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3 results on '"Gajate A. M. S."'

1. Radiomics and artificial intelligence

Author

Catalano, OA, Ghezzo, S, Bezzi, C, Neri, I, Mapelli, P, Presotto, L, Gajate, A, Bettinardi, V, Garibotto, V, De Cobelli, F, Scifo, P, Picchio, M, Ghezzo S., Bezzi C., Neri I., Mapelli P., Presotto L., Gajate A. M. S., Bettinardi V., Garibotto V., De Cobelli F., Scifo P., Picchio M., Catalano, OA, Ghezzo, S, Bezzi, C, Neri, I, Mapelli, P, Presotto, L, Gajate, A, Bettinardi, V, Garibotto, V, De Cobelli, F, Scifo, P, Picchio, M, Ghezzo S., Bezzi C., Neri I., Mapelli P., Presotto L., Gajate A. M. S., Bettinardi V., Garibotto V., De Cobelli F., Scifo P., and Picchio M.

Abstract

Positron emission tomography/magnetic resonance imaging (PET/MRI) is an innovative imaging technology that allows the simultaneous acquisition of metabolic, structural, and functional information for an accurate characterization of tissues. The qualitative interpretation of PET/MR images has shown great potential in tumor diagnosis, treatment planning, and follow-up. Furthermore, PET/MRI also potentially provides several quantitative imaging biomarkers, also called “radiomic features,” for tumor characterization extracted both from PET and MRI. In the new era of precision medicine, radiomics is an emerging translational field of research aiming to extract a large number of quantitative features followed by their interpretation through various analyses and integration into predictive models. In this chapter, different clinical applications of radiomics based on PET, MRI, and PET/MR images will be presented, with a specific focus on the characterization of brain tumors, breast cancer, pancreatic neuroendocrine tumors, and prostate cancer. Finally, some other applications of artificial intelligence applied to PET/MR images that can shortly enter into clinical practice will be shown.

Published
2022

2. Indicators of guideline-concordant care in lung cancer defined with a modified Delphi method and piloted in a cohort of over 5,800 cases

