The main field of Prof. Arturo Chiti interest and research is oncology, as witnessed by his track of clinical and research activities. He has extensive experience in leading clinical, educational and research projects, and also scientific associations and committees. He has broad knowledge in imaging techniques, both radiological and nuclear medicine. In recent years radiomics, mining of parameters derived from the texture analysis of medical images, and machine learning techniques (e.g. convolutional neural networks) have risen a great attention in medical imaging research field. Prof. Chiti contributed to the field coordinating projects dealing with solid cancers, in particular lung cancer. Currently, he leads a funded research project on lung cancer using a radiogenomics approach (AIRC IG 2016 – 18585) and a project aimed at the baseline risk assessment and staging of cancer patients using deep learning. During his scientific track of activities, he focused his efforts on the standardisation of imaging procedures in order to ensure reliable image derived parameters to be included in trials and clinics as imaging biomarkers. He contributed to numerous guidelines and standardisation initiatives. Radiation treatment plan relies on image acquisition, interpretation and delineation. Prof. Chiti collaborated with the European Radiation Oncology Society (ESTRO) and research groups to promote the value of medical imaging in the radiation treatment in different cancer types. At the beginning of his career Prof. Chiti dedicated most of his scientific activities to molecular imaging of neuroendocrine neoplasms, firstly using 111-In-pentreotide scintigraphy and then using 68-Ga labeled peptides and 18-F-DOPA PET/CT.
The main field of Prof. Arturo Chiti interest and research is oncology, as witnessed by his track of clinical and research activities. He has extensive experience in leading clinical, educational and research projects, and also scientific associations and committees. He has broad knowledge in imaging techniques, both radiological and nuclear medicine.
In recent years radiomics, mining of parameters derived from the texture analysis of medical images, and machine learning techniques (e.g. convolutional neural networks) have risen a great attention in medical imaging research field. Prof. Chiti contributed to the field coordinating projects dealing with solid cancers, in particular lung cancer.
Currently, he leads a funded research project on lung cancer using a radiogenomics approach (AIRC IG 2016 – 18585) and a project aimed at the baseline risk assessment and staging of cancer patients using deep learning.
During his scientific track of activities, he focused his efforts on the standardisation of imaging procedures in order to ensure reliable image derived parameters to be included in trials and clinics as imaging biomarkers. He contributed to numerous guidelines and standardisation initiatives.
Radiation treatment plan relies on image acquisition, interpretation and delineation. Prof. Chiti collaborated with the European Radiation Oncology Society (ESTRO) and research groups to promote the value of medical imaging in the radiation treatment indifferent cancer types.
At the beginning of his career Prof. Chiti dedicated most of his scientific activities to molecular imaging of neuroendocrine neoplasms, firstly using 111-In-pentreotide scintigraphy and then using 68-Ga labeled peptides and 18-F-DOPA PET/CT.
- Radionuclide assessment of left ventricular function in patients with myocardial infarction and diabetes mellitus.
Lomuscio A, Bestetti A, Vergani D, Chiaramello D, Chiti A, Ruffini L, Pozzoni L, Tarolo GL.Journal of internal medicine. 1992; 231(1):73-6.PubMed [journal]PMID:1732402
- [Final scintigraphic diagnosis with [99mTc] HIDA in a case of focal nodular hyperplasia with essential thrombocythemia and portal thrombosis]. Chiti A, Giovanella LC, Bestetti A, Castellani M, Gattoni F, Bossi MC, Tarolo GL. La Radiologia medica. 1992; 84(4):491-3.PubMed [journal]PMID:1455042
- Delayed effect of streptokinase on left ventricular function after acute myocardial infarction assessed by equilibrium gated radionuclide angiocardiography. Bestetti A, Lomuscio A, Chiti A, Giovanella LC, Castellani M, Tarolo GL. Journal of nuclear biology and medicine (Turin, Italy : 1991). 1993; 37(1):6-11.PubMed [journal]PMID:8329476
- [Decisive scintigraphic diagnosis in a case of Borrelia infective sacro-iliitis].Giovanella LC, Bestetti A, Chiti A, Castellani M, Tarolo GL.Minerva medica. 1993; 84(4):199-201.PubMed [journal]PMID:8506060
- A doubtful image of Le Veen shunt patency.Chiti A, Castellani M, Intra M, Bestetti A, Giovanella LC, Maioli C, Tarolo GL.Clinical nuclear medicine. 1993; 18(12):1096.PubMed [journal]PMID:8293637
- Thallium-201 lung uptake: comparison of an automatic and a manual method of ROI drawing. Castellani M, Chiti A, Giovanella LC, Bestetti A, Lomuscio A, Tarolo GL.Journal of nuclear biology and medicine (Turin, Italy : 1991). 1993; 37(4):213-7.PubMed [journal]PMID:8172962
- Fourier amplitude image circumferential profile analysis in the evaluation of the dipyridamole test. Bestetti A, Lomuscio A, Castellani M, Giovanella L, Pedrazzini L, Chiti A, Tarolo GL. Journal of nuclear biology and medicine (Turin, Italy : 1991). 1993; 37(4):185-90.PubMed [journal]PMID:8172958
- Sensitivity versus specificity in melanoma imaging using iodine-123 iodobenzamide and indium-111 pentetreotide [1]. Maffioli L, Chiti A, Gasparini M, Bombardieri E. European journal of nuclear medicine. 1994; 21(12):1366. PubMed [journal]PMID:7875175
- 111In-octreotide uptake in granulomatous and tumor lesions in a patient with small-cell lung cancer. Crippa F, Bombardieri E, Chiti A, Soresi E, Boffi R, Buraggi GL. Journal of nuclear biology and medicine (Turin, Italy : 1991). 1994; 38(4):576-8. PubMed [journal]PMID:7786920
- Case report: technetium-99m-hexakis-2-methoxy-isobutyl-isonitrile imaging of breast cancer and myocardial infarction in the same patient. Chiti A, Maffioli L, Castellani M, Gasparini M, Capri G, Bombardieri E. Tumori. 1994; 80(6):480-1.PubMed [journal]PMID:7900240