S-Net: a multiple cross aggregation convolutional architecture for automatic segmentation of small/thin structures for cardiovascular applications.

With the success of U-Net or its variants in automatic medical image segmentation, building a fully convolutional network (FCN) based on an encoder-decoder structure has become an effective end-to-end learning approach. However, the intrinsic property of FCNs is that as the encoder deepens, higher-level features are learned, and the receptive field size of the network increases, which results in unsatisfactory performance for detecting low-level small/thin structures such as atrial walls and small arteries. To address this issue, we propose to keep the different encoding layer features at their original sizes to constrain the receptive field from increasing as the network goes deeper. Accordingly, we develop a novel S-shaped multiple cross-aggregation segmentation architecture named S-Net, which has two branches in the encoding stage, i.e., a resampling branch to capture low-level fine-grained details and thin/small structures and a downsampling branch to learn high-level discriminative knowledge. In particular, these two branches learn complementary features by residual cross-aggregation; the fusion of the complementary features from different decoding layers can be effectively accomplished through lateral connections. Meanwhile, we perform supervised prediction at all decoding layers to incorporate coarse-level features with high semantic meaning and fine-level features with high localization capability to detect multi-scale structures, especially for small/thin volumes fully. To validate the effectiveness of our S-Net, we conducted extensive experiments on the segmentation of cardiac wall and intracranial aneurysm (IA) vasculature, and quantitative and qualitative evaluations demonstrated the superior performance of our method for predicting small/thin structures in medical images.

Identifying Predictors of Psychological Problems Among Adolescents With Congenital Heart Disease for Referral to Psychological Care: A Pilot Study.

Background: The lifelong care of patients with congenital heart disease (CHD) typically begins at a young age, giving paediatric cardiologists a unique perspective on the mental health of their patients. Our aim was to describe and predict reported psychological problems among adolescents with CHD. Methods: A retrospective review was performed on patients aged 12-17 years who presented to the congenital cardiology clinic during a 1-year timeframe. The presence of psychological problems was collected along with CHD class, clinical history, developmental delay, and patient demographics. We described the prevalence of psychological problems and then, using machine learning algorithms, trained and tested optimal predictive models. Results: Of the 397 patients who met inclusion criteria, the lifetime prevalence of any reported psychological problem was 35.5%. The most prevalent reported problems were attention-deficit/hyperactivity disorder (18.9%), anxiety (17.6%), and depression (16.1%). Contrary to our expectations, we could not predict the presence or absence of any psychological problem using routine clinical data. Instead, we found multivariate models predicting depression and attention-deficit/hyperactivity disorder with promising accuracy. Prediction of anxiety was less successful. Conclusions: Approximately 1 of 3 adolescents with CHD presented with the lifetime prevalence of 1 or more psychological problems. Congenital cardiac programmes are in a position of influence to respond to these problems and impact their patients' mental health as part of a comprehensive care plan. The discovered models using routine clinical data predicted specific psychological problems with varying accuracy. With further validation, these models could become the tools of routine recommendations for referral to psychological care.

Contexte: Le traitement à vie des patients atteints d'une cardiopathie congénitale commence habituellement dès un jeune âge. Ainsi, les cardiologues pédiatriques ont un point de vue unique sur la santé mentale de leurs patients. Notre objectif était de décrire et de prédire les troubles psychologiques signalés chez les adolescents atteints d'une cardiopathie congénitale. Méthodologie: Nous avons effectué une revue rétrospective des dossiers de patients âgés de 12 à 17 ans qui se sont présentés dans une clinique de cardiologie pour anomalies congénitales sur une période d'un an. Nous avons recensé toute présence de problèmes psychologiques, en plus de la classe de la cardiopathie congénitale, des antécédents cliniques, des retards de développement et des caractéristiques démographiques des patients. Nous avons également décrit la prévalence des troubles psychologiques; puis, à l'aide d'algorithmes d'apprentissage automatique, nous avons donné une formation sur des modèles prédictifs optimaux et les avons testés. Résultats: Chez les 397 patients qui avaient répondu aux critères d'inclusion, la prévalence de la survenue d'un problème psychologique au cours de leur vie s'élevait à 35,5 %. Les troubles signalés le plus souvent étaient le trouble déficitaire de l'attention avec hyperactivité (TDAH) (18,9 %), l'anxiété (17,6 %) et la dépression (16,1 %). Contrairement à nos attentes, nous n'avons pas pu prédire la présence ou l'absence de troubles psychologiques à l'aide des données cliniques courantes. Nous avons par contre découvert des modèles multivariés pouvant prédire la dépression et le TDAH avec une précision prometteuse. Toutefois, les prédictions relatives à l'anxiété se sont avérées moins exactes. Conclusion: La prévalence de la survenue d'au moins un problème psychologique chez les adolescents atteints de cardiopathie congénitale au cours de leur vie était d'environ un adolescent sur trois. Dans le cadre d'un plan de soins complet, les programmes en cardiologie congénitale se trouvent en position d'influence pour répondre à ces problèmes et ainsi améliorer la santé mentale des patients. Par ailleurs, les modèles que nous avons découverts à l'aide des données cliniques courantes ont permis de prédire des problèmes psychologiques en particulier, mais avec une précision variable. Après une validation plus poussée, nous pourrions recommander ces modèles de façon systématique afin d'orienter les patients vers des soins psychologiques.

