The global sphericity index (GSI) and 24-segment SI of the two groups were compared. The differences in the left and right ventricular 24-segment SI for each group were investigated. Results: There was no statistically significant difference in the GSI between the two groups (p > 0.05). The difference in the SI values of left ventricular segments 1–2 between the case group and control group was statistically significant (all p < 0.05), while the intergroup difference in SI of left ventricular segments 3–24 was not significant (all p > 0.05). The SI of the 24 segments of the right ventricle showed no significant intergroup difference (all p > 0.05). The difference in the left and right ventricular 24-segment SI in the case group did not reach statistical significance (all p > 0.05). In the control group, the SI values between the left and right ventricles were significantly different in segments 18–24 (all p < 0.05), and no significant difference was found in segments 1–17 (all p > 0.05). There was a statistically significant intergroup difference in the percentage of unusual left ventricular SI, determined based on Z-score (p < 0.05), and the percentage of outliers for the right ventricle between the two groups showed no significant difference (p > 0.05). Conclusion: The fetalHQ is regarded as a straightforward and reliable approach for assessing the cardiac GSI and 24-segment SI of left and right ventricles in fetuses diagnosed with CHD. While CHD may not significantly impact the overall shape of the fetal heart or the geometric shape of the right ventricle, in this study, a notable increase in SI values for the left ventricular 1–2 segments was observed, indicating a more flattened ventricular chamber. Additionally, the morphological distinctions between the left and right ventricles in fetuses with CHD are no longer discernible.

A Segmentation Framework with Unsupervised Learning-Based Label Mapper for the Ventricular Target of Intracranial Germ Cell Tumor.

Intracranial germ cell tumors are rare tumors that mainly affect children and adolescents. Radiotherapy is the cornerstone of interdisciplinary treatment methods. Radiation of the whole ventricle system and the local tumor can reduce the complications in the late stage of radiotherapy while ensuring the curative effect. However, manually delineating the ventricular system is labor-intensive and time-consuming for physicians. The diverse ventricle shape and the hydrocephalus-induced ventricle dilation increase the difficulty of automatic segmentation algorithms. Therefore, this study proposed a fully automatic segmentation framework. Firstly, we designed a novel unsupervised learning-based label mapper, which is used to handle the ventricle shape variations and obtain the preliminary segmentation result. Then, to boost the segmentation performance of the framework, we improved the region growth algorithm and combined the fully connected conditional random field to optimize the preliminary results from both regional and voxel scales. In the case of only one set of annotated data is required, the average time cost is 153.01s, and the average target segmentation accuracy can reach 84.69%. Furthermore, we verified the algorithm in practical clinical applications. The results demonstrate that our proposed method is beneficial for physicians to delineate radiotherapy targets, which is feasible and clinically practical, and may fill the gap of automatic delineation methods for the ventricular target of intracranial germ celltumors.

Assessment of longitudinal brain development using super-resolution magnetic resonance imaging following fetal surgery for open spina bifida.

