HPC+ in the medical field: Overview and current examples.

BACKGROUND: To say data is revolutionising the medical sector would be a vast understatement. The amount of medical data available today is unprecedented and has the potential to enable to date unseen forms of healthcare. To process this huge amount of data, an equally huge amount of computing power is required, which cannot be provided by regular desktop computers. These areas can be (and already are) supported by High-Performance-Computing (HPC), High-Performance Data Analytics (HPDA), and AI (together "HPC+"). OBJECTIVE: This overview article aims to show state-of-the-art examples of studies supported by the National Competence Centres (NCCs) in HPC+ within the EuroCC project, employing HPC, HPDA and AI for medical applications. METHOD: The included studies on different applications of HPC in the medical sector were sourced from the National Competence Centres in HPC and compiled into an overview article. Methods include the application of HPC+ for medical image processing, high-performance medical and pharmaceutical data analytics, an application for pediatric dosimetry, and a cloud-based HPC platform to support systemic pulmonary shunting procedures. RESULTS: This article showcases state-of-the-art applications and large-scale data analytics in the medical sector employing HPC+ within surgery, medical image processing in diagnostics, nutritional support of patients in hospitals, treating congenital heart diseases in children, and within basic research. CONCLUSION: HPC+ support scientific fields from research to industrial applications in the medical area, enabling researchers to run faster and more complex calculations, simulations and data analyses for the direct benefit of patients, doctors, clinicians and as an accelerator for medical research.

A novel formulation for the study of the ascending aortic fluid dynamics with in vivo data.

Numerical simulations to evaluate thoracic aortic hemodynamics include a computational fluid dynamic (CFD) approach or fluid-structure interaction (FSI) approach. While CFD neglects the arterial deformation along the cardiac cycle by applying a rigid wall simplification, on the other side the FSI simulation requires a lot of assumptions for the material properties definition and high computational costs. The aim of this study is to investigate the feasibility of a new strategy, based on Radial Basis Functions (RBF) mesh morphing technique and transient simulations, able to introduce the patient-specific changes in aortic geometry during the cardiac cycle. Starting from medical images, aorta models at different phases of cardiac cycle were reconstructed and a transient shape deformation was obtained by proper activating incremental RBF solutions during the simulation process. The results, in terms of main hemodynamic parameters, were compared with two performed CFD simulations for the aortic model at minimum and maximum volume. Our implemented strategy copes the actual arterial variation during cardiac cycle with high accuracy, capturing the impact of geometrical variations on fluid dynamics, overcoming the complexity of a standard FSI approach.

Adaptability and stability evaluation of maize hybrids using Bayesian segmented regression models.

The occurrence of genotype by environment interaction (G x E), which is defined as the differential response of genotypes to environmental variation, is frequently reported in maize cultures, making it challenging to recommend cultivars. Methods allowing to study the potential nonlinear pattern of genotype responses to environmental variation allied to prior beliefs on unknown parameters are interesting to evaluate the phenotypic adaptability and stability of genotypes. In this context, the present study aimed to assess the adaptability and stability of maize hybrids, by using the Bayesian segmented regression model, and evaluate the efficacy of using informative and minimally informative prior distributions for the selection of cultivars. Randomized complete-block design experiments were carried out to study the yield (kg/ha) of 25 maize hybrids, in 22 different environments, in Northeastern Brazil. The Bayesian segmented regression model fitted using informative prior distributions presented lower credibility intervals and Deviance Criterium of Information values, compared to those obtained by fitting using minimally informative distributions. Therefore, the model using informative prior distributions was considered for the adaptability and stability evaluation of maize genotypes. Once most northeastern farmers in Brazil have limited capital, the genotype P4285HX should be considered for planting, due to its high yield performance and adaptability to unfavorable environments.

Computational Fluid Dynamic Study for aTAA Hemodynamics: An Integrated Image-Based and Radial Basis Functions Mesh Morphing Approach.

