Publications by authors named "M Fato"
Objective: High Angular Resolution Diffusion Imaging (HARDI) models have emerged as a valuable tool for investigating microstructure with a higher degree of detail than standard diffusion Magnetic Resonance Imaging (dMRI). In this study, we explored the potential of multiple advanced microstructural diffusion models for investigating preterm birth in order to identify non-invasive markers of altered white matter development.
Approach: Rather than focusing on a single MRI modality, we studied on a compound of HARDI techniques in 46 preterm babies studied on a 3T scanner at term-equivalent age and in 23 control neonates born at term.
Article Synopsis
- PET imaging with [F]F-DOPA shows promise for assessing pediatric brain gliomas, but manual extraction of data is slow and inconsistent.
- A new semi-automated Python framework was developed to streamline the processing of PET images and improve efficiency and accuracy in calculating clinical scores.
- The study found that this new method significantly improved reproducibility in extracting important tumor metrics and reduced the variability associated with human input.
Article Synopsis
- - Pain management after pectus excavatum surgery is crucial, yet there's no international consensus on guidelines, prompting the need for research to compare pain relief methods and long-term effects, especially using eHealth solutions for better data collection and patient engagement.
- - The study, part of the COPPER project by Giannina Gaslini Children's Hospital, aims to evaluate traditional thoracic epidural analgesia against cryoanalgesia, employing a web and mobile app to streamline data collection and analysis effectively.
- - Preliminary results from a pilot study with 72 patients show successful enrollment and balanced demographics, indicating the app's potential to enhance pain management evaluation and potentially reduce hospital stays.
Purpose: Different methods are available to identify haematopoietically active bone marrow (ActBM). However, their use can be challenging for radiotherapy routine treatments, since they require specific equipment and dedicated time. A machine learning (ML) approach, based on radiomic features as inputs to three different classifiers, was applied to computed tomography (CT) images to identify haematopoietically active bone marrow in anal cancer patients.
View Article and Find Full Text PDFIn vitro three-dimensional models aim to reduce and replace animal testing and establish new tools for oncology research and the development and testing of new anticancer therapies. Among the various techniques to produce more complex and realistic cancer models is bioprinting, which allows the realization of spatially controlled hydrogel-based scaffolds, easily incorporating different types of cells in order to recreate the crosstalk between cancer and stromal components. Bioprinting exhibits other advantages, such as the production of large constructs, the repeatability and high resolution of the process, as well as the possibility of vascularization of the models through different approaches.
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