Advances in TEE-Centric Intraprocedural Multimodal Image Guidance for Congenital and Structural Heart Disease.

Percutaneous interventions are gaining rapid acceptance in cardiology and revolutionizing the treatment of structural heart disease (SHD). As new percutaneous procedures of SHD are being developed, their associated complexity and anatomical variability demand a high-resolution special understanding for intraprocedural image guidance. During the last decade, three-dimensional (3D) transesophageal echocardiography (TEE) has become one of the most accessed imaging methods for structural interventions. Although 3D-TEE can assess cardiac structures and functions in real-time, its limitations (e.g., limited field of view, image quality at a large depth, etc.) must be addressed for its universal adaptation, as well as to improve the quality of its imaging and interventions. This review aims to present the role of TEE in the intraprocedural guidance of percutaneous structural interventions. We also focus on the current and future developments required in a multimodal image integration process when using TEE to enhance the management of congenital and SHD treatments.

Antenatal Three-Dimensional Printing for Ex Utero Intrapartum Treatment Procedures.

BACKGROUND: Prenatal ultrasonography allows for timely identification of fetal abnormalities that can have an effect on securing the neonatal airway at delivery. We illustrate the role of antenatal three-dimensional printing in cases with fetal airway obstruction. CASE: We present two cases that highlight the utility of a three-dimensional printing technique to aid in ex utero intrapartum treatment procedures during cesarean delivery. CONCLUSION: Three-dimensional printing plays a complementary role to standard imaging options in optimizing presurgical planning, prenatal parental counseling, personalized patient care, and education of the multidisciplinary team in cases of fetal congenital airway obstruction.

Moving beyond two-dimensional screens to interactive three-dimensional visualization in congenital heart disease.

Beginning with the discovery of X-rays to the development of three-dimensional (3D) imaging, improvements in acquisition, post-processing, and visualization have provided clinicians with detailed information for increasingly accurate medical diagnosis and clinical management. This paper highlights advances in imaging technologies for congenital heart disease (CHD), medical adoption, and future developments required to improve pre-procedural and intra-procedural guidance.

Three-dimensional printing for surgical planning in complex congenital heart disease.

Surgical management of complex congenital heart disease (CHD) is challenging. Three-dimensional (3D) printing can improve multidisciplinary team decision-making, patient and family understanding, and education of medical professionals. We describe 3D printing for surgical management of five patients with complex CHD. The anatomical details of the 3D printed models were instrumental in planning surgical techniques especially in determining between single ventricle, 1.5 ventricle, and biventricular repair.

Integration of Computed Tomography and Three-Dimensional Echocardiography for Hybrid Three-Dimensional Printing in Congenital Heart Disease.

Three-dimensional (3D) printing is an emerging technology aiding diagnostics, education, and interventional, and surgical planning in congenital heart disease (CHD). Three-dimensional printing has been derived from computed tomography, cardiac magnetic resonance, and 3D echocardiography. However, individually the imaging modalities may not provide adequate visualization of complex CHD. The integration of the strengths of two or more imaging modalities has the potential to enhance visualization of cardiac pathomorphology. We describe the feasibility of hybrid 3D printing from two imaging modalities in a patient with congenitally corrected transposition of the great arteries (L-TGA). Hybrid 3D printing may be useful as an additional tool for cardiologists and cardiothoracic surgeons in planning interventions in children and adults with CHD.