Prenatal surgery is offered for selected fetuses with open spina bifida (OSB) to improve long-term outcome. We studied the effect of fetal OSB surgery on brain development using advanced magnetic resonance imaging (MRI) techniques to quantify the volume, surface area and shape of cerebral structures and to analyze surface curvature by means of parameters that correspond to gyrification. We compared MRI data from 29 fetuses with OSB before fetal surgery (mean gestational age (GA), 23 + 3 weeks) and at 1 and 6 weeks after surgery, with that of 36 GA-matched control fetuses (GA range, 21 + 2 to 36 + 2 weeks). Automated super-resolution reconstruction provided three-dimensional isotropic volumetric brain images. Unmyelinated white matter, cerebellum and ventricles were segmented automatically and refined manually, after which volume, surface area and shape parameter (volume/surface area) were quantified. Mathematical markers (shape index (SI) and curvedness) were used to measure gyrification. Parameters were assessed according to lesion type (myelomeningocele vs myeloschisis (MS)), postoperative persistence of hindbrain herniation (HH) and the presence of supratentorial anomalies, namely partial agenesis of the corpus callosum (pACC) and heterotopia (HT). Growth in ventricular volume per week and change in shape parameter per week were higher at 6 weeks after surgery in fetuses with OSB compared with controls (median, 2500.94 (interquartile range (IQR), 1689.70-3580.80) mm3 /week vs 708.21 (IQR, 474.50-925.00) mm3 /week; P < 0.001 and 0.075 (IQR, 0.047-0.112) mm/week vs 0.022 (IQR, 0.009-0.042) mm/week; P = 0.046, respectively). Ventricular volume growth increased 6 weeks after surgery in cases with pACC (P < 0.001) and those with persistent HH (P = 0.002). During that time period, the change in unmyelinated white-matter shape parameter per week was decreased in OSB fetuses compared with controls (0.056 (IQR, 0.044-0.092) mm/week vs 0.159 (IQR, 0.100-0.247) mm/week; P = 0.002), particularly in cases with persistent HH (P = 0.011), MS (P = 0.015), HT (P = 0.022), HT with corpus callosum anomaly (P = 0.017) and persistent HH with corpus callosum anomaly (P = 0.007). At 6 weeks postoperatively, despite OSB fetuses having a lower rate of change in curvedness compared with controls (0.061 (IQR, 0.040-0.093) mm-1 /week vs 0.094 (IQR, 0.070-0.146) mm-1 /week; P < 0.001), reversing the trend seen at 1 week after surgery (0.144 (IQR, 0.099-0.236) mm-1 /week vs 0.072 (IQR, 0.059-0.081) mm-1 /week; P < 0.001), gyrification, as determined using SI, appeared to be increased in OSB fetuses overall compared with controls. This observation was more prominent in fetuses with pACC and those with severe ventriculomegaly (P-value range, < 0.001 to 0.006). Following fetal OSB repair, volume, shape and curvedness of ventricles and unmyelinated white matter differed significantly compared with those of normal fetuses. Morphological brain changes after fetal surgery were not limited to effects on the circulation of cerebrospinal fluid. These observations may have implications for postnatal neurocognitive outcome. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

A U-Net with Statistical Shape Restrictions Applied to the Segmentation of the Left Ventricle in Echocardiographic Images

This paper aims to introduce an innovative approach to semantic segmentation by leveraging a convolutional neural network (CNN) for predicting the shape and pose parameters of the left ventricle (LV). Our approach involves a modified U-Net architecture with a regression layer as the final stage, as opposed to the traditional classification layer. This modification allows us to predict all the shape and pose parameters of a statistical shape model, including rotation, translation, scale, and deformation. The adapted U-Net is trained using data from a point distribution model (PDM) of the LV. The experimental results demonstrate a mean Dice coefficient of 0.82 on good quality images, and 0.66 including mean and low-quality images. Our approach successfully overcomes a common issue encountered in CNN-based semantic segmentation. Unlike the inaccurate pixel classification that often leads to unwanted blobs, our CNN generates statistically valid shapes. These shapes hold significant potential in initializing other methods, such as active shape models (ASMs). Our novel CNN-based approach provides a novel solution for semantic segmentation, offering shapes and pose parameters that can enhance the accuracy and reliability of subsequent medical image analysis methods.

First-in-human description of a novel transcatheter tricuspid valve prosthesis to preserve the asymmetric shape of the right ventricle.

First-in-human description of a novel transcatheter tricuspid valve prosthesis to preserve the asymmetric shape of the right ventricle.

