Assessing the performance of ultrafast vector flow imaging in the neonatal heart via multiphysics modeling and In vitro experiments

Ultrafast vector flow imaging would benefit newborn patients with congenital heart disorders, but still requires thorough validation before translation to clinical practice. This paper investigates 2-D speckle tracking (ST) of intraventricular blood flow in neonates when transmitting diverging waves at ultrafast frame rate. Computational and in vitro studies enabled us to quantify the performance and identify artifacts related to the flow and the imaging sequence. First, synthetic ultrasound images of a neonate's left ventricular flow pattern were obtained with the ultrasound simulator Field II by propagating point scatterers according to 3-D intraventricular flow fields obtained with computational fluid dynamics (CFD). Noncompounded diverging waves (opening angle of 60 degrees) were transmitted at a pulse repetition frequency of 9 kHz. ST of the B-mode data provided 2-D flow estimates at 180 Hz, which were compared with the CFD flow field. We demonstrated that the diastolic inflow jet showed a strong bias in the lateral velocity estimates at the edges of the jet, as confirmed by additional in vitro tests on a jet flow phantom. Furthermore, ST performance was highly dependent on the cardiac phase with low flows (< 5 cm/s), high spatial flow gradients, and out-of-plane flow as deteriorating factors. Despite the observed artifacts, a good overall performance of 2-D ST was obtained with a median magnitude underestimation and angular deviation of, respectively, 28% and 13.5 degrees during systole and 16% and 10.5 degrees during diastole

Ultrafast Magnetic Resonance Imaging for Iron Quantification in Thalassemia Participants in the Developing World The TIC-TOC Study (Thailand and UK International Collaboration in Thalassaemia Optimising Ultrafast CMR)

Thalassemia is the most common monogenetic disorder worldwide, with 60 000 infants with thalassemia major born annually.1 Survival often depends on regular blood transfusions to correct anemia and to reduce ineffective erythropoiesis, but these transfusions can result in iron overload and organ failure unless chelation therapy is undertaken. Serum ferritin levels continue to be used as a guide to chelation but are unreliable, and the availability of cardiovascular magnetic resonance (CMR) T2* imaging has transformed patient management by allowing organ-specific quantification of iron content. Countries with a high prevalence of thalassemia major have CMR, but magnet time is expensive and analytic expertise lacking. The aim of TIC-TOC (Thailand and UK International Collaboration in Thalassaemia Optimising Ultrafast CMR) was to investigate whether ultrafast CMR mapping could provide reliable immediate diagnoses of heart and liver iron content, eliminating the need for complex analysis, thus reducing costs to a level within local resources. The research received approval by the Institutional Review Board of the Faculty of Medicine at Chulalongkorn University. All participants provided written informed consent.</p

Numerical Evaluation of Microwave Thermal Ablation to Treat Small Adrenocortical Masses

In this paper microwave thermal ablation is numerically evaluated in the context of a treatment for Conn’s Syndrome. This condition is caused by a benign shallow tumour in the cortex of adrenal gland. The modelling and design of microwave applicator to deliver thermal ablation to the adrenal gland requires accurate tissue characterisation. Measuring the dielectric properties of the constituent tissues in the adrenal gland, i.e. cortex and medulla, enables more accurate numerical modelling for electromagnetic and thermal simulations. This study presents an anatomically and dielectrically realistic numerical model of the adrenal gland, and investigates the feasibility of applying controlled heating to small targets in the adrenal cortex. In addition, the use of dielectric contrast between the fat and the cortex of the adrenal gland to focus the thermal energy in the gland has also been studied. Being conscious of limitations of numerical simulation of complex multiphysics problems like the microwave ablative treatment, calculated results provide a preliminary description of the electromagnetic and thermal phenomena involved

Um Estudo Sobre o Desenvolvimento de uma Taxonomia para a Classificação de Trabalhos de um Mapeamento Sistemático sobre o uso de Ontologias em Informática Médica

Tendo em vista a importância que a Informática Médica tem adquirido juntamente com a utilização de técnicas de Inteligência Artificial em suas aplicações, principalmente no que diz respeito à Engenharia do Conhecimento e Ontologias, faz-se necessário mapear a evolução desta área de maneira completa, imparcial e sistemática. Para tanto foi construído um Mapeamento Sistemático sobre o uso de Ontologias em Informática Médica. Como não há uma taxonomia geral que defina as subáreas da Informática Médica, este trabalho apresenta um estudo sobre a construção de uma taxonomia que caracterize todas as subáreas da Informática Médica que permita classificar os estudos selecionados para o Mapeamento Sistemático

Regression Analysis of Rectal Cancer and Possible Application of Artificial Intelligence (AI) Utilization in Radiotherapy

Artificial Intelligence (AI) has been widely employed in the medical field in recent years in such areas as image segmentation, medical image registration, and computer-aided detection. This study explores one application of using AI in adaptive radiation therapy treatment planning by predicting the tumor volume reduction rate (TVRR). Cone beam computed tomography (CBCT) scans of twenty rectal cancer patients were collected to observe the change in tumor volume over the course of a standard five-week radiotherapy treatment. In addition to treatment volume, patient data including patient age, gender, weight, number of treatment fractions, and dose per fraction were also collected. Application of a stepwise regression model showed that age, dose per fraction and weight were the best predictors for tumor volume reduction rate