Ricercatore
Macro-area: Fisica Applicata, didattica e storia della Fisica
SSD: FIS/07
marianna.inglese@uniroma2.it
Marianna Inglese, ricercatore di Fisica medica presso l’Università di Tor Vergata, ha conseguito la laurea magistrale in Ingegneria biomedica presso l’Università di Roma “La Sapienza” nel 2014. La sua tesi, incentrata sulla correzione delle immagini PET per piattaforme ibride PET/MRI, è stata portata a termine presso il Lawson Health Research Institute della University of Western Ontario.
Ha conseguito il dottorato di ricerca in Bioingegneria presso l’Università di Roma “La Sapienza” nel 2019, ricercando metodi avanzati di quantificazione della perfusione per dati dinamici PET e RM.
Marianna è assegnista di ricerca onoraria presso l’Imperial College di Londra, dove in precedenza ha lavorato sulla quantificazione dei dati PET dinamici e sull’applicazione dell’apprendimento automatico per gli studi radiomici.
Ha ricevuto diversi riconoscimenti, tra cui un “Magna cum laude” dall’ISMRM e un premio per il secondo posto al Perfusion Workshop e al PET/MRI Workshop dell’ISMRM. È membro dell’AIIC, del GNB, del Capitolo britannico e irlandese dell’ISMRM, dell’ISMRM, del BNOS e dell’AISUK.
Malignant transformation is characterised by aberrant phospholipid metabolism of cancers, associated with the upregulation of choline kinase alpha (CHKα). Due to the metabolic instability of choline radiotracers and the increasing use of late-imaging protocols, we developed a more stable choline radiotracer, [^(18)F]fluoromethyl-[1,2-²H(4)]choline ([^(18)F]D4-FCH). [^(18)F]D4-FCH has improved protection against choline oxidase, the key choline catabolic enzyme, via a ¹H/²D isotope effect,...
CONCLUSIONS: This study reports results from the OSIPI-DCE challenge and highlights the high inter-software variability within K trans $$ {K}^{\mathrm{trans}} $$ estimation, providing a framework for ongoing benchmarking against the scores presented. Through this challenge, the participating teams were ranked based on the performance of their software tools in the particular setting of this challenge. In a real-world clinical setting, many of these tools may perform differently with...
CONCLUSIONS: SN-RPV may provide net-benefit in terms of earlier cancer diagnosis.
CONCLUSION: Tumoural FPIA PET uptake is higher in HGG compared to LGG. This study supports further investigation of FPIA PET/MRI for brain tumour imaging in a larger patient population.
Traditional imaging techniques for breast cancer (BC) diagnosis and prediction, such as X-rays and magnetic resonance imaging (MRI), demonstrate varying sensitivity and specificity due to clinical and technological factors. Consequently, positron emission tomography (PET), capable of detecting abnormal metabolic activity, has emerged as a more effective tool, providing critical quantitative and qualitative tumor-related metabolic information. This study leverages a public clinical dataset of...