Quantitative analysis of pre- and post-operative valvular annulus deformations following valvular insufficiency

Valvular insufficiency is a growingly common valvular heart disease that frequently is associated with regurgitation. Atrioventricular incompetency can lead to overall ventricular and atrial enlargement, volume overload, heart impairment and, if not treated, can culminate in heart failure. With the advances in technology and the increasing interest in devices that have lower post-operative burden on patients, transcatheter mitral and tricuspid valve repair systems are going through a phase of rapid development and growing use. In this work, we aimed to quantitatively assess the morphology of mitral and tricuspid annuli in patients who underwent transcatheter valve repair with MitraClip/TriClip, before and after the intervention, using three-dimensional transoesophageal echocardiography images, in order to evaluate the geometrical changes of the annulus following the intervention. For our purposes, firstly, we implemented a tool for the visualization and navigation of the volumetric data across the cardiac cycle. Then, in order to track the annulus over the cardiac cycle, we extracted five rotational slices from the volume data, selected two initial points on each slice, and tracked these points across the cardiac cycle using KLT algorithm. In a first stage we led a parameters optimization for the tracking method, and we studied the sensitivity of the KLT algorithm to the initialization points, that are manually chosen by the user. In a second stage, we analysed 10 subjects (5 for mitral regurgitation and 5 for tricuspid regurgitation), tracking their annulus before and after valve repairment. In conclusion, we found in all our 10 subjects that immediately after the intervention there is a shortening of the major diameters of the valves, mainly the shortest diameter, due to the clip application, that leads to a reduction of the perimeter and the area of the annulus.

Quantum computing and post-quantum cryptography

One of the main practical implications of quantum mechanical theory is quantum computing, and therefore the quantum computer. Quantum computing (for example, with Shor’s algorithm) challenges the computational hardness assumptions, such as the factoring problem and the discrete logarithm problem, that anchor the safety of cryptosystems. So the scientific community is studying how to defend cryptography; there are two defense strategies: the quantum cryptography (which involves the use of quantum cryptographic algorithms on quantum computers) and the post-quantum cryptography (based on classical cryptographic algorithms, but resistant to quantum computers). For example, National Institute of Standards and Technology (NIST) is collecting and standardizing the post-quantum ciphers, as it established DES and AES as symmetric cipher standards, in the past. In this thesis an introduction on quantum mechanics was given, in order to be able to talk about quantum computing and to analyze Shor’s algorithm. The differences between quantum and post-quantum cryptography were then analyzed. Subsequently the focus was given to the mathematical problems assumed to be resistant to quantum computers. To conclude, post-quantum digital signature cryptographic algorithms selected by NIST were studied and compared in order to apply them in today’s life.

Recognition of human activities through eSteps insoles

Recognition of everyday human activity through mobile personal sensing technology plays a central role in the field of pervasive healthcare. The Bologna-based American company eSteps Inc. addresses the growing motor disability of the lower limbs by offering pre-, during and post-hospitalisation monitoring solutions with biomechanics and telerehabilitation protocol. It has developed a smart, customised and sustainable device to monitor motor activity, fatigue and injury risk for patients and a special app to share data with caregivers and medical specialists. The objective of this study is the development of an Artificial Intelligence model to recognize the activity performed by a person with Multiple Sclerosis or a healthy person through eSteps devices.