The MP Dpt is involved in research activities related to

  • Participating to radiotherapy clinical trials and performing data analysis of clinical and dosimetric results.
  • Personalized dosimetry in selective radiation therapy with Y-90 for treatment of hepatic lesions. Personalized dosimetry in neuroendocrine tumors by Lu-177 dotatate. Implementation of a home-made software for personalized dosimetry in nuclear medicine.
  • Novel CT dosimetry.
  • Study and development of methods for evaluating the observer’s performance in radiology.
  • Optimization PROcesses in RAdiotherapy: clinical and dosimetric audits ( OPRORA ) Project Code: RF-2016 02362662 (Ministero Salute), Cod. IFO 20.01.R.13 RF. Co-investigator: A. Soriani
  • Early Diffusion Weighted Magnetic Resonance Imaging Changes to Predict Tumor Response to Chemoradiotherapy in HN Cancer. AIRC project (n° 17028). Co-investigator: S.Marzi
  • Development and optimization of a novel system to deliver hyperthermia for the treatment of sarcoma. Lazioinnova cod. IFO 18/14/R/29 PI: A. Soriani
  • Development of a real time system for the reporting and collection of data to be used to reconstruct the dose to the operator in unexpected exposure events in nuclear medicine. Progetto BRiC, INAIL, SIREN: Co-investigator V. Landoni
  • Techniques for the evaluation of the dose to lenses in workers exposed to ionization radiation in the medical field, modeling of biological effects and strategies for risk reduction. Progetto BRiC, INAIL: PI V. Bruzzaniti
  • A radiogenomic approach to assess treatment response to anti-PD-1 immune checkpoint inhibitor in metastatic melanoma patients using CT texture analysis combined with tumor molecular profile as potential predictive biomarker: a pilot study GR-2019-12369697 S. Ungania
  • Proton dosimetry : In the framework of the ItalianTOP-IMPLART project (Regione Lazio), ENEA-Frascati, ISS and IFO are developing and constructing the first proton linear accelerator based on an actively scanned beam for tumor radiotherapy with final energy of 150 MeV. COD IFO 13/41/R/30
  • Study of an artificial intelligence algorithm for the classification of digital breast tomosynthesis images for the automated diagnosis of breast cancer (RS N. 1414/20) V. Landoni
  • Dr Marzi is member of the WG “Quantificazione, interconfronti e assicurazione di qualità in RM”, AIFM, Associazione Italiana Fisica Medica.
  • Dr Landoni is member of the Scientific Committee of the AIFM, Associazione Italiana Fisica Medica
  • Dr Landoni is member of the Editorial Board of Physica Medica, Europ Journ of MedPhy