Carolina Bezzi
Vita-Salute San Raffaele University
26 Papers
14 Citations
Carolina Bezzi is an academic researcher from Vita-Salute San Raffaele University. The author has contributed to research in topics: Medicine & Prostate cancer. The author has an hindex of 2, co-authored 7 publications.
Chat about Author
Papers
68Ga-DOTATOC PET/MR imaging and radiomic parameters in predicting histopathological prognostic factors in patients with pancreatic neuroendocrine well-differentiated tumours
Paola Mapelli,Carolina Bezzi,Diego Palumbo,Carla Canevari,Samuele Ghezzo,Ana Maria Samanes Gajate,B. Catalfamo,Alberto Messina,Luca Presotto,Alberto Guarnaccia,Valentino Bettinardi,Francesca Muffatti,V. Andrei,Marco Schiavo Lena,Luigi Gianolli,Stefano Partelli,M. Falconi,Paola Scifo,Francesco De Cobelli,Maria Picchio +19 more
TL;DR: The role of the fully hybrid 68Ga-DOTATOC PET/MRI tool is demonstrated for the synergic function of imaging parameters extracted by the two modalities and highlights the potentiality of imaging and radiomic parameters in assessing histopathological features of PanNET aggressiveness.
27
Preliminary Results of an Ongoing Prospective Clinical Trial on the Use of 68Ga-PSMA and 68Ga-DOTA-RM2 PET/MRI in Staging of High-Risk Prostate Cancer Patients.
Paola Mapelli,Samuele Ghezzo,Ana Maria Samanes Gajate,Erik Preza,Giorgio Brembilla,Vito Cucchiara,Naghia Ahmed,Carolina Bezzi,Luca Presotto,Valentino Bettinardi,A. Savi,Patrizia Magnani,Raffaele Menichini,Angela Coliva,Ilaria Neri,Ettore Di Gaeta,Luigi Gianolli,Massimo Freschi,Alberto Briganti,Francesco De Cobelli,Paola Scifo,Maria Picchio +21 more
- 09 Nov 2021
TL;DR: In this article, the authors investigated the synergic role of 68Ga-PSMA PET/MRI and 68Gaa-DOTA-RM2PET/MRI in prostate cancer staging.
22
Role of [^68Ga]Ga-PSMA-11 PET radiomics to predict post-surgical ISUP grade in primary prostate cancer
Samuele Ghezzo,Paola Mapelli,Carolina Bezzi,Ana Maria Samanes Gajate,Giorgio Brembilla,Irene Gotuzzo,Tommaso Russo,Erik Preza,Vito Cucchiara,Naghia Ahmed,Ilaria Neri,S. Mongardi,Massimo Freschi,Alberto Briganti,Francesco De Cobelli,Luigi Gianolli,Paola Scifo,Maria Picchio +17 more
TL;DR: The findings support the role of [^68Ga]Ga-PSMA-11 PET radiomics for the accurate and non-invasive prediction of _PSISUP grade in primary prostate cancer (PCa).
17
Hybrid PET/MRI in Staging Endometrial Cancer
Gabriele Ironi,Paola Mapelli,Alice Bergamini,Federico Fallanca,Giorgio Candotti,Chiara Gnasso,Gianluca Taccagni,Miriam Sant'Angelo,Paola Scifo,Carolina Bezzi,Valentino Bettinardi,Paola M.V. Rancoita,Giorgia Mangili,Luca Bocciolone,Massimo Candiani,Luigi Gianolli,Francesco De Cobelli,Maria Picchio +17 more
TL;DR: 18F-FDG PET/MRI has good accuracy in preoperative staging of EC; PET and MRI parameters have synergic role in preoperatively predicting LVSI, with MRI parameters being also predictive for EC risk group.
12
External validation of a convolutional neural network for the automatic segmentation of intraprostatic tumor lesions on 68Ga-PSMA PET images
Samuele Ghezzo,S. Mongardi,Carolina Bezzi,Ana Maria Samanes Gajate,Erik Preza,Irene Gotuzzo,Francesco Baldassi,Lorenzo Jonghi-Lavarini,Ilaria Neri,Tommaso Russo,Giorgio Brembilla,Francesco De Cobelli,Paola Scifo,Paola Mapelli,Maria Picchio +14 more
TL;DR: Dejankostyszyn et al. as mentioned in this paper proposed a convolutional neural network (CNN) for the automatic segmentation of intraprostatic cancer lesions on PSMA PET images.