Left ventricular shape index and eccentricity index assessed by gated PET/CT. Promising parameters for detection of left ventricular remodelling

Abstract Funding Acknowledgements Type of funding sources: Public Institution(s). Main funding source(s): University of Groningen/University Medical Center Groningen. Background Left ventricular (LV) remodelling has been described as the pathway that precedes heart failure. This process consists of changes in the shape, size, volume and function of the left ventricle; all of this directly associated to increased risk of major adverse cardiac events (MACEs). Different parameters are used to evaluate cardiac geometry in multiple cardiac imaging modalities. In nuclear medicine, LV geometry can be studied through shape index (SI) and eccentricity index (EI). These values examine the degree of sphericity (SI) and elongation (EI) of the left ventricle. However, in cardiac perfusion PET/CT, the LV remodelling has not been extensively studied with SI and EI values, and their role is yet to be elucidated. Purpose This project aim to describe the role of SI and EI values in patients examined by gated 13N-ammonia PET/CT in ischemic and infarction scenario. Methods We retrospectively randomly selected 140 patients referred to 13N-ammonia PET/CT between 2016 and 2022 for suspected or diagnosed CAD. The patients were classified in 4 groups of 35 patients according to the presence and burden of ischemia or infarction: normal=0% of scar burden and ischemic burden; mild ischemia=5–10% of ischemic burden; moderate-severe ischemia≥10% of ischemic burden and infarction≥5% of scar burden. We collected the information regarding myocardial flows (myocardial blood flow (MBF) at rest, hyperaemic MBF at stress and coronary flow reserve (CFR)) and left ventricular geometry (SI end-diastolic at rest and stress, SI end-systolic at rest and stress, and EI at rest and stress). All the variables were automatically processed with QPS/QGS software. We performed a multicomparison analysis for the mentioned variables with One way ANOVA variance and Dunnett’s Test as Post Hoc, stablishing as the control the infarction group. Results The study population consisted of 35.7% women, all patients over 36 years old, with no significant differences between groups regarding the presence of cardiac risk factors. The control group showed important changes in all SI and EI when compared to the rest of the groups. With a maximum change of 0.090 observed in SI end-systolic stress in the mild ischemia group, and a minimum change of −0.041 in EI rest in the moderate-severe ischemia group. Control subjects had statistically significant higher values of SI end-diastolic rest (p&amp;lt;0.001) and stress (p = 0.005), end-systolic rest (p = 0.001)and stress (p&amp;lt;0.001) and statistically significant lower values of EI rest (p&amp;lt;0.001) and stress (p&amp;lt;0.001) when compared with all the other groups. Additionally, all SI and EI values in stress follow a linear change proportional to the degree of myocardial extend (Figure 1 and 2). Conclusions(s) SI and EI by 13N-ammonia PET/CT are variables that seem clinically relevant for the early detection of LV remodeling. However, there is still research to do for establishing cut-off values and evaluating the prediction of MACEs.

Predicting one-year left ventricular mass index regression following transcatheter aortic valve replacement in patients with severe aortic stenosis: A new era is coming.

Aortic stenosis (AS) is the most common valvular heart disease in the western world, particularly worrisome with an ever-aging population wherein postoperative outcome for aortic valve replacement is strongly related to the timing of surgery in the natural course of disease. Yet, guidelines for therapy planning overlook insightful, quantified measures from medical imaging to educate clinical decisions. Herein, we leverage statistical shape analysis (SSA) techniques combined with customized machine learning methods to extract latent information from segmented left ventricle (LV) shapes. This enabled us to predict left ventricular mass index (LVMI) regression a year after transcatheter aortic valve replacement (TAVR). LVMI regression is an expected phenomena in patients undergone aortic valve replacement reported to be tightly correlated with survival one and five year after the intervention. In brief, LV geometries were extracted from medical images of a cohort of AS patients using deep learning tools, and then analyzed to create a set of statistical shape models (SSMs). Then, the supervised shape features were extracted to feed a support vector regression (SVR) model to predict the LVMI regression. The average accuracy of the predictions was validated against clinical measurements calculating root mean square error and score which yielded the satisfactory values of 0.28 and 0.67, respectively, on test data. Our work reveals the promising capability of advanced mathematical and bioinformatics approaches such as SSA and machine learning to improve medical output prediction and treatment planning.

