Skip to Main Content (Press Enter)

Logo UNICH
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Professioni
  • Persone
  • Pubblicazioni
  • Strutture
  • Terza Missione
  • Attività
  • Competenze

UNI-FIND
Logo UNICH

|

UNI-FIND

unich.it
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Professioni
  • Persone
  • Pubblicazioni
  • Strutture
  • Terza Missione
  • Attività
  • Competenze
  1. Pubblicazioni

Generation of multiparametric MRI maps by using Gd-labelled-RBCs reveals phenotypes and stages of murine prostate cancer

Articolo
Data di Pubblicazione:
2018
Abstract:
Prostate Cancer (PCa) is the second most common and fifth cause of cancer-related mortality in males in Western Countries. The development of innovative tools for an early, more precise and noninvasive diagnosis is a medical need. Vascular volume (Vv) and hypoxia are two of the most important tumor hallmarks. Herein, they have been assessed in TRAMP mice by using MRI. Their quantification has been carried out by injecting autologous Red Blood Cells (RBCs), ex vivo labelled with Gd-HPDO3A or Gd-DOTP complexes, respectively. Gd-labelled-RBCs are stably confined in the intravascular space, also in presence of a very leaky tumor endothelium, thus representing efficient probes for vascular space analysis. Vv enhancement and hypoxia onset have been demonstrated to be present at early stages of PCa and their expression largely increases with tumor development. Moreover, also Diffusion weighted MRI and Amide Proton Transfer MRI have been herein applied to characterize PCa. The herein applied multiparametric MRI (mpMRI) analysis allows a detailed in vivo characterization of PCa, in which each histotype and cancer stage displays a specific MRI pattern. This provides an unprecedented opportunity to feature prostate tumor, making possible a non-invasive, precise and early diagnosis, which could direct treatments towards a more personalized medicine.
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
TUMOR MICROENVIRONMENT; CONTRAST AGENTS; HYPOXIA; LOCALIZATION; PH
Elenco autori:
Ferrauto, G.; Di Gregorio, E.; Lanzardo, S.; Ciolli, L.; Iezzi, M.; Aime, S.
Autori di Ateneo:
IEZZI MANUELA
Link alla scheda completa:
https://ricerca.unich.it/handle/11564/711468
Link al Full Text:
https://ricerca.unich.it//retrieve/handle/11564/711468/161202/generation%20of%20multiparametric%20MRI%20maps%202018.pdf
Pubblicato in:
SCIENTIFIC REPORTS
Journal
  • Dati Generali

Dati Generali

URL

www.nature.com/srep/index.html
  • Utilizzo dei cookie

Realizzato con VIVO | Designed by Cineca | 25.5.0.1