MRI is a fundamental tool for non-invasive study of the human brain and body in life sciences and in clinical practice. With appropriate combinations of pulse sequences, it alters the atomic spins of the body to gather information about multiple physiological parameters, including molecular motion, temperature, pH, chemical environment, water diffusion, neural morphometry and activation, and many others.
The availability of high performance 3 tesla (T) platforms enabled the diffusion of new approaches, substantially increasing the potential for quantitative in vivo investigations in life sciences, and for multimodal integration with complemental techniques. The potentials of MRI for innovative applications need a multidisciplinary approach to be fully developed.
The aim of our project is to develop a Research Center for life sciences focused on the development and application of advanced MRI techniques, exploiting the integration of multidisciplinary expertise available locally and fostering excellence in biomedical research, a trademark of the Sapienza community.
Research will integrate research in neuroscience and cardiology, from medical engineering and information technologies for the development of a high performance, flexible platform, integrating cutting-edge data acquisition and innovative processing, which can be translated to experimental neuroscience, medicine, psychology, and human cognition.
Applications will include integrated research approaches focused on the study of functional aspects in human physiology, pathophysiology and psychology. The development of innovative MRI and quantitative image processing approaches will be integrated synergistically.
The platform will be a substantial improvement of the regional scientific infrastructure, allowing significant synergy with the biomedical industry, via the implementation of a flexible and advanced research infrastructure open to collaborations for the development of new treatments and drugs.
Neurosciences
The accessory and optional systems necessary for the multimodal study of the brain, (i.e. the VISUASTIM system, fMRI projector, response pad, BIOPAC system, control workstation and related software, electroencephalographic and DC-stimulator) mainly consist of a series of hardware and software products for multimodal brain stimulation and simultaneous response recording. New discoveries in brain organization structure and function lead to a network view of the brain allowing the assessment of connectivity through MRI. Detailed measurements require fine settings: the increasing sensitivity in techniques and sequences, increasing spatial and temporal resolution and higher fields and gradient strengths lead to higher impact of scanner artifacts (e.g. signal drift, magnetic susceptibility, and other), physiological rhythms (e.g. of cardiac or respiratory origin), subjective factors (e.g. involuntary movement, one of the most problematic) and many other confounding factors, that need targeted monitoring and control. To overcome these problems and optimize the MR signal an international efforts with multisite collaborative projects have indicated procedures and guidelines to follow.
The Department of Human Neuroscience has been involved in multicenter international studies based on MRI standards approved by various international centers. The accessory and optional systems necessary for the present project will allow the specifications indicated by most major international protocols. Finally the concurrent acquisition of functional MRI and neurophysiological recordings (including EEG and Electromyographic activity) offers the opportunity to identify patterns of neural activity associated with motor performance with high spatial and temporal resolution.
Both the Departments of Human Neurosciences and Psychology have a long-standing experience in the field of Functional MRI and Neurophysiology with various types of stimuli, that is acknowledged by the scientific international community. In the last years the improvement in brain stimulation and measurement systems under fMRI has reached a high level of precision and accuracy that requires the update of the experimental settings and imposes the choice of well re-known and validated systems, that guarantee reproducibility and comparability of results.
Cardiology
Unique tissue characterization capabilities combined with functional assessment and precise quantification of biventricular volumes and flows, has rendered CMR the method of reference for the in-vivo evaluation of the vast majority of myocardial diseases. However, the rapid development of more elaborate sequences caused an increasing complex mass of data requiring implementation of more advanced image analysis software.
Current research trends in cardiovascular imaging are aimed to improve and refine techniques both on the quantitative analysis of tissue relaxivity, on the geometric mechanic distortions of the cardiac chambers over the cycle and the three-dimensional evaluation of the blood flows. This requires today to move towards to an analysis in 4D environment and to combine the different parametric tissue characteristics in fusion maps.
The proposed software enables to perform tissue mapping, advanced analysis of myocardial contraction through feature tracking algorithm and evaluation of 4D flow dataset. Moreover, the recent development of artificial intelligence systems promises to provided new valuable diagnostic tools in post-processing and finding interpretation.
To maintain cutting ¿ edge researches in the CMR field there is absolute need of these state-of-the-art features, which are currently lacking or only partially available on our MRI systems. Tissue mapping pulse sequences are currently only available in one of our 1.5T scanner, while 4D flow sequences only as prototype on a 3T scanner with limited application. Feature tracking technique is a analysis algorithm exploiting the information already present on the traditional ECG-gated cineMR images, widely available in all of our scanner. Having these software tools available would allow us to collaborate on equal terms with the most modern research centers, with the possibility of being leaders in international studies with centralized data analysis.
The rise of artificial intelligence has yet to come, as extensive validation of algorithms in several different populations is needed before clinical application. In this context there are several ongoing multicentric studies that we could participate in, if we had advanced enough hardware and software.
With time, the absence of these techniques will become heavier and heavier, and will inevitably reflect on the attractiveness of our institution.