The comprehension of molecular recognition phenomena demands the understanding of the energetic and kinetic processes involved. General equations valid for the thermodynamic analysis of any observable that is assessed as a function of the concentration of the involved compounds are described, together with their implementation in the AFFINImeter software.Here, a maximum of three different molecular species that can interact with each other to form an enormous variety of supramolecular complexes are considered. The corrections currently employed to take into account the effects of dilution, volume displacement, concentration errors and those due to external factors, especially in the case of ITC measurements, are included. The methods used to fit the model parameters to the experimental data, and to generate the uncertainties are described in detail. A simulation tool and the so called kinITC analysis to get kinetic information from calorimetric experiments are also presented. An example of how to take advantage of the AFFINImeter software for the global multi-temperature analysis of a system exhibiting cooperative 1:2 interactions is presented and the results are compared with data previously published. Some useful recommendations for the analysis of experiments aimed at studying molecular interactions are provided.

Lung vessel segmentation has been widely explored by the biomedical image processing community; however, the differentiation of arterial from venous irrigation is still a challenge. Pulmonary artery-vein (AV) segmentation using computed tomography (CT) is growing in importance owing to its undeniable utility in multiple cardiopulmonary pathological states, especially those implying vascular remodelling, allowing the study of both flow systems separately. We present a new framework to approach the separation of tree-like structures using local information and a specifically designed graph-cut methodology that ensures connectivity as well as the spatial and directional consistency of the derived subtrees. This framework has been applied to the pulmonary AV classification using a random forest (RF) pre-classifier to exploit the local anatomical differences of arteries and veins. The evaluation of the system was performed using 192 bronchopulmonary segment phantoms, 48 anthropomorphic pulmonary CT phantoms, and 26 lungs from noncontrast CT images with precise voxel-based reference standards obtained by manually labelling the vessel trees. The experiments reveal a relevant improvement in the accuracy ( ~ 20%) of the vessel particle classification with the proposed framework with respect to using only the pre-classification based on local information applied to the whole area of the lung under study. The results demonstrated the accurate differentiation between arteries and veins in both clinical and synthetic cases, specifically when the image quality can guarantee a good airway segmentation, which opens a huge range of possibilities in the clinical study of cardiopulmonary diseases.

Background The EU gadolinium-based contrast agents (GBCA) market has changed in recent years due to the European Medicines Agency decision to suspend the marketing authorisation of linear GBCA and the marketing authorisation of new generic macrocyclic GBCA. The study aims to understand the patterns of (GBCA) use, and to study the effectiveness and safety of GBCA in routine practice across Europe. Methods Prospective, cross-sectional, multicentre, observational study in patients undergoing contrast-enhanced magnetic resonance. Reported usage patterns included indication, referral and examination details. Assessment of effectiveness included changes in radiological diagnosis, diagnostic confidence and image quality. Safety data were collected by spontaneous patient adverse event (AE) reporting. Results 2118 patients were included from 8 centres across 5 European countries between December 2018 and November 2019. Clariscan, Dotarem (gadoteric acid), Gadovist (gadobutrol) and ProHance (gadoteridol) were utilised in 1513 (71.4%), 356 (16.8%), 237 (11.2%) and 12 (0.6%) patients, respectively. Most were performed in CNS-related indications (46.2%). Mean GBCA doses were 0.10 mmol/kg body weight, except for Gadovist (mean 0.12 mmol/kg). GBCA use increased confidence in diagnosis in 96.2% of examinations and resulted in a change in radiological diagnosis in 73.9% of patients. Image quality was considered excellent or good in 96.1% of patients and across all GBCA. Four patients reported AEs (0.19%), with only 1 (0.05%) considered serious. Conclusions This European study confirmed that GBCAs are used appropriately in Europe for a wide range of indications. The study demonstrated a significant increase in diagnostic confidence after GBCA use and confirmed the good safety profile of GBCAs, with comparable results for all agents used.

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