Cardiac hypertrophy simulations using parametric and echocardiography-based left ventricle model with shell finite elements

In our paper, we simulated cardiac hypertrophy with the use of shell elements in parametric and echocardiography-based left ventricle (LV) models. The hypertrophy has an impact on the change in the wall thickness, displacement field and the overall functioning of the heart. We computed both eccentric and concentric hypertrophy effects and tracked changes in the ventricle shape and wall thickness. Thickening of the wall was developed under the influence of concentric hypertrophy, while the eccentric hypertrophy produces wall thinning. To model passive stresses we used the recently developed material modal based on the Holzapfel experiments. Also, our specific shell composite finite element models for heart mechanics are much smaller and simpler to use with respect to conventional 3D models. Furthermore, the presented modeling approach of the echocardiography-based LV can serve as the basis for practical applications since it relies on the true patient-specific geometry and experimental constitutive relationships. Our model gives an insight into hypertrophy development in realistic heart geometries, and it has the potential to test medical hypotheses regarding hypertrophy evolution in a healthy and heart with a disease, under the influence of different conditions and parameters.

Comparison of two ellipsoidal models for the estimation of left ventricular end-systolic stress in patients with significant coronary artery disease.

The shape of the left ventricle (LV) is an important index to explore cardiac pathophysiology. A comparison was provided to estimate circumferential, longitudinal, and radial wall stress in LV based on the thick-walled ellipsoidal models of Mirsky and Ghista-Sandler for discriminating significant coronary artery disease (CAD) patients from no CAD patients. According to the angiography findings, 82 patients with CAD were divided into two groups: 25 patients without significant CAD and 57 patients with significant CAD of single vessel and multivessel. An ellipsoidal LV geometry was used to calculate end-systolic passive stress as the mechanical behavior of LV. Echocardiographic views-based measurements of LV diameters used to estimate the end-systolic wall stress. Circumferential wall stress between the control group and significant CAD groups was significantly elevated for the Ghista model (P = 0.008); also, radial and longitudinal stress of the multi-vessel CAD group was significantly higher than the control group (P = 0.01 and P = 0.005, respectively). All stress parameters of the multi-vessel CAD group were statistically significant compared to the control group for the Mirsky model. Receiver operating characteristics curve analysis was shown the circumferential stress of multi-vessel CAD with an area under the curve (AUC) of 0.736 for the Ghista model and an AUC of 0.742 for the Mirsky model. These results indicated that Ghista and Mirsky model estimates of circumferential passive stress were the potential biomechanical markers to predict patients with multi-vessel CAD. It could be a noninvasive and helpful tool to quantify the contractility of LV.

Phenotypic spectrum of patients with Poretti-Boltshauser syndrome: Patient report of antenatal ventriculomegaly and esophageal atresia

Poretti-Boltshauser syndrome (PTBHS) is an autosomal recessive disorder characterized by cerebellar dysplasia with cysts and an abnormal shape of the fourth ventricle on neuroimaging, due to pathogenic variants in the LAMA1 gene. The clinical spectrum mainly consists of neurological and ophthalmological manifestations, including non-progressive cerebellar ataxia, oculomotor apraxia, language impairment, intellectual disability, high myopia, abnormal eye movements and retinal dystrophy.We report a patient presenting with ventriculomegaly on antenatal neuroimaging and a neonatal diagnosis of Type III esophageal atresia. She subsequently developed severe myopia and strabismus with retinal dystrophy, mild developmental delay, and cerebellar dysplasia. Genetic investigations confirmed PTBHS.This report confirms previous reports of antenatal ventriculomegaly in PTBHS patients and documents a so far unreported occurrence of esophageal atresia in PTBHS. We additionally gathered phenotype and genotype descriptions of published cases in an effort to better define the spectrum of PTBHS.