Author

Andreano, A, Valsecchi, M, Russo, A, Siena, S, Andruccioli, M, Ardizzoia, A, Assi, A, Baisi, A, Bedini, A, Beretta, G, Bersani, M, Bertagna, F, Berti, E, Bertolini, A, Bettini, A, Bignardi, M, Bini, F, Bna, C, Bono, F, Ottoni, D, Borghesi, A, Borghetti, P, Brunelli, A, Buffoli, A, Cacioppo, C, Calati, A, Calcagno, A, Casagrande, S, Casartelli, C, Castellani, M, Castro, A, Catalano, G, Catena, L, Ceresoli, G, Cergnul, M, Ciocia, G, Colombo, A, Conti, B, Corti, D, Cortinovis, D, Cozzi, C, Crippa, F, De Monte, A, Candis, D, De Toma, D, De Marinis, F, Dimarco, B, Di Nuovo, F, Doglioni, C, Fabbris, V, Faccioli, P, Fagnani, D, Farina, G, Fariselli, L, Filipazzi, V, Franzi, F, Frata, P, Gajate, A, Gardani, G, Gasparini, M, Giordano, M, Grignani, F, Landoni, C, Lombardi, C, Lombardi, F, Luciani, A, Maffioli, L, Marchione, R, Mariani, P, Maspero, A, Meriggi, F, Miedico, A, Morbini, P, Muriana, G, Orlandoni, G, Paris, E, Pedrazzoli, P, Pepe, G, Pezzica, E, Piccoli, F, Pinotti, G, Quadri, A, Ravasio, A, Ravenna, F, Ricchiuti, E, Rinaldo, D, Roda, G, Rossi, G, Santoro, A, Soatti, C, Stiglich, F, Tagliabue, L, Tirelli, V, Tironi, A, Tomirotti, M, Travaini, L, Ucci, G, Vaghi, A, Vanzulli, A, Veronesi, G, Vittimberga, I, Zambelli, C, Andreano A., Valsecchi M. G., Russo A. G., Siena S., Andruccioli M., Ardizzoia A., Assi A., Baisi A., Bedini A. V., Beretta G., Bersani M., Bertagna F., Berti E., Bertolini A., Bettini A., Bignardi M., Bini F., Bna C., Bono F., Ottoni D. B., Borghesi A., Borghetti P., Brunelli A., Buffoli A., Cacioppo C., Calati A., Calcagno A., Casagrande S., Casartelli C., Castellani M., Castro A., Catalano G., Catena L., Ceresoli G. L., Cergnul M., Ciocia G., Colombo A., Conti B., Corti D., Cortinovis D., Cozzi C., Crippa F., De Monte A., Candis D. D., De Toma D., De Marinis F., DiMarco B., Di Nuovo F., Doglioni C., Fabbris V., Faccioli P., Fagnani D., Farina G., Fariselli L., Filipazzi V., Franzi F., Frata P., Gajate A. M. S., Gardani G., Gasparini M., Giordano M., Grignani F., Landoni C., Lombardi C., Lombardi F., Luciani A., Maffioli L. S., Marchione R., Mariani P., Maspero A., Meriggi F., Miedico A., Morbini P., Muriana G., Orlandoni G., Paris E., Pedrazzoli P., Pepe G., Pezzica E., Piccoli F., Pinotti G., Quadri A., Ravasio A., Ravenna F., Ricchiuti E., Rinaldo D., Roda G., Rossi G., Santoro A., Soatti C. P., Stiglich F., Tagliabue L., Tirelli V., Tironi A., Tomirotti M., Travaini L. L., Ucci G., Vaghi A., Vanzulli A., Veronesi G., Vittimberga I., Zambelli C., Andreano, A, Valsecchi, M, Russo, A, Siena, S, Andruccioli, M, Ardizzoia, A, Assi, A, Baisi, A, Bedini, A, Beretta, G, Bersani, M, Bertagna, F, Berti, E, Bertolini, A, Bettini, A, Bignardi, M, Bini, F, Bna, C, Bono, F, Ottoni, D, Borghesi, A, Borghetti, P, Brunelli, A, Buffoli, A, Cacioppo, C, Calati, A, Calcagno, A, Casagrande, S, Casartelli, C, Castellani, M, Castro, A, Catalano, G, Catena, L, Ceresoli, G, Cergnul, M, Ciocia, G, Colombo, A, Conti, B, Corti, D, Cortinovis, D, Cozzi, C, Crippa, F, De Monte, A, Candis, D, De Toma, D, De Marinis, F, Dimarco, B, Di Nuovo, F, Doglioni, C, Fabbris, V, Faccioli, P, Fagnani, D, Farina, G, Fariselli, L, Filipazzi, V, Franzi, F, Frata, P, Gajate, A, Gardani, G, Gasparini, M, Giordano, M, Grignani, F, Landoni, C, Lombardi, C, Lombardi, F, Luciani, A, Maffioli, L, Marchione, R, Mariani, P, Maspero, A, Meriggi, F, Miedico, A, Morbini, P, Muriana, G, Orlandoni, G, Paris, E, Pedrazzoli, P, Pepe, G, Pezzica, E, Piccoli, F, Pinotti, G, Quadri, A, Ravasio, A, Ravenna, F, Ricchiuti, E, Rinaldo, D, Roda, G, Rossi, G, Santoro, A, Soatti, C, Stiglich, F, Tagliabue, L, Tirelli, V, Tironi, A, Tomirotti, M, Travaini, L, Ucci, G, Vaghi, A, Vanzulli, A, Veronesi, G, Vittimberga, I, Zambelli, C, Andreano A., Valsecchi M. G., Russo A. G., Siena S., Andruccioli M., Ardizzoia A., Assi A., Baisi A., Bedini A. V., Beretta G., Bersani M., Bertagna F., Berti E., Bertolini A., Bettini A., Bignardi M., Bini F., Bna C., Bono F., Ottoni D. B., Borghesi A., Borghetti P., Brunelli A., Buffoli A., Cacioppo C., Calati A., Calcagno A., Casagrande S., Casartelli C., Castellani M., Castro A., Catalano G., Catena L., Ceresoli G. L., Cergnul M., Ciocia G., Colombo A., Conti B., Corti D., Cortinovis D., Cozzi C., Crippa F., De Monte A., Candis D. D., De Toma D., De Marinis F., DiMarco B., Di Nuovo F., Doglioni C., Fabbris V., Faccioli P., Fagnani D., Farina G., Fariselli L., Filipazzi V., Franzi F., Frata P., Gajate A. M. S., Gardani G., Gasparini M., Giordano M., Grignani F., Landoni C., Lombardi C., Lombardi F., Luciani A., Maffioli L. S., Marchione R., Mariani P., Maspero A., Meriggi F., Miedico A., Morbini P., Muriana G., Orlandoni G., Paris E., Pedrazzoli P., Pepe G., Pezzica E., Piccoli F., Pinotti G., Quadri A., Ravasio A., Ravenna F., Ricchiuti E., Rinaldo D., Roda G., Rossi G., Santoro A., Soatti C. P., Stiglich F., Tagliabue L., Tirelli V., Tironi A., Tomirotti M., Travaini L. L., Ucci G., Vaghi A., Vanzulli A., Veronesi G., Vittimberga I., and Zambelli C.