We present a novel framework for the fluid dynamics analysis of healthy subjects and patients affected by ascending thoracic aorta aneurysm (aTAA). Our aim is to obtain indications about the effect of a bulge on the hemodynamic environment at different enlargements. Three-dimensional (3D) surface models defined from healthy subjects and patients with aTAA, selected for surgical repair, were generated. A representative shape model for both healthy and pathological groups has been identified. A morphing technique based on radial basis functions (RBF) was applied to mold the shape relative to healthy patient into the representative shape of aTAA dataset to enable the parametric simulation of the aTAA formation. Computational fluid dynamics (CFD) simulations were performed by means of a finite volume solver using the mean boundary conditions obtained from three-dimensional (PC-MRI) acquisition. Blood flow helicity and flow descriptors were assessed for all the investigated models. The feasibility of the proposed integrated approach pertaining the coupling between an RBF morphing technique and CFD simulation for aTAA was demonstrated. Significant hemodynamic changes appear at the 60% of the bulge progression. An impingement of the flow toward the bulge was observed by analyzing the normalized flow eccentricity (NFE) index.

Evaluation of maize top crosses under two nitrogen levels / Avaliação de top crosses de milho em duas doses de nitrogênio

Maize crops in Brazil have a wide diversity of management systems. There is a large contingent of family agriculture, which uses little or no agricultural inputs, compared to the rural enterprise which uses the most modern production systems. This difference in the management systems is particularly noticeable in relation to consumption of fertilizers, especially nitrogenous ones. Therefore it is necessary to obtain plants with efficient nitrogen (N) use that also respond to applied nitrogen. Thus, the aim of the study was to evaluate the performance of S0:1 progenies, in top crosses, under two nitrogen levels and select the best ones based on responsiveness and efficiency. Sixty seven S0:1 progenies from populations of single cross hybrids were crossed with two testers (T1 - single cross hybrid; T2 - population per se). A hundred and thirty four hybrid progenies plus ten controls were evaluated in two field trials with different levels of nitrogen (one with average levels - 50 kg ha-1 of N - and the other with low levels of nitrogen - 25 kg ha-1 of N) in a 12 x 12 triple lattice design. It is possible to identify and to select progenies from commercial single cross hybrids that are efficient and responsive to nitrogen application. The non-additive effect was as important as the additive effect for grain yield under different nitrogen levels.

A cultura do milho no Brasil tem uma ampla diversidade no sistema de manejo. Há um grande contingente de agricultura tipicamente familiar que usa pouco insumo agrícola, e também empresas rurais que utilizam o que há de mais moderno em sistema de produção. Essa diferença no sistema de manejo fica bem evidenciada no que refere ao consumo de fertilizantes, especialmente os nitrogenados. Por isso, é necessário obter plantas eficientes no uso de nitrogênio (N) e, ao mesmo tempo, que sejam responsivas ao N aplicado. Desse modo, neste trabalho, objetivou-se avaliar a resposta, a diferentes níveis de N, de progênies S0:1 de milho e sua capacidade de combinação, utilizando dois testadores diferentes. Foram utilizadas 67 progênies S0:1, oriundas de híbridos comerciais, em topcross com dois testadores (T1 - híbrido simples; T2 - população per ser das progênies S0:1). Os top crosses foram avaliados, juntamente com 10 testemunhas, em dois experimentos com diferentes níveis de nitrogênio (nível médio - 50 kg ha-1 de N - e outro com nível baixo - 25 kg ha-1 de N), no delineamento experimental látice triplo 12 x 12. Os resultados obtidos permitiram verificar que não ocorreu alteração no comportamento dos top crosses em diferentes doses de nitrogênio, para produtividade de grãos. É possível identificar e selecionar progênies parcialmente endogâmicas responsivas e eficientes na utilização de N, provenientes de híbridos comerciais. Os efeitos não-aditivos foram tão importantes quanto os efeitos aditivos para produtividade de grão sob diferentes níveis de nitrogênios.