Publications by authors named "Michela Azzarito"

We present the motivation, experience, and learnings from a data challenge conducted at a large pharmaceutical corporation on the topic of subgroup identification. The data challenge aimed at exploring approaches to subgroup identification for future clinical trials. To mimic a realistic setting, participants had access to 4 Phase III clinical trials to derive a subgroup and predict its treatment effect on a future study not accessible to challenge participants.

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Motor skill learning relies on neural plasticity in the motor and limbic systems. However, the spatial and temporal characteristics of these changes-and their microstructural underpinnings-remain unclear. Eighteen healthy males received 1 h of training in a computer-based motion game, 4 times a week, for 4 consecutive weeks, while 14 untrained participants underwent scanning only.

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Background: The ability to assess brain and cord atrophy simultaneously would improve the efficiency of MRI to track disease evolution.

Objective: To test a promising tool to simultaneously map the regional distribution of atrophy in multiple sclerosis (MS) patients across the brain and cord.

Methods: Voxel-based morphometry combined with a statistical parametric mapping probabilistic brain-spinal cord (SPM-BSC) template was applied to standard T1-weighted magnetic resonance imaging (MRI) scans covering the brain and cervical cord from 37 MS patients and 20 healthy controls (HC).

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Quantitative MR imaging is increasingly favoured for its richer information content and standardised measures. However, computing quantitative parameter maps, such as those encoding longitudinal relaxation rate (R), apparent transverse relaxation rate (R) or magnetisation-transfer saturation (MT), involves inverting a highly non-linear function. Many methods for deriving parameter maps assume perfect measurements and do not consider how noise is propagated through the estimation procedure, resulting in needlessly noisy maps.

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Objective: To track the interplay between (micro-) structural changes along the trajectories of nociceptive pathways and its relation to the presence and intensity of neuropathic pain (NP) after spinal cord injury (SCI).

Methods: A quantitative neuroimaging approach employing a multiparametric mapping protocol was used, providing indirect measures of myelination (via contrasts such as magnetisation transfer (MT) saturation, longitudinal relaxation (R1)) and iron content (via effective transverse relaxation rate (R2*)) was used to track microstructural changes within nociceptive pathways. In order to characterise concurrent changes along the entire neuroaxis, a combined brain and spinal cord template embedded in the statistical parametric mapping framework was used.

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To validate a simultaneous analysis tool for the brain and cervical cord embedded in the statistical parametric mapping (SPM) framework, we compared trauma-induced macro- and microstructural changes in spinal cord injury (SCI) patients to controls. The findings were compared with results obtained from existing processing tools that assess the brain and spinal cord separately. A probabilistic brain-spinal cord template (BSC) was generated using a generative semi-supervised modelling approach.

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Objective: To quantify neurodegenerative changes along the cervical spinal cord rostral to a spinal cord injury (SCI) by means of quantitative MRI (qMRI) and to determine its relationship with clinical impairment.

Methods: Thirty chronic SCI patients (15 tetraplegics and 15 paraplegics) and 23 healthy controls underwent a high-resolution T1-weighted and myelin-sensitive magnetization transfer (MT) MRI. We assessed macro- and microstructural changes along the cervical cord from levels C1 to C4, calculating cross-sectional spinal cord area, its anterior-posterior and left-right width and myelin content (i.

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Modern concepts for the treatment of myocardial diseases focus on novel cell therapeutic strategies involving stem cell-derived cardiomyocytes (SCMs). However, functional integration of SCMs requires similar electrophysiological properties as primary cardiomyocytes (PCMs) and the ability to establish intercellular connections with host myocytes in order to contribute to the electrical and mechanical activity of the heart. The aim of this project was to investigate the properties of cardiac conduction in a co-culture approach using SCMs and PCMs in cultured cell strands.

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This paper presents new learning-based techniques for measuring disease progression in Multiple Sclerosis (MS) patients. Our system aims to augment conventional neurological examinations by adding quantitative evidence of disease progression. An off-the-shelf depth camera is used to image the patient at the examination, during which he/she is asked to perform carefully selected movements.

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