Abstract

Background: To identify indicators of guideline-concordant care in lung cancer, to implement such indicators with cancer registry data linked to health databases, and to pilot them in a cohort of patients from the cancer registry of the Milan Province. Methods: Thirty-four indicators were selected by revision of main guidelines by cancer epidemiologists, and then evaluated by a multidisciplinary panel of clinicians involved in lung cancer care and working on the pathway of lung cancer diagnosis and treatment in the Lombardy region, Italy. With a modified Delphi method, they assessed for each indicator the content validity as a quality measure of the care pathway, the degree of modifiability from the health professional, and the relevance to the health professional. Feasibility was assessed using the cancer registry and the routine health records of the Lombardy region. Feasible indicators were then calculated in the cohort of lung cancer patients diagnosed in 2007–2012 derived from the cancer registry of the Milan Province. Criterion validity was assessed reviewing clinical records of a random sample of 114 patients (threshold for acceptable discordance ≤20%). Finally, reliability was evaluated at the provider level. Results: Initially, 34 indicators were proposed for evaluation in the first Delphi round. Of the finally 22 selected indicators, 3 were not feasible because the required information was actually not available. The remaining 19 were calculated on the pilot cohort. After assessment of criterion validity (3 eliminated), 16 indicators were retained in the final set and evaluated for reliability. Conclusion: The developed and piloted set of indicators is now available to implement and monitor, over time, quality initiatives for lung cancer care in the studied health system.

Published
2021

3. New positron emission tomography derived parameters as predictive factors for recurrence in resected stage I non-small cell lung cancer.

Author

Melloni G, Gajate AM, Sestini S, Gallivanone F, Bandiera A, Landoni C, Muriana P, Gianolli L, and Zannini P

Subjects
Adult, Aged, Aged, 80 and over, Analysis of Variance, Carcinoma, Non-Small-Cell Lung diagnostic imaging, Carcinoma, Non-Small-Cell Lung surgery, Female, Fluorodeoxyglucose F18 metabolism, Humans, Kaplan-Meier Estimate, Lung Neoplasms diagnostic imaging, Lung Neoplasms surgery, Male, Middle Aged, Neoplasm Recurrence, Local diagnostic imaging, Neoplasm Recurrence, Local metabolism, Neoplasm Staging, Odds Ratio, Predictive Value of Tests, Prognosis, Radiopharmaceuticals metabolism, Recurrence, Risk Assessment, Risk Factors, Tomography, X-Ray Computed, Carcinoma, Non-Small-Cell Lung metabolism, Carcinoma, Non-Small-Cell Lung pathology, Glycolysis, Lung Neoplasms metabolism, Lung Neoplasms pathology, Positron-Emission Tomography methods
Abstract

Background: The recurrence rate for stage I non-small cell lung cancer is high, with 20-40% of patients that relapse after surgery. The aim of this study was to evaluate new F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) derived parameters, such as standardized uptake value index (SUVindex), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), as predictive factors for recurrence in resected stage I non-small cell lung cancer., Methods: We retrospectively reviewed 99 resected stage I non-small cell lung cancer patients that were grouped by SUVindex, TLG and MTV above or below their median value. Disease free survival was evaluated as primary end point., Results: The 5-year overall survival and the 5-year disease free survival rates were 62% and 73%, respectively. The median SUVindex, MTL and TLG were 2.73, 2.95 and 9.61, respectively. Patients with low SUVindex, MTV and TLG were more likely to have smaller tumors (p ≤ 0.001). Univariate analysis demonstrated that SUVindex (p = 0.027), MTV (p = 0.014) and TLG (p = 0.006) were significantly related to recurrence showing a better predictive performance than SUVmax (p = 0.031). The 5-year disease free survival rates in patients with low and high SUVindex, MTV and TLG were 84% and 59%, 86% and 62% and 88% and 60%, respectively. The multivariate analysis showed that only TLG was an independent prognostic factor (p = 0.014) with a hazard ratio of 4.782., Conclusion: Of the three PET-derived parameters evaluated, TLG seems to be the most accurate in stratifying surgically treated stage I non-small cell lung cancer patients according to their risk of recurrence., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Published
2013
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