My PhD project araises from the major change that medicine and healthcare are experiencing in the last decades, moving from reactive to proactive approaches by providing Predictive, Preventive and Personalised medical solutions for the individual patients. The aim of this PhD project was to explore the role of radiomics and radiogenomics in lung and prostate cancers. At first I focused on the possible contribution of detecting circulating tumor cells and microemboli to diagnostic work up of patients with suspected malignant pulmonary lesions. At the same time we investigate the potential role of quantitative shape analysis in allowing CT differentiation between benign and malignant pulmonary nodules. In this perspective of translational medicine I started to collaborate with some engineers for the evaluation of the potential applications of Radiomics in the oncological field. Prostate cancer is extremely fit for this purpose, so we evaluate the role of radiomics features in predicting prostate cancer aggressiveness.

The era of translational medicine: from circulating tumor cells to radiomics and deep learning.

2019

Abstract

My PhD project araises from the major change that medicine and healthcare are experiencing in the last decades, moving from reactive to proactive approaches by providing Predictive, Preventive and Personalised medical solutions for the individual patients. The aim of this PhD project was to explore the role of radiomics and radiogenomics in lung and prostate cancers. At first I focused on the possible contribution of detecting circulating tumor cells and microemboli to diagnostic work up of patients with suspected malignant pulmonary lesions. At the same time we investigate the potential role of quantitative shape analysis in allowing CT differentiation between benign and malignant pulmonary nodules. In this perspective of translational medicine I started to collaborate with some engineers for the evaluation of the potential applications of Radiomics in the oncological field. Prostate cancer is extremely fit for this purpose, so we evaluate the role of radiomics features in predicting prostate cancer aggressiveness.
14-dic-2019
Italiano
Caramella, Davide
Serni, Sergio
Università degli Studi di Pisa
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14242/149767
Il codice NBN di questa tesi è URN:NBN:IT:UNIPI-149767